Really enjoyed speaking with tech ethicist Tristan Harris, who you might know from the Netflix documentary "The Social Dilemma" or his work with the Center for Humane Technology.

🎥 Watch here on YouTube: www.youtube.com/watch?v=TFm3...

🎧 Listen on Spotify: open.spotify.com/episode/0Oi6...

Our recent review article "The Psychology of Virality" with @jayvanbavel.bsky.social
is on the front cover of this month's issue of
@cp-trendscognsci.bsky.social.

The sycophantic chatbot also amplified people’s belief that they were "better than average" on a number of desirable traits (e.g., intelligence, empathy), and the disagreeable chatbot had the opposite effect.

In other words, AI sycophancy might lead to inflated self-perceptions.

One might think sycophantic AI would be considered less competent, since training chatbots to be warm makes them less accurate (arxiv.org/abs/2507.21919).

However, sycophantic AI was rated by participants as both warmer *and* more competent.

People viewed the sycophantic chatbot as unbiased and the disagreeable chatbot as highly biased.

In reality, *both* chatbots were biased: the sycophantic chatbot was simply biased in the user’s favor.

However, people enjoyed the sycophantic chatbot much more than the disagreeable chatbot and were more likely to choose to use it again!

Compared to a control condition:
-The sycophantic chatbot led to more extreme & certain beliefs
-The disagreeable chatbot led to less extreme & certain beliefs
-The off-the-shelf model had no impact on belief extremity

🚨 New preprint 🚨

Across 3 experiments (n = 3,285), we found that interacting with sycophantic (or overly agreeable) AI chatbots entrenched attitudes and led to inflated self-perceptions.

Yet, people preferred sycophantic chatbots and viewed them as unbiased!

osf.io/preprints/ps...

Thread 🧵

Check out the full paper with @jayvanbavel.bsky.social here: authors.elsevier.com/c/1lRke4sIRv...

Future work on virality should leverage recent advances in AI (pnas.org/doi/10.1073/...) to explore what goes “viral” across languages, cultures, and time periods.

This may explain, in part, why widely shared content is often not widely liked, a phenomenon we call the “paradox of virality” (journals.sagepub.com/doi/abs/10.1...)

We review several studies in the virality literature. Most of them find that negativity and high-arousal emotions go viral. Yet, not all studies support this conclusion, and sometimes positivity goes viral. Why is that?

Similar to how some viruses are more “contagious” than others, some forms of information appear to be more contagious than others across contexts.

The information-as-virus metaphor can be extended even further:

🚨New paper in @cp-trendscognsci.bsky.social 🚨

Why do some ideas spread widely, while others fail to catch on?

We review the “psychology of virality,” or the psychological & structural factors that shape information spread online and offline: authors.elsevier.com/c/1lRke4sIRv...

I'm thrilled to announce that I'll be joining Carnegie Mellon as an Assistant Professor of Human-Computer Interaction (with a courtesy joint appointment in Social and Decision Sciences) in 2026!

Very excited to be included in the @forbes.com 30 under 30 list this year!

www.forbes.com/30-under-30/...

Only paying attention to people's behavior (or revealed preferences) may lead social media to amplify various forms of harmful content -- such as misinformation, division, or moral outrage -- since these types of content are excellent at capturing people's attention.

🚨 Now out in Perspectives on Psychological Science 🚨

People engage with divisive and negative content online. But, does this mean that people *like* divisive content? No! We find that people across the political spectrum do not want divisive content to spread.

journals.sagepub.com/doi/10.1177/...