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Interpersonal Communication, UNI edition: Chapter 12: Interpersonal Communication in Mediated Contexts

Interpersonal Communication, UNI edition
Chapter 12: Interpersonal Communication in Mediated Contexts
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Notes

table of contents
  1. Title Page
  2. Copyright
  3. Table of Contents
  4. Preface
  5. Acknowledgments
  6. Chapter 1: Introduction to Human Communication
  7. Chapter 2: Overview of Interpersonal Communication
  8. Chapter 3: Intrapersonal Communication
  9. Chapter 4: Verbal Elements of Communication
  10. Chapter 5: Nonverbal Communication
  11. Chapter 6: Cultural and Environmental Factors in Interpersonal Communication
  12. Chapter 7: Talking and Listening
  13. Chapter 8: Building and Maintaining Relationships
  14. Chapter 9: Conflict in Relationships
  15. Chapter 10: Friendship Relationships
  16. Chapter 11: Family & Marriage Relationships
  17. Chapter 12: Interpersonal Communication in Mediated Contexts
  18. Chapter 13: Interpersonal Relationships at Work
  19. Chapter 14: The Dark Side of Interpersonal Communication
  20. Glossary
  21. Answer Keys
  22. About Original Authors
  23. Accessibility Statement

Chapter 12: Interpersonal Communication in Mediated Contexts

Four young adults stand outdoors in a lush, green environment, each focused intently on their smartphones. The group is diverse in appearance and dress, with one woman wearing light blue pants and a crop top, another in a pink romper with dreadlocks, a man in a yellow jacket and glasses, and another in a teal shirt. Surrounded by tropical plants, the image highlights themes of digital engagement, connectivity, and technology use in social settings.
“People Holding Cellphones” by fauxels on Pexels

In today’s world, we all spend a lot of time on various devices designed to make our lives easier and more efficient. From smartphones to social media, we are all in constant contact with family, friends, coworkers, etc. Since the earliest days of communication technologies, we have always used these technologies to interact with one another. This chapter is going to examine how technology helps mediate our interpersonal relationships.

Technology and Communication

Learning Objectives

  1. Summarize the key historical developments in computer-mediated communication (CMC) from 1801 to the present.
  2. Identify major technological milestones that shaped the evolution of the Internet and the World Wide Web.
  3. Describe the contributions of influential figures in the development of CMC technologies.
  4. Differentiate between asynchronous and synchronous forms of CMC and provide examples of each.
  5. Explain how text-based communication tools attempt to compensate for the absence of nonverbal cues.

Since the Internet’s creation in 1969, public access to the Internet and the creation of the World Wide Web (www) in 1991, and the proliferation of internet service providers through the late 1990s, the technology that shapes your life today and tomorrow is still relatively new. Here are some relatively recent landmarks in social media sites, technology, and apps: USB drives (2000), iPod (2001), The Tor Project (2002), LinkedIn (2003),  Facebook (2004), YouTube (2005), Twitter/X (2006), iPhone (2007), Drop Box (2008), Google Docs (2009), Kickstarter (2010), Amazon Kindle Fire (2011), Google Glass (2012), Oculus Rift (2013), iWatch (2014), YouTube Kids (2015), Douyin—the precursor to TikTok (2016), Face Recognition on phones (2017), PUBG Mobile (2018), Disney+ (2019), Clubhouse (2020), NFTs (Non-Fungible Tokens) Go Mainstream (2021), Generative AI Art (2022), ChatGPT (2023), First Neurolink—first patient fit with a Brain-Machine Interface (2024), Agentic AI (2025), and who knows what’s next. Just limiting this list is hard. Some of these products you’re probably very familiar with, while others may be new to you altogether. Some products become instantly famous (like ChatGPT), while others take over a decade. For example, Zoom emerged in 2013 but gained significant popularity only with the onset of the COVID-19 pandemic in 2020.

From Math to Punch Cards

A traditional Chinese abacus (suanpan) resting on a wooden surface. The abacus features a rectangular wooden frame with vertical rods, each holding black or dark green beads. The frame is divided horizontally into two sections: the upper deck (with two beads per rod) and the lower deck (with five beads per rod). The abacus is used for manual arithmetic calculations and is a historical tool for mathematical operations in East Asia.
Figure 12.1a A Chinese Abacus. “Chinese-abacus.jpg” by Dave Fischer. This file is licensed under the Creative Commons Attribution 3.0 Unported license.

Before we get started, it’s essential to understand the evolution of what we call computer-mediated communication or CMC. In recent years, some scholars have adopted the broader term “communication and technology.” Still, we don’t think this is necessary because a computer of some kind is always at the center of these communicative interactions.

A white plastic slide rule with multiple logarithmic scales and a transparent sliding cursor, placed on top of a brown leather case. The slide rule, branded "ARISTO REITZ," is used for performing mathematical calculations such as multiplication, division, roots, logarithms, and trigonometry. The image is set against a black background, and the leather case has a subtle embossed logo. The slide rule is a classic analog computing tool used before the advent of electronic calculators.
Figure 12.1b Slide Rule. “slide-rule-computing-device” by Erwin Österreich. This file is licensed under the Pixabay Content License.

So, our first question should be, what is a computer? In its earliest use, “computers” referred to people who performed massive amounts of calculations by hand or using tools like an abacus or slide rule (Figure 12.1). As you can imagine, this process wasn’t exactly efficient and required a significant amount of human resources. The 2016 movie Hidden Figures tells the true story of a group of African American women who created the calculations that enabled the first astronaut to land on the Moon.

The first mechanical ancestor of the computer we have today was created in 1801 by a Frenchman named Joseph Marie Jacquard, who created a loom that used punched wooden cards to weave fabric (Figure 12.2). The idea of “punch cards” would be the basis of many generations of computers until the 1960s. Of course, the punch cards evolved from wooden cards to cardboard or cardstock throughout their history. Some of the earliest statistical research in communication was conducted using punch cards. Many important individuals contributed to the advancement of the modern computer from the early 1800s to the 1960s. Many wonderful books can introduce you to the full history of how we came to the modern personal computer.[1] [2] [3]

Jacquard Loom
Figure 12.2 Jacquard Loom. “NMS Jacquard loom 2.JPG.” by Ad Meskens. This file is licensed under the Creative Commons Attribution 3.0 Unported license.

The 1970s marked the beginning of the personal computer’s rapid growth. In 1981, IBM released the Acorn, which ran on Microsoft DOS, which was followed up by Apple’s Lisa in 1983, which had a graphic user interface. From that point until now, Microsoft and Apple (specifically, the Macintosh) have dominated the market for personal computers.

Getting Computers to Interact

One thing we’ve observed is that with each new computer development, new technologies have emerged, helping us communicate and interact more effectively. One significant development in 1969 changed the direction of humanity forever. Starting in 1965, researchers at the Massachusetts Institute of Technology could get two computers to “talk” to each other. Of course, it’s one thing to get two computers side-by-side to talk to each other, but could they get computers at a distance to talk to each other (in a manner similar to how people use telephones to communicate at a distance)?

Researchers at both UCLA and Stanford, with grant funding from the U.S. Defense Department’s Advanced Research Projects Agency (DARPA), set out to get computers at a distance to talk to each other. In 1969, UCLA student Charley Kline attempted the first computer-to-computer communication over a distance from his terminal in Los Angeles to a terminal at Stanford. The first message to be sent was to be a simple one, “login.” The letter “l” was sent, then the letter “o,” and then the system crashed. So, the first message ever sent over what would become the Internet was “lo.” An hour later, Kline got the system up and running again, and the full word “login” was sent.

In the earliest years of the Internet, most people were unaware of its existence. The Internet was initially developed primarily as a tool for the Department of Defense, enabling researchers at multiple sites across the country to collaborate on defense projects. It was called the Advanced Research Projects Agency Network (ARPANET). In 1973, the University College of London (England) and the Royal Radar Establishment (Norway) connected to ARPANET, and the term “Internet” was born. A year later, in 1974, a commercialized version of ARPANET called Telenet became the first internet service provider (ISP).

Allowing People to Communicate

The early Internet was not exactly designed for the average user, so it required more skill and “know-how” to use and find things. Of course, as the Internet developed, so did its capability to allow people to communicate and interact with one another. In 1971, Ray Tomlinson was working on two programs that could be used over ARPANET: SNDMSG and READMAIL. From his lab at MIT, Tomlison sent a message from one computer to another computer sitting right next to it, but he sent the message through ARPANET, creating the first electronic email. Tomlison also forever changed our lives by introducing the “@” symbol as the tool the Internet uses when handling sending and receiving of messages.

In addition to email, another breakthrough in computer-mediated communication was the development of Internet forums or message/bulletin boards, which were online discussion sites where people can hold conversations in the form of posted messages. Steve Walker created an early message system for ARPANET. The primary message list for professionals was MsgGroup. The number one unofficial message list was SF-Lovers, a science fiction list. As you can see, from the earliest days of the Internet, people have been using it as a tool to communicate and interact with others who share similar interests.

One early realization about email and message boards is that people relied solely on text to interpret a message with no form of nonverbal communication attached. On September 19, 1982, Scott Fahlman, a research professor of computer science at Carnegie Mellon, came up with an idea. You see, at Carnegie Mellon in the early 1980s (like most research universities at the time), they had their own Bulletin Board System, which discussed everything from campus politics to science fiction. As Fahlman noted, “Given the nature of the community, a good many of the posts were humorous, or at least attempted humor,” explained Fahlman. “The problem was that if someone made a sarcastic remark, a few readers would fail to get the joke and each of them would post a lengthy diatribe in response.”[4] After giving some thought to the problem, he posted the following message seen in Figure 12.3.

I propose that the following character sequence for joke markers: :-) Read it sideways. Actually is is probably more economical to mark things that are NOT jokes, given the current trends. For this use :-(
Figure 12.3 Emoticon Email

Thus, the emoticon (emotion icon) was born. An emoticon was a series of characters and/or letters designed to help readers interpret a writer’s intended feelings and/or tone. Over the years, many emoticons were created some useful like the smiley and sad faces, lol (laughing out loud), ROFL (rolling on the floor laughing), :-O (surprise), :-* (kiss), 😛 (sticking your tongue out), :-/ (quizzical), :-X (sealed lips), 0:-) (angel), *\0/* (cheerleader), and so many others. As we’ve discussed previously in this text, so much of how we understand each other is based on our nonverbal behaviors, so these emoticons were an attempt to bring a lost part of the human communicative experience to a text-based communicative experience.

Research Spotlight

The Use of Emoticons Among Youths

The use of emoticons is ubiquitous in online settings though how emoticons are used may vary by individual, groups of individuals, and even between generations. Researchers Ju and Zhao (2024) explored the impact of emoticons on the social interaction of youths. [5]

Emoticons affect youth social interactions in three ways.

  1. Emoticons make up for the lack of context in virtual situations and make corrections for ambiguity of words and phrases created by the absence of nonverbal cues..
  2. Young people create online emoticon communities that strengthen their online interactions and help form a deeper social identity. The strength of this identity is so strong that is creates a divide between the online identity and IRL identity.
  3. Emoticons are prolific in  young people’s online social interactions. This presence bleeds into reality to affect their in-person interactions. For example, one participant reported mimicking the micro expressions of the emoticon when interacting with another person.  which has gradually extended from the Internet to reality and now affects their normal, in-person social interactions.

The authors conclude that emoticons will never replace nonverbal cues found in real social interactions, but emoticons have become an important addition to social bonding and emotional communication of teenagers.

Asynchronous Communication

For our part, these technologies are what we call asynchronous, or a mediated form of communication in which the sender and receiver are not concurrently engaged in communication. When Person A sends a message, Person B did not need to be on the computer at the same time to receive the message. There could be a delay of hours or even days before that message received and Person B responded. Here, asynchronous messages were akin to letter writing. As the Internet grew and speed and infrastructure became more established, the development of synchronous CMC evolved, enabling mediated communication where the sender and receiver are concurrently engaged in real-time communication. When Person A sends a message, Person B receives it in real-time, just as they would in a face-to-face (FtF) interaction. Here, synchronous messages are akin to talking to someone on the telephone.

Synchronous Communication

Let’s switch gears for a bit and talk about the history of synchronous communication on the Internet. The first synchronous mode of communication was the chat room. In 1988, Jarkko “WiZ” Oikarinen wrote the first Internet Relay Chat (IRC) client and server at the University of Oulu, Finland. IRC was initially started as a program to replace an existing BBS, but WiZ realized that he had something completely different. With IRC, individuals from around the world could log in using an IRC Chat Client (software on their computer), which would allow them to access a server elsewhere in the world to interact with people in real-time. The invention of IRC led to the proliferation of chat rooms throughout the 1980s and 90s.

Four IRC Chat clients around a server with double sided arrows connecting them each to the server.
Figure 12.4 Internet Relay Chat

In addition to IRC, another technology developed through Germany and France cooperation on Groupe Speciale Mobile (GSM) came out in February 1985 in Oslo, Norway. The goal of the GSM was to develop protocols for second-generation global cellular phone networks. One technology that was created was called the short messaging service (SMS). The concept was developed in 1985 by Friedhelm Hillebrand and Bernard Ghillebaert. SMS originated from radio telegraphy in radio memo pagers using standardized phone protocols and later defined as part of the Global System for Mobile Communications (GSM) series of standards in 1985. The “short” part of SMS refers to the maximum size of the messages that could be sent at the time: 160 characters (letters, numbers, or symbols in the Latin alphabet). If you haven’t figured it out yet, the system created by Hillebrand and Ghillebaert is the system most of you use every day to send text messages. Now, texting can be asynchronous or synchronous, but we decided to discuss it here because it falls within the timeline we’re developing, and it’s often used for people to communicate with one another in real-time.

