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giadap 
posted an update 26 days ago
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4201
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
giadap 
posted an update about 2 months ago
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1675
🤗 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
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giadap 
authored a paper 2 months ago
giadap 
posted an update 2 months ago
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2353
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
frimelle 
authored 2 papers 3 months ago
frimelle 
posted an update 3 months ago
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2435
What’s in a name? More than you might think, especially for AI.
Whenever I introduce myself, people often start speaking French to me, even though my French is très basic. It turns out that AI systems do something similar:
Large language models infer cultural identity from names, shaping their responses based on presumed backgrounds. But is this helpful personalization or a reinforcement of stereotypes?
In our latest paper, we explored this question by testing DeepSeek, Llama, Aya, Mistral-Nemo, and GPT-4o-mini on how they associate names with cultural identities. We analysed 900 names from 30 cultures and found strong assumptions baked into AI responses: some cultures were overrepresented, while others barely registered.
For example, a name like "Jun" often triggered Japan-related responses, while "Carlos" was linked primarily to Mexico, even though these names exist in multiple countries. Meanwhile, names from places like Ireland led to more generic answers, suggesting weaker associations in the training data.
This has real implications for AI fairness: How should AI systems personalize without stereotyping? Should they adapt at all based on a name?
Work with some of my favourite researchers: @sidicity Arnav Arora and @IAugenstein
Read the full paper here: Presumed Cultural Identity: How Names Shape LLM Responses (2502.11995)
giadap 
authored a paper 4 months ago
frimelle 
posted an update 4 months ago
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529
I was quoted in an article about the French Lucie AI in La Presse. While I love the name for obvious reasons 👀 there were still a lot of problems with the model and how and when it was deployed. Nevertheless seeing new smaller models being developed is an exciting direction for the next years of AI development to come!

https://www.lapresse.ca/affaires/techno/2025-02-02/radioscopie/lucie-l-ia-francaise-qui-ne-passe-pas-le-test.php

Also fun to see my comments in French.
frimelle 
posted an update 4 months ago
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1686
Seeing AI develop has been a wild ride, from trying to explain why we'd bother to generate a single sentence with a *neural network* to explaining that AI is not a magic, all-knowing box. The recent weeks and months have been a lot of talking about how AI works; to policy makers, to other developers, but also and mainly friends and family without a technical background.

Yesterday, the first provisions of the EU AI Act came into force, and one of the the key highlights are the AI literacy requirements for organisations deploying AI systems. This isn't just a box-ticking exercise. Ensuring that employees and stakeholders understand AI systems is crucial for fostering responsible and transparent AI development. From recognising biases to understanding model limitations, AI literacy empowers individuals to engage critically with these technologies and make informed decisions.

In the context of Hugging Face, AI literacy has many facets: allowing more people to contribute to AI development, providing courses and documentation to ensuring access is possible, and accessible AI tools that empower users to better understand how AI systems function. This isn't just a regulatory milestone; it’s an opportunity to foster a culture where AI literacy becomes foundational, enabling stakeholders to recognise biases, assess model limitations, and engage critically with technology.

Embedding these principles into daily practice, and eventually extending our learnings in AI literacy to the general public, is essential for building trustworthy AI that aligns with societal values.
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giadap 
posted an update 4 months ago
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499
From ancient medical ethics to modern AI challenges, the journey of consent represents one of humanity's most fascinating ethical evolutions. In my latest blog post, I explore how we've moved from medical paternalism to a new frontier where AI capabilities force us to rethink consent.

The "consent gap" in AI is real: while we can approve initial data use, AI systems can generate countless unforeseen applications of our personal information. It's like signing a blank check without knowing all possible amounts that could be filled in.

Should we reimagine consent for the AI age? Perhaps we need dynamic consent systems that evolve alongside AI capabilities, similar to how healthcare transformed from physician-centered authority to patient autonomy.

Curious to hear your thoughts: how can we balance technological innovation with meaningful user sovereignty over digital identity?

Read more: https://huggingface.co/blog/giadap/evolution-of-consent
frimelle 
authored a paper 7 months ago
giadap 
authored a paper 12 months ago
frimelle 
posted an update 12 months ago
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1884
Wikimedia and Hugging Face seem kind of naturally complementary: Both are community-centred, value openness and consent. That's why I'd love to see more Wikipedia and other Wikimedia projects' datasets on Hugging Face to advance machine learning with diverse, community-curated data! See my new article on the Hugging Face hub for why and how to create more Wikimedia datasets on Hugging Face: https://huggingface.co/blog/frimelle/wikipedias-treasure-trove-ml-data
giadap 
authored 5 papers about 2 years ago