|Title||AI Recruitment and Promotion|
|Focus||Social Responsibly AI – Practical|
|Topic||CSR – Using HCAI Systems|
AI Ethics, AI Decision-Making, Bias, CSR, AI Recruitment
Learning Events to be Completed Before
- Lecture: Fair Operating Practices – AI Recruitment and Malpractices of AI Monitoring
- Lecture: Decision-Making and (Cognitive) Biases
Obligatory for Students
- Review the materials for the expected Learning Events
Optional for Students
- Browse through a previous discussion topic
- Interesting to read: Automated Hiring
Background for Students
Recommended for Teachers
Instructions for Teachers
- Instigate the students to engage in discussions.
- Lead and guide the discussion within the scope of the discussion points.
- Encourage students to focus on the evidence and interrupt if they are speaking over others.
- Keep a note of all the discussion points and share the trail of discussion at the end of class.
- Provide conclusive remarks on the discussion with possible open questions and challenges.
Topics to cover
- Review of AI-based decision making. Problem Definition, Points of Discussion (5 mins)
- Discussion of benefits and challenges of AI recruitment and promotion (covering AI Tech limitations and Bias – Algorithm and Data) (10 mins)
- Guided discussion. Actions are taken and creative solutions to challenges and any possible alternatives (25 mins)
- Discussion of results, conclusions, and open-ended questions (10-15 mins)
The Human-Centered AI Masters programme was Co-Financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.
The materials of this learning event are available under CC BY-NC-ND 4.0