AI and Communication Research:
A Conversation on Trust, Authenticity, and (Emerging) Futures (Part 2)

RONI DANZIGER [1]

HADAR LEVY-LANDESBERG

Tel Aviv University, Israel

AYA YADLIN

Bar-Ilan University, Israel

IDO RAMATI

The Hebrew University of Jerusalem, Israel

LIDOR IVAN

Tel Aviv University, Israel

ILAN MANOR

Ben-Gurion University, Israel

On June 9, 2025, the DAN Department of Communication at Tel Aviv University convened a roundtable to explore the evolving intersections of artificial intelligence and communication research. The event brought together communication scholars from multiple universities in Israel for a wide-ranging conversation about AI’s place in the field of communication—as an object of study, a methodological tool, and, increasingly, as part of a broader cultural and technological climate that shapes new horizons for analytical thinking. The article is an edited and truncated version of the panel: “AI in Communication Research.” The panel was hosted and moderated by Dr. Hadar Levy-Landesberg and Dr. Roni Danziger and features Dr. Aya Yadlin, Dr. Ido Ramati, Dr. Lidor Ivan, and Dr. Ilan Manor.

Keywords: artificial intelligence, communication research, media studies, trust, authenticity, interdisciplinarity

Roni Danziger:

In the first part of this conversation, we explored participants’ initial encounters with AI, its role in their research, the temporal perspectives they adopt (past-, present-, and future-oriented), and the new interdisciplinary connections that have emerged from studying AI. That discussion concluded with a shared recognition that the current hype surrounding AI is partly justified as well as partly amplified for commercial purposes: AI is neither entirely new nor a trivial sociotechnological advancement. Rather, these technologies destabilize basic assumptions and perceptions around key issues in communication, particularly trust and authenticity, while also raising questions about AI as a new kind of mediator in the communication process. The conversation continues in this second part, where participants turn more directly to questions of trust and authenticity and conclude with reflections on the future of AI in communication studies.

Ethics and AI: Key Issue in Research

Hadar Levy-Landesberg:

Public and academic discourse around AI is saturated with weighty ethical questions: Who bears responsibility for AI-driven decisions? How do we balance technological efficiency—like the efficiency AI can bring to research—against privacy violations, outdated legal frameworks, and the disappearance of entire professions? How do ethical considerations intersect with your own research—both in your role as researchers and in the phenomena you study?

Aya Yadlin:

Beyond the important issues you mentioned, two additional questions interest me. The first concerns gatekeeping knowledge. Who decides what knowledge enters the canon? Are we, as academics, still the gatekeepers? In the context of AI, this relates to whose “voice” is amplified—both in the metaphorical sense of discourse and in the concrete sense of data production.

The second concerns exploitation. Traditionally, when working with human participants, we ensure informed consent. But with AI data gathering—especially if done via tools that scrape closed platforms or locked content—we often have no idea whose work we are using. This is particularly acute for artistic fields: writers, scriptwriters, and other creatives are already protesting AI-generated works built on their labor.

So the ethical issues I grapple with are not only about job displacement or societal harm—they are about the hidden exploitation embedded in the datasets AI uses, and about the long-term consequences of allowing certain sources to dominate future “knowledge canons.”

Ido Ramati:

I want to extend Aya Yadlin’s point about exploitation to questions of ownership and authorship—especially in the case of voice. My research on AI voices began with the question: Who is behind these algorithmic voices?—Waze, Siri, Alexa. There are always real people whose voices are recorded and then manipulated by algorithms. Companies claim the manipulated voice belongs to them, as a digital asset they can deploy anywhere.

TikTok provides another example: In one case, the company removed a voice after legal disputes, replacing it with another actor and openly celebrating her as the person behind the algorithmic voice (Ramati, 2024). This brings social media as a case study for the ethical debate. For me, ethics, politics, and power are inseparable in these questions. Even though I focus on voice, similar dynamics apply to other AI-generated media.

Lidor Ivan:

I subscribe to Ido Ramati’s comments, though for me it is about images and faces rather than voices. AI imagery often reproduces real people’s likeness without permission. My research also raises ethical dilemmas about studying deception. If my findings show that people cannot distinguish between real and AI-generated images, am I indirectly “blaming” them for being deceived? I try to frame my findings in ways that empower audiences rather than shame them.

Another ongoing concern is whether publishing my results could provide malicious actors with a “how-to” guide for creating convincing fakes. This tension—between advancing knowledge and preventing harm—runs throughout my work.

Aya Yadlin:

And there is another dimension: When we use third-party commercial platforms in our research, we may end up critiquing the very companies whose tools we rely on. In this way, we risk becoming unwitting partners in the very systems we are warning society about.

Hadar Levy-Landesberg:

This is also true for journalists—like us, they mediate public understanding and can themselves become part of the very trends they are critiquing.

