IDWSDS 2025 - S202: Artificial Intelligence: Beyond Bias скачать в хорошем качестве

IDWSDS 2025 - S202: Artificial Intelligence: Beyond Bias

AI is no longer futuristic—it’s woven into our lives, shaping what we watch, buy, and how decisions are made in healthcare, finance, and justice. The rise of agentic AI, capable of autonomous perception, reasoning, and action, promises transformation—but also brings challenges, especially AI bias. Bias in AI can harm real lives: from hiring algorithms excluding qualified women to facial recognition misidentifying people of color, or healthcare tools failing certain populations. "AI: Beyond Bias" unites three experts to share actionable strategies for a fairer AI future. The first will urge us to “break away from the familiar,” challenging entrenched assumptions and expanding perspectives to tackle the roots of bias. The second will stress the need for authentic data—capturing the complexity of real human experience—over token diversity, to build AI that truly understands. The third will highlight methodological and conceptual diversity, blending technical, social, and ethical expertise to address systemic causes of bias. This isn’t just theory—it’s a call to action for technologists, policymakers, and citizens to shape an equitable AI future. The session brings together three leading experts to explore this critical challenge. They will offer actionable insights and fresh perspectives on how we can build a more equitable and sustainable AI ecosystem. It’s a call to action for anyone who cares about the future of technology and its impact on society. ORGANIZER: Suhwon Lee, University of Missouri CHAIR: Mihye Kim, Chungbuk National University SPEAKERS: Dr. Heisook Lee, GISTeR Dr. Jeong-han Kang, Department of Sociology, Yonsei University Dr. Keon Myung Lee, School of Computer Science, Chungbuk National University Dr. Sang-Wook Yi, Hanyang University