When it comes to implementing data science solutions at scale at the point of care, only half of the problem has anything to do with data science. The other half is entirely down to human behavior.
How will the solution be used?
How do we ensure it will be adopted?
How do we plan for, mitigate, detect, and adjust for unintended consequences?
How do we buy down operational risk and adhere to relevant laws and regulations?
How should processes change to address the root problem - and is this truly a data science problem?
The objective of this seminar is to share these and other key issues associated with real-life implementations of AI and data science solutions and discuss tangible ways in which these challenges can be approached. We will discuss the role of human-centered design in creating solutions that prioritize the needs and experiences of people. We will share how AI governance can be flipped on its head by considering it as AI trust and safety, and the importance of fostering a culture of data science and AI curiosity through literacy and experimentation.

Presenter: Karen Hegarty, Head of AI and Innovation-VP of Cognitive Computing

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