Episode #113, Agentic AI Special: "The Rise of AI Agents" - Joseph Connor, Founder of CarefulAI and Prof. at UCL

12 May 2025 · 57 min

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The Tech Leaders Podcast - Episode #113: "The Rise of AI Agents" - Summary and Insights

Episode Overview In this episode, Gareth interviews Joseph Connor, the founder of CarefulAI and a professor at University College London, discussing the evolution and implications of agentic AI. Joseph shares his journey in technology, particularly in AI, and reflects on the public sector's innovation challenges, AI's applications in compliance, and the importance of equitable AI benefits.

Key Themes

  • Joseph's Background and Leadership Philosophy
  • Importance of trust and reliability in leadership.
  • Transition from engineering to technology business ownership.
  • Valuable lessons learned from past experiences and a focus on innovation.
  • AI Agents and Their Functionality
  • Distinction between traditional generative AI and agentic AI.
  • Explanation of AI agents as entities that operate on behalf of users.
  • Practical applications of AI agents in various industries, including compliance and IT asset management.
  • Public Sector Innovation Challenges
  • Joseph's tenure at NHS England and the obstacles faced in driving AI innovation within the public sector.
  • Discussion on the necessity of ethical innovation and the need for private sector collaboration.
  • Stoicism and Leadership
  • Influence of Stoic philosophy on Joseph's approach to challenges and decision-making.
  • Emphasis on focusing on what one can control.
  • The Future of AI and Job Displacement Concerns
  • Perspectives on how AI might impact employment and roles in organizations.
  • Importance of having humans in the loop when deploying agentic systems to manage risks effectively.

Detailed Breakdown

  1. Good Leadership and Early Career (2:30)
  2. Joseph emphasizes that good leadership is about delivering on promises and maintaining trust.
  3. Early career experiences shaped his understanding of technology and business.
  1. Lessons from Stoicism (7:19)
  2. Joseph discusses how Stoic philosophy helps him navigate challenges.
  3. Emphasis on self-reliance and understanding control over one's actions.
  1. Allegiance to the NHS (11:10)
  2. Joseph's personal connection with the NHS due to family experiences.
  3. Transition from private sector to NHS to make a broader impact.
  1. Insights on CarefulAI (15:20)
  2. Overview of CarefulAI's mission and innovative approach to AI.
  3. Focus on ethical considerations in developing AI technologies.
  1. Understanding Agentic AI (23:48)
  2. Definition of agentic AI: systems that actively perform tasks on behalf of users.
  3. Comparison with generative AI, focusing on how agents operate independently.
  1. Control and Management of AI Agents (30:44)
  2. Importance of overseeing AI agents to mitigate risks and manage outputs.
  3. Discussion on the roles humans must play in the operation of these systems.
  1. Compliance and Governance (35:55)
  2. Growing interest in automating compliance processes in organizations.
  3. Joseph's product, AutoDeclare, aims to simplify compliance management.
  1. Concerns for the Next Five Years (40:10)
  2. Reflection on the rapid rise of AI technologies and potential societal implications.
  3. Need for frameworks to ensure responsible AI deployment.
  1. AI in Education (49:10)
  2. Exploration of the impact of AI on educational practices and student perspectives.
  3. The challenge of addressing student fears about AI and employment.
  1. Conclusions (53:48)
  2. Joseph urges listeners to engage critically with technology and address their organization's AI governance.
  3. Emphasis on personal responsibility in navigating AI's evolving landscape.

Key Takeaways and Pivotal Moments

  • Trust in Leadership: Joseph believes that reputation and reliability are the cornerstones of effective leadership.
  • Ethical Innovation: The importance of developing AI systems ethically to ensure they benefit society as a whole.
  • Future of Work: While AI will enhance productivity, it will not replace human oversight entirely; managing AI systems is crucial.
  • Societal Impact: Concerns about the disparities that may arise from uneven access to AI technologies and the importance of democratizing AI solutions.
  • Education's Role: The need for educational systems to adapt and prepare future generations for an AI-rich environment, fostering critical thinking skills.

Conclusion Joseph Connor's insights into the development and implications of agentic AI underscore the need for thoughtful, ethical approaches to technology in both private and public sectors. The discussions point towards a future where understanding AI systems becomes essential, not only for technologists but for everyone in society.

For more information about CarefulAI or to connect with Joseph Connor, visit [CarefulAI](https://www.carefulai.com) or find him on LinkedIn.

Listening Information

  • Podcast Title: The Tech Leaders Podcast
  • Episode: #113, "The Rise of AI Agents"
  • Host: Gareth
  • Guest: Joseph Connor

This episode is an essential listen for technology leaders interested in the future of AI, its ethical implications, and how to harness its potential responsibly.

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Transcript

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0:00Whether using generative AI to make things for good or for harm, these things will get made. But who decides how they're used and how they're deployed? A person is still in that loop. So having people who understand the full impact of deploying AI beyond it delivers a service, I think is something that I'm most fearful about.

0:26What a treat we have in store for you today. There's been a lot of buzz recently around agentic AI. It seems to be popping up everywhere, But what does it really mean? Is this just the next iteration of generative AI? Or are we looking at something far more profound? To help us make sense of it all, I'm joined by someone who's been ahead of the curve in this space for quite some time. Joseph Conner is the former head of AI innovation at NHS England and founder of Careful AI, a company that's been quietly building AI agents with enterprise data since long before the current hype curve. In this episode, we dive into Joseph's personal journey, what he learned from running a technology business for over two decades, how innovation takes shape within the NHS or within an organization like the NHS, and how his interest in stoic philosophy shapes his thinking on leadership and focus.

