Decoding the algorithm: Why explainability and transparency matter when building AI-driven systems

Imagine a law enforcement officer deciding whether to deploy a SWAT team or an oncologist relying on an algorithm to shape a cancer treatment plan. The stakes are high, and the need for informed decisions, corrections, and human intervention is paramount.

In a world increasingly shaped by AI, this talk delves into the pivotal significance of transparency, explainability, and human involvement in algorithmic decision-making.

Drawing from a diverse set of case studies, both from personal experiences and the industry, this talk will illustrate why these aspects matter and explore practical solutions to ensuring that the design of AI-driven delivers all the benefits we expect but remains conscientious and minimises the risk of detrimental consequences

Participant takeaways:

• An understanding of why transparency, explainability, and human involvement are critical in AI applications
• Strategies for embedding these values into team and organisational culture
• Practical strategies for designing systems that not only comply with legal standards but contribute to a more responsible, humane and ethical future.

Themes:

AI, ML, Ethics, Explainability, Product management, Compliance, Leadership