PassW0rd – 12 January 2022 (AI & Business Ethics)

Speaker A: This program is brought to you by Resonance FM. If you like what you hear, please support our work by making a donation at resonancefm.com/donate.

Speaker B: Hello and welcome to the Password Radio Show on Resonance FM. Our monthly look at the ramifications of digital technology and its relentless takeover of our lives. The last program of last year was about how to get into artificial intelligence, or AI, and if you didn’t hear it, you can find it on Resonance’s listen again or on our website futureintelligence.co.uk. If you want to know why then listen to this month’s program, which is also about AI, the most searched technology term on the internet, which experts predict will completely revolutionize the world of work and via the wacky world of the geek, stop business from being bad and make it good. Currently the focus of incredible attention over how to regulate it, AI is set to dramatically shake up both the worlds of work and business. Eradicating routine and mundane jobs on production lines and making delivery drivers a thing of the past by replacing them with drones, taking jobs from building sites, lawyers, and accountants. Here’s Professor Paul Clough, the Professor of Search and Analytics at the University of Sheffield and a top business advisor, to tell us more.

Speaker C: I see AI very much as being the kind of I guess that, that use of, you know, technology, digital technology to kind of create systems that are capable of performing tasks that I guess you would associate with human intelligence. So I don’t know, it could be things like recognizing images or holding a conversation, helping make a decision, you know, that kind of thing. So I tend to think very much of AI around that, that, that I guess sort of notion. So the idea of sort of exhibiting intelligence. I think the problems sort of come that there are different levels of AI or types of AI. So I think when I’ve talked to a lot of people about AI, I think immediately they think of kind of like robots and Terminator and Skynet and so on and things kind of spiraling out of control. And I guess that’s kind of one form of AI, which you might call sort of general kind of AI. But a lot of the time when we’re actually doing AI in in practice, to be honest, it’s more what we might call narrow or weak AI, where you’re kind of using AI and in particularly the sort of the most common form of AI I’m using. So I think again, there are a range of applications and AI can range from kind of the simple small tasks to something that’s incredibly complex, probably requiring a lot more intelligence.

Speaker D: The word here is this use of the word intelligence, isn’t it? That’s the thing that’s causing the confusion.

Speaker C: I think so, yeah, because I think again, it’s where do you define that intelligence? So human intelligence, it could be something like imagine that we had a document and you— I asked you to highlight people’s names or email addresses. I mean, that’s showing intelligence, being able to do that. Well, I could write a program to do that where it would literally be a few lines of code using rules because things like people’s names or postcodes follow very kind of specific forms and formats. Now, that to me isn’t really AI. Now, if I were to train an algorithm to do that, to me that’s more intelligent, but it’s still not able to be— it’s just still a program, even if it’s learned a bunch of rules on its own. It hasn’t got a conscience, it’s not able to think for itself. And I think there is a lot of confusion, particularly in the business world, about what AI actually is and what it can do, and probably what it can’t do. As well.

Speaker D: Because to an extent, what differs us from the machines is that we have the desire for something, to do something, the need to do something. They don’t. We give them the desire to do something.

Speaker C: Yeah, yeah, absolutely. And I think like machines typically are not particularly creative. Now there are examples of AI, particularly these new kind of deep learning methods that are coming along, which have been trained on huge amounts of data, incredibly complex, which are showing elements of intelligence through creative writing, for example, or creating art on their own. And they’ve completely unsupervised— they’re left to do it on their own because they’ve been trained on enough examples. But the intelligence in that case has been through looking at lots of examples that intelligent people have created. They’re still not able to sense the world in the way that we are, and, you know, navigate their way through it and do stuff that they’ve not necessarily come across before. That becomes a lot, a lot more difficult.

Speaker D: So in a sense, like the poets who were practicing automatic writing in the 1930s, they at least are selecting from the automatic writing that they’re doing what they consider to be something that’s interesting, something that might have some significance. But they are the ones who are selecting it and the machine is not the one that’s selecting it.

Speaker C: Yeah, that’s right. That’s right. And I think when we think about the intelligence that a machine has today, with the likes of machine learning and so on, even the best examples of the algorithms like that Google are using, Microsoft and so on, that they’re all being trained on sort of stuff that’s produced by people. So the intelligence is being fed into the systems. They’re not necessarily, the algorithms aren’t coming up with the intelligence themselves. Now it’s not to say that there aren’t incredibly impressive algorithms out there that are developing and pushing the boundaries, but I think they’re more in the kind of research arena as opposed to maybe in production and in general use.

Speaker D: Right. So this, the machine learning is essentially taking tasks that are actually quite mundane and tasks that are actually repetitive tasks that we would consider, or we use the word boring to talk about. It’s taking those away.