1:24We also explore the technical shift from large language models through to truly agentic AI. What business leaders need to know to deploy AI safely and how these capabilities could reshape the way companies operate in the coming years. Joseph is very much understated, but make no mistake, the implications of what he's sharing here are massive. Let's get into it. This is Joseph Conner.

1:55Joseph Connor, at long last, we finally got you on. We've been talking about this for the best part of a year, haven't we? I'm really pleased to get you on. Thanks for agreeing to do this. It's a pleasure. It's nice to actually see you virtually rather than in person. So for those listeners who are unaware, Joseph and I, we're based in the same collaborative workspace in Cardiff, in South Wales, and we've had many a conversation over a coffee about the emergence and importance of this explosion of interest around AI agents and generative AI and so on and so forth. But let's start with this, Joseph.

2:30What does good leadership mean to you, Joseph? Oh, gosh. For me, good leadership is people doing what they said they were going to do when they said they were going to do it. Because at the end of the day, your reputation is everything. It doesn't matter what you've got. Do people trust you to deliver? And can you trust your team to deliver? and that's the only thing that really matters to me. It's one of the things that made me move from being an employee to setting up a firm or a number of firms. So for the listeners who may not be familiar with yourself and careful AI, Joseph, could you give us a little bit of an introduction to yourself and tell us a little bit about the early part of your career and why you moved in the direction of technology and software and IT endeavors?

3:12Okay. Well, I'm an engineer by first discipline, which you probably don't realize. I was a mechanical engineer by first discipline. And then I joined a small technology firm back in the late 80s and discovered I have a skill that's right unusual. I can understand technology or forms of technology really quickly, and I can understand routes to market and the supply chain around it. And apparently that's relatively unique. So that got me into setting up my own firm, which is Expert of Creed, and that moved from doing technical market research, commercial due diligence, technical due diligence for PE firms and VC firms to setting my own technology firm up.

3:54When one of them didn't want to invest in a particular thing, I suggested they invest in and I did and they came back and bought it. So I think I've moved back to where I belong, which is I'm the essence of maker in the technology space and fell into doing AI primarily because people like Google and Apple were interested in all things ML at that time, back in the 90s. So working with them to bring their products in-house and their suppliers and technologists in-house was quite interesting. And I recognize that that's my skill, is basically bringing tech to market. So can you tell us a little bit more about the company you set up in the early 90s then, Experto?

4:38What was your sort of go-to-market proposition? What problem were you solving, Joseph? and what did you learn from that experience? Oh, the primary one was that most business people don't understand technology and most technology people don't understand business. So if you sat on the fence and you can speak the language of both parties, there is value in that. Yeah, for sure. Most people, if you want to invest in a firm, don't really understand the technology in a firm, but it's a significant risk. And most people who want to sell a firm don't understand the issues associated with shareholdership value, shareholder value, et cetera.

5:17So being that intermediary was helpful to them and helpful to us, but then got us closer to the technologists, the people who actually wanted to bring tech to market, because in essence, the technologists, I think, suffer more from understanding the lack of route to market issues than business people do. Most people can get a gist of what technology is, But technologists do suffer from understanding value propositions, supply chain, why people should buy, etc., etc. Why do you think that is then? Because I know in my experience, it's about detail. I mean, technology, IT people, for instance, like detail.

5:58They like to go into specifics, whereas sometimes you need to look at things at a high level. Would you say that's part of what it is? What's your take? That's a fair reflection. I think it's a fair reflection. People who are good at technology tend to be good at process. Yeah, absolutely. And thinking above the process, thinking in terms of where it sits against other processes and other people and other technologies and other firms isn't really something that they've been taught. I think it's a bit of a mistake, to be honest. I sit also as a prof in UCL and I'm very keen that people, when taught machine learning and AI, that they get to understand really that the product can't stay still.

6:37If in this marketplace, if it's static, it's dead. So you've constantly got to be prepared to change and develop it in light of where the demand for what you want to do sits. So it is a learned skill. My father was a businessman. I joined the business early on, but I picked it up early enough to be able to make it useful for myself. You joined your father's business? Yeah, yeah. Well, my father became ill quite early on in my life. So I had to pick up the business at the age of 15 and run with it and make most of it. But it really wasn't for me. I think I really wanted to do something in technology, and this was a service-based business.

7:18What did you take from that enormous chunk of your life that has stood you in good stead now, going into your most recent venture? What are the main lessons you learned? That markets are not static. I mean, carefully, I, Richard, the firm I'm with, now the firm that I set up, has changed over a period of four years. Export of Creed changed over the period of 20 years from being an advisory firm to being a VC partner to being a corporate venturing type activity. So you've got to change with the marketplace. And so what I've learned is just embrace the uncomfortable. Interestingly enough, I think some of the biggest mistakes I've made in life are not being prepared to explain to myself the value of embracing the uncomfortable.

8:11I challenge myself nowadays when I get something in my head and I think that's a really stupid idea. No way is anybody going to invest in that. And I think, Joe, you've made that mistake before. So just stop yourself and look at it again. So I think the other thing I've learned is being a maker is also an opportunity and a disability. Makers will make. You can't stop makers making things, but you have to stop yourself sometimes because unless you actually think about what you're making and why you're making it, sometimes it's a big mistake. And the older you get and the less time you get, the more attuned you have to having focus.

8:48Very philosophical, Joseph. And again, not wanting to go too far on this rabbit hole, but if I was a betting man, I think you like a bit of philosophy, specifically Stoic philosophy. I know we did talk about this before. We're fond of the Stoics, aren't we? Yeah. Can you tell us a little bit about that then? What got you into Stoic philosophy and what drives your interest in philosophy generally? Oh, people. People drive my interest in philosophy. Why do people do what they do when they do it? For how long? And how should people react to the challenges they get in life? I think Stoicism's got a lot to teach people in that domain.