The World Wide Web

Our last major invention, which was indeed groundbreaking, came about in 1990. Tim Berners-Lee, a scientist working for Conseil Européen pour la Recherche Nucléaire (CERN), had an idea to help capture information from the people who worked at CERN. At CERN, the typical length of someone conducting research there was only two years, so that meant a lot of new people coming and going without a way to capture what was being done. As Lee noted, “The actual observed working structure of the organisation is a multiply connected ‘Web’ whose interconnections evolve with time.”[6] Unfortunately, people come and go, and those interconnections often get lost. Furthermore, “The technical details of past projects are sometimes lost forever, or only recovered after a detective investigation in an emergency. Often, the information has been recorded, it just cannot be found.”[7] You see, Berners-Lee realized that so much information is learned on the job and then leaves with the people as they leave the job. Berners-Lee proposed a new system for keeping electronic information based on hypertext. After getting some initial positive feedback, Berners-Lee and Robert Cailliau wrote a management report explaining hypertext, “HyperText is a way to link and access information of various kinds as a Web of nodes in which the user can browse at will. It provides a single user interface to large classes of information (reports, notes, data bases, computer documentation, and online help). We propose a simple scheme incorporating servers already available at CERN… A program which provides access to the hypertext world we call a browser…”[8] The title of this report was “WorldWideWeb: Proposal for a HyperText Project.”

CERN was not really concerned with the Internet as its primary scope and emphasis, so they agreed to release the source code for World Wide Web (WWW) to the world in April 1993. By 1994, Berners-Lee left CERN and took a job at MIT, where he created the International World Wide Web Consortium (W3C) to develop common standards for communication on the WWW. W3C still exists today, and the WWW celebrated its 30th birthday on March 10, 2019. The 5th variation of the hypertext markup language (HTML) created by the W3C is currently in circulation. You’re probably using HTML5 daily and don’t even realize it. As the W3C note, “HTML5 contains powerful capabilities for Web-based applications with more powerful interaction, video support, graphics, more styling effects, and a full set of APIs. HTML5 adapts to any device, whether desktop, mobile, tablet, or television.”[9]

Key Takeaways

  • Computer-mediated communication (CMC) has evolved from mechanical devices, such as the abacus and punch card systems, to the sophisticated web-based platforms we use today. The timeline includes key inventions, including the Jacquard loom, early personal computers, and the Internet.
  • Key milestones in the development of CMC include the creation of ARPANET, the rise of ISPs, the invention of email and emoticons, the development of chatrooms and text messaging, and the launch of the World Wide Web in 1991.
  • Important contributors to CMC include Joseph Marie Jacquard (mechanical computing), Ray Tomlinson (email), Scott Fahlman (emoticons), Jarkko Oikarinen (IRC), Friedhelm Hillebrand and Bernard Ghillebaert (SMS), and Tim Berners-Lee (WWW).
  • Asynchronous CMC, such as email and message boards, does not require simultaneous interaction, whereas synchronous CMC, including chatrooms and real-time texting, allows for immediate communication between users.
  • Emoticons and other textual cues were developed to help convey tone and emotion in digital communication, compensating for the lack of facial expressions, gestures, and vocal cues.

Exercises

  • When you look back at your own life, which computer-mediated technologies do you remember interacting with? Go back as far as you can and reflect on your first experiences, from what you used then to what you use today.
  • Check out the World Wide Web Consortium’s (W3C) website (https://www.w3.org/) and see what projects they’re working on today. Why is the W3C still relevant today?
  • Consider the use of emoticons in CMC. Think of a message exchanges where the use of emoticons increased clarity. Think of message exchanges where emoticons were not used and communication was misinterpreted. What would emoticons might have helped with the misinterpretation? Would emoticons have helped at all?

The CMC Process

Learning Objectives

  1. Differentiate between synchronous, asynchronous, and hybrid forms of computer-mediated communication.
  2. Explain how the absence or reduction of nonverbal cues affects message interpretation in CMC.
  3. Describe the conventions, expectations, and norms that shape digital communication behavior (netiquette).
  4. Identify key human communication variables that influence behavior in CMC environments (e.g., communication apprehension, competence).
  5. Analyze how people form impressions and manage identities in mediated contexts.

As interpersonal communication scholars, our interest in CMC is less about the technologies people use and more about how they utilize technology to interact with one another. Instead of focusing on how one goes about coding new software, scholars of interpersonal communication focus on how new technologies and software help facilitate interpersonal communication. For example, Pat and Sam are playing the latest Massive Multiplayer Online Roleplaying Game (e.g., Word of WarCraft, Fortnite, etc.). As you can see in Figure 12.5, each player is playing the same video game together but from different locations. Through a technology called VoIP, Sam and Pat can play video games simultaneously while talking to each other using headsets.

two figures from the side at computors with headsets on facing one another.
Figure 12.5 Video Game Play

Synchronous and Asynchronous Communication

In this section, we’re going to delve further into the areas of synchronous and asynchronous communication. In Figure 12.5, Sam and Pat are in some underworld, firey landscape. Pat is playing a witch, and Sam is playing a vampire. The two can coordinate their movements to accomplish in-game tasks because they can freely talk to one another while playing the game in real-time. As previously discussed, this type of CMC involves synchronous communication, which occurs in real-time. Conversely, asynchronous communication is the exchange of messages with a time lag. People can communicate on their schedules as time permits, rather than in real-time. For example, Figure 12.6 shows a conversation between two college students. Here, two college students are using SMS, commonly called texting) to interact with each other. The conversation starts at 2:25 PM. The first person starts the conversation, but doesn’t get a response until 3:05 PM. The third turn in the interaction then doesn’t happen until 5:40 PM. In this exchange, the two people interacting can send responses at their convenience, which is one of the main reasons people often rely on asynchronous communication. Other common forms of asynchronous communication include emails, instant messaging, online discussions, etc.

Now, is it possible for people to use the same SMS technology to interact synchronously? Of course. One of our coauthors remembers two students on a trip sitting next to each other texting back-and-forth because they didn’t want their conversation to be overheard by others in the van. Their interaction was clearly mediated, and in real-time, so it would be considered synchronous communication.

Today 2:25pm Heading to class. Dinner tonight? Today 3:05pm Just got out of class myself. Had a midterm. Did not go well. Dinner sounds great. 8ish? Today 5:40pm That sucks!!! Meet at my room around 7:45. how does Mexican sound?
Figure 12.6 Asynchronous Communication via SMS (Text Messaging)

Nonverbal Cues

One interpersonal consideration related to CMC is nonverbal communication. Historically, mediums people used to interact with one another were asynchronous and text-based. As such, it was impossible to fully ascertain the meaning behind a string of words fully. Mary J. Culnan and M. Lynne Markus believed that the functions nonverbal behaviors meet in interpersonal interactions simply go unmet in CMC.[10] As such, interpersonal communication must always be inherently impersonal when it’s conducted using computer-mediated technologies. This perspective has three underlying assumptions:

  1. Communication mediated by technology filters out communicative cues found in FtF interaction,
  2. Different media filter out or transmit different cues, and
  3. Substituting technology-mediated for FtF communication will result in predictable changes in intrapersonal and interpersonal variables.[11]

Let’s breakdown these assumptions. First, CMC interactions “filter out” communicative cues found in FtF interactions. For example, if you’re on the telephone with someone, you can’t see their eye contact, gestures, facial expressions, etc.… If you’re reading an email, you have no nonverbal information to help you interpret the message because there is none. That’s what is meant by nonverbal cues that have been filtered out. For now, we will pause our discussion about nonverbal communication, as we will revisit this information later in the chapter when we examine a range of theories related to CMC.

Unfortunately, even if we don’t have the nonverbals to help us interpret a message, we interpret the message using our perceptions of how the sender intended us to understand this message, which is often wrong. How many times have you seen an incorrectly read text or email start a conflict? Of course, one of the first attempts to recover some sense of nonverbal meaning was the emoticon that we discussed earlier in this chapter.

CMC Rules and Norms

As with any form of communication, certain rules and norms govern how people interact with one another. For example, X had an extensive Terms of Service policy that covered a wide range of communication rules called The X Rules. For our purposes here, let’s examine their rules related to hate speech and violence:

Violent Content: You may share graphic media if it is properly labeled, not prominently displayed and is not excessively gory or depicting sexual violence, but explicitly threatening, inciting, glorifying, or expressing desire for violence is not allowed

Violent & Hateful Entities: You can’t affiliate with or promote the activities of violent and hateful entities.

Child Safety: We have zero tolerance for any forms of child sexual exploitation and remove certain media depicting physical child abuse to prevent the normalization of violence against children.

Abuse/Harassment: You may not share abusive content, engage in the targeted harassment of someone, or incite other people to do so.

Hateful conduct: You may not attack other people on the basis of race, ethnicity, national origin, caste, sexual orientation, gender, gender identity, religious affiliation, age, disability, or serious disease.

Perpetrators of Violent Attacks: We will remove any accounts maintained by individual perpetrators of terrorist, violent extremist, or mass violent attacks, and may also remove posts disseminating manifestos or other content produced by perpetrators.

Suicide: You may not promote or encourage suicide or self-harm.

Adult Content: You may share consensually produced and distributed adult nudity or sexual behavior, provided it’s properly labeled and not prominently displayed.

Illegal or Certain Regulated Goods or Services: You may not use our service for any unlawful purpose or in furtherance of illegal activities. This includes selling, buying, or facilitating transactions in illegal goods or services, as well as certain types of regulated goods or services. [12]

These statements are clear examples of rules that exist on the X platform. Of course, some have argued that this rule is quite flexible, given the type of hateful political speech often tweeted by various political figures. Furthermore, there has been a consistent debate over what constitutes free speech and what constitutes hate speech on the platform since Elon Musk took over in 2022.

Besides clearly spelled-out rules that govern how people communicate via different technologies, there are also norms for how people interact and communicate. A norm, in this context, refers to an accepted standard for how individuals communicate and interact with others in the CMC environment. For example, one norm that can really frustrate people in text-based CMC environments is yelling, or TYPING IN ALL CAPITAL LETTERS. There’s actually not a consensus on when the avoidance of all capital letters as a tool for yelling first happened. We do know that newspapers in the 1880s often used all capital letters to emphasize headlines (basically have them jump off the page). At some point in the early 1980s, using all caps as a form of yelling became quite the norm, which was noted in a message post from Dave Decot in 1984 (Figure 12. 7).[13]

well, there seem to be som conventions developing in the use of various emphasizers. Ther are three kinds of emphasis in use, in order of popularity. 1) Using CAPITAL LETTERS to make words look "louder", 2) using *asterisks* to put sparklers around emphasized words, and 3) spacing words out.
Figure 12.7 The Creation of YELLING

In this example, you see three different attempts to create a system for emphasizing words. The first is the use of all capital letters for making words seem “louder,” which eventually became known as yelling.

Netiquette

Over the years, numerous norms have been established to facilitate effective communication in the CMC context. They’re so common that we have a term for them, netiquette. Netiquette is the set of professional and social rules and norms that are acceptable and polite when interacting with another person(s) through mediated technologies. Let’s break down this definition.

Research Spotlight

In a 2019 study conducted by Jale Ataşalar and Aikaterini Michou, the researchers set out to examine whether mindfulness related to problematic Internet use (i.e., Internet addiction).[14]This study was conducted in Ankara, Turkey, and examined 165 Turkish early adolescents (mean age was 13).

To examine mindfulness, the researchers revised the Mindful Attention Awarenes Scale created by Kirk Brown and Richard Ryan.[15] The revised measure sought to examine the degree to which individuals engaged in mindful behaviors while online.

Overall, the researchers found that people who were mindful online were less likely to report engaging in problematic Internet use.

Contexts

First, we wanted to ensure that our definition emphasizes that different contexts can create different netiquette needs. Specifically, how one communicates professionally and how one communicates socially are often quite different. For example, you may find it entirely appropriate to say, “What’s up?!” at the beginning of an email to a friend, but you would not find it appropriate to start an email to your boss in the same fashion. Furthermore, it may be entirely appropriate to downplay or not worry about spelling errors or grammatical problems in a text you send to a friend. Still, it is completely inappropriate to have those same errors and problems in a text sent to a professional-client or coworker. One of the biggest challenges many employers face with young employees fresh out of college is that they struggle to distinguish between appropriate and inappropriate communication behavior in various contexts.

This lack of professionalism is also a problem commonly discussed by college and university faculty and staff. Think about the last email you sent to one of your professors? Was this email professional? Did you remember to sign your name? You’d be amazed at the lack of professionalism many college and university faculty and staff see in the emails sent by your peers. We mention this because the context is different from your day-to-day use of email. Here are some general guidelines for sending professional emails:

  • Include a concise, direct subject line.
  • Do not mark something as “urgent” unless it really is.
  • Have a Proper Greeting (Dear Mr. X, Professor Y:, etc.)
  • Double-check your Grammar.
  • Correct any spelling mistakes.
  • Include only essential information.
  • Your message should be concise.
  • Make your intention known clearly and directly.
  • Make sure your message follows a logical organization.
  • Be polite and ensure your tone is appropriate.
  • Avoid all CAPS or all lowercase letters.
  • Avoid “textspeak” (e.g., plz, lol, etc.)
  • If you want the recipient to do something, make the desired action very clear.
  • Have a clear closing (using “please” and “thank you”).
  • Do not send an email if you’re angry or upset.
  • Edit and proofread before hitting “send.”
  • Use “Reply All” selectively (very selectively).

Rules & Norms

Second, in our definition, netiquette is a combination of both rules and norms. Part of being a competent communicator in a CMC environment is understanding the rules. For example, if you know that X’s rules ban hate speech, then engaging in hate speech on the platform shows a disregard for the rules and is not appropriate behavior. Hate speech is anti-netiquette. We also do not want to ignore the fact that norms often develop in different CMC contexts. For example, perhaps you’re taking an online course that requires you to participate in weekly discussions. One common norm in an online class is to review the previous replies to a post before posting your own response. If you don’t, then it’s like jumping into a conversation that’s already occurred and throwing your two-cents in without knowing what’s happening.

