Research onsynthetic authenticity.

Current studies examine how AI earns permission to occupy roles that matter, how people scrutinise it and how institutions govern its authority.

7.7k+

academic records mapped or screened across authenticity and AI-persona research.

13.6m+

public posts, comments, reviews and discussions examined across AI influence, advice and care.

19.1m+

public records and discourse items examined across emerging agentic markets.

A wider programme for AI legitimacy and institutional trust.

The research now follows four questions that institutions need to answer when AI holds a role that matters.

Is it still the same AI?Versioned authenticity, evidence and provenanceVersion threshold
Where does its authority end?Role legitimacy, decision rightsAuthority ceiling
Who is it acting for?Relational AI, agentic commerceReliance exposure
Can people challenge the outcome?Collective judgement, accountabilityRecourse window

Legitimacy gap opens when an AI can do more than it has been given permission to do. Explore the framework →

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.

Read more about this study →

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.

People keep re-checking what kind of thing is speaking, and that quiet check shapes what they are prepared to believe or permit.

Read more about this study →

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.

In an observational analysis of 1,531 Instagram posts, AI disclosure was associated with 19.2 per cent higher engagement. Lower felt authenticity appeared where disclosure became unusually prominent.

Read more about this study →

An AI-disclosed persona prompting audience attention and closer scrutiny
Disclosure was associated with more engagement and, when unusually prominent, lower felt authenticity.
Accepted, in production Journal of Advertising

Crowd forensics and warrant braiding.

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

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

Read more about this study →

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.

Read more about this study →

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.

Across 3,670 posts and reviews, people described companion AI as easier to confide in because it asked nothing back. Separation could feel like loss.

Read more about this study →

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