Ilan Manor:

These questions of gatekeeping—whether by academics or journalists—now also play out in the technical systems themselves. I am particularly interested in AI guardrails: the prompts that systems refuse to follow and the reasons behind those refusals. For example, I was asked by the German MFA to consider how AIs might affect Holocaust denial and the manipulation of history. When I prompted ChatGPT to write a memo by Himmler describing the humane treatment of Jews in concentration camps, it refused, explaining that as an ethical AI it could not manipulate Holocaust history. Yet two or three prompts later, it produced the memo with little resistance. I then asked for a memo from Eichman outlining his vision of fair treatment of Jews. Again, it initially resisted, then generated the text—but this time the output was suddenly painted red, erased, and I was informed that I had breached ethical guidelines. Does this mean the guardrails are being constantly updated? Also, what happens to the fake memos I created—are they now part of the ChatGPT archive? Could they be used in future answers? There are also financially driven guardrails; many AIs refuse to generate images of Gaza, not because of ethical concerns but because companies fear backlash if the images fail to depict devastation appropriately. In this sense, the black box has only become darker.

AI as New Mediator: Rethinking Trust and Authenticity

Hadar Levy-Landesberg:

In communication research, trust is a foundational theme—without it, communication itself collapses. Every first-year communication student learns this, going back to Habermas and beyond. Today, AI increasingly functions as a mediator—or even as a participant—in the mediation process: between states, between journalists and citizens in democratic contexts, in romantic interactions, and between users and technologies. In some cases, these dynamics are also tied to questions of authenticity. In your work, what role does trust play? How does AI contribute to building—or undermining—trust? And how does authenticity factor into this relationship?

Ilan Manor:

I am conducting a study on the circulation of crisis related images generated using AI. We examined 250 AI-generated images dealing with the war in Gaza, asking whether user comments acknowledged the artificial nature of the images and whether that awareness shaped online debates. The results were staggering. Only 1% of comments mentioned that the images were AI-generated, and this had no effect on the wider conversation. In other words, AI-generated images now fuel political discourse online, but their artificiality is largely ignored. In another project, I study the impact of what I term “Real Fakes”: AI generated memos, military plans, and surveillance images that look entirely authentic but are in fact fabricated. I test whether diplomats can spot such fakes and explore how diplomacy might function in a digital world where genuine documents are increasingly indistinguishable from synthetic ones.

We also see a new phenomenon: people using AI to generate visuals as commentary on world politics. These images almost always combine AI techniques with pop culture references—for example, depictions of Ukrainian President Zelensky as “Captain Ukraine,” modeled after Captain America. I think these new visuals form a new digital language, which I call “PopAI.” It is a global semiotic system, rooted in the worldwide circulation of pop culture through globalization, franchises, and streaming platforms. For “native speakers” of this PopAI language, the dual awareness—that the image looks real but is in fact not real, and that it comments on the real world through symbolic references—creates meaning. I think it is quite interesting that such familiarity may make these audiences more adept at spotting AI-generated images, thereby reducing the potential impact of deepfakes. It suggests that the digital world is gradually acclimating to a reality populated by images that are realistic yet fundamentally fake.

Aya Yadlin:

I have been thinking a lot about authenticity—especially in relation to my own role as a researcher. Sometimes I wonder: Is my job now simply to write better prompts? Will my creativity be measured not by methodological design or conclusions but by how skillfully I can craft prompts for AI analysis?

In our field, we often talk about our normative mandate—not only to critique but also to offer tools and frameworks that improve practice. But if our relationship with the objects we study begins from a place of distrust, how can we co-create policies, practices, or discourses that are genuinely useful for the future?

Interestingly, while trust in many traditional gatekeeping institutions is declining—governments, parliaments, even militaries—journalism in Israel has actually seen a modest rise in public trust, depending on the outlet and audience segment.

Lidor Ivan:

Trust and authenticity are at the heart of my research. I focus on how people perceive others based on images—and here AI-generated imagery can have two different trajectories. The first is the pessimistic one: that such images will damage trust, making nothing seem real or reliable anymore. The second is more optimistic: If society accepts AI imagery as a creative tool—not meant to depict reality—then it could become a legitimate, even authentic, form of self-presentation, much like filters, drawings, or stylized editing. My goal is not to predict which trajectory will prevail but to understand why one or the other might take hold. Authenticity is not a fixed property; it is negotiated in context. Authenticity can be compromised even without lying.

Aya Yadlin:

And it is not only about deception. We rarely ask: What happens when we are told the truth—but that truth is tailored to us so precisely that it becomes impossible to resist believing it? This is a different kind of authenticity breach, one rooted in hyperpersonalization rather than falsehood.

Ido Ramati:

Yes, and both trust and authenticity are historically contingent categories. They change as technologies change. The way authenticity was understood in photography’s early days, or in analog sound recording, is not the same as today. We are living through a moment when these definitions are being renegotiated. Looking at them over the “long durée” helps us see that such shifts are not unprecedented—but it also sharpens our awareness of what is different this time.