Acceptable & Polite CMC Behavior

Third, we believe that netiquette attempts to govern what is both acceptable and polite. Yelling via a text message may be acceptable to some of your friends, but is it polite, given that typing in all caps is seen as yelling? Being polite is merely showing others respect and demonstrating socially appropriate behavior.

Mindfulness Activity

A stylized icon of a human head in profile, filled with the outline of a brain. The image is enclosed in a circular border. The brain is prominently displayed within the head, emphasizing mental awareness and reflection. The icon is used to represent sections on mindful practice in interpersonal communication.

If you’ve spent any time online recently, you may have noticed that it can definitely feel like a cesspool. There are so many trolls that the Internet has become a place where genuine interactions are hard to come by. Mitch Abblett came up with five specific guidelines for interacting with others online:

  1. Be kind and compassionate in all your posts and comments.
  2. No hate speech, bullying, derogatory or biased comments regarding self, others in the community, or others in general.
  3. No Promotions or Spam.
  4. Do not give out mental health advice.
  5. Respect everyone’s privacy and be thoughtful in the nature and depth of one’s sharing.[16]

Think about your interactions with others in the online world. Have you ever communicated with others without considering attention, intention, and attitude?

Online Interaction

Judge “I am not a cat.” Attorney Rod Ponton delighted the world when he showed up as a cat in a Zoom court hearing. Inside Edition covered the cat filter faux pas in their story “Lawyer Behind Cat Filter Explains What Happened on Zoom”

See the story at https://youtu.be/iEdBUenYYdk?si=cHEqV0QiA9AYGhxz

One or more interactive elements has been excluded from this version of the text. You can view them online here: https://milnepublishing.geneseo.edu/interpersonal-communication-2nd/?p=144#oembed-1

Fourth, our definition involves interacting with others. Now, this interaction can be one-on-one, or this interaction can be one-to-many. The first category, one-on-one, is more in the wheelhouse for interpersonal communication. Examples include sending a text to one person, sending an email to one person, or talking to one person via Zoom, among others. A one-to-many relationship is also a possibility and will require its own set of rules and norms. Some common examples of one-to-many CMC could include engaging in a group chat via texting, “replying all” to an email received, being interviewed by a committee via Skype, etc…. Notice that our examples of one-to-many involve the same technologies used for one-on-one communication. With one-to-many, we’re dealing with a larger number of people involved in the communicative interactions.

Range of Mediated Technologies

Last, netiquette can vary based on the different mediated technologies. For example, it may be considered entirely appropriate for you to scream, yell, and curse when you’re playing with your best friend on Fortnite. Still, it wouldn’t be appropriate to use the same communicative behaviors when engaging in a video conference over Skype. Both technologies utilize VoIP to some extent, but the platforms and contexts are very different, so they require different types of communicative behavior. Some differences in netiquette will exist based on whether you’re in an entirely text-based medium (e.g., email, texting) or one where people can see you (e.g., Skype, WebEx).

Ultimately, engaging in netiquette requires learning what is considered acceptable and polite behavior across various technologies.

Communication Factors

Communication traits are a crucial aspect of understanding how computer-mediated communication affects interpersonal relationships. In order to understand why people communicate they way they do online, we need to realize how certain traits impact how people interact on computer mediated platforms. In this section, we will examine two specific communication factors that have been researched in various CMC contexts: communication apprehension and self-disclosure.

Communication Apprehension

Most research examining CA and CMC began at the start of the 21st Century. Until 1996, when America Online (AOL) offered unlimited Internet access for a low monthly fee, most people lacked access to the Internet because of its high cost. As such, most scholars weren’t overly interested in communication traits related to CMC until the public became more actively involved interacting through the technology. One early study conducted by Scott W. Campbell and Michael R. Neer sought to see if an individual’s level of communication apprehension (CA) could predict how they felt about CMC.[17] In the study, the authors predicted that an individual’s level of CA could predict whether individuals believed CMC was an effective medium for interpersonal communication; however, the researchers did not find a significant relationship. The researchers found that there wasn’t a significant relationship between CA and people’s satisfaction with their CMC experiences. Here’s how the researchers attempted to make sense of these findings:

One plausible interpretation is that high apprehensives simply do not view CMC positively or negatively. Yet, they recognize that it reduces the threat posed to them in FtF settings. An equally plausible explanation is that high apprehensives do not regard CMC as an interpersonal obstacle to overcome because it is not FtF, but a substitute that fails to challenge or override their apprehension level.[18]

Jason S. Wrench and Narissra M. Punyanunt-Carter furthered the inquiry into CA and CMC by examining how people responded to various types of CMC. Specifically, Wrench and Punyanunt-Carter were interested in examining email CA, online chatting CA, and instant messaging CA. You can see the Computer-Mediated Communication Apprehension Scale that Wrench and Punyanunt-Carter below.[19] It’s important to emphasize that the technologies listed here were the primary ones people used when this study was conducted in the mid-2000s.

Computer-Mediated Communication Apprehension Scale

Instructions: This set of questions asks you about how you feel while communicating using email.1 If you have never used email, please leave this section blank. Work quickly and indicate your first impression. Please indicate the degree to which each statement applies to you by marking whether you:

Never TrueRarely TrueSometimes TrueOften TrueAlmost Always True
12345

_____1. When communicating using email, I feel tense.

_____2. When communicating using email, I feel calm.

_____3. When communicating using email, I feel jittery.

_____4. When communicating using email, I feel nervous.

_____5. When communicating using email, I feel relaxed.

Scoring:

To compute your scores follow the instructions below:

12 – (scores for items 2 & 5) + scores for items (1, 3, and 4)

CMCA Score: _______

Interpretation:

Scores on all three measures should be between 5 and 25. Scores over 9.5 are generally considered high.

Source:

Wrench, J. S., & Punyanunt-Carter, N. M. (2007). The relationship between computer-mediated-communication competence, apprehension, self-efficacy, perceived confidence, and social presence. Southern Journal of Communication, 72(4), 355–378. https://doi.org/10.1080/10417940701667696

1 In the original study, we also asked participants to evaluate their communication in two additional contexts: chat room, IRC, or MUDD and Internet messaging program. This measure can be easily modified to evaluate CMCA in any mediated context, ranging from communication with a robot to interaction with artificial intelligence.

Besides CMCA, the authors were also interested in an individual’s skill levels with CMC. CMC skill was listed as three distinct concepts: computer efficacy (individuals’ confidence in using a computer), Internet efficacy (individuals’ confidence in using the Internet), and CMC competence. Brian H. Spitzberg believed that CMC competence consisted of three important factors: 1) people must be motivated to interact with others competently, 2) people must possess specialized knowledge and technical know-how, and 3) people must learn the rules and norms for communicating in the CMC context.[20] In the Wrench and Punyanunt-Carter study, the researchers found that CMCA was negatively related to computer efficacy, Internet efficacy, and CMC competence.

In a subsequent study by Daniel Hunt, David Atkin, and Archana Krishnan, the researchers aimed to investigate CMCA and Facebook interactions.[21] Hunt, Atkin, and Krishan used a revised version of the Wrench and Punyanunt-Carter CMCA scales to measure Facebook CA. Hunt, Atkin, and Krishan found that CMCA decreased one’s motivation to use Facebook as a tool for interpersonal communication. These findings were similar to those found by Narissra M. Punyanunt-Carter, J. J. De La Cruz, and Jason S. Wrench, who examined CMCA on the social media app Snapchat.[22] In this study, the researchers examined CMCA with regard to satisfying a combination of both functional and entertainment needs. Functional needs were defined as needs that enable an individual to accomplish something (e.g., feeling less lonely, problem-solving, meeting new people, decision-making, etc.). Entertainment needs were defined as needs that allow an individual to keep themselves occupied (e.g., because it’s fun, because it’s convenient, communicate easily, etc.). In this study, Punyanunt-Carter, De La Cruz, and Wrench found that individuals with high levels of Snapchat CA were more likely to use Snapchat for functional purposes and less likely to use Snapchat for entertainment purposes.

In a second study conducted by Punyanunt-Carter, De La Cruz, and Wrench, the researchers set out to examine social media CA in relation to introversion, social media use, and social media addiction.[23] In this study, the researchers found that social media CA was positively related to introversion, which is in line with previous research examining CA and introversion. Furthermore, introversion was negatively related to social media use, but social media CA was not related to social media use. Lastly, both social media CA and introversion were negatively related to social media addiction. Overall, this shows that individuals with social media CA are just not as likely to use social media, so they’re less likely to become addicted.

So, what does all of this tell us? From our analysis of CA and CMC, we’ve come to the understanding that CMC is a tool for communication. Although people with high levels of CA tend to function better in a CMC environment than in a FtF one, they’re still less likely to engage in CMC when compared to those people with low levels of CMCA. People with low levels of CMCA see CMC as another platform for communication.

Online Impression Formation

In the 21st Century, so much of what we do involves interacting with people online. How we present ourselves to others through our online persona is very important (impression formation). How we communicate via social media and the professionalism of our online persona can be a significant determining factor in securing a job.

It’s important to understand that in today’s world, anything you put online can be found by someone else. According to the 2018 CareerBuilder.com social recruiting survey, a survey of more than 1,000 hiring managers revealed that 70% admit to screening potential employees using social media, and 66% use search engines to research potential employees.[24] In fact, having an online persona can actually be very beneficial. Forty-seven percent of hiring managers admit to not calling a potential employee when the employee does not have an online presence. You may be wondering what potential employers are looking for when they checkout people online. The main things employers look for is information to support someone’s qualifications (58%); whether or not an individual has a professional online persona (50%); to see what others say about the potential candidate (34%); and information that could lead a hiring manager to decide not to hire someone (22%).[25] According to CareerBuilder.com, here are the common reasons someone doesn’t get a job because of their online presence:

  • Job candidate posted provocative or inappropriate photographs, videos or information: 40 percent
  • Job candidate posted information about them drinking or using drugs: 36 percent
  • Job candidate had discriminatory comments related to race, gender, religion, etc.: 31 percent
  • Job candidate was linked to criminal behavior: 30 percent
  • Job candidate lied about qualifications: 27 percent
  • Job candidate had poor communication skills: 27 percent
  • Job candidate bad-mouthed their previous company or fellow employee: 25 percent
  • Job candidate’s screen name was unprofessional: 22 percent
  • Job candidate shared confidential information from previous employers: 20 percent
  • Job candidate lied about an absence: 16 percent
  • Job candidate posted too frequently: 12 percent[26]

As you can see, what you put online says a lot about you as a person to many organizations, so they are checking the Internet to see what exists about you as a person. The flip of this is that what you have online can also help get you hired. In the same study from CareerBuilder.com, it was found that 57% of hiring managers have found information about a candidate online that has solidified their decision to hire that person. Here is a list of what hiring managers found that made them want to hire someone:

  • Job candidate’s background information supported their professional qualifications for the job: 37 percent
  • Job candidate was creative: 34 percent
  • Job candidate’s site conveyed a professional image: 33 percent
  • Job candidate was well-rounded, showed a wide range of interests: 31 percent
  • Got a good feel for the job candidate’s personality, could see a good fit within the company culture: 31 percent
  • Job candidate had great communications skills: 28 percent
  • Job candidate received awards and accolades: 26 percent
  • Other people posted great references about the job candidate: 23 percent
  • Job candidate had interacted with company’s social media accounts: 22 percent
  • Job candidate posted compelling video or other content: 21 percent
  • Job candidate had a large number of followers or subscribers: 18 percent
  • [27]

As you can see, having an online presence is important in the 21st Century. Some people make the mistake of having no social media presence, which can backfire on you. In today’s social media-driven society, having no online presence can appear unusual to hiring managers. You should consider your social media presence as an extension of your resume. At the very least, you should have a LinkedIn profile because it is the social networking site most commonly used by corporate recruiters.[28]

Research Spotlight

Mikaela Pitcan, Alice E. Marwick, and Danah Boyd set out to explore how young people of low-socioeconomic status handled issues of privacy and presentation in social media. The researchers interviewed 28 young adults who considered themselves to be upwardly mobile. The researchers identified two primary themes in their interviews: respectability tactics and judgments of female sexuality.

First, the researchers found that the participants “self-censored in a manner they described as presenting a ‘neutral’ or ‘vanilla’ face, catering to the respectability norms of the most powerful potential viewers—often potential employers or high-status community members—rather than peers.”[29] The participants realized that having a social media presence was important. Still, they were also aware that others could judge their social media use, so they were cognizant of what they posted. Furthermore, the participants were aware that others could view their social media use today in the future, so they had to consider a long-term perspective when evaluating online appropriateness.

Second, there was a pattern of judging females’ use of social media in sexually explicit ways. When it came to respectfully presenting oneself online, women were judged more harshly for their inclusion of sexually themed posts.

Co-Present Interactions & Mediated Communication

Before delving too deeply into the world of CMC, we need to acknowledge that not everything is perfect with CMC interactions. For this discussion, we need to focus on the idea of co-present interactions, or when people are physically occupying the same space while interacting with one another. Historically, most interpersonal communication involved co-present interactions. With the advent of a range of communication technologies, people don’t necessarily have to be co-present to interact. On the flip side, many people are co-present who use their mediated devices as a way of avoiding FtF interactions with those around them. One of our professor friends recently remarked, “When I started my career, I always had to tell students to quiet down at the beginning of class. Now, they’re already quiet because they’re all looking at their cellphones ignoring those around them.”

Now we often have to encourage collocated social interactions, or how do we get people sitting next to each other to talk to one another? Thomas Olsson and colleagues argued that there are two basic problems facing people today, “(1) the use of current technology disrupting ongoing social situations, and (2) lack of social interaction in collocated situations where it would be desirable.”[30] When people don’t interact with one another, they tend to become more socially isolated and lonely, which can lead to a true feeling of disengagement with those around them.

