Psychology of AI 1: Human vs AI Decision-Making
About This Course
This two-day standalone course examines how humans and Artificial Intelligence (AI) systems approach decisions differently. Participants will explore human cognition, intuition, heuristics, bias, attention, memory, cognitive offloading and productive struggle, and consider what these mean for judgement, learning and accountability in AI-assisted work. The course focuses on the human thinking process: how people form initial views, make assumptions, seek support from AI, and decide whether to accept, revise or reject a recommendation. Through practical exercises using the Capabara AI Assistant, participants will practise commit-then-consult, reflective decision-making, reasoning trace and verification by stakes to strengthen human judgement and use AI as a thinking partner rather than a substitute for thinking.
What You'll Learn
- Describe the cognitive parallels and differences between human and Artificial Intelligence (AI).
- Identify how cognitive and psychological biases influence human–AI decision-making.
- Identify risks such as fluency illusion, cognitive offloading, automation bias, overconfidence and shallow acceptance of AI outputs.
- Evaluate AI-generated outputs using appropriate standards, including relevance, sufficiency, evidence, bias, consequences and verification by stakes.
- Evaluate the trustworthiness and reliability of AI systems using reflective and evidence-based reasoning.
- Design a simple human-in-the-loop decision checklist that supports responsible and balanced use of AI in a professional context.
Entry Requirements
Participants should preferably hold a degree or diploma and have at least three years of relevant work experience.