What do we do to build fair, trustworthy technology when our tools are based on data from a biased world? The experts at the recent Future Labs Focus | AI event, supported by Capgemini AIE, have some ideas
The technology itself will also have to improve. Prashant Bhuyan mentioned during the presentation his startup, Accrete, that AI needs the ability to scale human expertise. “At Accrete, we’re teaching machines to read so they can generate useful insights about the world,” he said, adding that generating insights is complicated. Machines have to understand the context of the information they collect. At Accrete, this manifests via ranking sources of information by reliability, awarding value to sources that make fewer mistakes.
But even with a better framework and better technology, bias can still exist. There will always be room for improvement. “We should never be so complacent as to say we’ve ‘solved’ bias,” Triveni said. “It is a continual process.”