Bias in AI is a key topic of concern: Capgemini VP

‘UNESCO framework to have far-reaching impact’

UNESCO’s framework for ethical AI would have a far-reaching impact on the entire gamut of AI activities, including development, application, ethicality, data privacy, and regulation, says , VP, Analytics & Artificial Intelligence – India, Capgemini in an interview. Excerpts:

AI systems, we know, are built in an attempt to mimic human intelligence. The systems are taught through sharing enormous data of past human actions to learn from. While this is useful on one end, to reduce the human interference in repetitive decision making and allowing for larger, more complex problem solving, this approach is wrought with inherent challenges of bias and discrimination. Historic data is studded with biases and discriminations that are at times deliberate and many times, inadvertent, in nature. How to identify, segregate/correct them and feed it back to the algorithm to ignore them or systematically adjust for the same, is one of the biggest challenges.

The general view is that the more information we have about individuals, one could build sharper algorithms to target them for offers/recommendations/treatments etc. Recommendation (through data filtering) algorithms have off late, come hugely under the radar for ethical reasons. There is a lot of talk around it, for infringing on personal, sensitive information and its negative impact. They are useful in many scenarios like recommending the right treatment plan for patients or offering useful recommendations that consumers are looking for. But the question again is, where to draw the line on how much information about an individual would be tantamount to infringing on sensitive personal data.