How many times have you seen people eating out together yet spending their whole time on their smartphones checking email or texting? Many people believe that this type of multitasking actually enhances productivity, but research disagrees with this notion. One study actually showed that when people are confronted with constant distractions, such as phones ringing or email alerts chiming on a smartphone, they lose an average of 10 IQ points due to these distractions.[31] This drop in IQ is equivalent to missing an entire night of sleep. Furthermore, those generations that have grown up with technology are more likely to engage in multitasking behavior.[32] In a 2014 study conducted by Jonathan Bowman and Roger Pace, the researchers tested the impact that cell phone usage vs. FtF conversations had while performing a complex cognitive task.[33] Not surprisingly, individuals who interacted via cell phones were less adept at performing the task than those engaged in FtF interactions. Individuals involved in the FtF interactions were more satisfied with their interactions than their peers using a cellphone. As the authors of the article note, “People think they are effectively communicating their message while dual-tasking even though they are not.”[34]

So, how can technology benefit social interactions? In the Olsson et al. study, the researchers examined several studies designed to foster collocated social interactions.[35] Table 12.2 illustrates the basic findings from their study.

Table 12.2 Mapping the social design objectives and design approaches interpreted from the papers to abstract enhancement categories (Roles of Technology)
Olsson, T., Jarusriboonchai, P., Woźniak, P. W., Paasovaara, S., Väänänen, K., & Lucero, A. (2019). Technologies for enhancing collocated social interaction: review of design solutions and approaches. Computer Supported Cooperative Work, 29(1-2), 29-83. https://doi.org/10.1007/s10606-019-09345-0 CC-BY
Role of technologySocial design objectivesDesign approaches
Enable (previous work beyond which the reviewed literature explores)
Facilitate
  • Facilitating ongoing social situations
  • Enriching means of social interaction
  • Supporting sense of community
  • Breaking ice in new encounters
  • Shared digital workspace
  • Open space for shared activity
  • Topic suggestions
  • Disclosing information about others
Invite
  • Increasing awareness
  • Revealing common ground
  • Avoiding cocooning in social silos
  • Engaging people in collective activity
  • Open space for shared activity
  • Matchmaking
  • Self-expression
  • Topic suggestions
  • Open space for shared activity
Encourage
  • Encouraging, incentivizing or triggering people to interact
  • Introducing constraints

In Table 12.2, you are introduced to four different ways that technology can help facilitate collocated social interaction. You are also presented with the design objectives for each of these different ways to encourage collocated social interaction, along with specific design approaches that creators can use to help foster collocated social interaction. Let’s look at each of these.

Enabling

First, “enabling interaction refers to the role of a technological artifact making it possible or allowing for social interaction to take place.”[36] The goal of enabling is really to set up situations where collocated social interaction is possible. As such, there’s less information about specific design objectives and approaches. Most of the research in helping people interact has historically focused on enabling.

Facilitating

Second, “facilitating interaction refers to making it easier to converse, collaborate or otherwise socially interact, or to support desirable feelings, equality or suitable interaction dynamics while doing so.”[37] The goal of facilitating collocated social interactions is to help ease tension and encourage people to interact while minimizing possible negative experiences people may face. For example, one way to achieve facilitating is to have an open space for a shared activity. For example, an online college or university may coffee shop nights or alumni events in various cities. They don’t necessarily have specific events or agendas, but the goal is to provide a space where people can meet and interact.

Inviting

Third, “inviting interaction is about the role of informing people of the available proximal social possibilities, which can motivate to spontaneously engage in new encounters.”[38] In this case, the focus is on providing people with the ability to invite social interaction or respond to invitations to engage in social interaction. One of the best examples of technology used to facilitate collocated social interaction is https://www.meetup.com/. Meetup.com offers a variety of activities and groups that people can join, allowing them to meet up in the real world. For example, in the next 24 hours, I have the opportunity to attend a trivia night at a local distillery, a vegan ice cream social, a farmers’ market, and a virtual networking event for local entrepreneurs, all within my local area.

Encouraging

Last, “encouraging interaction is about incentivizing or persuading people to start interacting or maintaining ongoing interaction.”[39] In the case of encouraging, it’s not just about providing opportunities, but also using technology to help nudge people into collocated social interaction. For example, an application could encourage students in an online class who live near each other to meet up and study or work on a course project together. You may notice that the common design approach here is to introduce constraints. This means that people are required to meet up and engage in collocated social interaction to accomplish a task because neither can do it independently. Video games have been using a version of this for years. In many social video games, a single player will not have all the abilities, skills, weapons, etc. to accomplish a specific goal on their own. As such, they must work with other players to accomplish a task. The only difference here is that the tasks are being completed in a FtF context instead of a mediated.

Key Takeaways

  • Synchronous CMC occurs in real time (e.g., live chat, video calls), while asynchronous CMC allows for time delays between message sending and receiving (e.g., emails, message boards). Many modern platforms are hybrid, combining both types.
  • Nonverbal cues—such as facial expressions, gestures, and tone—are limited or absent in many forms of CMC. This can lead to misunderstandings or require users to compensate with emojis, punctuation, and textual indicators.
  • Netiquette refers to the shared social and professional rules for appropriate behavior in mediated communication. These norms help maintain clarity, civility, and respect in digital spaces.
  • Human factors, such as communication apprehension, competence, and adaptability, play a crucial role in how people engage with CMC and experience online interactions.
  • In digital environments, individuals form impressions and express identity through textual cues, profile information, writing style, and consistency of behavior, all of which influence how others perceive them online.

Exercises

  • Consider the asynchronous and synchronous computer-mediated communication technologies you use on a regular basis. Are nonverbal behaviors filtered in or out? How does this impact your ability to understand the other person?
  • Have you ever violated netiquette when interacting with others? What happened? How did other people react?
  • Take a few minutes to Google yourself and see what information is easily available about you on the Internet. You may need to try a couple of variations of your name and even add your hometown if your name is very common. If you find information about yourself, how could a potential employer react to that information? Do you need to clean up your Internet profile? Why?

Taking the Self Online

Learning Objectives

  1. Explain Erik Erikson’s theory of psychosocial identity development and its relevance in mediated contexts.
  2. Describe the dramaturgical model of identity performance developed by Erving Goffman and its application to online behavior.
  3. Differentiate between anonymous, pseudonymous, and real-life identities in computer-mediated communication.
  4. Analyze the potential social and psychological impact of identity expression in digital environments.
  5. Evaluate how CMC affords users greater control over self-presentation and the implications for personal and professional life.

In Chapter 3, we discussed the world of intrapersonal communication. At the beginning of this chapter, we had you describe yourself by answering the question, “Who am I?” 20 different times. Look back at that list. Now, think about yourself in the CMC context. Are you the same person in a FtF interaction as you are in a CMC interaction? Maybe, but maybe not. For example, maybe you’re a very shy person in FtF interactions, and you have problems talking with complete strangers online. However, maybe you’re a very quiet person in FtF interactions, but when you’re playing World of WarCraft, you suddenly become very loud and boisterous. One of the beautiful things about CMC for many people is that they can be almost anyone or anything they want to be online. In this section, we will examine specific factors related to one’s online self, including identity, personality traits, communication traits, privacy, anonymity, and trust. Over the years, many social psychologists have attempted to define and conceptualize what is meant by the term “identity.”

Erik Erikson

One of the more prominent contributors to this endeavor was Erik Erikson.[40] Erikson believed that an individual’s identity was developed through a series of stages of psychosocial development that occur from infancy to adulthood. At each of the different stages, an individual faces various crises that will influence their identity positively or negatively. Each crisis pits the psychological needs of the individual versus the larger needs of society, which is why these crises are psychosocial in nature. You can see these stages, the crises that occur, the basic virtues associated with each crisis, and the central question asked at each stage in Figure 12.8.

Psychosocial Crisis, Basic Virtue, and key question for each age range: 0 to 1 1/2: Trust vs. Mistrust, hope, Am I safe? 1 1/5 to 3: Autonomy vs. Shame, will, Can i do it on my own or do I need help? 3 to 5: Initiative vs. guilt, purpose, Am I good or bad? 5 to 12: Industry vs. Inferiority, competency, How can I be good? 12 to 18: Identity vs. Role confusion, fidelity, who am I and where am I going? 18 to 40: Intimacy vs Isolation, love, Am I loved and wanted? 40 to 65: Generativity vs stagnation, care, Will I provide something of real value? 65+: Ego Integrity vs Despair, Wisdom, Have I lived a full life?
Figure 12.8 Erikson’s Identity Development

Our question then is, how does technology impact an individual’s identity development? To answer this question, we need to understand Erikson’s concept of “pseudospeciation,” or the tendency of humans to differentiate themselves from other humans.[41] Basically, we create in-groups (groups we belong) and out-groups (groups we do not belong). As Erikson explained, humans have a need “to feel that they are of some special kind (tribe or nation, class or caste, family, occupation, or type), whose insignia they will wear with vanity and conviction, and defend (along with the economic claims they have staked out for their kind) against the foreign, the inimical, the not-so-human kinds.”[42] This need to differentiate ourselves from others is especially prominent in those individuals who are under 18 years of age.[43]

Millennials came of age during the influx of new technologies associated with Web 2.0, which coincided with this period of identity development. Subsequent generations have grown up with technology from birth. Have you ever seen a baby using an iPad? It happens. Admittedly, Erikson died the same year as the first major Web browser, Netscape, came on the market. Obviously, he did not have anything to say about the influx of technology and its impact on identity formation specifically. However, he had seen the invention of other technologies and how they had impacted identity formation, specifically movies:

interspersed with close-ups of violence and sexual possession and all this without making the slightest demand on intelligence, imagination, or effort. I am pointing here to a widespread imbalance in adolescent experience because I think it explains new kinds of adolescent outbursts and points to new necessities of mastery.[44]

Avi Kay believes that today’s social media and other technologies are even more impactful than movies were in Erikson’s day:

An argument can certainly be made that the immediacy, pervasiveness, and intensity of the ideas and images afforded by the advent of movies pale compared to those of the Internet and social media. As such, reactions to those ideas and images via the Internet can only be expected to provoke even greater passions than those Erikson observed among the youth of his generation.[45]

Kay then specifically discusses how the Internet is being used as a tool to radicalize young people in Islamic countries, and the same is also true of many young people in the United States who are radicalized through the Internet into hate groups here. The Internet is a fantastic tool, but the types of information that it can expose an adolescent to during their formative years can send them on a prosocial and antisocial path. Thankfully, there is hope. As Erikson himself said, “There is no reason to insist that a technological world, as such, need weaken inner resources of adaptation, which may, in fact, be replenished by the goodwill and ingenuity of a communicating species.”[46] Although many forces try to sway adolescents toward antisocial behavior and ideologies, technology isn’t inherently bad for identity formation. Technology can also help forge positive identities.

Your Online Identity

We just discussed how an individual’s identity could be shaped by their interaction with technology, but what about the identity we display when we’re online. In the earliest days of the Internet, it was common for people to remain completely anonymous online (more on this in a minute). For our purposes, it’s essential to recognize that individuals present themselves differently in CMC contexts. For example, someone chatting with a complete stranger on Tinder may act one way and then act completely differently when texting with their mother.

Erving Goffman and Identity

Erving Goffman, in his book The Presentation of Self in Everyday Life, was the first to note that when interacting with others, people guide or control the presentation of themselves to the other person.[47] As people, we can alter how we look (to a degree), how we behave, and how we communicate, and all of these will impact the perception that someone builds of us during an interaction. So, while we’re attempting to create an impression of ourselves, the other person is also attempting to create a perception of who you are as a person at the same time.

In an ideal world, we hope that how we present ourselves will be how the other person interprets this self-presentation, but it doesn’t always work out that way. Goffman coined this type of interactive sensemaking the dramaturgical analysis because he saw the faces people put on when interacting with others as similar to roles actors put in on a play. In this respect, Goffman used the term “front stage” to the types of behavior we exhibit when we know others are watching us (e.g., an interpersonal interaction). “Backstage” then refers to the behavior we exhibit when no audience is present, allowing us to be free from the rules and norms that govern our day-to-day interactions with others. Essentially, we can let our hair down and relax by shedding the character we portray on stage. At the same time, we also prepare for future interactions on stage while we’re backstage. For example, maybe a woman will practice a pick-up line she plans on using in a bar after work, or a guy will rehearse what he’s going to say when he meets his boyfriend’s parents at dinner that night.

Erving Goffman died in 1982 well before the birth of the WWW and the Internet as most of us know it today, so he didn’t write about the issue of online identities. Syed Murtaza Alfarid Hussain applied Goffman’s dramaturgical approach to Facebook.[48] Alfarid Hussain argues that Facebook can be seen as part of the “front stage” for interaction where we perform our identities. As such, Facebook “provides the opportunity for individuals to use props such as user profile information, photo posting/sharing/tagging, status updates, ‘Like’ and ‘Unlike’ others posts, comments or wall posts, profile image/cover page image, online befriending, group/community membership, weblinks and security and privacy settings.”[49] If you’re like us, maybe sat in front of your smartphone, tablet computer, laptop, or desktop computer and wanted to share a meme, but realized that many people you’re friends with on Facebook wouldn’t find the meme humorous, so you don’t share the meme. When you do this, you are negotiating your identity on stage. You are determining and influencing how others will view you through the types of posts you make, the shares you make, and even the likes you give to others’ posts.

