2023-08-16 –, Aula
In the rapidly evolving landscape of Machine Learning (ML), significant advancements like Large Language Models (LLMs) are gaining critical importance in both industrial and academic spheres. However, the rush towards deploying advanced models harbors inherent ethical tensions and potential adverse societal impacts. The keynote will start with a brief introduction to the principles of ethics, viewed through the lens of philosophy, emphasizing how these fundamental concepts find application within ML. Grounding our discussion in tangible realities, we will delve into pertinent case studies, including the BigScience open science initiative, elucidating the practical application of ethical considerations. Additionally, the keynote will touch upon findings from my recent research, which investigates the synergy between ethical charters, legal tools, and technical documentation in the context of ML development and deployment.
In the rapidly evolving landscape of Machine Learning (ML), significant advancements like Large Language Models (LLMs) are gaining critical importance in both industrial and academic spheres. However, the rush towards deploying advanced models harbors inherent ethical tensions and potential adverse societal impacts. The keynote will start with a brief introduction to the principles of ethics, viewed through the lens of philosophy, emphasizing how these fundamental concepts find application within ML. Grounding our discussion in tangible realities, we will delve into pertinent case studies, including the BigScience open science initiative, elucidating the practical application of ethical considerations. Additionally, the keynote will touch upon findings from my recent research, which investigates the synergy between ethical charters, legal tools, and technical documentation in the context of ML development and deployment.
Integrating Ethics in ML: From Philosophical Foundations to Practical Implementations
Category [High Performance Computing] –Parallel Computing
Category [Community, Education, and Outreach] –Learning and Teaching Scientific Python
Category [Machine and Deep Learning] –Supervised Learning
Category [Scientific Applications] –Astronomy
Category [Data Science and Visualization] –Data Analysis and Data Engineering
Expected audience expertise: Domain –none
Expected audience expertise: Python –some
Giada Pistilli is a philosophy researcher specializing in ethics applied to Conversational AI. Her research is mainly focused on ethical frameworks, value theory, and applied and descriptive ethics. After obtaining a master’s degree in ethics and political philosophy at Sorbonne University, she pursued her doctoral research in the same faculty. Giada is also Principal Ethicist at Hugging Face, where she conducts philosophical and interdisciplinary research on AI Ethics and content moderation. Her publications, resume, and contact information are available on her website.