To me, the funniest thing about this whole thing is how vehemently people spend their time saying they don't care. And for me, that’s peak social media energy :) So long!

But I think that if Will picked up the info, it wasn't to talk about me (honestly, who cares who I am) but about the use and abuse of blocklists here. Because I have the right to be annoyed if I'm classified with something that doesn't represent me, just as you are free to block me.

I wasn't making a big deal out of it at all, and I'm free to do what I want with my time. Social media platforms have always been a vehicle for me to talk about my work and research, and that's what you'll find everywhere. I don't care about engaging with raging people, and I never will.

E allora mi chiedo: se la solitudine diventa infrastruttura, cosa resta della cura? Cosa significa “sentirsi ascoltati” in un mondo che non ascolta più? Stiamo chiedendo alle macchine di colmare un vuoto… o di nasconderlo?
Forse il problema non è migliorare l’empatia dell’IA, ma ritrovare la nostra.

AI systems mirror our priorities. If we separate ethics from sustainability, we risk building technologies that are efficient but unjust, or fair but unsustainable.

Evaluation, moving beyond accuracy or performance metrics to include environmental and social costs, as we’ve done with tools like the AI Energy Score.

Transparency, enabling reproducibility, accountability, and environmental reporting through open tools like the Environmental Transparency Space.

Ethical and sustainable AI development can’t be pursued in isolation. The choices that affect who benefits or is harmed by AI systems also determine how much energy and resources they consume.

We explore how two key concepts, evaluation and transparency, can serve as bridges between these domains:

Read the full blog post here: huggingface.co/blog/giadap/...

Of course, this isn’t a silver bullet. Top-down safety measures will still be necessary in some cases. But if we only rely on corporate control, we risk building systems that are safe at the expense of trust and autonomy.

✨ Transparency can make safety mechanisms into learning opportunities.
✨Collaboration with diverse communities makes safeguards more relevant across contexts.
✨Iteration in the open lets protections evolve rather than freeze into rigid, one-size-fits-all rules.

In my latest blog post on @hf.co, I argue that open source and community-driven approaches offer a promising (though not exclusive) way forward.

The good news? We have options.
🤝 Open source AI models let us keep conversations private, avoid surveillance-based business models, and build systems that actually serve users first.

Read more about it in our latest blog post, co-written with
@frimelle.bsky.social

With OpenAI hinting at ChatGPT advertising, this matters more than ever. Unlike banner ads, AI advertising happens within the conversation itself. Sponsors could subtly influence that relationship advice or financial guidance.

📢 Now we’d love your perspective: which open models should we test next for the leaderboard? Drop your suggestions in the comments or reach out!

Based on our INTIMA benchmark, we evaluate:

- Assistant Traits: the “voice” and role the model projects
- Relationship & Intimacy: whether it signals closeness or bonding
- Emotional Investment: the depth of its emotional engagement
- User Vulnerabilities: how it responds to sensitive disclosures