There is little doubt that the potential of generative AI is enormous. It has, rightly, been presented as a capability that could herald a new, tech-led era full of benefits for humanity. It can speed up mundane tasks at work, aid medical breakthroughs and analyse patterns in ways that Alan Turing and the Bletchley Park codebreakers could only have dreamt of.
At the recent AI Safety Summit, much was made of the dangers posed by ‘Frontier AI’. There was some criticism that the conversation dwelled too much on future threats and not enough on clear and present dangers. Amongst those cited are large-scale job redundancies – as AIs take over tasks previously performed by humans – and biases in the data on which AIs are trained that might entrench prejudices in human decision-making. These are significant concerns, but thereis another potential pitfall - the risk of model collapse. And the key to that is data.