Speaker C: So I think yes, in one respect, although not always. So AI is being used for automation and could be used to automate kind of boring and repetitive tasks. However, you could also use the likes of machine learning for things like forecasting, where you might have volumes and volumes of data and really complex data that would be too much for a human to try and process. Therefore, the machine needs to process it on its own. I think there’s a mixture of some AI tasks are quite mundane and boring. It’s maybe the low-hanging fruit, the ones that can sort of free people up to do more exciting things. But there are other types of machine learning problems which are far more complex. So imagine the machine learning algorithm that’s trying to distinguish, I don’t know, it’s got an image and you’re trying to recognize what objects are in the image, sort of trying to train it up. It’s a task that’s quite easy for somebody to do, but you write a set of rules to try and identify objects in an image, it becomes really hard. So if you can train a machine, or a machine can learn on its own to come up with a way of being able to distinguish between different objects and so on, yeah, that’s amazingly powerful.

Speaker D: It is, isn’t it? My son has a border collie. The other day, The border collie likes going outside because it’s a border collie and it likes running up and down hills lots. And, um, the other— it’s been studying people before they go out for a walk, and one of the people who takes it for a walk smokes, unfortunately. And, um, the border collie went into her handbag, picked up her packet of cigarettes, brought them to her, and put them onto her lap. So the border collie has obviously learned that behavior, hasn’t it? But that’s a completely different sort of learning to the learning that you’re talking about because you’re— well, perhaps it’s not, perhaps it’s going through a massive data and finding something that is significant in it. Is that a similar process?

Speaker E: Yeah.

Speaker C: So there are different types of learning and then one form of learning is a little bit like what you’ve described there, which would be what you might call reinforcement learning. So where the machine is learning from experience. Other types of learning can be things like supervised learning, where you have a set of historical examples which you label. So maybe your data could be whether somebody defaults on a loan or not, and you want to build an algorithm that’s able to make those predictions in the future if you’re given a new person and their kind of history. So it’s supervised in the sense that you give it some training examples. So here’s the past data, here’s what the outcome is. And you can train up the machine that’s effectively able to learn a mapping between the inputs and the output. So that’s what we might call a more supervised approach. And that’s a little bit different from what you described there, Peter, which was more the, what you might call the reinforcement learning or learning by experience type of approach.

Speaker D: Everybody’s saying that this is the future. Everybody’s saying that the cars will be driving themselves, that large parts of our lives will be automated, for want of a different word, or be taken over by machines. Is that right?

Speaker C: I don’t know. I mean, I think, I think AI is certainly going to make big advances. I think it’s going to automate a lot of what we do. I think it’s going to be entangled within our life as it already is. I mean, you know, everything we touch probably has some AI element somewhere.

Speaker B: That was Professor Paul Clough on the subject of today’s program, Making Big Business Ethical. Do you remember this?

Speaker E: The point is, ladies and gentlemen, that greed, for lack of a better word, is good. Greed is right. Greed works.

Speaker D: Greed clarifies, cuts through, and captures the essence.

Speaker E: Of the evolutionary spirit. Greed in all of its forms— greed for life, for money, for love, knowledge— has marked the upward surge of mankind.

Speaker B: Michael Douglas as Gordon Gekko from the 1987 film Wall Street, the film that typified the end of the Thatcher era and defined the end of the 20th century. But now many are saying that things have changed. And that the greed is good ethos has had its day, killed by its own excess. At the start of the year, the New York Times announced that Ronald Perelman, the billionaire and celebrated exemplar of the mantra, had fallen on hard times caused by the changes in the world wrought by the pandemic. A pandemic that is also moving from the top of the news agenda and was this week ushered aside by climate change, according to the World Economic Forum. The experts that we interviewed for this program said that AI is not only one of the vital tools to combat climate change, in so doing, it will change business forever. Here’s a philosopher, Luciano Floridi, the Oxford Internet Institute’s Professor of Philosophy and Ethics of Information at the University of Oxford. Where he’s also the director of the Digital Ethics Lab.

