Hybrid Human-Artificial Intelligence (HHAI)

Program Overview

The strongest results from AI often come not from full automation but from well-designed collaboration between people and machines. This course examines hybrid intelligence: how to allocate tasks between humans and AI according to their complementary strengths, design human-in-the-loop and human-on-the-loop workflows, calibrate trust to avoid both automation bias and unjustified rejection, and use explainability so that people can challenge AI recommendations. Participants analyse decision processes in areas such as customer service, risk assessment and operations control and redesign them for effective human and AI teaming.

Learning Outcomes

• ✓Analyse a decision process and allocate tasks between humans and AI based on complementary strengths.
• ✓Design human-in-the-loop and human-on-the-loop control points for an AI-supported workflow.
• ✓Identify signs of automation bias and over-reliance and define safeguards to address them.
• ✓Specify explanation requirements that let users understand and challenge AI recommendations.
• ✓Measure joint human and AI performance against human-only and AI-only baselines.

Target Audience

• Operations and process managers introducing AI decision support
• User experience and service designers
• AI product owners and data scientists
• Risk and quality managers overseeing automated decisions

Detailed Program Modules

Training Methodology

Applied Project & Assessment