Human Factors—Expanding the Science of Predictive Analytics and Artificial Intelligence (AI)
James Guszcza |
Research Affiliate, Center for Advanced Study in the Behavioral Sciences, Stanford University
AI is reshaping economic and societal landscapes. But the list of AI failures and data science projects that yield no economic value continues to grow. Jim shared insights on what’s missing—a broader, design-led perspective that blends ethics, psychology, and the local knowledge of end users in developing hybrid human-machine intelligence systems.
- Human-machine hybrid intelligence is a better framework to guide practice than “AI.”
- The focus of hybrid-intelligence design is real-world results, not machine outputs.
- Hybrid-intelligence design goes beyond machine learning to take into account human values, needs, and relative cognitive strengths and limitations.
Human Factors—Expanding the Science of Predictive Analytics and Artificial Intelligence (AI) Video