Speaker F: I think it’s a very likely possibility. And if you look at companies, the big companies, they’re already doing what is called the ESG, the environmental social governance, you know, checking of their behavior. That is on top of— basically, it’s good corporate responsibility check. And increasingly, those labels, ESG, corporate responsibility, data ethics, you name it, but that sort of cluster of activities and concepts is, allow me for the metaphor, is bubbling up all the way to the C-suite, basically, in terms of understanding how crucial it is. I think that I agree with the comment is that they’re kind of getting that a bit late, but they’re getting it. I mean, courses in the United States, we used to have conferences on what at the time was called computer ethics in the ’80s. I mean, that’s almost half a century ago. People forget, but ’80s is a long time ago. And 40 or almost 50 years later, we start thinking, oh, this is important. Yeah, of course it is. But if you compare this to the same development that environmental ethics or environmental impact has had in the past decades, that’s a very similar course. Essentially companies ignoring it, not thinking it’s important. Paying lip service to it, a bit of facade, et cetera, until it starts hurting your business. There are a couple of things here that is worth highlighting is that you might do all this because you are a good company, whatever, or because it’s good business. Because if you don’t do it, then a couple of things can hurt very badly. One is external reputation. You start getting the reputation for being not one of the good guys, that is gonna be difficult business. Hiring is gonna be more complicated and expensive. Contracts with other companies, B2B is gonna be a little bit more, with traction and everything. So reputation is a big deal and increasingly so. The more visible, the bigger you are. And the other thing that people hugely underestimate, and I spoke to business people sometimes who didn’t quite see that way immediately is the internal turnover. You want to retain your best people. The best resource that any company has is the people in that company. Anybody from the biggest to the smallest, those people, those brains, those inspirations, the know-how, et cetera. You want to retain the best. And how do you do it if not by having the right environment, the right ethics, the right, et cetera, et cetera. So I was recently, I can’t quote by memory, but I was recently checking why there’s a very interesting statistic, statistics recently in the United States, why people leave companies. And most of the reasons, wrong atmosphere, wrong philosophy, wrong approach, wrong life balance, wrong, you name it, is all about values. Hardly ever about salary. And that is really a telling story. Of course, people also move jobs because, you know, I can earn an extra £1,000 here or there, or maybe even more, but You know, at some point, given also the taxes that we pay anyway, it’s the package that counts. The, for example, name of the company. Am I ashamed to work with that company? Am I mumbling to say, oh, do you work for blah, blah, something, something, as opposed to, oh, I work for this big company that is a fantastic company. I saw also this with my students. I mean, without mentioning any particular company would be unfair, but they have moved in, say, within a decade from working for that company is so cool, to working for the other company is much cooler. I don’t want to work for X, I want to work for Y. That is workforce, that’s Oxford, for example. So all this as a package makes ethics broadly understood, bubbling up all the way to where decisions are being taken for real. And that’s why I know an officer at that level, the information officer, the CEO, ICO, etc., and an ethics kind of officer, I wouldn’t be surprised.

Speaker B: It’s a sensitivity that is particularly strong among the big technology companies because of the demand for top AI, cyber, and computer professionals. Employee revolts within Google have been particularly damaging to the company. In one in 2018, thousands of the company’s employees forced Google to drop Project Maven, a top-secret US military drone program that used AI to target drone strikes. Until 2018, the company’s informal slogan had been “Don’t be evil,” something that, according to Professor Floridi, it may need to adopt once again in the new coming business world of 2022.

Speaker F: Doing the right thing pays back. That’s what I keep saying to any company I work with sometimes, I’ll consult, etc. I said, you may want to do it because it’s the right thing to do, which is great, or this is good business. Either way, you better do it.

Speaker D: Right. I mean, do you think that we’re going to see ethical accounting, for want of a better phrase? I mean, what we have seen in the past is that some factors have not been necessarily written into the economic equation, say plastic waste, for example, we’ve seen that that’s become a big issue. So do you think that we are going to see ethical accounting where people are going to say, actually, no, we do need to put this into the balance sheet for our reputation, the reputation you’ve just been talking about?

Speaker F: I think we’re going to. In fact, we’re already seeing it. The question next to your point, which is well taken, is what form of accounting? I don’t think it will be of a legal strict sense. So now with some kind of boxes, et cetera, but in terms, for example, of customer satisfaction or where the investments go, I mean, there’s so much funding now in our history, you know, in this particular stage of our human history that needs to flow somewhere. And I just was reading the news, you know, I think yesterday or today it was a 30% increase in companies that take ESG seriously. 30% increase. Why? Well, because people know, they just know that I have to invest now gazillions of dollars and do I put it in this company that has a good ESG, for example, profile, or in one that doesn’t care? To me, it’s the same, I go with ESG, it’s just an extra bonus. So even if you think of ethics as the cherry on top of the cake, well, when you have two cakes and one has and the other one doesn’t have the cherry, which one do you buy for the same price?

Speaker D: And ESG is what, Luciano?

Speaker F: So ESG is, is a, it’s one of the standards for the ethical assessment of a company, and it stands for environmental, social governance features that a company checks to see whether it’s doing well or not.

Speaker B: The growing power of reputational damage is something that Daniel Castro, the vice president of the influential US technology think tank the Information Technology Innovation Forum, acknowledges. He agrees that employee power and opinion about the reputation of the company that they work for is gaining momentum. It’s a movement that Castro thinks will only increase because of the decision by companies to appoint both ethical officers and hire in ethical consultants like Oxford University’s Professor Floridi to try to protect them. Against unintended forays into bad behavior. For the companies, it is going to be a balancing act because they will not be able to depend on lawmakers to guide them, something confirmed in an interview given to Password by the head of the House of Lords AI Select Committee, Lord Clement-Jones, who also sits on the Parliamentary Committee on Online Harms. According to Lord Clement-Jones, They want companies to form codes of conduct that they will be judged by, and they want companies to take their lead from other companies in their area. It’s a position that Castro thinks will work.

Speaker H: Reputation does still matter, but it matters more to some companies than others. I mean, you have some companies that really have a strong, positive consumer brand and others that don’t, and they still thrive. And so I think it We can’t just rely on that. I want to be very clear. I think there are cases where we need regulation. And there are cases where even if you’re relying on reputational damage, you still need regulators to create the reputational damage by taking action against companies that are doing things wrong. So I think a lot of that plays into part. I also think that there’s a role for the employees within many of these businesses to shape how the direction of these companies and what they do and what they don’t do. And I think we’re seeing that a lot of some of these big tech firms where there’s a lot of employee activism of employees saying, you know, this is how, you know, this is why we joined the company. We want to do these positive things and we’re going to encourage leadership to make sure that that’s reflective in how they’re investing in technology. So I think, you know, there’s a lot of factors that play in I mean, it’s interesting, isn’t it?

Speaker D: Here in the UK, the both Houses of Parliament joined together to put a committee together to look at online harms. And the reason that they said that they were drawing up this bill was because there had been a failure by the internet companies to actually address and police a lot of these, these internet harms. So they were having to step in. They said that they’d given the opportunity for this light touch. Do you think that these large technology companies will learn from that, will learn from the employee activism that you’ve been talking about?

Speaker H: I think they will. I think the idea of companies causing kind of inadvertent harm or, you know, having some kind of negative externalities is something that more tech companies are paying attention to. I think the problem that we’re seeing with some of these debates around online speech is there’s not a good consensus on what harms exist and what harms companies should take action against. If there was consensus, and, you know, in areas where there is consensus, for example, child sexual abuse material, you know, there’s no debate that companies don’t want that on their platform, that it’s illegal, it’s immoral, and that, you know, it should be taken off. And so you don’t really see any hesitation to do that. With some of this other online content, hate speech being an example of this, there are different lines that people draw in this area, and, you know, it’s really hard for one company to make that determination on their own. There’s certainly, I think, a lot of this where it is black and white, but there is a lot of gray area, and I think that’s the challenge for these companies, especially multinational ones that have to operate in multiple jurisdictions, is trying to figure out where they’re going to draw those lines you know, when there is a lot of gray area.

Speaker D: But how do you address that gray area? Do you have some organization in, you know, that’s put together by a group of universities to describe what— define what they call as ethical, or do you employ your own ethical offices?

Speaker H: I think companies, you know, are going to have to make some decisions on their own. They’re going to have to set their own baseline. They also have to follow laws. So, you know, if something goes so far that we think as a nation that something should be illegal, then we move it out of the harm space and move it into the illegal space. And then companies have to be responsive. But it’s that area where I think it’s troubling, where there’s just legislators and regulators kind of pound the table and say more should be done, but they can’t specify exactly what that more is. And that’s where I think it’s troubling, and you can’t just tell the companies to do more because they’re caught also on the other side of being told that they’re censoring legitimate speech, and there are competing interests here, and that’s why they haven’t addressed this. I think it’s— I don’t want to say it’s not fair, but it’s kind of unreasonable to expect companies to take action when we can’t agree on what that action should be as a society. And that’s a real challenge. And it’s something, though, that I think, you know, in kind of our Western democracies, we’re having a legitimate debate about what that should be. And I think that’s still a good thing. And you compare that to other parts of the world where if the government says they don’t like it, it just goes down, or companies are overly aggressive in taking down speech because they don’t want to draw the ire of a central government. And so there’s certainly harms online on these platforms, but it’s reflective of the permissive liberal democracies we live in. And so right now, at least, I’d still take that over the alternative.

