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Do ethics and compliance go hand in hand with AI initiatives?
Woensdag 12:00 - 12:45
Keynote
Ger Janssen
AI Ethics & Compliance Lead
AI that creates value depends on good and representative data. In this keynote, a number of practical examples will be used to illustrate how Philips deals with this and how, for example, AI development teams are supported throughout the entire AI lifecycle using a bias risk assessment tool.
Bias mitigation is very important for healthcare applications and goes beyond discrimination-related bias, for example. In addition, other AI-related challenges and Philips' learning moments in various areas will be discussed in practical terms, such as ‘how do you prepare your organization for the EU AI Act’ and ‘how do you get a good overview of all the AI that an organization uses and develops’ with all the pitfalls you need to avoid.
Bias mitigation is very important for healthcare applications and goes beyond discrimination-related bias, for example. In addition, other AI-related challenges and Philips' learning moments in various areas will be discussed in practical terms, such as ‘how do you prepare your organization for the EU AI Act’ and ‘how do you get a good overview of all the AI that an organization uses and develops’ with all the pitfalls you need to avoid.
AI that creates value depends on good and representative data. In this keynote, a number of practical examples will be used to illustrate how Philips deals with this and how, for example, AI development teams are supported throughout the entire AI lifecycle using a bias risk assessment tool.
Bias mitigation is very important for healthcare applications and goes beyond discrimination-related bias, for example. In addition, other AI-related challenges and Philips' learning moments in various areas will be discussed in practical terms, such as ‘how do you prepare your organization for the EU AI Act’ and ‘how do you get a good overview of all the AI that an organization uses and develops’ with all the pitfalls you need to avoid.
Bias mitigation is very important for healthcare applications and goes beyond discrimination-related bias, for example. In addition, other AI-related challenges and Philips' learning moments in various areas will be discussed in practical terms, such as ‘how do you prepare your organization for the EU AI Act’ and ‘how do you get a good overview of all the AI that an organization uses and develops’ with all the pitfalls you need to avoid.
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