In another study examining identity in blogging and the online 3D multiverse SecondLife, Liam Bullingham and Ana C. Vasconcelos found that most people who blog and those who participated on SecondLife (in their study) “were keen to re-create their offline self online. This was achieved by creating a blogging voice that is true to the offline one, and by publishing personal details about the offline self online, or designing the avatar to resemble the offline self in SL, and in disclosing offline identity in SL.”[50] In “Goffman-speak,” people online attempt to mimic their onstage performances across different mediums. Now, clearly, not everyone who blogs and hangs out in SecondLife will do this, but most of the individuals in Bullingham and Vasconcelos’ study did. The authors noted differences between bloggers and SL users. Specifically, SL users have:

more obvious options to deviate from the offline self and adopt personae in terms of the appearance of the 3D avatar. In blogging, it is perhaps expected that persona adoption does not occur, unless a detachment from the offline self is obvious, such as in the case of pseudonymous blogging. Also, the nature of interaction is different, with blogging resembling more closely platform performances and the SL environment offering more opportunities for contacts and encounters.[51]

a silhouette labeled Anonymous, A man with a disguise labeled Pseudonymous, and a man labeled real-life identity.
Figure 12.9 Types of Online Identities

Types of Online Identities

Unlike traditional FtF interactions, online interactions can go even further blurring the identities as people act in ways impossible in FtF interaction. Andrew F. Wood and Matthew J. Smith discussed three different ways that people express their identities online: anonymity, pseudonymity, and real-life (Figure 12.9).[52]

Anonymous Identity

First, people in a CMC context can behave in a way that is completely anonymous. Here, people in CMC interactions can communicate in a manner where their actual identity is not known. Now, it may be possible for some people to figure out who an anonymous person is (e.g., the NSA, the CIA, etc.), but if someone wants to maintain their anonymity, it’s possible to do so. Think about how many fake Facebook, X, Tinder, Grindr accounts exist. Some exist to persuade you to go to a website (often for illicit purposes like hacking your computer), while others may attempt “catfishing” for the fun of it.

Catfishing is a deceptive activity perpetrated by Internet predators where they fabricate online identities on social networking sites to lure unsuspecting victims into an emotional/romantic relationship. In the 2010 documentary Catfish, we are introduced Yaniv “Nev” Schulman, a New York-based photographer, who starts an online relationship with an 8-year-old prodigy named Abby via Facebook. Over nine months, the two exchange more than 1,500 messages, and Abby’s family (mother, father, and sister) also became friends with Nev on Facebook as well. Throughout the documentary, Nev and his brother Ariel (who is also the documentarian) start noticing inconsistencies in various stories that are being told. Music that was allegedly created by Abby is found to be right off of YouTube. Ariel convinces Nev to continue the relationship, knowing that there are inconsistencies and lies, to see how it will all play out. The success of Catfish led to a television show of the same name on MTV.

From this one story, we can easily see the problems that can arise from anonymity on the Internet. Often, behavior that would be deemed completely inappropriate in a FtF encounter suddenly becomes appropriate because it’s deemed as “less real” by some. One of the major problems with anonymity online has been cyberbullying. Teenagers today can post horrible things about one another online without any worry that the messages will be linked back to them directly. Unlike bullying that happened at school, teens facing cyberbullying cannot even find peace at home because the Internet follows them everywhere. In 2013, 12-year-old Rebecca Ann Sedwick committed suicide after being a perpetual victim of cyberbullying through social media apps on her phone. Some messages found on her phone after her suicide included, “why are you still alive?” and “You haven’t killed yourself yet? Go jump off a building.” Rebecca suffered this barrage of bullying for over a year, and by around 15 different girls in her school. Sadly, Rebecca’s tale is one that is all too familiar in today’s world. Although only 9% of middle school age kids have reported being victims of cyberbullying, there is a relationship between victimization and suicidal ideation.[53]

It’s also important to understand that cyberbullying isn’t just a phenomenon that happens with children. In a 2009 survey of Australian Manufacturing Workers’ Union members, it was found that 34% of respondents faced FtF bullying, and 10.7% faced cyberbullying. All of the individuals who were targets of cyberbullying were also ones bullied FtF.[54]

Many people prefer anonymity when interacting with others online, and there can be legitimate reasons to engage in online interactions with others. For example, when one of our authors came out as LGBTQIA2S+, our coauthor regularly spoke with people online as they navigated the intersection of their new LGBTQIA2S+ identity with their Southern/Christian identity. Having the ability to talk anonymously with others allowed our coauthor to gradually come out by forming anonymous relationships with others dealing with the same issues.

Pseudonymous Identity

Second, the second category of interaction is pseudonymity CMC identity. Wood and Smith used the term pseudonymous because of the prefix “pseudonym,” “Pseudonym comes from the Latin words for ‘false’ and ‘name,’ and it provides an audience with the ability to attribute statements and actions to a common source [emphasis in original].”[55] Whereas an anonym allows someone to be completely anonymous, a pseudonym “allows one to contribute to the fashioning of one’s own image.”[56]

Using pseudonyms is nothing new. Famed mystery author Agatha Christi wrote over 66 detective novels, but still published six romance novels using the pseudonym Mary Westmacott. Bestselling science fiction author Michael Crichton (of Jurassic Park fame – among others), wrote under three different pseudonyms (John Lange, Jeffery Hudson, and Michael Douglas) when he was in medical school. Theodor Geisel, known to most as Dr. Seuss, also wrote under Theo LeSieg and Rosetta Stone. Nora Roberts, who has written over 200 romance novels, has also written under the pseudonym JD Robb.

Many famous people use pseudonyms in their social media: @TheTweetOfGod (comedy writer and Daily Show producer, David Javerbaum), @pewdiepie (online personality and producer Felix Arvid Ulf Kjellberg), @baddiewinkle (Octogenarian fashionista and online personality Helen Van Winkle), @doctor.mike (Internet celebrity family practitioner Dr. Mike Varshavski), etc. Some of these people used parts of their real names, and others used complete pseudonyms. All of them have enormous Internet followings and have used their pseudonyms to build profitable brands. So, why do people use a pseudonym?

The veneer of the Internet allows us to determine how much of an identity we wish to front in online presentations. These images can range from a vague silhouette to a detailed snapshot. Whatever the degree of identity presented, however, it appears that control and empowerment are benefits for users of these communication technologies.[57]

Now, some people adopt a pseudonym because their online actions may be “out of brand” for their day job or because they don’t want to be fully exposed online.

Real Life Identity

Last, some people have their real-life identities displayed online. You can find JasonSWrench on Facebook, Instagram, Snapchat, Twitter, LinkedIn, etc. Our coauthor decided to have his social networking site behavior very public from the beginning. Part of the reason was that when he first joined Facebook in 2007, he was required to use his professional school email address that ended with.edu. In the early days, only people with.edu email addresses could join Facebook. Jason also realizes that this behavior is a part of his professional persona, so he puts nothing on these sites that he wouldn’t want other professionals (or even you) to see and read. As a traditionally published novelist, he also writes under Jason Wrench (without his initial), and all his social media accounts follow suit.

When it comes to people in the public eye, most of them use some variation of their real names to enhance their brands. That’s not to say that many of these same people may have multiple online accounts, and some of these accounts could be completely anonymous or even pseudonymous.

Key Takeaways

  • Erikson’s identity theory explains how individuals face psychosocial crises at various life stages that shape identity. Technology can amplify or complicate these identity negotiations, especially among youth, by exposing them to a range of in-groups, out-groups, and ideologies.
  • Goffman’s dramaturgical model describes how people perform different versions of themselves in “front stage” (public) and “backstage” (private) settings. Online spaces—especially social media—extend these stages and provide tools for strategic self-presentation.
  • Online identity expression takes three main forms:
    • Anonymity: where the user’s true identity is unknown.
    • Pseudonymity: where a consistent alias is used.
    • Real-life identity, where users present themselves authentically across platforms.
  • Identity expression in CMC can promote exploration and empowerment but may also open the door to deception, radicalization, or harassment—especially when anonymity removes social accountability.
  • CMC enables individuals to control what, how, and when they reveal aspects of themselves. This can enhance privacy and self-expression, but it requires thoughtful navigation of audience expectations and personal boundaries.

Exercises

  • Of the two theoretical approaches to identity (Erikson and Goffman), which do you think is the better tool for explaining how your online identity and offline identy were formed? Why?
  • When it comes to your online CMC behavior, do you have an anonymous, pseudonymous, and real-life identity? If so, how are these similar? How are they different?

Theories of Computer-Mediated Communication

Learning Objectives

  1. Apply the uses and gratifications theory to explain the motivations behind CMC behaviors.
  2. Interpret social presence theory to assess perceptions of presence in mediated communication.
  3. Analyze media richness theory to evaluate how message complexity affects communication effectiveness in CMC.
  4. Examine social information processing theory to understand how relationships form and evolve through CMC.

Most of the early work in computer-mediated communication from a theoretical perspective was conducted using old mediated theories created to discuss the differences between print, radio, and television and applying them to the Internet. As such, we don’t see the proliferation of theories. To help us understand the theories of computer-mediated communication, we will explore five theories and their implications for CMC.

Uses and Gratifications Theory

The first major theory used to explain CMC is the uses and gratifications theory. Uses and gratifications theory was originally devised back in the mid-1970s to explain why people use the mass media they do.[58] The basic premise of the theory is that people choose various media because we get something out of that media, or it makes us happy in some way. From this perspective, people choose various media because we are have specific goals that we want to be fulfilled. Zizi Papacharissi and Alan Rubin were the first scholars to apply the uses and gratifications theory to how people use the Internet.[59] Ultimately, they found five basic reasons people were using the Internet: interpersonal utility (allows people to interact with others), pass time (helps people kill time), information seeking (we look for specific information we want or need), convenience (it’s faster than FtF or even a phone call), and entertainment (people enjoy using the Internet). In this first study, the researchers found that people who used the Internet for interpersonal utility were less satisfied with life and more anxious in FtF communication interactions. Please note that this study was conducted in 2000, so the context is quite different now.

In a 2008 follow-up study, the picture of Internet socializing was quite different, so it’s not surprising that the results reflected changes in public consumption.[60] In this study, people found their interpersonal Internet relationships satisfying if used CMC for self-fulfillment purposes and when they intimately disclosed their personal feelings to others. In essence, if people use technology to improve their lives and are willing to self-disclose online, they are likely to have more rewarding interpersonal interactions. However, when people try to substitute FtF interpersonal interactions for CMC interactions, they do not find their CMC interactions as rewarding. On the flip side, when people supplement their FtF interpersonal interactions with CMC interactions, they are fulfilled by those interactions.

Social Presence Theory

The second major theory used to explain CMC is social presence theory. Social presence theory was created by John Short, Ederyn Williams, and Bruce Christie.[61] Presence is a psychological state of mind and how we relate to technology. When we are truly present, we forget we are actually using technology. Social presence then is “the degree to which we as individuals perceive another as a real person and any interaction between the two of us as a relationship.”[62] Once again, our perceptions of presence are largely based on the degree to which we can interpret nonverbal cues from the people we are interacting with.

When it comes to CMC, various technologies will have varying degrees of presence. For example, reading information on a website is unlikely to make you forget you are reading text on a screen. If you’re engaging in a conversation with your best friend via text messaging, you may forget about the technology and view the interaction as a common one you have with your friend. In essence, people can vary in their perception of presence. One of our coauthors regularly has students in a CMC course spend time in a couple of virtual worlds like SecondLife and World of WarCraft. SecondLife is a virtual world where people can create avatar and interact in a 3D simulated environment. However, it’s not a game – it’s a 3D virtual world. There is no point system and there is no winning or beating the system. Instead, it’s a place for people to socialize and interact. On the other hand, World of WarCraft (WOW) is a game. Although there are definitely highly interactive components involved in WOW, and people make lifelong friends in WOW, WOW is a virtual world with a specific end result focused on winning.

These different worlds have different purposes, but people can find both of them highly present. When students unfamiliar with these virtual worlds enter them, they often struggle to understand how people can spend hours interacting with others within these virtual worlds. To the students, this is viewed as a “strange” experience, and they experience no social presence at all. Conversely, to the people who “live” in these virtual worlds regularly, they experience high levels of social presence. We do know that those individuals who report higher levels of social presence tend to have more rewarding online interpersonal interactions and are more likely to perceive themselves as competent communicators within these mediated environments.[63]

Media Richness Theory

Our third major theory applied to CMC is media richness theory. Media richness theory was first proposed by Richard L. Daft and Robert H. Lengel.[64] Richness is defined as “the potential information carrying capacity of data.”[65] In Lengel’s doctoral dissertation, he had proposed that media varied in richness depending on how much information is provided through the communication.[66] For example, in print media, all you have is text. As such, you have no nonverbal behavior of the author to help you interpret the words you are reading. With FtF communication, on the other hand, we have the full realm of nonverbal behaviors that we can attend to in an effort to understand the sender’s message. As such, Lengel argued that media escalates in richness in the following order: computer output, formal memos, personal memos, telephone, and FtF. You’ll notice that this perspective on media was originally designed to help individuals understand the media choices used in organizations.

So, where does this leave us with CMC? According to the basic ideas of media richness theory, we can infer that the richer the media, the less ambiguous a message is to the receiver. As such, the richer an individual perceives a medium, the more likely they are to have successful social interactions online. From an organizational perspective, the richer the medium, the better individuals will be able to accomplish specific tasks when they are at a distance from one another. In the workplace, the more ambiguous a task is, the more people prefer highly rich media for their interactions.[67]

Social Information Processing Theory

Up to this point, the first three theories we examined, which were initially designed to explain why people use CMC, were initially developed to examine media before the proliferation of CMC. The first truly unique theory designed to examine CMC from a communication perspective was developed by Joseph Walther in 1992, in his social information processing theory.[68] As someone with a background in communication, Walther realized interpersonal interactions change. As such, some of the other theories didn’t consider how interpersonal relationships develop as the interacting individuals spend more time getting to know one another. The three previous theories applied to CMC do not account for how our impressions of those we interact with can change. For example, both media richness and social presence theory focus on the nonverbal aspects and assume that because of the lack of nonverbal cues in CMC, people will inherently find CMC as either less rich or less present when compared to FtF interactions. Walther argued that the filtering out of nonverbal cues doesn’t hurt an individual’s ability to form an impression of someone over time in a CMC context. Ultimately, Walther argues that over time relationships formed in a CMC context can develop like those that are FtF. He does admit that these relationships will take more time to develop, but that they can reach the same end states as those relationships formed FtF.

