Research

Synthetic Authenticity.Multiple use cases.

Synthetic Authenticity is tested across care, social robots, AI influencers, classrooms, advice communities, and companion AI. Every study asks the same question in a different room: what makes an authentic AI persona authentic enough to act on?

Illustrated programme map connecting synthetic form to human judgement through permission to hold a role
Care
How human should a helper feel?

The threshold matters more than realism.

Social robots
Who is speaking?

People keep checking the communicator.

AI influencers
What does disclosure change?

Attention and authenticity move differently.

Classrooms
How does doubt travel?

One viewer's suspicion becomes a shared cue.

Advice communities
Whose advice survives review?

Groups audit AI and humans for different faults.

Companion AI
Why do people confide?

Burdenless listening changes the exchange.

7,798

academic records screened across two systematic reviews of authenticity and AI-persona research.

8,139

social media posts, comments and reviews coded by hand across four studies.

60

years of authenticity literature mapped, from 1966 to 2025.

23

national contexts represented in the AI-persona meta-synthesis.

Published International Journal of Human-Computer Interaction

The authenticity paradox.

Saxena, P., & Prahl, A. (2026). The authenticity paradox: The threshold model of synthetic authenticity. International Journal of Human-Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2026.2680242

The foundational study. A map of 2,685 articles and 111 AI-persona studies shows where human cues help and where they start breaking trust.

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SJR 2025 Q1JCR Ergonomics #2 of 24Impact Factor 2025 6.1CiteScore 2025 10.1h-index 110

Journal standing for the venue of a published article.

Conceptual threshold model showing too few cues, calibrated sufficiency and closer scrutiny
Calibrated sufficiency at the threshold.
Under review Human-Machine Communication

When the communicator is code.

Saxena, P., & Prahl, A. (manuscript under review). When the communicator is code. Human-Machine Communication.

This is the process behind the construct. People keep re-checking what kind of thing is speaking, and that quiet check decides what gets believed.

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SJR 2025 Communication Q1Indexing Scopus + DOAJAccess Diamond open access

Standing of the target journal, not an achieved publication credential.

Illustrative map of care, teaching, listening, influence and speaking against role stakes and ontological load
Roles shift the level of scrutiny.
Under review International Journal of Advertising

The transparency tax.

Saxena, P., & Prahl, A. (manuscript under review). The transparency tax on virtual influencer engagement. International Journal of Advertising.

Across 1,531 Instagram posts, AI disclosure lifted engagement 19.2%, yet lower felt authenticity appeared when the account leaned too hard on disclosure.

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ABDC 2025 ASJR 2025 Q1SJR value 3.182h-index 95

Standing of the target journal, not an achieved publication credential.

An AI-disclosed persona prompting audience attention and closer scrutiny
Disclosure lifts attention and taxes authenticity.
Accepted, in production Journal of Advertising

Doubt spreads.

Saxena, P., & Prahl, A. (in press). Crowd forensics and warrant braiding: Collaborative persuasion knowledge in AI influencer threads. Journal of Advertising. DOI 10.1080/00913367.2026.2711050

Public comment threads become forensic investigations. One viewer's private suspicion turns into the next viewer's public cue.

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ABDC 2025 ASJR 2025 Q1AJG 2024 3SJR value 4.201h-index 151

Accepted for publication. DOI registered; the link resolves once the article publishes. Official journal of the American Academy of Advertising.

Hand-drawn evidence strands braided through shared scrutiny into collective judgement
Suspicion becomes social evidence.
Under review Internet Research

Advice goes public.

Saxena, P., & Prahl, A. (manuscript under review). When advice goes public: Carrier framing and community adjudication of AI and human recommendations. Internet Research.

Across 174 carrier posts and 87 full threads, communities audit AI and human advice for different faults. AI advice is called generic; human advice is questioned on process. The split runs 55.8 standardised percentage points.

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ABDC 2025 ASJR 2025 Q1AJG 2024 3Impact Factor 2025 7.2CiteScore 2025 14.8h-index 129

Standing of the target journal, not an achieved publication credential.

Inherited human or AI advice reviewed by a community and accepted, revised or rejected
Advice becomes an object a group can rework.
Revise & resubmit Journal of Macromarketing

Burdenless listening.

Saxena, P., & Prahl, A. (manuscript under revise and resubmit). Burdenless listening in AI care markets. Journal of Macromarketing.

From 3,670 posts and reviews: people confide because the AI asks nothing back, and that same ease can make leaving feel like loss.

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ABDC 2025 Ah-index 76

Standing of the target journal, not an achieved publication credential.

A person confiding in an AI companion beside an illustration of possible platform dependence
One-way confiding can feel safe.