AI for accessibility
Inaccessible AI systems exclude employees and customers with disabilities from participation. This course teaches how to use AI for voice recognition, image descriptions, and assistive tools that improve access. Objectives:
Designing human-centric AI workflows
Poorly designed AI workflows create bottlenecks, errors, and frustration. This course teaches how to build processes that automate effectively while preserving human judgment, transparency, and accountability. Objectives:
Gen AI and copyright concerns
Generative AI blurs ownership lines and creates copyright risks when employees use it carelessly. This course teaches how to create content responsibly, respect intellectual property, and avoid legal violations. Objectives:
Understanding algorithmic bias
Algorithms trained on biased data reproduce unfair patterns in hiring, evaluations, and customer decisions. This course teaches how to recognise bias in AI systems and take steps to promote fairer outcomes. Objectives:
AI monitoring and employee boundaries
Course Curriculum Understanding monitoring limits Learn how to distinguish useful insights from overreach so monitoring supports performance without affecting trust or privacy. What monitoring is meant to achieve Where monitoring becomes intrusive Difference between insight and overreach Recognising limits of tracking tools Communicating monitoring clearly Learn how to communicate monitoring practices transparently so employees understand […]
Adapting to the new way of working
Workplace transformation creates uncertainty and resistance when employees lack preparation. This course teaches how to embrace technology changes, build digital skills, and stay confident through AI-driven shifts. Objectives:
