Plenty of speakers, way more than I'd expect, were showing a slide blaming Google for aiding the Palestinian genocide, providing a QR link to the UN report, and highlighting Google is a sponsor of the conference.
That was brave of these mostly young researchers, and they have my admiration

I'm happy to highlight our
Pedagogy Panel:
"How (and to Whom) Do We Teach AI Ethics?"
which I shared with brilliant people: @shannonvallor.bsky.social and Julienne LaChance, chaired by @emanuelleburton.bsky.social

We tackled practical challenges on educating the conference topics to the new gen

"How LLM Counselors Violate Ethical Standards in Mental Health Practice: A Practitioner-Informed Framework"
by Zainab Iftikhar et al

A brilliant talk about the malpractices of current LLMs acting as therapists, highlighting the AI is constantly lying when saying "it cares" (since obv it can't)

"No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy"
by @kyrawilson.bsky.social et al

It shows how people trust AI hiring proposals blindly, even when the AI's being racist. This highlights the importance to tackle algorithmic bias

"AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights"
by @jiannanxu.bsky.social et al

A surprising bias:
- If a job candidate building their CV uses the same LLM as the evaluator, there is a strong bias to be selected
- And LLMs prefer AI-generated CVs over manual ones

"Govern With, Not For: Understanding the Stuttering Community’s Preferences and Goals for Speech AI Data Governance in the US and China"
by Jingjin Li et al

On an often invisibilized marginalized community: the stuttering community

"Disability Across Cultures: A Human-Centered Audit of Ableism in Western and Indic LLMs"
by @mahika.bsky.social et al

was fascinating, exploring how different LLMs categorize ableist comments in different degrees, depending on the language they were written (English vs Hindi).

I enjoyed a lot:
"Documenting Patterns of Exoticism of Marginalized Populations within Text-to-Image Generators"
by Sourojit Ghosh et al

Unsurprisingly, AIs show stereotypical imagery when trying to represent Global South cultures, to the point of absurdity

I was very happy to join the AI Ethics conference ACM AIES 2025 in my hometown, Madrid, at @ieuniversity.bsky.social

The program was amazing, I encourage to check out the lineup and proceedings:
www.aies-conference.com/2025/

I'll share some highlights in this thread🧵

#AIES #AIethics #AI

Attention is considered the scarce resource. Their Holographic Consensus governance model tried to solve it via prediction-market “boosting.” It filtered well (≈97% precision) but failed to sustain independent stakers. In fact, 83% of the stakes came from insiders

DAOstack, like other DAO platforms, promised scalable cooperation and democratic governance.
Reality check: most DAOs are tiny, short-lived, and oligarchic-leaning as they grow. In fact, far from democratic:
• ~65% members never voted
• ~8% avg voter turnout/proposal

We analyzed DAOstack's 92 organizations in terms of size, lifespan, activity, power concentration, and governance model effectiveness. And interviewed core users to better understand their experience.