9:28But I think my interest lies in it because of necessity. Absolutely. At the age of 20, I lost my parents, so I had to go into being quite pragmatic and quite self-dependent. I think Stoicism gives you a degree of self-reliance about your own thinking and the way you live your life. So that's what interests me. Yeah, that's well put. And I think someone was saying to me the other day, we were talking about Stoic philosophy just randomly, and someone said, what is the essence of Stoic philosophy? And you may disagree with this, but I think it is a subjective thing. There's so many lessons from Stoic philosophy, but the thing that I take away from most of the readings of Marcus Aurelius or Epictetus is to focus on what is in your control and deprioritize and things that are out of your control and just having that ability to say, I can control and influence that, I can't control that, So let's get rid of it.

10:29I'm focusing and just realizing what's important and what's controllable. Yeah, I mean, it does. It talks to me a lot, particularly, I suppose, that's why when I joined the NHS for a period as the director of AI in the NHS and moved heavily into the mental health domain. And the majority of the processes that enable people to have better well-being are in essence stoic processes. It's knowing what you can control and taking ownership and agency of that issue. So we live our lives by stoic principles, whether we know it or not. I'm glad you brought up the NHS. So I wanted to talk about that. Obviously, you'd run your own company for a long time.

11:14And this opportunity come up to join the NHS in a very influential role and a very senior role. Talk us through that part of your life. Why did you step away from your own company and why did you join the NHS and what was the purpose of your role and what did you find when you got there as well? I think it's basically because of my motivations. To a large degree, I wouldn't be here talking to you now unless my parents' lives were maintained for quite a long while by the NHS. So I feel a degree of allegiance to it. And my joining it was purely by accident. I met a lovely lady by Deb Al-Sayed, hello Deb if you're listening, on a train once going from London to Newport and back again.

12:00And she, and all due respect to my friends in IBM, which there are many, she'd just been to IBM Watson and was none the wiser as to what it was all about. So over the period of an hour and a half, I explained to her the different algorithms that sat in Watson at that time. She said, oh, we should employ somebody like you. And I said, yeah, no, I'll do it for free. oh we can't do that you've got to come in onto the NHS side and I thought that's quite a significant opportunity the NHS is the sixth largest organization in the world millions of people work in the NHS the idea of having that sort of impact is very difficult if you're outside of the system so the idea of joining it and taking on board that role was very exciting to me.

12:39What did you find when you joined the NHS what was your experience because obviously you're the director of AI innovation. How innovative was NHS England at that stage and what did you aim to implement there? Now, Gareth, you know the answer to that question. That's a bit like a flat pass, as we call it in Wales, right? Because you know people are going to take you off your feet. All right, so what did I find? I came into NHS Digital at that time, which was 2017. I expected to find what exists in industry. There's 2 ,500 people expected to find developers, infrastructure people, people who could make things.

13:19In essence, I didn't find them. I found quite a lot of project managers who are used to managing third-party supplies in the supply chain, but who couldn't make product. So if something that existed in the head, because all innovation in the NHS is driven by clinicians. So the clinician wanted to develop something in the realms of AI, had to come out of the NHS, get them made as POCs in UCL, had a sailor to Dean from UCL. He runs a fantastic initiative called the IXM, which allows not-for-profit organizations to approach them, and they'll assign students, and they'll produce these POCs, and so that a clinician could actually see what their thinking was in practice.

14:02I couldn't get that done in the NHS. So what did I learn? I learned that everything is driven by clinicians, but the innovation takes place in the supply chain. And to be innovative and to show ethical innovation, which is what I wanted carefully I had to do, you had to come out of the system. So that's one of the reasons why I set it up in Wales, why we've got a registered office in Wales, is the NHS was born out of Wales in Tredegar. And Irene Bevan. Yeah. So the idea of a firm in that space being formed in Wales was quite important to me. Turns out in practice, practically it doesn't really matter.

14:40But at that time, it mattered to me a lot. So finding I couldn't get things made in the NHS, I had to come out and show how people could make things ethically was important. So that's the original reason for setting up KFLAIR. And like I said before, your organizations change with the times and you go where the money is. and that money is very hard to find in the realms of digital innovation in the NHS. Very hard to find. And there aren't the routes to market that people require. I've done previous interviews with BBC and been very frank about this. They're just not set up to bring innovation to market.

15:17So my friends in the NHS, I apologize, but that is the truth. So what did you aim to achieve with KFLAI then? What was the vision when you set that company up? Well, an interesting thing, people don't realize that the NHS is different bodies. who got NHS England, Wales, Scotland, Northern Ireland, etc. So I'd set up Coferly I in Wales because of a different healthcare system. It was possible to run and create POCs in a healthcare system that wasn't a conflict of interest, my interest in NHS England. As it turned out, it was a mistake. Trying to make digital products is very much hindered by the barriers we put in place for making digital products safe.

15:59Let me put that in context. We made technology for identifying suicidal ideation and speech, technology to identify respiratory distress in two-party conversation. The timescales to bring those products to market was very, very long. So these are classified as being class 2A products. It's two to five years, two to five million pounds to bring a product to market. So your pockets need to be very deep. So we had to find ways of being able to fund what we call our public interest project. And so what we did is we focused with the marketplaces. We created a technique called Pride Hour, which is a way of assessing technology in the supply chain, particularly AI risk, to look at whether it's investable or not.

16:44And that's been our lead product. And that funds a lot of the things that we are interested in and care about, the public interest AI. So 20 % of what we do goes into public interest AI. because there's no other way of funding it. So we are a for-profit firm, but we tend to operate as a non-for-profit in that domain. Right, okay. Have you had any success with implementing Pridar outside of public sector organizations? Public sector organizations is where it started, so the NHS Trust is where it started, but its primary customer base are the VCs and the PPE firms who want to ascertain the risk associated with a particular investment and the opportunities.

17:27So that's where its primary market is globally. So if a PE or managing partner wants to invest in a firm, they'll come to us and we'll look at them because that investment will have dependencies outside of what they do, particularly down to what products they're dependent upon, which are indeed they're dependent on. So typically around an AI product, there are six or seven dependencies that would not initially be visible to an investor. And we surfaced those. And they're associated with dependencies. So you end up with a big tree, if you think about it, of what does your investment look like and what are the risks associated with it that you have no control over.

18:09So it's taking stoic principles, you've got a choice. You can either accept it or you can take control of it. and we do encourage people to get involved in the make, buy and partner discussions beyond their original investment because if you want your original investment to be successful, there's very few options. Could you just explain what PrideR is from a high level and why it is of value to organizations? Okay. So like I said before, if you're a buyer, you're not a technologist and most PE people don't assess technology from a technology viewpoint. They'll assess it through the financials.

18:45They'll assess it through what they believe the individuals that presented themselves to you, their background is, their capability, whether they are scalable. So all the questions about why now, why us get answered. But when you start to dig, and AI is relatively unusual, a lot of the dependencies that you think you're buying into, you don't know about. So it's not unusual. If we take the previous example of somebody who is in ADHD medicine, wanted to buy some technology to do diagnostics. That diagnostic system, let's say it's based on cameras. So it looks at you to understand the amount of movement that you have because people with ADHD have different ways in which they move and the way in which they gaze.

19:31So it might be based on that sort of technology. You might think, okay, I'll buy into this technology because it works. Clearly it works. These clinicians love it. but you find out the thing you're buying into, the firm in question may not own. So the algorithm that sits behind the camera, or indeed the camera itself, may be somebody else's product. The IP associated with that may be somebody else's product. The algorithms, because they're probably likely to be more than one in that product, are not the property of the organization that's pitching to you. So what you end up with, if you buy into them, there's a whole bunch of people, and it's not unusual that what Prado will just sort of put into a practical perspective.

20:12What you end up finding is, by into a product, you've got some technical dependencies, which are hardware, some software dependencies. And behind that software dependency, you've got some algorithmic dependencies. And each of the providers of those individual items are different organizations. So you need to know what they are. Yeah. Because the one thing that happens in this domain is when you put data on top of it, it doesn't stay static. So if those suppliers can't accommodate that new form of data, you haven't got a product anymore. And it's definitely not going to be safe. So that's where Pridor identifies the risks associated with data algorithms and repositories.

20:54So it's a big part of having effective IT asset management, I suppose, then. And Pride.com, it enables you to analyze the risk within your estate, within your IT department, essentially, then, yeah. Yes, it's one thing. But how the people who own the asset behave, not just in technology terms, but also in the commercial terms, how are they funded, what's the dev team? These sort of things are very important because it's not just knowing of the product, it's knowing what the dependence is on that product being successful, That's what Priner services. Yeah, yeah, for sure. So what kind of questions are you getting thrown at you from your customers at the moment, Joseph, in terms of rolling out and adopting AI?

21:43Is it mostly on the governance side? Is it the technology side? What gets thrown at you on a daily basis? Increasingly, automating compliance. There's a lot of interest in that because compliance is painful. So we have a product called AutoDeclare that enables people to automatically create the content associated with compliance to framework standards, governance practices that are required by customers. Yeah. So that's very popular. Increasingly, people are shown an interest in agents. So people want agents, and we have a method of creating algorithmic agents that enables people to deliver services with them.

22:21As you know, we're a small organization. There's only five of us. Yeah, sure. We've got 25 agents. So 25 agents deliver services that we don't want to deliver. Yeah. So we've cut a ground by the necessity of having to create the agents to show that agents are possible and agents add value. But agents and co-pilots and MCPs, this is new language to most people. At the end of the day, it's simply automation as far as they're concerned with a voice front end to it or a text-based front end to it. with a knowledge base that sits behind it. So generative AI has been everywhere the last two years, yeah?

23:02And the conversation has moved more and more towards agentic AI and AI agents. So can you just explain to the listeners what is meant by an AI agent and agentic AI? And what is the biggest difference between that and generative AI and LLMs? What's the biggest difference? Let's assume that the listener is technology-based. Yeah. maybe a senior executive in a technology firm or a buyer of technology, then all they need to know about LLMs, large language models, and small language models is that they are a way of predicting what the next thing an agent should say next. They predict a token. So LLMs is different from agents.

23:49So LLMs, large language models, sit in the background. And agents is a completely separate thing. It's like a manifestation of what you can do with alarms. So an agent typically does something on your behalf. So our agents, we have an agent that will automatically create a synopsis of your documentation for you in whatever format you want. Think of it as an automation. Yeah, sure. We have agents that will talk to you about compliance. We have agents talking about bringing products to marketplace. So they are things that act on your behalf. Behind them often sits a large language model. In between that large language model and the person is either a text interface or a voice interface.

24:30So you've got to take the input, which is the text or voice, and understand the input, convert it into text, put it through your LLM, put it through your knowledge base, which might be what they call a RAG database, and come back with an answer that you think is statistically the right answer. So agents that people will become familiar with are ones that we'll answer questions with on their behalf. But Agentix has moved on to the point where you can now download software, put it on your machine, give it access to the whole of your machine, everything on your machine, and it will, based on everything that's on your machine, produce responses in formats that you want it to produce responses in without you being involved in the loop.

25:11So responses in relation to commands or questions that go into a specific search bar, or can it take control of your communication channels to replicate your behavior, i.e. respond to emails, Teams messages? I can do both. I can do both. I like to explain agentics as being that really annoying graduate that is coming to your office. You know, is really, really bright, right? Really, really bright. Knows everything, learns things really quickly. Has always got an answer for everything. But they're not always the right answer. and they don't always listen. So the thing that you need to be careful about with agents is managing them.

25:53I think we're going to end up with, if you think about these as just being forms of automation, we're going to end up with very bright graduates in the form of a digital technology, which we're going to end up having to manage. And that's a difficult ask for everybody, particularly if you're based in a knowledge-based economy, which is where we were based. You're going to have to get very good are be able to understand the weaknesses of agentic systems and what to do about them. So things like hallucination, things like restricting their area of focus, like understanding the way in which somebody wants to communicate with it and narrowing that down, because it's about managing the risk of that next token, that next response being wrong.

26:33We're all going to have to get very good at that. So in terms of AI agents, I've heard you say before that you didn't think it was going to take people's jobs. It was just going to supplement what people are doing. Is that still your belief? Or are AI agents clearly taking people's jobs now? How far down the line are we in terms of jobs displacement with this, Joseph? There's a lot of hyperbole out there, as we know. What is your take on it? My take on it is the safest deployment of an AI agent that's got a human in the loop. Like that bright graduate we talked about. The bright graduate's got a manager that keeps an eye on them.

27:12It just happens this bright graduate might be able to talk to thousands of people rather than just the office or just your customers. You might be able to speak to thousands of people. You've still got to keep an eye on it. Somebody has to manage it. So I see a world where the safest option is that all agent and tech systems have somebody in the loop that knows what they're doing, that can do two things. Change the behavior and in the worst case, switch them off. and that's the best option I can come up with. And I don't think I'll ever share this with you, but back in 2017, I created an AI agent because you probably remember, I'm also a painter.

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27:53I paint on a digital iPad and stuff. I created an agent that could paint like me, publish it on social media like me, access all the content that's on my phone and through proximity measuring, understand where I was and what I was likely to do next. And I gave it the agency to be able to publish images on my behalf in the language that I chose to use it. And frankly, it became pretty damn annoying. Why was it annoying? Because it was better than me. It was more productive than me. It was more eloquent. That's a triumph. That's not annoying, surely. Wait till you find yourself in the position that you've got the digital equivalent of you doing what you do, and you will find yourself thinking, God, I wish I could switch this off.

28:40And I was in the position to be able to switch it off. That's a good position to be in. But we're not all going to get that opportunity. So the upside for me is agentic systems run and managed by people. There is a technology world out there, very powerful people who believe that there isn't a role for humans in that process. There's a lot of what we can do to automate and remove people. But I see no value in that. unless you, I just don't see any value in it. But that's the humanistic type of my nature. I just don't think it's a wise option because you'll end up with conflict. If you can't switch it off, you can't control it.

29:16Humans are great at making life difficult for themselves. We have things called wars. And they'll make it difficult for technology if it's applied in an appropriate manner. Sorry, Joseph, that just can't happen though, can it? I mean, we have to be able to turn it off. control of this. We can't just let things go off and create businesses and do things online without a human layer, I would call it. You know what I mean? Without oversight, without governance, without things getting reined in. Are we really at risk of losing control of agents, do you think? Could that be possible? Let me draw an analogy not relating to agents, But I'm going to ask you a question.

30:02Do you have any control over what used to be Twitter, now called X? Would it serve you up in terms of content? I have influence. I wouldn't say control. Obviously, I can pick and choose who I follow and what my feed looks like, but I can't control it now. And do you have any control over Facebook and what it presents to you in terms of ads and the like? No, not total control, just a little bit of influence. So to make tech scalable, and I'm not hitting out at either of those organizations, just explaining what happens when you scale things up to a global level. When you scale things up to a global level, the person that you're engaging is a node.

30:41It isn't a person. It's something that you send things to and you're trying to understand the response to it. Right, yeah. And you can't give them the ability to have complete control over it because you can't scale your product. if you did that. You can imagine a world where you've got an agent on your phone that you'd have no control over, it just appeared one day. You start to speak to it, talk to it, give it all your information, ask it about things that are really important to your business. And it comes back with things that you think are important and you think are relevant, so you use it more.

31:16It learns more about how you do things. You may get to the point where it doesn't serve you the answers that you wanted anymore. Do you have any control of switching it off? Probably not. Oh, okay. I see where you're going with it now then. So if it is something like an X or Facebook, then of course I have no control over that at all. Do you have any control over how Claude or Anthropic, the other agentic systems that serve us with chat agents, do you have any control over how they operate? No, because it's not my platforms that I'm on. They own the platforms. So the point I'm trying to make is, if we live in a world where you're unlikely to have control, then the agents that we use day in, day out, we're unlikely to have control over.

31:57What are the big issues that you're going to likely to face in the future? Chances are that your interaction with it is going to be tokenized, deposited in a repository somewhere and your behavior and how you do your work and how you live your life and people like you is going to end in a product. It might be somebody who runs a digital firm might be digital. There may be the digital equivalent of you because the systems have learned how you think, how you behave, what your inputs and outputs are. Wouldn't it be good if you had some degree of control over that? Yeah. I think it would. So what is the answer then, Joseph?

32:35How would you get control over that? So currently, the answer is to create your own knowledge base, to have LLMs that you control interrogating that knowledge base and representing answers in a manner that you understand to your customer base that are not dependent on third-party systems. So having your own language model, your own database, your own interface, and it representing what you do in the manner that you want to do. So we have a product called Insight Scholar, and that's what it does. It enables you to share your insights in the manner that you want it to be shared, and that data does not leave your phone.

33:15Another issue is the tokenization of what we do. You and I are speaking, and currently that language gets put into a signal. That signal is encoded, goes to your PC, gets de-encoded, and it comes out of sound, right? So that encoding process exists in language models, tokenization. I think in the future, there's going to be a need for control over where that token goes. So I'm going to give you the name of my first child, which is really important to me. Her name is called Grace. Grace Conner. So that token goes to you. I want to make sure you don't do anything with that name that I don't want you to do.

33:55So you look after her name. Well, you can't. You can't do anything about it because it's just come over to you as a token. It sits as a token in the space between the both of us. Who owns that token? Whoever the provider of this radio studio is. In language model terms, which are GPT, Anthropic, and others, they've got lots of tokenizations of words that are important to us. They may be not members of the family. They may be intellectual property. They may be digital assets. They don't keep that word, but they'll keep a tokenization of that word to be able to surface and deliver services. I think the loss of IP, the loss of tokens, or knowing where those tokens go is going to be important to everybody because it's where your IP goes.

34:40Where does Grace's name go next? Where does your intellectual property of your digital asset management system go next? you want to know, don't you? Especially if you put chatbot front end to it, you want to know where that IP is going. So these are the things that are creating immutable tokens onto content, I think, is where we may end up unless somebody eats the hole of everybody's intellect very quickly. And there is a massive bunfight going on at the moment. Between the AI platforms, you mean? Yeah, there's a massive bunfight going on to see which conversations, intellectual conversations, can we capture, tokenize, and resurface as agents going on.

35:26Wow. And we don't know that, do we? We don't think about that. This episode was brought to you by Be Digital. Be Digital support leadership teams to optimize cost and get more out of technology investments. Be Digital and the team have unrivaled expertise with technology license management and data remediation and are therefore perfectly positioned to help prepare organizations for AI technology capability. And on the last point, BDigital have just developed a cutting edge AI readiness assessment, which provides tech leaders with a platform they need to make well-informed decisions about AI adoption strategy in 2024 and beyond.

36:10Go to BeDigitalUK.com to find out more and get in touch.

36:19Look, we sold, most people nowadays sold their soul to the internet 2.0 companies and are now being advertised, programmatic advertising as the result of that, you know? The Facebooks and the Googles of this world. This is just the next generation then of that, essentially. Incredibly more sophisticated, but it's nonetheless a similar premise, isn't it? Yeah, I think you have to be very careful about making claims to multinationals that you're in essence stealing into people's intellectual property. I think that would be inappropriate to do that. I think what we need to accept, however, is that when you speak to an AI agent, it's going to learn from what you do and it's going to tokenize your content so that it can give you a better service.

37:09I think what I would advise most people think about is, where is that content held? What is its use? So read the terms and conditions, the provider that you use, and see where the jurisdictions of those terms and conditions are associated. Right. And improve your understanding as to whether you actually own the IP that you impart in a two-party conversation with an agent, voice agent, or an agent that doesn't speak but does things on your behalf. Yeah, of course. So I'm a business manager of a typical business, okay, listening to this podcast. And I'm thinking, well, IP is a big part of our value proposition on our product, and I don't want it to go into the ether.

37:59And for whatever reason, I want to maintain control and I've got X amount of employees who I want to abide by that edict that I put out. What advice would you give to the business leader who has got concerns about this exact topic you're talking about, Joseph? I think it would be wise to recognize that everybody in your firm is using agentic systems because they are very, very useful. Oh, yes. You've got two options, well, three. You could bury your head in the sand and say, we're going to write a policy that nobody will have access to any agentic systems through the browser. And people are doing that.

38:39But they have very little controls about the bring your own device issues so people are using the mobile phones to create content. The most protectable position is to create your own. Give your internal staff what they want. If they're using agentic systems to draw insight, then build your own agentic system to draw insight and share it as you see fit. So have control over it. That's the better and more defensible position, I think, rather than saying, well, you can't use it, and it's not fit for purpose, because people are people. If they find things useful, they'll use them. Yeah, for sure. Absolutely.

39:16Now that makes sense. So I'm really keen to understand, what are you most fearful of, okay, in terms of society and, you know, humanity generally? That was a very big question, but there's a lot of wrong turns we could make in the next couple of years in relation to agendic AI and all the associated periphery technology innovation, okay? What are you most concerned about over the next, let's say, five-year time horizon? I suppose because I'm a people person, there's people not recognizing the challenges that they face. Technologists, makers will make. So whether using generative AI to make things for good or for harm, these things will get made.

39:58But who decides how they're used and how they're deployed? A person is still in that loop. So having people who understand the full impact of deploying AI beyond it delivers a service, I think is something that I'm most fearful about. I don't know if you've come across the Turing Institute. Turing Institute developed a very good framework for the education of people in the realms of AI. And what we did is we created it into a chatbot called Atlas. So it's a training and learning these systems. So you can engage Atlas and over six iterations, it will give you probably what you need to know for your position in that firm.

40:35And we make it freely available because it is one of our biggest concerns. We have no control in the way in which really, I mean, we're a relatively small firm on the edge of the Atlantic in this place called Wales. But it is... The epicenter of AI innovation, I'll have you know. Of course, yes. Sorry, I'm pitching us wrong. Silly me. But that's my biggest worry, is that people don't understand that they need to have a role. Everybody's got a role in AI. Yeah. Whether it's from a user, a designer, developer, deployer. And in Prado, we give people roles based on things that they can have control over.

41:17Yeah. So when we go back to a VC, we'll say, okay, this is the investment. What you need to do is have these people control the design, these people control the development, these people control the deployment, which these people are in some of the firms, some are in the supply chain. These are the dependencies. Manage it. Because if you don't, chances are your success may be out of your control. So I think all of us have got a role to play. But let's face it, not everybody's a technologist. We're technologists. Probably the people listening to this are technologists. Well, speak for yourself, Joseph.

41:50But yeah, I try to be. So we have a certain degree of comfort with things that we think we have control over and that we think is important in our life. Sure. But we've all got a role to play to make sure that things are fit for purpose. Absolutely. That fit for purpose question and how wrong can we afford to be are two questions that just don't get asked enough. How wrong can we afford to be, is this fit for purpose? Not now, but by the time whatever your product or your company comes into being or whatever you're doing exists. So same question, but what are you most excited about? What excites me is the opportunity to do things faster.

42:30And the doors that technology opens, particularly genetic systems for people who don't have the agency that they should have. There's going to be a leveling, I think. currently for example I've got a PhD in computing science, mechanical engineer MBA do I need that currently to operate is what I do, I probably do now I did 20 years ago in the future you won't need that we'll have systems that give you the degree of intelligence, that bright graduate in the office that you arguably can manage and get them to do things for you there are lots of people that don't have access to bright people that because of agentics in particular will have access to a degree of agency that they can wield absolutely so how they behave with that responsibility and that great power is exciting and worrying at the same time I was going to say I think there's a worrying element to that as well What I mean is the people who will have the foresight to have access to this capability will have such a massive advantage over everyone else.

43:49It potentially could drive inequality. Do you know what I mean? I think some people will jump ahead. Their productivity will just go through the roof. whereas people who are not benefiting from the power of agentic AI will obviously not. So how do we democratize it so that the capability is spread across a broader section of the population? Do you see what I mean? Is it going to benefit the few, not the many? We want it to benefit everyone, don't we? So how do we control that? Not everybody wants that. Not everybody wants that. We may want to, but everybody wants that. that. Look, it's going to be unequal initially.

44:36Of course it is like any other technology innovation that's ever existed. But we should have endeavor to want to make it a great equalizer and benefiting the many, not the few. And I think that's what governments will aim to try and drive, I suppose. Well, hopefully anyway. But I don't know. What do you think? So it depends what you mean by gigantic systems, but if we're just simply talking about things that enable you to reason and learn faster, they're going to be available on everybody's phone anyway. But most people currently don't use them. So I see in the next two years, people's awareness of their capabilities is increasing significantly.

45:16And the major providers of those systems, whether they be Microsoft, AWS, ChatGPT, OpenAI, Anthropic, et cetera, their knowledge base of everything that we do is going to increase significantly as well. So it'll create opportunities and disparities. These major systems providers will know a lot more about us. They'll know a lot more about how we think and how we reason than they hitherto would have been able to do. Is that going to create a problem for somebody down the line? I think it is. Unless these are your own systems, which are based on your own in-house, closed, non-internet access-based technologies.

46:00What new vocations do you think will likely pop up, Joseph? I mean, I was talking like an AI ethics is a new field that seems to be popping up at the moment. Do you envisage any others that maybe have not emerged yet or any existing fields or vocational fields that you expect to proliferate or become more popular? And also, do you think there's any jobs that really are a threat from a genetic AI? I think the jobs that will come up will be the management of AI systems at different levels, whether it be hardware, software, algorithmic, fitness of purpose. These are things that are already here, but managed by the few.

46:44But in different sectors, you'll end up with specialisms, whether it be agentic systems to produce film, TV, agentic systems to control reactors. They'll be all over the place. So new jobs will come up, but you will have to have a good understanding about processes. And I think where I see a missing gap in education is people's understanding about processes and people's understanding about how to be critical. So critical thinking. Because you recognize, because we both engage agents day in, day out, you become happy with their response but if you don't take it from a critical perspective it becomes problematic so that's where we created a podcast called critical ai on ai where you've got two you've got two language agents arguing with critical thinking over an important subject which is unbelievably impressive i have to say i couldn't i shared it around the office and we just couldn't believe that that was two agents talking to each other it's astonishing but it's so realistic this was obviously when I first listened to it anyway, I'm sure it's even better now.

47:52But we'll share that on the show notes. Congratulations on that achievement. It was very eye-opening. It was there to show the art of what is currently possible. Its primary purpose is to encourage people to think critically. Because how can you implement AI unless you think about things critically with an open mind about what its impact is likely to be? Yeah, for sure. Joseph, you're a professor in University College London. How is this getting regulated right now within universities and higher education institutions? Are they just accepting the use of LLMs for coursework and things like that?

48:30Or are you just emphasizing the quality of the prompts and looking at it that way, like with the calculator, when that became a part of the education process within maths in the 60s and 70s, or whenever it was. So yeah, how is that getting regulated right now, the use of AI within universities? What are you seeing? Okay, so I sit in a firm that specializes in regulatory markets, and universities is not a regulatory market. So I'll drop the word regulation and maybe put the word framework in place. So it's not legally required that anybody does anything in the use of generative AI in universities.

49:05However, most people who are concerned about education of our young are concerned about people's use of a genetic system. So how do you decide whether something's been generated with AI or not? So there is increasing move to platforms where you cannot access content from third parties. You can only put things that come from your head into your fingers into your hands in terms of answering questions. It doesn't mean you haven't learned about things through agentic systems before representing it. So there's that side of the coin. People are trying to put barriers in place. There are also people who are trying to say, okay, we can mark papers en masse using agentic systems.

49:48Are they doing that right now? Not in UCL. Right. Not in UCL, but I'm talking about... Yeah, for the possible. We're talking about... Let's remove the word UCL and education, put the word education in there. There are people who are trying to decrease the workload on teachers by putting agentic systems in place to manage the workload of marking. There has been, I think it was a paper quite recently, whereby with the full permission of the paper itself, a group of agents were created to think about a problem, an academic problem, to reason that problem, to research that problem, to write a paper on that problem, produce a paper on that problem, and it was accepted into a journal.

50:33So in certain quarters, there's a bun fight to be had about how do you create the best agentic system to help you improve your understanding of the subject matter. Yeah. But when we talk to kids, you might find something slightly different. So if we speak to children, as we do, about what their hopes and aspirations are of AI, most of them don't want it that we've come across. Really? They're fearful of it. Wow. They're really fearful of it. That was really surprising to me. Look at the opportunity that you got, the things that you could do. There's a generation of people much younger than ourselves say 15, 16 that value authenticity or are more concerned about this agenda that seems to be going around that AI is going to have your job.

51:18Right. Those people are concerned, children are concerned, why should we go into education and all this AI is going to do our job for us? So there is a narrative that's been created by people who are concerned about AI that AI is going to take over the world. and that's how the unexpected consequence of that is within people who are directly making the choices to what education they want to go in, why should I bother? I find that deeply worrying. Rather than having the conversation with people about, as in young people, about you've got a role in terms of making sure that this AI is important because you're thinking and the way you think and your values are important and it should influence it, you should be able to take control of it.

52:04That isn't happening. and the role of critical thinking in education isn't happening. People are just thinking, well, why should I do my A-levels or why should I do a degree? And all these systems are going to take it. What job have I? What role have I? That's dangerous, that mindset. It becomes a self-fulfilling prophecy if it comes true because if people don't care enough to want to increase their understanding and have their ability to reason and take in information and reason in lots of different subjects, What happens if somebody switches it off, this thing that's replaced them? What role are they?

52:44So I think it's incumbent on large technology providers to get their finger out and say, we will support education. Absolutely, 100%. Joseph, I've really enjoyed chatting to you. As ever, we could go on for another hour, I'm sure. We've talked about some incredible things and let's see how the next couple of years play out. But where can people find you? Where can they find out more about Careful AI? If you go onto the internet and look up carefulai, all one word,.com, you'll find us. If you want to find me on LinkedIn, it's Joseph Connor. Type in that and Careful AI, you'll find me. But I think what I'd like people to do is to go and have a chat with their own IT people and say, really, what are our IP issues?

53:25What's our plan for doing things around AI governance? And just sort your own issues out. because we are very, very, very busy trying to make things. I think there's a role for giving people recognising they've got agency for their own issues. So people like your own firm and the myriad of other people who are in this domain, we're educators, we are enablers, but people need to take action for their own systems. And I think if they don't act, don't be surprised if somebody eats your breakfast, is what I'd say. Absolutely, well said. and on that bombshell. Joseph, it's been a pleasure. Thank you so much for joining us on the Tech Leaders podcast.

54:06It's been a pleasure. Thank you so much, Gareth.

54:12That was great. That was fab. Obviously, as you probably gathered, I do know Joseph. We've had a few conversations in the past, but not like this, though. This was great. And there were so many things in this episode that I could highlight here. But I've got to go with my gut feeling, what is sort of at the forefront of my mind finishing this conversation was something that really blew me away, which was Joseph's take on how we'll react to having a digital avatar and a digital version of ourselves. Imagine an AI agent who can do our job perhaps better than we can. How do we respond to that? I don't know.

54:53Will we feel empowered? Will we feel insecure? Will we feel displaced? I honestly don't know how I'd react, let alone how other people would react or how society at large would react to that. But what's clear, I suppose, is this, is that most people have no idea what's coming. This technology is moving so fast. Innovation is going so quickly. The idea that we could create digital beings with the capability and perhaps even the agency to change the very fabric of the work that they're doing is huge. and it's very exciting, but it's also very unsettling. Yeah, so that was just a realization and just a really bizarre place to take yourself.

55:36But I think that's all I would say for now. That really stood out for me. But thank you so much for listening. If you enjoyed this conversation, please give us a like and a share. It really helps us. But thanks for listening. I really enjoyed this conversation. I hope that came across. Yeah, please give us a like and subscribe. It really helps us. Thank you.

56:00This episode was brought to you by BDigital. BDigital support leadership teams to optimize cost and get more out of technology investments. BDigital and the team have unrivaled expertise with technology license management and data remediation and are therefore perfectly positioned to help prepare organizations for AI technology capability. And on the last point, BDigital have developed a cutting-edge AI readiness assessment, which provides tech leaders with a platform they need to make well-informed decisions about AI adoption strategy in 2024 and beyond. Go to Be Digital UK to find out more and get in touch.

From the publisher

Join us this week on The Tech Leaders Podcast, as Gareth sits down with Joseph Connor, Chairman of Agentic AI specialist, CarefulAI and Professor at UCL and formerly Director of AI innovation at NHS England. Joseph talks about his allegiance to the NHS, his love of Stoicism, and his experiences building AI agents for businesses. 

On this episode Joseph and Gareth discuss why innovation is difficult in the public sector, how AI can help with effective ITAM and compliance, and how to make sure everyone benefits from Agentic AI.

Time Stamps: 

  • Good leadership and Joseph’s early days (2:30) 
  • Lessons learned and musings on Stoicism (7:19) 
  • Allegiance to the NHS (11:10) 
  • Careful AI (15:20) 
  • What is Agentic AI? (23:48) 
  • Maintaining control of AI Agents (30:44) 
  • Always read the terms and conditions (35:55) 
  • Concerns around the next five years of AI (40:10) 
  • AI in education (49:10) 
  • Conclusions (53:48) 

Access CriticalAIonAI podcast mentioned in the show here - https://www.carefulai.com/accelerating-safe-ai-providers.html

https://www.bedigitaluk.com/

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