How AI Augments Human Creativity at Scale: The WPP Blueprint

**Daniel Hulme** (0:00)
The big question is, can we, should we build machines that are conscious? And the hypothesis that we're asking ourselves is, would a conscious super intelligence be safer for humanity than a zombie super intelligence?

**Cindi Howson** (0:22)
Hi, I'm Cindi Howson, host of The Data Chief. If you've heard me talk about data and AI before, you know that I believe everyone, not just data teams, should be able to get the insights they trust. That's why I'm proud to say that ThoughtSpot sponsors this podcast. ThoughtSpot's agentic analytics platform lets you simply ask a question in natural language and get clear governed answers right when you need them. No fuss, no waiting. It's why companies like Cisco, Lyft, Hyatt and Roche count on ThoughtSpot. See what the future of analytics feels like at thoughtspot.com.
Welcome to The Data Chief. I'm your host, Cindi Howson. Today, we're joined by Daniel Hulme, Chief AI Officer at WPP and CEO of Satalia, an award-winning AI company that WPP recently acquired. Daniel is also the founder and CEO of Consium, the world's first commercial research organization focused on understanding machine consciousness. I can't wait to dig in to see what he means by that. Is it real? Do machines have a conscience? I don't know, let's see. But Daniel has spent more than two decades working across academia, startups, global enterprises, helping organizations understand what AI really is about and how to use it effectively. We'll talk about how AI agents are changing business decision making and how leaders can move past the hype and how AI can or should augment rather than replace human creativity. Daniel, welcome to The Data Chief.

**Daniel Hulme** (2:24)
Thanks, Cindi, it's great to be here.

**Cindi Howson** (2:26)
Yeah, and where in the world is here today, Daniel?

**Daniel Hulme** (2:29)
It's usually on an airplane or in an airport lounge, but today I'm at home in London.

**Cindi Howson** (2:34)
Oh, very nice. I suspect we'll meet in one of these airport lounges. Now, Daniel, you have founded and scaled multiple AI organizations, startups, and worked across enterprises. How did you get into this space?

**Daniel Hulme** (2:51)
My undergraduate 25 years ago was in AI at UCL at a university here in London. There were two people on my course. But I guess when you're curious about what it means to be human, what's intelligence, can you build intelligence machines? Can you build machines that are conscious? When you start to ask these questions, you can't help but get involved in the world of AI. So I started very early and I've been passionate about the subject ever since.

**Cindi Howson** (3:17)
You have started early. I started a little earlier than you in the data space, and it always makes me laugh when somebody tells me, oh, a degree in data science is required or a degree in AI is required. I'm like, these degrees did not exist 35 years ago. You also have a very interesting role, an entrepreneur in residence at University of College of London. Tell us a little bit about that.

**Daniel Hulme** (3:45)
Yeah, my entire academic career has been at UCL. I did my undergraduate in AI, my master's in AI agents. That was 23 years ago.
I did my PhD at UCL where I was modeling bumblebee brains, so neural networks back in the day. I ran a master's program actually in applied AI at UCL for many years, five years where I had 100 of the students coming out there applying these technologies. So I've got a very good sense about how organizations have adopted and embraced AI technologies over the past few decades. And I am now entrepreneur in residence at UCL. So I help them navigate, spin out deep tech companies. That keeps me honest. It keeps me close to the bleeding edge.

**Cindi Howson** (4:25)
Yeah. It's an interesting cross-section of academia where sometimes I think they think big and you have time to do the research and then startups who think anything is possible. And then enterprises like at WPP that really have to make it work. How do you balance this cross-functional view?

**Daniel Hulme** (4:52)
Yeah. When I advise startups or academics that want to get into this world, I often say to them there's a really big difference between research and technology. So getting research to the point where it's a technology that's working is a big step. And there's an even bigger step from research technology to business. And I think often people don't appreciate the leaps that you need to make, the skills that you need to be able to translate all of that cool stuff that's happening in academia to actually creating impact in the world. In fact, the company that I started, Satalia, 18 years ago, the idea was to provide AI as a service. The idea was that all of these incredible algorithms are being developed in academia, but they very rarely reach the light of day. So could you create a service where companies could send questions or problems to a machine, and it would then identify the right algorithms to then solve that problem, giving academics the ability to commercialize their IP? Arguably, that was very early, 20 years ago. I think it's still early now.