AI SPECIAL
IS AI BIASED? Examples of AI reinforcing social biases are myriad, including an infamous occasion when a Google image recognition algorithm classified black people as gorillas. “Bias is a really important problem in AI,” says Libby Kinsey, a machine learning specialist and advisor at Iprova, the Cambridge company which uses AI to help companies develop new inventions. “It occurs when people make generalised claims which aren’t backed up by sufficient data, or data which has been wrongly applied to all user groups. “But we’re all a bit biased, and I think these cases shine a light on problematic areas for humans in general. In the industry we’re starting to see a move away from the old Facebook mantra of ‘move fast and break things’ – people are becoming more conscious about how they use data and there’s a lot of work going on around establishing good practice.” Iprova’s team of invention developers (surely a candidate for the world’s best job title?) uses AI to
find the most promising opportunities. Our system helps them to make those connections.” Libby’s background is in venture capital, but she retrained in machine learning after seeing a rapid rise in opportunities in the sector. “When I tell people I work in AI, reactions tend to fall into the extreme positive or extreme negative category,” she says. “One of the most common fears is around loss of jobs, but I think machine learning has the potential to transform roles, rather than replace them, because it’s good at doing the routine, boring tasks that humans find difficult. “There was a time, around 2014 to 2016, where people were simply saying, ‘there’s AI, what can we do with it?’. Now I think people are becoming more aware of what it can do and thinking more about how it can be translated into value for businesses.” Iprova is based at the Bradfield Centre on Cambridge Science Park, and is currently hiring across a range of roles. iprova.com
LEFT LibbyKinsey, amachine learning specialist and advisorat Iprova, withcolleagues
generate potential game-changing inventions based on parameters set by its clients, which include global big names such as Philips and Panasonic. By using algorithms to search and cross-reference breakthroughs in relevant areas, the company says it can dramatically cut product development times. “We use AI to augment human innovation,” Libby says. “Invention teams within companies often become top experts in a particular area, but this sometimes makes it difficult for them to scan around and
ISSUE 04 12
cambridgecatalyst.co.uk
Powered by FlippingBook