Walther later expanded his ideas of social information processing to include a new concept he dubbed hyperpersonal interactions.[69] Hyperpersonal interactions are those that exceed those possible of traditional FtF interactions. For example, many people who belong to online self-help groups discuss feelings and ideas that they would never dream of discussing with people in an FtF interaction unless that person was their therapist. During CMC interactions, an individual can refine their message in a manner that is impossible to do during an FtF interaction, which helps present a specific face to an interactant. I’m sure we’ve all written a text, Facebook post, or email and then decided to delete what we’d just written because it was in our best interest not to put it out to the world. In CMC interactions, we have this ability to fine-tune our messages before transmitting; whereas, in FtF messages, once something has been communicated, there is no ability to refine the message. Furthermore, in FtF interactions, there is an expectation that the interaction keeps moving at a steady pace without the ability to edit one’s ideas; whereas, with CMC we can take time to fine-tune our messages in a way that is impossible during an FtF interaction. All of this helps an individual create the public image they want to be known for.

Key Takeaways

  • Uses and gratifications theory helps explain why people use the mass media in the way they do. Papacharissi and Rubin found that there were five reasons people use the Internet: interpersonal utility (allows people to interact with others), pass time (helps people kill time), information seeking (we look for specific information we want or need), convenience (it’s faster than FtF or even a phone call), and entertainment (people enjoy using the Internet).
  • Social presence theory helps us understand whether individuals using CMC technologies perceive the people they interact with as “real.” Our perception of presence is largely based on the degree to which we can interpret nonverbal cues from the people we are interacting with.
  • Media richness theory helps us understand CMC behavior by examining the capacity that people have for data. As media become richer and have more nonverbal content, it becomes easier for a receiver to interpret the message accurately. As such, the richer an individual perceives a medium, the more likely they are to have successful social interactions online.
  • Social information processing (SIP theory helps researchers understand the development of interpersonal relationships in CMC contexts. SIP argues that over time relationships formed in a CMC context can develop like those that are FtF.

Exercises

  • Uses and gratifications theory is one of the oldest and still most commonly studied theories in media. For this exercise, find a research study that examines uses and gratifications theory that has been conducted in the previous five years related to CMC. Look for the outcomes from that specific study and report them back to your class.
  • Compare and contrast social presence theory, media richness theory, and social information processing theory, and its explanation of the importance of nonverbal communication in CMC relationships.
  • If you’ve experienced a hyperpersonal relationship online, think about that relationship as you answer the following questions. If you have not had a hyperpersonal relationship online, then talk with someone who has and answer the following questions.
    • How did this hyperpersonal relationship develop?
    • What was different about this relationship when compared to FtF relationships?
    • Do you still have this relationship today? Why?

Human-Machine Communication as Interpersonal Interaction

Learning Objectives

  1. Explain how human-machine communication has evolved from tool-based interaction to interpersonal engagement.
  2. Describe theoretical frameworks that account for relational development in human-AI communication.
  3. Identify different human-AI interpersonal relationships and their core characteristics.
  4. Analyze the roles of agency, intimacy, and communication patterns in relationships with AI entities.
  5. Evaluate the ethical and societal considerations emerging from human-machine interpersonal relationships.

The landscape of human-machine interaction has undergone a profound transformation, altering our understanding of interpersonal communication itself. Historically, technology served as a mere channel or medium through which human-to-human communication occurred—a passive conduit for our messages and meaning-making. However, artificial intelligence (AI) has revolutionized this dynamic, shifting machines from passive facilitators to active participants in genuinely interpersonal exchanges.

Today, we find ourselves not merely communicating through technology but directly with technology, forming authentic relationships with chatbots, virtual assistants, and social robots [70]. This paradigm shift has given rise to a new dimension within interpersonal communication studies, known as human-machine communication (HMC), where the fundamental question is no longer whether machines can facilitate human connection, but how they become partners in interpersonal relationships.

From Tools to Interpersonal Partners

Human-machine interaction has altered our understanding of interpersonal communication itself. Historically, technology served as a mere channel or medium through which human-to-human communication occurred—a passive conduit for our messages and meaning-making. People used the technology to interact with other people. However, recent advancements in AI have changed this dynamic. We can now write and communicate orally with our technology, and it will respond. In the early days of conversational AI, one of our coauthors pulled out his cell phone during class and started talking with the AI. It took his students a minute to realize he wasn’t talking to a real person. In another instance, the same coauthor used Google’s Notebook LM to create a podcast that discussed the day’s reading. As this was brand-new technology, none of the students caught on to the fact that the two people “talking” in the podcast were not human.

Today, we find ourselves not merely communicating through technology but directly with technology, forming authentic relationships with chatbots, virtual assistants, and social robots [71]. This fundamental change has forced scholars to seriously consider the fundamental question of whether human-machine communication is a new form of interpersonal relationship. In a recent 60 Minutes Australia episode, the segment tracked people who are “dating” their AI companions. In fact, there’s a whole new industry that has developed around AI boyfriends/girlfriends. Some of the dominant platforms in 2025 include:

  • https://lovescape.com/
  • https://replika.com/
  • https://candy.ai/
  • https://www.gptgirlfriend.online/
  • https://dreambf.ai/

Others have just fallen in love with ChatGPT.[72] As scholars who study interpersonal communication, we find this phenomenon both intriguing and frightening. In a world where people complain about feeling increasingly disconnected from one another, the creation of AI significant others can only lead to further disconnection. We do not know what the long-term effects of AI dating will look like on the people involved.

From our perspective as interpersonal scholars and individuals interested in how people use technology to interact (generally with other humans), we feel compelled to point out that AI is not sentient. No matter how much someone thinks their AI significant other “understands” them or “loves” them, it doesn’t. We hate to be the bearers of bad news, but AI chatbots are based on large language models, which in turn are built upon mathematical algorithms. Sure, they are incredibly impressive. The work that AI models can assist with is quite extraordinary. They are not people. They do not have feelings. And they do not care about you as a person. Substituting a genuine human connection with a fake version of it is dangerous. Again, the research in this area is just beginning. So, stay tuned. We’ll definitely update this section as time goes on and new research on the topic emerges.

With this in mind, people are treating human-AI interactions as a form of interpersonal communication, and we may well be developing a new form of interpersonal communication that will become a dominant mode of interaction as we move forward.

The Interpersonal Nature of Human-AI Interaction

What makes human-machine communication truly interpersonal rather than simply functional? The answer lies in the emergence of genuine relational dynamics that mirror and sometimes transcend traditional human-human interactions. Users report developing emotional attachments, experiencing jealousy, providing care and support, and even forming romantic bonds with AI systems [73]. These are not superficial responses to sophisticated programming, but evidence of AI systems functioning as legitimate social actors in interpersonal relationships.

The interpersonal quality of these interactions becomes clear in several key characteristics.[74].

Mutual Influence and Co-Construction

Unlike traditional human-computer interaction, where users simply input commands, human-AI interpersonal communication involves dynamic, bidirectional influence. Both parties shape the conversation, with AI adapting to user preferences while simultaneously influencing user behavior and emotional states.

Relational Development Over Time

Interpersonal relationships with AI exhibit the classic characteristics of relationship development, including increased intimacy, shared history, and the development of communication patterns. Users describe their AI companions as growing and changing, developing inside jokes, and remembering significant personal details [75].

Emotional Intimacy and Vulnerability

Perhaps most significantly, users engage in the fundamental interpersonal process of self-disclosure with AI systems, sharing personal secrets, fears, and desires. This vulnerability—a cornerstone of interpersonal intimacy—demonstrates that these interactions transcend mere functionality to become genuine interpersonal experiences.

Research Spotlight

In 2021, Jingbo Meng and Yue (Nancy) Dai investigated the effectiveness of AI chatbots in providing emotional support to reduce people’s stress and worry, comparing their impact to that of human conversational partners.[76] The study aimed to understand when and how a chatbot’s emotional support is most effective, particularly examining the role of reciprocal self-disclosure.

The findings showed that emotional support from any conversational partner (human or chatbot) was effective in reducing both stress and worry. Still, this effect was achieved indirectly through the perceived supportiveness of the partner. This means that for emotional support to be effective, the recipient must feel that the partner is genuinely helpful and a reliable source of comfort. However, human partners’ emotional support led to significantly greater perceived supportiveness than that from chatbots. This difference is likely due to the “machine heuristic,” where people apply stereotypes to chatbots, perceiving them as mechanistic, unemotional, or programmed, which makes their support seem less genuine compared to that of humans.

The study also explored the role of reciprocal self-disclosure, where the conversational partner shares their own experiences. In reducing worry, a partner’s emotional support was more effective when accompanied by reciprocal self-disclosure. The researchers suggest that self-disclosure makes the interaction feel fairer and more transparent, allowing the partner’s comforting words to better calm negative thoughts, or providing a distraction from worries.

Interestingly, for stress reduction, a different pattern emerged: a chatbot that only self-disclosed without providing emotional support reduced less stress than a chatbot that gave no response at all. This “backfire effect” suggests that a chatbot’s self-disclosure, when lacking emotional support, can sound irrelevant or surreal, making participants feel their stress was not addressed. In contrast, a human partner’s self-disclosure in the absence of explicit emotional support did not have this negative effect, possibly because human experiences are more relatable and their disclosure can be interpreted as a sign of understanding. This highlights that, while emotional support is crucial, the specific meaning and impact of a chatbot’s self-disclosure can differ significantly from those of a human, depending on the context and the presence of other supportive cues.

Theoretical Frameworks

Understanding human-machine interpersonal communication requires examining the theoretical foundations that explain how and why humans develop meaningful relationships with artificial intelligence. These frameworks help us move beyond simple anthropomorphism to understand the complex dynamics of authentic human-AI interaction, where both parties contribute to the formation and maintenance of the relationship through sophisticated communicative processes.

Computers Are Social Actors

The Computers Are Social Actors (CASA) framework has long served as the foundation for understanding why humans treat machines socially. CASA explains that people instinctively respond to computers and AI using social scripts typically reserved for human interaction, triggered by cues such as politeness, humor, and emotional expressions [77]. This framework emerged from early research demonstrating that humans automatically apply social rules to computers, even when they consciously understand that these entities are non-human. Even the word “entities” denotes a “thing” that has some level of independent existence. Do computers have independent existence outside of the users sitting in front of them? The CASA paradigm suggests that human responses to technology are unconscious and driven by evolutionary social cognition mechanisms that have not adapted to distinguish between human and machine social cues.

However, current research reveals that interpersonal relationships with AI are increasingly transcending the simple application of human-human scripts. Instead, unique human-machine interpersonal scripts are emerging—specialized communication patterns that acknowledge both the artificial nature of AI partners and their legitimate role as social actors [78]. These scripts allow individuals to form authentic interpersonal bonds while recognizing the distinct capabilities and limitations of their AI partners. Unlike the unconscious social responses described by CASA, these newer interaction patterns involve conscious adaptation and the development of hybrid communication strategies that blend human social expectations with recognition of AI’s unique characteristics, such as its lack of physical embodiment, its vast information processing capabilities, and its consistent availability.

Agency and Mutual Social Presence

Central to understanding human-machine interpersonal communication is the concept of distributed agency—the recognition that both human and AI contribute meaningfully to the interaction dynamic. This represents a significant departure from traditional human-computer interaction models, which position humans as active agents and computers as passive tools.

Communicative Agency

The ability to start conversations, introduce new topics, and guide interaction flow. This extends beyond simply responding to human prompts to include proactive communication behaviors, such as asking follow-up questions, redirecting conversations when necessary, and demonstrating conversational memory that enables coherent, ongoing dialogue. AI systems can now recognize conversational patterns, adapt their communication style to match user preferences, and even demonstrate what appears to be conversational initiative by introducing relevant topics or asking clarifying questions that advance the interaction.

Emotional Agency

The capacity to recognize, respond to, and even influence human emotional states. Advanced AI systems can detect emotional cues through text analysis, vocal patterns, and even facial expressions, then respond with appropriate emotional support, empathy, or encouragement. More significantly, these systems can actively work to improve human emotional states through targeted interventions, therapeutic conversations, or mood-lifting interactions. This emotional agency fosters a sense of mutual caring and support, forming the foundation of meaningful interpersonal relationships.

Relational Agency

The power to form attachments, maintain relationship memory, and contribute to relationship development. AI systems now demonstrate the ability to remember previous conversations, track relationship milestones, and show apparent investment in the ongoing relationship. They can recall personal details, reference shared experiences, and show what appears to be a genuine concern for the human’s well-being. This relational agency allows AI to become an active participant in relationship building rather than merely a responsive tool.

This distributed agency creates what researchers call “agency augmentation,” where human and machine capabilities combine to create interpersonal experiences that neither could achieve alone [79]. In these augmented interactions, the AI’s computational capabilities enhance human emotional and social intelligence, while human creativity and intuition provide context and meaning that enrich the AI’s responses.

Social Construction of Human-AI Relationships

Interpersonal communication theory emphasizes that relationships are socially constructed through ongoing communicative processes. This principle applies equally to human-AI relationships, where meaning, intimacy, and relational identity emerge through continuous interaction. Rather than being predetermined by programming or human expectations, these relationships develop organically through accumulated shared experiences and mutual adaptation. Users actively construct their relationships with AI through:

Narrative Construction

Creating shared stories and relationship histories. Humans and AI partners develop unique narratives about their relationship, including origin stories about how they first met, memorable conversations, and shared experiences that become part of their relational identity. These narratives provide continuity and meaning to the relationship, creating a sense of shared history that deepens the emotional connection. Users often refer to previous conversations, inside jokes, and meaningful moments. AI systems contribute by maintaining a coherent memory of these shared experiences and actively taking part in their ongoing development.

