E6: AI Ethics, Data Governance, & Training Challenges with Giada Pistilli
Oct 19, 2023
auto_awesome
Giada Pistilli, Principal Ethicist at Huggingface, discusses AI ethics and data governance. Topics include training data inconsistencies, potential biases in AI, ethical training guidelines, 'moral charter' in AI models, and hazards of 'Ethics Shopping'.
Importance of ethical training guidelines and alignment principles in AI models.
Significance of transparency, open collaboration, and ongoing research to address biases in multi-modal models.
Deep dives
Key Takeaways from Building and Training LLMs
During the discussion, Jata Pastili, the principal ethicist at Huggingface, highlighted the key takeaways from their experience in building and training LLMs, particularly focusing on fairness and ethics. They emphasized the importance of showcasing the possibility of creating large language models in a responsible and inclusive manner. This involved gathering multilingual datasets and employing a strong data governance process to ensure responsible data collection. They also highlighted the significance of transparency and open collaboration in the process, allowing diverse perspectives to be heard and considered.
Organizational Structure and Team Management
Jata discussed the organizational structure and team management at Big Science, an interdisciplinary effort involving over a thousand researchers. They explained that the project initially started with a small group, gradually expanding as more people joined. Communication and collaboration were facilitated through tools like Slack, ensuring transparency and open access to information. The team relied on recorded meetings and specific working groups to address different areas such as bias, multilingual data collection, and architecture. The success of the project was attributed to effective coordination, inclusivity, and the willingness to listen to diverse opinions and backgrounds.
Challenges of Addressing Bias in LLMs
Jata emphasized the challenges of addressing bias in LLMs, particularly in relation to cultural values and interpretation. They highlighted the example of different interpretations of secularism between France and the US, which led to conflicting results when querying LLMs trained in each country. The presence of inconsistent values and biases raised important questions about the representation of societies and cultures within language models. Jata emphasized the need to understand the sources of bias, whether from training data, inputs, or user behavior. They emphasized the importance of comparative analysis and exploration to better understand and address these biases.
Considerations for Multi-Modal Models
The conversation extended to the implications of multi-modal models, where biases and value conflicts can become more pronounced. Jata discussed the amplification and multiplication of biases in such models, highlighting the need for careful evaluation and assessment of biases across different modalities. They emphasized the importance of understanding the sources of biases, whether from text or images, and the challenge of detecting and addressing them. Additionally, Jata stressed the significance of value pluralism, where different cultures and perspectives coexist, and the need for ongoing research and collaboration to navigate the complexities of bias in multi-modal models.
In the sixth episode of Practically Intelligent, join us as we delve deep into the intricacies of AI ethics and data governance with Giada Pistilli, Principal Ethicist at Huggingface. We explore the unpredictable implications of training data inconsistencies and discuss the tough societal questions surrounding potential biases in AI. Giada underscores the importance of ethical training guidelines, alignment principles, and the need for a 'moral charter' in AI models. Don't miss our engaging conversation about the hazards of "Ethics Shopping" as AI continues to evolve. An enlightening blend of philosophy and tech awaits you!
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode