Zöe Webster

"We are in a hype cycle, And there’s a bit of Fomo [fear of missing out] around AI. Everyone thinks everyone else is doing it and doing it at scale and getting it right – and that’s not really the case. Everyone is in the same period of uncertainty."

"Something like ChatGPT is only one possible solution, AI is far broader."

"It may be a lot of fancy maths, but it’s easy to forget there’s a whole supply chain involved with AI,For example, where’s the data from, who’s supplying the algorithms, who maintains it, who’s keeping track, and what happens if something degrades over time or customer behaviour changes? Making sure the right people are accountable in the right way is really important."

"Not only is the underlying data itself a problem – “It comes from a western view of the world which can be full of poor data and horrific stuff,– but also there is not enough diversity among the people working in that space. We need people in the room to be able to say, ‘I’m not comfortable with that."

"There is lots of amazing work being done out there by people such as Maggie Philbin [the former presenter of BBC’s Tomorrow’s World] and Anne-Marie Imafidon [Stemettes founder]. But if you think about who is going to play around with algorithms at the weekend to gain experience, it’s less likely to be a woman with kids or anyone with caring responsibilities. When do women have time to experiment with it?"

"AI is a “fundamentally useful technology”, It harnesses lots of different varieties of maths to solve problems, but as it grows we’ll increasingly need human context and human understanding. The organisations who are going to win will be those who bring those things together in the most effective, inclusive, empathetic way."

"“AI is nothing without the data,” she says. “But there’s a lot to think through: where is the data coming from, is it representative, is it sustainable, do you have the rights over that data, could it be biased?"

"Machines can only learn from things that are in digital form,so unless something is in noughts and ones, they can’t learn from it. Think about all the experiences you have learnt from that are not digitised – things that have gone well or not so well that are not accessible to machines. There is so much that machines don’t know. They have harvested a lot of data but there’s a lot of knowledge and life experience that’s within us all – but not on the web."

"Everyone is talking about it, but not everyone who claims to be doing it really is"

"where can we put AI?” theme going on in boardrooms. “But AI is one of several tools, It can provide insight from data, it can find patterns, generate content, enable conversations between chatbot and customer – but we must use it for the right reasons."

"I’ve been in this space for a long time, “When I did my degree I was one of two women doing computer science, so I am used to it. But I haven’t seen radical progress. AI is still pretty male dominated."

"Sometimes it’s straightforward, say, if a company ran an AI model and attracted 5% more new business. But often it’s much more difficult to assess – for example, how it also affects productivity within wider systems and potentially impacts society more widely"