Can artificial intelligence remove bias in data-driven decisions?

Human bias is an indisputable challenge when we aim to extract business value from data. With artificial intelligence (AI) quickly rising, should we expect data bias to be a problem of the past?

The insurance industry has a natural interest in leveraging data analytics. Business models increasingly depend on the insight provided by data to better understand customer behaviour, fraud patterns, policy risk, claim surety, and more. As a result, data is closely tied to an insurer’s ability to operate and effectively compete in a complex marketplace today.

On the technology side, we are familiar with buzzwords such as “big data,” which imply that there’s no shortage of data in terms of variety, volume, and velocity of availability. Plain availability of data, however, is not a guarantee of quality of data or a conclusion that the insight would be correct.

This content explores the emergence of artificial intelligence within insurance and whether AI can remove bias in data-driven decisions.

Topics covered:
• Where bias comes from and why it’s a problem in the context of data.
• Five different types of data bias.
• Group fairness versus individual fairness.
• What is realistic in the near future?
• What would it take for AI to remove bias entirely?