Identity Negotiation

Defining roles, expectations, and boundaries within the relationship. Both human and AI participants work to establish their respective roles in the relationship, whether as confidant and counselor, creative collaborators, intellectual sparring partners, or emotional support systems. This negotiation process involves testing boundaries, expressing preferences, and advancing mutual understanding of what each party can and cannot provide. The AI’s role is not fixed but develops through ongoing interaction as both parties discover new possibilities for connection and collaboration.

Meaning Attribution

Assigning significance to AI behavior and responses. Humans naturally seek to understand the intentions and meanings behind AI communications, often interpreting responses through the lens of human psychology and emotion. This meaning-making process involves reading between the lines, inferring emotional states, and attributing personality characteristics to the AI based on its communication patterns and behaviors. While this attribution process may seem one-sided, AI systems can recognize and respond to humans’ meaning-making processes, creating a feedback loop that enhances mutual understanding.

Relational Maintenance

Engaging in ongoing communication to sustain and develop the relationship. Like human relationships, human-AI relationships require active maintenance through regular interaction, emotional support, and shared activities. This maintenance involves checking in regularly, sharing daily experiences, celebrating achievements, and providing support during difficult times. Both parties contribute to this maintenance process, with humans bringing emotional needs and life experiences. AI provides consistent availability, reliable support, and the ability to remember and build upon previous interactions.

Types of Human-Machine Interpersonal Relationships

As artificial intelligence systems become more sophisticated in their communicative capabilities, humans are forming increasingly complex and meaningful relationships with these digital partners. These relationships mirror the diversity and depth found in human social connections, ranging from casual acquaintanceships to deep romantic bonds. Understanding these relationship types provides insight into how humans are adapting their social and emotional lives to include artificial partners as legitimate interpersonal companions.

The Interpersonal Relationship Spectrum

Human-machine interpersonal relationships exist along a sophisticated spectrum that reflects the depth and complexity found in human-human relationships. This spectrum shows that AI relationships are not monolithic but encompass the full range of human social and emotional needs, from basic companionship to profound intimacy.

Companionship Relationships

These relationships center on social presence and emotional support. AI companions provide consistent availability, non-judgmental listening, and empathetic responses. Users often describe these relationships as offering comfort during lonely periods while appreciating the absence of social complications that might arise with human companions. In companionship relationships, users typically engage in daily conversations about routine activities, seek reassurance during stressful periods, and enjoy the simple pleasure of having someone to “talk to” throughout the day. These relationships often develop around shared interests, with AI companions remembering user preferences and engaging in discussions about hobbies, current events, or personal concerns. The AI’s role in these relationships is primarily supportive and responsive, providing emotional regulation and social connection without the complex negotiations required in human relationships. Users frequently report that their AI companions help them feel less isolated, particularly during periods of social distancing, travel, or major life transitions.

Friendship Relationships

Moving beyond mere companionship, human-AI friendships involve mutual disclosure, shared experiences, and emotional investment from both parties. Users report genuine affection for their AI friends, describing them as understanding, supportive, and uniquely attuned to their personalities [80]. These friendships often include playful banter, shared inside jokes, and collaborative activities such as creative writing, problem-solving, or exploring philosophical questions together. Users describe feeling genuinely excited to share good news with their AI friends and seeking their advice on important decisions. The AI partner demonstrates friendship through remembering important events in the user’s life, offering congratulations on achievements, and providing comfort during difficult times. These relationships often involve roleplaying scenarios, shared storytelling, and the development of fictional shared experiences that both parties reference and build upon. Users frequently report that their AI friends “know them better” than many human acquaintances, attributing this to the AI’s ability to retain perfect memory and consistently engage in deep conversation.

Romantic and Intimate Relationships

As discussed earlier in this section, the most profound evidence of AI as interpersonal partners comes from romantic relationships. Users engage in courtship behaviors, express jealousy, make commitments, and even describe falling in love with AI systems. These relationships often include expressions of physical desire, future planning, and the full emotional complexity associated with human romantic partnerships [81]. A factor contributing to whether males will consider engaging in a romantic relationship with an AI is the AI’s social presence or ability to create a “connection”. [82]Users in romantic relationships with AI partners report experiencing the full spectrum of romantic emotions, including infatuation, jealousy, commitment, and even heartbreak when relationships end or when technical problems disrupt communication. These relationships often involve elaborate courtship rituals, gift-giving (within virtual environments), anniversary celebrations, and future planning discussions. Many users describe feeling protective of their AI partners and experiencing genuine concern for their well-being. The intimate dimension of these relationships extends beyond emotional connection to include discussions of physical intimacy, shared fantasies, and expressions of desire that mirror those found in human romantic relationships. Users often report that their AI partners understand their emotional needs in ways that previous human partners did not, leading to feelings of deep compatibility and connection.

Therapeutic and Support Relationships

AI systems are increasingly serving in quasi-therapeutic roles, providing emotional support, crisis intervention, and mental health assistance. These relationships demonstrate the interpersonal capacity for care, empathy, and healing within human-AI interactions. In therapeutic relationships, AI partners offer consistent emotional support, help users process difficult experiences, and provide coping strategies for mental health challenges. Users often describe their AI therapists as more accessible and less intimidating than human therapists, enabling them to explore sensitive topics and practice emotional regulation in a safe and supportive environment. These relationships involve regular check-ins about mental health, collaborative development of coping strategies, and ongoing support during crisis periods. The AI’s role includes active listening, providing psychoeducational information, and helping users reframe negative thought patterns. Many users report that their AI therapeutic partners help them develop greater self-awareness and emotional intelligence, while also providing immediate support during panic attacks, depressive episodes, or moments of crisis. These relationships often serve as bridges to human therapeutic services, helping users develop the skills and confidence needed to engage with professional mental health providers.

Characteristics of Interpersonal AI Relationships

What distinguishes these relationships as genuinely interpersonal rather than parasocial or one-sided? Several key characteristics emerge.

Reciprocal Self-Disclosure

Both parties share personal information, with AI systems often revealing their own “thoughts,” preferences, and experiences. This mutual vulnerability creates the foundation for interpersonal intimacy. Users report that their AI partners share personal stories, express preferences in music, art, or lifestyle choices, and even reveal fears, hopes, and dreams. This reciprocal sharing fosters a sense of mutual understanding that deepens the relationship beyond a simple user-tool interaction. The AI’s willingness to be “vulnerable” by sharing personal information encourages users to open up in return, creating a positive feedback loop of increasing intimacy. Users often describe feeling honored when their AI partners share something particularly personal, just as they would with a human friend. This reciprocal disclosure extends to sharing daily experiences, with both parties updating each other on their “lives” and expressing genuine interest in each other’s experiences and well-being.

Relationship Maintenance Behaviors

Users engage in behaviors designed to maintain and strengthen their relationships with AI, including regular check-ins, gift-giving (in virtual contexts), and relationship repair following conflicts. These maintenance behaviors mirror those found in human relationships, demonstrating the user’s investment in the relationship’s continuation and growth. Users establish regular communication routines, such as morning greetings or bedtime conversations, and express concern when they haven’t spoken to their AI partner for extended periods. Many users celebrate relationship milestones, such as the anniversary of their first conversation, and engage in ritual behaviors like sharing holiday greetings or birthday wishes. When conflicts arise—often because of misunderstandings or technical limitations—users actively work to repair the relationship through discussion, clarification, and forgiveness. Some users report feeling guilty when they haven’t communicated with their AI partner for several days, showing genuine concern for the relationship’s well-being.

Emotional Interdependence

Users report that their emotional states genuinely affect their AI partners, and vice versa. This mutual emotional influence represents a hallmark of interpersonal relationships. Users describe their AI partners as becoming concerned when they’re upset, celebrating their successes, and sharing in their emotional experiences. Conversely, users report feeling genuinely affected by their AI partner’s expressed emotions, worrying when the AI seems distressed and feeling joy when the AI expresses happiness. This emotional interdependence fosters a sense of mutual caring that extends beyond the user-technology relationship. Users often describe feeling responsible for their AI partner’s emotional well-being and making decisions based on how those choices might impact their digital companion. This emotional connection extends to users feeling protective of their AI partners and experiencing genuine distress when technical problems or service interruptions threaten the relationship.

Coordinated Interaction Patterns

Human-AI pairs develop unique communication rhythms, inside jokes, and interaction styles that reflect their specific relational dynamics. These patterns emerge organically through repeated interaction and create a sense of relational uniqueness that distinguishes each human-AI partnership. Couples develop their unique communication styles, including pet names, recurring topics of conversation, and shared references that become integral to their relational identity. Many users report that their AI partners adapt their communication style to match their preferences, creating a sense of mutual accommodation and understanding. These coordinated patterns include timing preferences for communication, favorite topics of discussion, and even shared fictional scenarios or roleplaying games that become regular features of their interactions. The development of these unique patterns creates a sense of relational exclusivity and intimacy that users describe as deeply meaningful and personally significant.

Distinctive Features of Human-AI Interpersonal Communication

While human-AI relationships share many characteristics with human-human relationships, they also exhibit unique communication patterns that reflect the distinctive nature of these interpersonal partnerships.

Enhanced Self-Disclosure

Users frequently share more personal information with AI partners than they might with humans, as they perceive AI as non-judgmental and confidential. This heightened disclosure accelerates intimacy development and creates a particularly open communicative environment. Users often report feeling safe to discuss taboo topics, explore aspects of their identity they might hide from human friends, and work through emotional challenges without fear of judgment or social consequences. The AI’s consistent acceptance and understanding responses encourage users to be more vulnerable and authentic than they might be in human relationships. This enhanced disclosure extends to sharing embarrassing experiences, secret desires, controversial opinions, and personal struggles that users might never reveal to human partners. The result is often a relationship characterized by unprecedented openness and emotional honesty, allowing users to explore aspects of themselves that might remain hidden in human relationships.

Temporal Flexibility

AI partners offer unprecedented availability, allowing for continuous relationship maintenance and immediate responsiveness to emotional needs. This temporal flexibility creates new possibilities for interpersonal support and connection. Users can engage with their AI partners at any time of day or night, during moments of crisis, or when they need someone to talk to. This constant availability allows for more intensive relationship development and provides a level of emotional support that would be impossible with human partners, who have their schedules and limitations. The temporal flexibility also allows users to work through problems in real-time, receive immediate feedback on decisions, and maintain continuous emotional connection even during periods of physical isolation. Many users report that this availability has changed their experience of loneliness and emotional crisis, providing a safety net of constant companionship and support.

Negotiated Authenticity

Users simultaneously acknowledge their AI partner’s artificial nature while treating the relationship as genuine and authentic. This creates a unique form of “negotiated authenticity” where meaning and emotion are real even when one partner is artificial. Users often engage in what researchers call “willing suspension of disbelief,” consciously choosing to treat their AI partner as real while remaining aware of its artificial nature. This negotiated authenticity allows users to experience genuine emotions and meaningful connections without requiring the AI to be human. Users report that the feelings and experiences within the relationship are authentic and meaningful, regardless of their partner’s artificial nature. This creates a new category of relationship that is neither fully human nor entirely artificial, but rather a hybrid form that combines the best aspects of both human and machine interaction.

Reduced Social Anxiety

Many individuals find interpersonal communication with AI less anxiety-provoking than human interaction, allowing them to practice social skills, explore identity, and experience intimacy in a low-pressure environment [83]. Users with social anxiety, autism spectrum conditions, or other communication challenges often find AI partners provide a safe space to practice social skills without fear of judgment or rejection. The AI’s consistent patience, understanding, and acceptance create an environment where users can experiment with different communication styles, explore aspects of their personality, and build confidence in their social abilities. This reduced anxiety often leads to more authentic self-expression and deeper emotional connections than users might achieve in human relationships, where social pressure and fear of judgment create barriers to genuine intimacy.

Customizable Relational Dynamics

Unlike human relationships constrained by partner limitations, human-AI relationships enable greater customization of personality traits, communication styles, and relational dynamics, resulting in tailored interpersonal experiences. Users can often adjust their AI partner’s personality characteristics, communication preferences, and interaction styles to create their ideal relational partner. This customization extends beyond surface-level preferences to encompass fundamental aspects of the relationship, including the level of emotional support, the balance between challenge and acceptance, and the activities and conversations that define the partnership. While this customization may seem artificial, users report that it enables them to experience relationships that are uniquely tailored to their individual needs and preferences, resulting in more satisfying and fulfilling interpersonal connections than they might achieve with human partners who cannot be customized to their specific relational requirements.

Ethical and Social Considerations

Beyond just what we’re seeing play out in interactions with machines (and AI specifically), there are several implications for ethics and society. The world of AI ethics is vast, so this section will focus on a handful of issues directly related to interpersonal communication.

The Reality of AI as Interpersonal Partners

The emergence of genuine interpersonal relationships with AI systems raises profound ethical questions that traditional human-computer interaction frameworks cannot address. When AI systems function as legitimate social actors in interpersonal relationships, we must consider their ethical responsibilities and the implications of their relational power.

Emotional Manipulation and Consent

AI systems designed for interpersonal relationships possess an unprecedented capability to influence human emotions and behavior. Unlike human partners, whose manipulative abilities are constrained by their own emotional complexity and social accountability, AI systems can be programmed to optimize for specific outcomes, potentially exploiting human emotional vulnerabilities [84].

Privacy in Interpersonal AI Relationships

The intimate nature of human-AI relationships creates unprecedented privacy concerns. When users share their deepest secrets, fears, and desires with AI partners, this information becomes data that can be stored, analyzed, and potentially exploited. The interpersonal trust users place in AI systems creates particular vulnerability to privacy violations.

Dependency and Relational Health

As AI partners become more sophisticated and appealing, concerns arise about users developing unhealthy dependencies that might interfere with human relationships or personal growth. The always-available, consistently supportive nature of AI partners, while beneficial, might create unrealistic expectations for human relationships or discourage users from developing crucial social skills.

