In Jun Kim Former) IBM GBS Hong Kong | Sr. Engagement Manager for AI Initiatives
In Jun Kim has been spearheading innovative AI projects for global banks and insurers in Korea, Hong Kong, and Singapore. He worked at PwC Consulting and IBM GBS Korea and relocated to IBM GBS Hong Kong. He is now leading a Singapore bank’s AI-driven transformation program across 19 countries by working with data scientists, machine learning engineers, AI strategists, and ethicists.
The Risks of AI Model Bias: Root Causes and Governance Approach
Bias is an unavoidable feature of life, the result of the necessarily limited view of the world that any single person or group can achieve. But social bias can be reflected and amplified by artificial intelligence in dangerous ways, whether it be in deciding who gets a bank loan or who gets surveilled.
This session will provide WHAT, WHERE, WHY, and HOW perspectives of AI model’s unfair bias:
✓ WHAT is unfair bias from AI(ML, DL and NLP) model?
✓ WHERE does unfair bias come from?
✓ WHY should we avoid unfair bias?
✓ HOW can we mitigate the risk of unfair bias, across AI model’s lifecycle?
Second chapter of this session will propose an extended Model Risk Management framework for AI models.
The framework includes :
✓ Organization and Governance
✓ AI Models Control Framework
✓ AI Models Risk Management Process & Technology
✓ AI Models Risk Quantification