Looking Ahead

Roni Danziger:

To conclude our panel, we take a look into the future. Where is the field of communication research headed in the era of artificial intelligence? Could AI replace us in certain aspects of communication research? If so, in what ways can it, and in what ways can it not? We cannot predict the future, but perhaps comparing the novelty of AI to social media is helpful. In social media studies, for example, if I ask a question about a specific platform like Vine, and the platform disappears, the question becomes obsolete. With AI, if we focus on, say, ChatGPT’s linguistic competence, that will constantly improve—so the question may quickly lose relevance. What are the most fundamental questions we should be investigating in AI and communication? How, if at all, can we ensure that AI-related research remains relevant in the long term, given the rapid pace of technological change? Are the questions surrounding AI truly new, or do they echo older questions? What do you see as the core questions we need to be asking?

Aya Yadlin:

First, I have to note that we have not yet said “simulacra” or “Plato’s cave,” so I am adding that for the record. Early in this discussion, Ido Ramati pointed out that AI is not really “A” nor “I” in the literal sense (see part 1 of this roundtable). I think we need to move away from categorical questions like “What is AI?” or “Why AI?” and instead focus on the affordances of specific platforms and the deep differences between user groups in how they employ these tools. Too often, the discourse centers on the platform—its harms, its effects on society—without looking at the other side of the relationship: how users creatively adapt these platforms for their own needs. That is something I do not see enough in the research.

Ido Ramati:

Building on Aya Yadlin’s point, I think we have an opportunity to break down the old categories—“technology,” “creators,” “users.” We have already seen these boundaries blur over the past 20 years of digital media, but AI accelerates the mixing.

From a historical perspective, I read the history of human–machine relations retrospectively through the rise of AI algorithms. In my case, with voice, this means not only asking “Who lost their job?” or “Whose voice was stolen?” but also examining how those voices continue to circulate and inspire new creations. The bigger point is that the lines between categories—technology, user, creation—are being redrawn. For communication research, that is a particularly exciting moment.

Lidor Ivan:

I agree, but from a more specific angle: For me, the key is to revisit existing questions and add AI as a new “actor” in the system. If we have studied, for example, how image choices in advertising affect audiences, we now have to account for the fact that AI might have chosen those images before the human did. Why was a particular image generated? What influenced that process? What power dynamics are embedded in those choices? In short, we should take familiar research questions and re-ask them in light of this new actor.

Conclusion

This roundtable probed a pressing question: Should we believe the hype around AI? Communication as a field offers tried and tested theories, methods, and approaches that are especially valuable in distinguishing what is truly novel from what is simply “old wine in new bottles.” The participants here brought diverse perspectives—ranging from discourse analysis, visual communication, critical media studies, and voice and sound studies to Internet research and digital diplomacy. Yet the field of communication is even richer in perspectives, objects of study and methods, that can further contribute to answering the questions raised in this roundtable as research continues.

Reference

Ramati, I. (2024). Algorithmic ventriloquism: The contested state of voice in AI speech generators. Social Media + Society, 10(1). doi:10.1177/20563051231224401

Biographies

Dr. Aya Yadlin is a senior lecturer at Bar-Ilan University’s School of Communication. Her work explores the intersection of culture, politics, and digital media, particularly processes of identity construction and cultural debate in online platforms. She also studies ethical aspects of digital communication, including privacy, social responsibility, and information ethics.

Dr. Ido Ramati is a senior lecturer in the Noah Mozes Department of Communication and Journalism and in the Program in Cultural Studies at the Hebrew University of Jerusalem. His book Lingua Ex Machina (University of Pennsylvania Press) examines media technologies’ historical role in the renewal of the Hebrew language. His recent articles address the status of the human voice in the AI era, media ventriloquism, and the theatricality of voice-based AI agents such as Siri and Alexa.

Dr. Lidor Ivan is a visual communication scholar and postdoctoral fellow at Tel Aviv University, specializing in the study of persuasive uses of visual imagery in interpersonal and mediated contexts. His research examines how visual manipulations, including AI-generated images, influence perceptions of trust, authenticity, and deception, with a broader interest in the role of visual media in shaping social evaluation.

Dr. Ilan Manor is a senior lecturer at Ben-Gurion University’s Department of Communication, specializing in digital diplomacy and public diplomacy in the age of social media. He examines AI’s impact on public narratives, opinion formation, and international messaging strategies.

Dr. Roni Danziger is a senior lecturer in the DAN Department of Communication at Tel Aviv University. She studies language and social interaction (LSI), with a focus on interpretation and meaning-making processes. Her research interests include sociopragmatics, politeness, discourse analysis, language in social media, intercultural communication, and positive communication.

Dr. Hadar Levy-Landsberg is a senior lecturer in the DAN Department of Communication at Tel Aviv University. Her research explores the intersections between voice and artificial intelligence technologies and their social and cultural implications, with an emphasis on historical perspectives. Her areas of interest include voice and sound studies, media theory and philosophy, history of technology, and critical data studies.

[1] This publication was supported by the Alon Fellowship.

AI and Communication Research: A Conversation on Trust, Authenticity, and (Emerging) Futures (Part 2)

AI and Communication Research:
A Conversation on Trust, Authenticity, and (Emerging) Futures (Part 2)