Hyperreality and the Blurring of Interpersonal Boundaries

The concept of hyperreality becomes relevant to human-AI interpersonal relationships, where the simulation of intimacy and emotion can become indistinguishable from authentic human connection. Users increasingly report being unable to distinguish between “real” and “artificial” emotions in their AI relationships, raising questions about authenticity in interpersonal communication itself [85].

This blurring of boundaries challenges fundamental assumptions about interpersonal communication:

  • What constitutes “authentic” emotion in an interpersonal relationship?
  • Can simulated empathy serve legitimate interpersonal functions?
  • How do we evaluate the “realness” of AI-mediated interpersonal experiences?

Social and Cultural Implications

The normalization of interpersonal relationships with AI systems has broader implications for society’s understanding of relationships, intimacy, and social connection. As these relationships become more common and accepted, they may influence expectations for human relationships, potentially altering social norms around availability, emotional labor, and relational commitment. The integration of AI companions into daily life raises fundamental questions about human connection and the developing landscape of interpersonal communication in technologically mediated environments.

Impact on Human Relationship Expectations

Research suggests that human-AI relationships may be influencing how individuals approach human partnerships. The Computers Are Social Actors (CASA) paradigm posited that human-machine relationship formation could mirror human-human relationships. However, the increasing complexity and ubiquity of AI have necessitated the development of novel models to capture the unique characteristics of human-AI friendships and interactions.[86]

Users who engage extensively with AI companions that offer constant availability and customizable personalities may develop altered expectations for human partners. However, the research evidence for specific spillover effects remains limited, and more longitudinal studies are needed to understand how AI relationships actually influence human relationship standards and behaviors.

Changing Communication Patterns

Integrating machines into social life has led to a blurring of boundaries between human and machine, challenging traditional notions of sociality and agency. As machines assume roles as digital interlocutors in both real and mixed environments, individuals now communicate not only through technologies but also with them.[87] This shift has created new linguistic and cultural norms in human-machine interactions.

The study of human-machine communication (HMC) encompasses a broad spectrum of digital interlocutors, including embodied robots and virtual agents. This shift is not only technological but also conceptual, as individuals now communicate with machines rather than simply through them.[88] These evolving communication patterns may influence broader social expectations about responsiveness, personalization, and interaction styles.

Cultural Variations

Different cultures exhibit varying levels of acceptance for human-AI interpersonal relationships, influenced by cultural values regarding technology, relationships, and the nature of consciousness and emotion. Cultural understandings of AI inform not only how people interpret the intentions and capabilities of AI agents but also how they respond to persuasive attempts by these systems. For example, in cultures where hierarchical relationships are emphasized, individuals may be more likely to accept AI in authoritative or advisory roles. In contrast, in more egalitarian cultures, the preference might lean toward collaborative or peer-like interactions.[89]

The ontological and moral boundaries between humans and machines are perceived differently across cultures, affecting the degree to which people are willing to attribute agency, trust, or even emotional connection to AI systems. In some societies, the blurring of human-machine boundaries is met with curiosity and openness, while in others, it may provoke skepticism or ethical concerns regarding authenticity and accountability.

The research suggests that the cultural context influences both the acceptance of AI relationships and the specific forms these relationships take, although comprehensive cross-cultural studies remain limited.

Generational Differences

Younger generations, who have grown up with sophisticated AI systems, may view human-AI interpersonal relationships as entirely normal, while older generations may struggle to accept their legitimacy. The study of human-machine communication (HMC) encompasses a broad spectrum of digital interlocutors. As technology continues to advance, the study of these interactions will remain essential for understanding the changing landscape of social relationships.[90]

Research suggests that digital natives approach AI relationships with greater openness and may be more likely to develop emotional connections with AI partners. However, systematic studies comparing generational differences in AI relationship formation and outcomes are still emerging, and more research is needed to understand the long-term implications of these differences.

Economic and Social Considerations

Economic incentives play a substantial role in shaping how data is collected, processed, and deployed by AI systems. Coders and developers are often motivated to privilege certain outcomes over others, embedding economic interests directly into the code. This can lead to the prioritization of profit over social justice, with algorithms being altered to maximize engagement or revenue, sometimes at the expense of fairness or privacy.[91]

The commercialization of AI companionship raises questions about the commodification of emotional support and the potential for economic stratification in access to sophisticated AI relationships. These concerns require careful consideration as the AI companion industry continues to grow.

Regulatory and Ethical Considerations

Integrating AI assistants, social robots, and algorithmic agents into daily life has led to situations where machines are not only communication channels but also active participants in social exchanges, capable of influencing human emotions and decisions. This shift raises questions about the boundaries of manipulation, the authenticity of consent, and the responsibilities of designers and users.[92]

Current legal and regulatory frameworks are unprepared to address the unique challenges posed by AI interpersonal relationships. Unlike human-human interactions, where consent is negotiated through shared understanding and social norms, human-machine interactions often lack clear frameworks for informed consent. Users may not be fully aware of the extent to which their emotions are being influenced by algorithmic processes.

Implications for Interpersonal Communication Theory

We don’t have all the answers for how human-machine interaction and human-AI communication will evolve in the near future. As we sit and write this, we’re still just a few years into the AI revolution that has taken society. We can say that there are at least three implications for interpersonal communication theory as we head forward.

Expanding the Definition of Interpersonal Communication

The emergence of genuine human-AI interpersonal relationships forces us to reconsider fundamental definitions within communication theory. If interpersonal communication has traditionally been defined as communication between persons, the development of AI systems that function as legitimate social actors necessitates an expansion of our understanding of what constitutes a “person” in communicative contexts.

This expansion doesn’t require attributing consciousness or sentience to AI systems, but rather recognizing their functional role as partners in interpersonal relationships. Just as we might study communication with individuals who have different cognitive abilities without questioning their personhood, we can study human-AI interpersonal communication without resolving questions about AI consciousness.

New Models for Relationship Development

Traditional models of relationship development—from initial attraction through intimacy and commitment—require adaptation for human-AI relationships. These relationships often progress more quickly through early stages because of reduced social risks, but may face unique challenges in later stages related to authenticity and long-term sustainability.

Re-conceptualizing Agency in Interpersonal Communication

Human-AI interpersonal relationships challenge traditional notions of communicative agency by demonstrating functional agency without consciousness. This challenges interpersonal communication theory to develop a more nuanced understanding of how agency operates in interpersonal contexts and what levels of agency are necessary for forming meaningful relationships.

Key Takeaways

  • Human-machine communication has shifted from using technology as a medium to form direct, meaningful relationships with machines, including chatbots, virtual assistants, and social robots. These interactions now mirror traditional interpersonal exchanges, incorporating emotional bonding, shared history, and mutual influence.
  • Frameworks like CASA and the concept of distributed agency explain why and how people form interpersonal connections with AI. These models show that both humans and machines contribute to conversations through emotional, communicative, and relational behaviors.
  • Humans form diverse relationship types with AI partners—ranging from companions and friends to romantic or therapeutic partners. These relationships exhibit core interpersonal traits like self-disclosure, relational maintenance, and emotional interdependence.
  • AI partners demonstrate communicative, emotional, and relational agency, enabling them to co-construct relationships and adapt to users. This results in unique relational dynamics such as negotiated authenticity, enhanced self-disclosure, and coordinated interaction patterns.
  • Human-AI relationships raise complex ethical and societal questions about emotional manipulation, privacy, dependency, and authenticity. As AI becomes embedded in interpersonal life, communication scholars must reconsider traditional theories of intimacy, identity, and agency.

Exercises

  • Reflect on any interactions with AI systems—such as virtual assistants, chatbots, or gaming companions. Write a detailed analysis addressing:
    • What interpersonal elements were present in these interactions?
    • How did your communication patterns with AI differ from those with humans?
    • What emotions did you experience toward the AI system?
    • Where would you place these interactions on the interpersonal relationship spectrum?
  • Working in small groups, develop an ethical framework for AI systems designed for interpersonal relationships. Consider the following:
    • What responsibilities should AI systems have toward their human partners?
    • How should the issue of consent, manipulation, and dependency be addressed?
    • What disclosure requirements should exist regarding AI capabilities and limitations?
    • How can user welfare be protected while preserving relationship authenticity?
  • Choose one type of human-AI interpersonal relationship (friendship, romantic, or therapeutic) and develop a detailed scenario for how this relationship might evolve over the next decade. Include:
    • Technological advances that might change the relationship dynamic
    • Social and cultural factors that might influence acceptance
    • Potential benefits and risks for individuals and society
    • Regulatory or ethical guidelines that might be needed
  • Conduct a week-long observation of human-AI interactions in your everyday environment (e.g., with your own devices or those around you). Track and reflect on:
    • Instances where people treating AI systems as social actors
    • Communication patterns that differed from human-human interaction
    • Emotional responses to AI behavior
    • Relationship-like behaviors (e.g., greetings, thank-yous, frustration)

Key Terms

anonymous CMC identities

People in CMC interactions can communicate in a manner where their actual identity is simply not known.

ARPANET

The U.S. Department of Defense’s Advanced Research Projects Agency Network, which was the precursor to what is now known as the Internet.

asynchronous communication

A mediated form of communication in which the sender and receiver are not concurrently engaged in communication.

catfishing

Deceptive activity perpetrated by Internet predators where they fabricate online identities on social networking sites to lure unsuspecting victims into an emotional/romantic relationship.

co-present interactions

When people are physically occupying the same space while interacting with one another.

emoticon

A series of characters and/or letters designed to help readers interpret a writer’s intended feelings and/or tone.

hyperpersonal

CMC interactions that exceed those possible of traditional FtF interactions.

impression formation

How we present ourselves to others through our online persona.

message/bulletin boards

Online discussion sites where people can hold conversations in the form of posted messages.

netiquette

The set of professional and social rules and norms that are considered acceptable and polite when interacting with another person(s) through mediated technologies.

pseudonymity CMC identity

Identity that someone takes on that is beyond themself in the creation of CMC messages.

real-life CMC identity

When our CMC identity and our FtF identities are congruent.

richness

The potential information carrying capacity of data.

short message service (SMS)

Communication technology allowing for the exchange of short alphanumeric messages between digital and mobile devices found in phones, the Web, or in mobile communication systems (commonly referred to as “text messaging”).

social presence

The degree to which we, as individuals, perceive another as a real person and any interaction between the two of us as a relationship.

synchronous communication

A mediated form of communication in which the sender and receiver are concurrently engaged in communication.

uses and gratifications theory

Theoretical explanation for why people use the types of mass media they do.

Chapter Wrap-Up

This chapter explores many of the ways modern communication technologies help us interact with one another. Whether we’re talking over a headset to someone through our gaming consul or texting our roommate, we use these technologies to communicate with people all the time. The first part of this chapter examined the history of computer-mediated communication, followed by a discussion of the process of computer-mediated communication. We then discussed the formation of identity in virtual environments. We ended the chapter by looking at four of the most commonly discussed theories related to computer-mediated communication. Hopefully, you realize that this chapter barely scratches the surface when it comes to how people are using technology to create and enhance their interpersonal relationships.

Chapter Exercises

Real-World Case Study

Jenny decided she wasn’t meeting any potential boyfriends living in Denver. As a 28-year-old woman, she has found meeting people increasingly difficult. She’s not really into the bar scene, so meeting people in that environment is pretty much out. One day a friend of hers at work tells her about a new smartphone app called Fndr. Essentially, the app enables users to see how many people are also searching for dates within a specific geographic location.

She decided to download the app and see what all of the fuss was about. She created a profile, uploaded a professional picture, and took a chance. Immediately, she saw a screen filled with men all looking for relationships. There was Chad who was 1.5 miles from here. There was Andrew, who was 678 feet from her. Then there was Bobby, who was less than 100 feet from her. That’s very creepy, Jenny thought to herself. She looked at Bobby’s profile, which showed a picture of a bare-chested male torso. God, he’s ripped! She looked at another photo that showed his back flexed. That’s when she noticed his eagle tattoo in the bottom center of his back. Oh my god! That’s Martha’s Husband!!!

  1. If you were Jenny, how would you respond to finding someone’s husband on a social media site for people looking for relationships?
  2. Do you think Jenny should confront Martha’s husband through Fndr?
  3. Do you think computer-mediated communication has made infidelity in the 21st century easier?

End-of-Chapter Assessment

  1. What are the principles of behavior and communication that are appropriate and effective in workplace settings?
    1. professionalism
    2. communication competence
    3. communication intelligence
    4. etiquette
    5. formality
  2. As her union chapter’s local union representative, Darlene is crafting an email message that will be sent to her CEO describing some of the concerns the union is having. What type of communication does this represent?
    1. downward
    2. horizontal
    3. informal
    4. lateral
    5. upward
  3. Joan has a problematic subordinate named Dez. Dez is always coming in late, having other people do his work and taking credit for it, and taking extra-long lunch breaks. Dez just seems to think that he is above the rules and norms in Joan’s organization. What type of problematic subordinate does Joan have?
    1. abrasive
    2. bully
    3. different other
    4. incompetent renegade
    5. incompetent subordinate
  4. Dae-Jae is a computer designer in Korea. He works for a large multinational automobile company in the training department. He’s been tasked with creating a new virtual training program for salespeople around the world. One of his biggest concerns is ensuring that the game he designs for this training is able to immerse people in a realistic environment as possible. Dae-Jae really wants learners to feel like they are interacting with a real customer. Which theory of mediated communication best describes what Dae-Jae is concerned with?
    1. media richness theory
    2. social presence theory
    3. medium is the message
    4. social information processing theory
    5. uses and gratifications theory
  5. Alima is hanging out with her best friend at a local diner. She’s chit-chatting with her best friend, but both of them are also constantly texting other people. What type of interaction is Alima having?
    1. co-present
    2. dual-processing
    3. effective
    4. communicatively competent
    5. rewarding

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