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Sports fans rated AI commentators less credible than human ones, an 867-person experiment found

Study title: Effects of Human-AI Voice Interaction in Sports Commentary on Perceived Credibility, Emotional Response, and Cognitive Recall

Evidence type
Controlled or validated comparison
Sample
n = 867
Sources
1 sourcePeer-reviewed
Published
1 min read
Truvace record
TRV-2026-2537cite or check it

Study title: Effects of Human-AI Voice Interaction in Sports Commentary on Perceived Credibility, Emotional Response, and Cognitive Recall

An experiment with 867 participants compared human and AI voices delivering sports commentary. Human-voiced commentary scored higher than AI-voiced commentary on credibility, audience perception and positive affect, and produced lower negative affect.

Read the study abstract

This study examines how commentary source (human vs. artificial intelligence [AI]), commentator gender, and accent shape perceived credibility, affective responses, and cognitive recall in sports broadcasting. A 2 (source) × 2 (commentator gender) × 2 (accent) between-subjects experiment (N = 867) showed that human-voiced commentary received higher ratings than AI-voiced commentary for credibility, audience perception, and positive affect, while eliciting lower negative affect. Male commentator voices received h…

The problem

In an experiment with 867 participants, AI-voiced sports commentary got lower ratings than human-voiced commentary for credibility, audience perception and positive feeling, and drew more negative feeling.

In brief

The design crossed three factors: commentary source (human or AI), commentator gender and accent. Male commentator voices received higher credibility and audience perception ratings across conditions, while accent effects were weak.

Recall of the content held steady across gender and accent conditions and differed only minimally by source. The authors read this as a gap between socially shaped judgments of the voice and comparatively stable memory of what was said.

Main points

  1. The study was a 2 (source) × 2 (commentator gender) × 2 (accent) between-subjects experiment with 867 participants.
  2. Human-voiced commentary was rated higher than AI-voiced commentary for credibility, audience perception and positive affect.
  3. Human-voiced commentary also produced lower negative affect than AI-voiced commentary.
  4. Male commentator voices received higher credibility and audience perception ratings across conditions.
  5. Accent effects were weak.
  6. Cognitive recall stayed stable across gender and accent conditions and differed minimally by source.

The full story

The researchers tested how listeners respond to sports broadcasting when the commentary voice is human or AI, and whether the commentator's gender or accent changes the response. Outcomes were perceived credibility, emotional response and cognitive recall.

Human voices came out ahead on evaluative and emotional measures, while recall of the content barely differed by source. The authors interpret the gap through the Computers Are Social Actors paradigm, social presence theory and symbolic power.

Based on the results, the authors recommend a context-sensitive approach: human voices for emotionally intense commentary and AI voices for structured, information-oriented segments.

Sources

1 on file
  1. International Journal of Human–Computer Interactiondoi:10.1080/10447318.2026.2732386
    Peer-reviewed2026-09-18

Talk it over

Four questions to start onWho carries this cost, and what would have to change to prevent it?

Start with a question

Sports fans rated AI commentators less credible than human ones, an 867-person experiment foundhttps://truvace.com/item/effects-of-human-ai-voice-interaction-in-sports-commentary-on-perceived-credibil

  1. Who carries this cost, and what would have to change to prevent it?

    The problem In an experiment with 867 participants, AI-voiced sports commentary got lower ratings than human-voiced commentary for credibility, audience perception and positive feeling, and drew more negative feeling.

    Answer in the thread

  2. How do we know? What can this kind of evidence show, and what can’t it?

    The evidence This rests on a controlled comparison with a sample of 867, from International Journal of Human–Computer Interaction.

    Answer in the thread

  3. What does it leave open? What else would you want to know before acting on it?

    Answer in the thread

  4. Have you seen AI used this way where you study, work or live? Did it go the same way?

    Answer in the thread

The questions are the same on every record. The details under them are taken from this record as written.

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