Date: Thursday, May 23
Start Time: 12:00 pm
End Time: 12:30 pm
From autonomous driving to immersive shopping, and from enhanced video collaboration to graphic design, AI is placing a wealth of possibilities at our fingertips. However, AI comes with vulnerabilities, which can result in costly mishaps. In this talk, we will explore risks related to bias in AI models. We’ll examine the different types of biases that can arise in defining, training, evaluating and deploying AI models, and illustrate them with examples. We will then introduce practical techniques and tools for detecting and mitigating bias, outlining their capabilities and limitations. We will also touch on fairness metrics that can be useful when developing models.