Responsible ai

Ideas: Community building, machine learning, and the future of AI

Ideas: Community building, machine learning, and the future of AI

Co-founders Jenn Wortman Vaughan and Hanna Wallach reflect on 20 years of the Women in Machine Learning (WiML) workshop, discussing its origins, their parallel careers in responsible AI, and the future challenges of evaluating generative AI and fostering critical thought.

Ideas: Community building, machine learning, and the future of AI

Ideas: Community building, machine learning, and the future of AI

Jenn Wortman Vaughan and Hanna Wallach, co-founders of the Women in Machine Learning (WiML) workshop, reflect on their intersecting careers, the founding and evolution of WiML over 20 years, and their influential research in responsible AI, from interpretability and fairness to the current challenges in generative AI.

935: Global Issues Accelerated by AI (with Solutions), feat. Stephanie Hare

935: Global Issues Accelerated by AI (with Solutions), feat. Stephanie Hare

Researcher Stephanie Hare discusses the need for a guiding ethos in AI, similar to the Hippocratic Oath, to balance innovation with harm reduction. She explores the challenges of regulating technology, the degradation of the internet with AI-generated content, and the critical collision between AI's infrastructural demands and the climate crisis.

Human Neurons are 1M x Energy Efficient than Digital AI Processors | Dr. Ewelina Kurtys | FinalSpark

Human Neurons are 1M x Energy Efficient than Digital AI Processors | Dr. Ewelina Kurtys | FinalSpark

Dr. Ewelina Kurtys of FinalSpark explains their pioneering work in building biocomputers from living human neurons, which are up to one million times more energy-efficient than traditional silicon chips. The conversation covers the technology of reprogramming skin cells into neurons, the company's growth strategy, and the profound ethical and philosophical questions, such as potential 'Matrix' scenarios, that arise from merging biology with AI.

Ethics in AI: Biases & Responsibilities • Michelle Frost & Hannes Lowette

Ethics in AI: Biases & Responsibilities • Michelle Frost & Hannes Lowette

AI advocate Michelle Frost and consultant Hannes Lowette discuss the complex ethical landscape of AI development. They cover the value alignment problem, balancing competing values like accuracy versus fairness, the impact of recent US regulatory changes, and market disruptions from innovations like Deep Seek, ultimately calling for individual and corporate accountability to develop AI responsibly.

Security & AI Governance: Reducing Risks in AI Systems

Security & AI Governance: Reducing Risks in AI Systems

The video explains the distinct but complementary roles of AI governance and security in mitigating AI risks. It contrasts their focuses, from self-inflicted policy violations (governance) to intentional external attacks (security), and proposes a layered framework combining both for comprehensive protection.