Demis Hassabis says he is not in the "pessimistic" camp about artificial intelligence. But that did not stop the CEO of Google DeepMind signing a statement in May warning that the threat of extinction from AI should be treated as a societal risk comparable to pandemics or nuclear weapons. That uneasy gap between hope and horror, and the desire to bridge it, is a key reason why Rishi Sunak convened next week's global AI safety summit in Bletchley Park, a symbolic choice as the base of the visionary codebreakers – including computing pioneer Alan Turing – who deciphered German communications during the second world war. "I am not in the pessimistic camp about AI obviously, otherwise I wouldn't be working on it," Hassabis tells the Guardian in an interview at Google DeepMind's base in King's Cross, London. "But I'm not in the'there's nothing to see here and nothing to worry about' [camp]. This can go well but we've got to be active about shaping that."

Deep learning (DL) has crept into almost all parts of Artificial Intelligence. DL methods constitute the state of the art for almost all tasks in image processing, natural language processing, recommendation systems…etc. Consequently, as more and more of these models are being deployed, the interpretability of these models is coming into question. Deep learning is a form of machine learning based on learning hierarchical, distributed models to solve difficult AI problems. Broadly speaking, these models work extremely well for most tasks, but because they have so many learnable parameters (order of millions), it's hard to predict what the effect of 1 single parameter, or a few of them, would be on the overall neural network.

Artificial intelligence (AI) will shape the destiny of humanity, but first humanity has the opportunity to shape AI. At times, anxiety about the former causes us to overlook the latter. We forget that artificial intelligence is going to serve the goals with which we're now programming it. Its implementation will follow the standards we now have the opportunity to set. This leaves citizens -- and those representing us in government -- with an urgent responsibility.

CSOs represent many of the most marginalised individuals and communities in our society; and since these groups are likely to be hit soonest and hardest by the negative impacts of AI, it is vital that the organisations representing them are in a position to speak out on their behalf. If they do not, then not only will those CSOs be failing to deliver on their missions, but also the chances of minimising the wider harmful effects of AI will be significantly reduced.