Hugging Face AI & Society Team

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https://huggingface.co/hfmlsoc

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Research and Policy Questions raised by (open) AI technology

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evijit updated a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

yjernite updated a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

evijit published a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

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hfmlsoc's activity

giadap

posted an update 1 day ago

Post

1946

Ever notice how some AI assistants feel like tools while others feel like companions? Turns out, it's not always about fancy tech upgrades, because sometimes it's just clever design.

Our latest blog post at Hugging Face dives into how minimal design choices can completely transform how users experience AI. We've seen our community turn the same base models into everything from swimming coaches to interview prep specialists with surprisingly small tweaks.

The most fascinating part? When we tested identical models with different "personalities" in our Inference Playground, the results were mind-blowing.

Want to experiment yourself? Our Inference Playground lets anyone (yes, even non-coders!) test these differences in real-time. You can:

- Compare multiple models side-by-side
- Customize system prompts
- Adjust parameters like temperature
- Test multi-turn conversations

It's fascinating how a few lines of instruction text can transform the same AI from strictly professional to seemingly caring and personal, without changing a single line of code in the model itself.

Read more here: https://huggingface.co/blog/giadap/ai-personas

evijit

updated a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

Viewer • Updated 2 days ago • 75.3M • 166 • 2

yjernite

updated a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

Viewer • Updated 2 days ago • 75.3M • 166 • 2

evijit

published a dataset 2 days ago

hfmlsoc/hub_weekly_snapshots

Viewer • Updated 2 days ago • 75.3M • 166 • 2

evijit

authored a paper 7 days ago

In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI

Paper • 2503.16861 • Published Mar 21

yjernite

published a Space 8 days ago

Policy Docs Qa

🏆

Retrieves passages and answers questions from HF policy docs

yjernite

updated a Space 8 days ago

Policy Docs Qa

🏆

Retrieves passages and answers questions from HF policy docs

yjernite

updated a Space 15 days ago

README

📚

yjernite

published a Space 15 days ago

README

📚

evijit

authored 2 papers 20 days ago

Stop treating `AGI' as the north-star goal of AI research

Paper • 2502.03689 • Published Feb 6 • 4

"It's not a representation of me": Examining Accent Bias and Digital Exclusion in Synthetic AI Voice Services

Paper • 2504.09346 • Published 26 days ago • 4

giadap

posted an update 21 days ago

Post

1620

🤗 Just published: "Consent by Design" - exploring how we're building better consent mechanisms across the HF ecosystem!

Our research shows open AI development enables:
- Community-driven ethical standards
- Transparent accountability
- Context-specific implementations
- Privacy as core infrastructure

Check out our Space Privacy Analyzer tool that automatically generates privacy summaries of applications!

Effective consent isn't about perfect policies; it's about architectures that empower users while enabling innovation. 🚀

Read more: https://huggingface.co/blog/giadap/consent-by-design

3 replies

yjernite

posted an update 22 days ago

Post

3183

Today in Privacy & AI Tooling - introducing a nifty new tool to examine where data goes in open-source apps on 🤗

HF Spaces have tons (100Ks!) of cool demos leveraging or examining AI systems - and because most of them are OSS we can see exactly how they handle user data 📚🔍

That requires actually reading the code though, which isn't always easy or quick! Good news: code LMs have gotten pretty good at automatic review, so we can offload some of the work - here I'm using Qwen/Qwen2.5-Coder-32B-Instruct to generate reports and it works pretty OK 🙌

The app works in three stages:
1. Download all code files
2. Use the Code LM to generate a detailed report pointing to code where data is transferred/(AI-)processed (screen 1)
3. Summarize the app's main functionality and data journeys (screen 2)
4. Build a Privacy TLDR with those inputs

It comes with a bunch of pre-reviewed apps/Spaces, great to see how many process data locally or through (private) HF endpoints 🤗

Note that this is a POC, lots of exciting work to do to make it more robust, so:
- try it: yjernite/space-privacy
- reach out to collab: yjernite/space-privacy

giadap

authored a paper about 1 month ago

Bridging the Gap: Integrating Ethics and Environmental Sustainability in AI Research and Practice

Paper • 2504.00797 • Published Apr 1 • 2

giadap

posted an update about 1 month ago

Post

2347

We've all become experts at clicking "I agree" without a second thought. In my latest blog post, I explore why these traditional consent models are increasingly problematic in the age of generative AI.

I found three fundamental challenges:
- Scope problem: how can you know what you're agreeing to when AI could use your data in different ways?
- Temporality problem: once an AI system learns from your data, good luck trying to make it "unlearn" it.
- Autonomy trap: the data you share today could create systems that pigeonhole you tomorrow.

Individual users shouldn't bear all the responsibility, while big tech holds all the cards. We need better approaches to level the playing field, from collective advocacy and stronger technological safeguards to establishing "data fiduciaries" with a legal duty to protect our digital interests.

Available here: https://huggingface.co/blog/giadap/beyond-consent