Should Attention Be All We Need? The Ethical and Epistemic Implications of Unification in Machine Learning
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore the ethical and epistemic implications of unification in machine learning in this thought-provoking 17-minute conference talk presented at an Association for Computing Machinery (ACM) event. Delve into the question of whether attention mechanisms should be the sole focus in AI development as speakers Nic Fishman and Leif Hancox-Li examine the potential consequences of pursuing a unified approach in machine learning technologies. Gain insights into the complex interplay between technological advancements and their broader societal impacts, challenging conventional wisdom and encouraging critical reflection on the future direction of AI research and development.
Syllabus
Should attention be all we need? The ethical and epistemic implications of unification in machine...
Taught by
ACM FAccT Conference
Related Courses
Translation Tutorial - Thinking Through and Writing About Research Ethics Beyond "Broader Impact"Association for Computing Machinery (ACM) via YouTube Translation Tutorial - Data Externalities
Association for Computing Machinery (ACM) via YouTube Translation Tutorial - Causal Fairness Analysis
Association for Computing Machinery (ACM) via YouTube Implications Tutorial - Using Harms and Benefits to Ground Practical AI Fairness Assessments
Association for Computing Machinery (ACM) via YouTube Responsible AI in Industry - Lessons Learned in Practice
Association for Computing Machinery (ACM) via YouTube