ELEMENTS OF AI – Talk Time: Gender Bias in AI

This talk explores how gender bias can be embedded in artificial intelligence systems and how, if left unchallenged, AI can reinforce and amplify existing stereotypes. Through concrete case studies and real-world uses of widely adopted AI tools, we will demonstrate how bias can emerge from data, design choices, and underlying assumptions in AI development.

Particular attention will be given to the impact of these biases on younger generations, who often engage with AI technologies without the critical awareness or technical knowledge needed to recognise underlying issues. This makes it essential to address bias early and responsibly.

The session will also highlight the importance of closing the gender gap within the AI ecosystem itself. Ensuring diversity among those who design, develop, and deploy AI is a key condition for building fairer technologies. Ultimately, this talk calls for a collective responsibility to shape AI in a way that supports an equitable, inclusive, and sustainable future of work.

This module will cover the following points:

• Gender stereotypes and biases  in AI: Why are they occurring? What are the risks?
• Case study: Concrete examples of AI which are biased
• Prompt and Results: What does it mean? What can we do?

By the end of this training, the participant will be able to:

• Be better aware of gender biases in AI

This interactive session invites participants to examine how AI represents gender today, using real-life cases to spark discussion around their consequences and implications.