Speaker B: That was Daniel Castro of the US think tank ITIF. You’re listening to Password on Resonance FM with me, Peter Warren. And after this, you can hear DJ Ritu with A World in London. In last month’s program, We heard from Professor Jim Hendler, author of Social Machines: The Coming Collision of Artificial Intelligence, Social Networks, and Humanity. Hendler is one of the US’s leading data scientists with a CV as long as your arm, the director of the Institute for Data Exploration and Applications and the Tetherless World, professor of computer, web, and cognitive sciences at Wenceslas Polytechnic Institute. He is the acting director of the RPI-IBM Artificial Intelligence Research Collaboration and serves as a member of the board of the UK’s charitable Web Science Trust. He’s also the former chief scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency. As Hendler lays out here, His objective, and that of many of his fellow teachers, has been to teach AI students not only how to build AI systems, but also what their impact could be, essentially instilling the ethics into the AI workforce that some could call employee activism.

Speaker I: We often have courses about making AI work and other courses about its impact on society, the human interaction with AI, things like that. So it’s really, if we are going to move it to the overall education, I think it’s very important we think hard about what we are teaching. Right. And, you know, I use analogies back to much earlier technologies, books in the original days, but easier for a modern audience, television.

Speaker E: Right.

Speaker I: If you look at a lot of the literature around early television, people were talking about we need to educate people on what is an advertisement, what is a program, what is a documentary versus a fictional program. And over time, people became much better at that. So we don’t even think of that as something that we should have in the schools. But there were curricula that actually looked at helping people understand some of that. I think I think that’s where AI is today. I think, I hope 20 years from now, no one will be having this conversation as about what it is. I think we’ll still have a lot of conversation about how to deploy it and how to use it. But I hope that that kind of understanding of what the field is really about and what its impacts are rather than how to program it is what we can start really getting people to understand.

Speaker D: So essentially what you’re talking about is the societal ramifications and an underpinning with some sort of morality and ideas about where AI should be deployed.

Speaker H: Yeah.

Speaker I: And again, you know, morality is a tricky one to talk about, but certainly how it impacts things so that your own moral decisions can come into that. You know, we had a So, so several well-known people in the UK, Dame Wendy Hall, Sir Tim Berners-Lee, Sir Nigel Shadbolt, myself, and a couple of other Yanks about a decade or more ago published a paper called Creating a Science of the World Wide Web, which was about, you know, really getting people to understand how the technology and the use of that technology, so its impact, so really getting social scientists and web architects talking together, and that’s become a subfield of its own. AI has always had a little bit of that, but I think we need much more. So I use the analogy of bioethics. You had an ethics community really come together with a biological community and create a world where, you know, most biologists will not do certain things because they understand why it matters, or if they are doing it, they understand they are risking the condemnation of their field or need to work within certain constraints. AI has never had that. There’s some new— there’s, you know, there’s a new journal, AI and Ethics Journal, that Springer has just put out and things like that. And they just told us today— I’m on the editorial board— that it’s one of the fastest-growing journals they’ve ever had in academia. And I think that’s crucial. I think it’s really important that we start building these conversations. That people who understand how the medical ethics feel, which really grew out of World War II and the horrible things that happened. Hopefully we can do AI ethics before those horrible things happen at scale.

Speaker D: Right. So if people want to get into AI, what you seem to be suggesting is not just programming, but, and having an understanding of how AI works, You’re also suggesting that there is this new field of AI and ethics that people can start to become involved in, which theoretically argues for where it is deployed and where it is not deployed.

Speaker H: Yeah.

Speaker I: So, you know, again, there’s lots of different— peeling that onion you just created for me. Let me say that.

Speaker E: Yes.

Speaker I: You know, but again, AI and ethics is sort of a lot of pieces to that. So one is understanding the technology, what it does. And there’s lots of books out. You’re writing one. I’ve written one. One. There’s some very good books out there. There’s a book called Rebooting AI, which really looks at what are the limits of this new tech. So, so because of the, the what’s called deep learning technology, that’s really what’s caused this great boom in AI. But understanding that it caused boom in certain parts of the field but not others, and that those must be kept separate, is really crucial. So starting with understanding, and that’s understanding those books are now much more accessible. They’re not something you need to be a college-educated computer scientist to access. So starting place is just learn a little more about the technology, then start— then, you know, there’s going to be policy aspects of that, which is just as with anything else in policy, informed citizens who can help their government try to make the right decisions is crucial. Beyond that, you start getting into what really needs to be a much more formal academic and scientific field of sort of AI ethics analogy to bioethics. But I do think it’s important that people in the social sciences and people in the technical sciences start coming together more. We are putting together a big AI program at my university one of the required courses in that at the graduate level is going to be social implications, ethics, some of the— what are the unpredictable circumstances? You know, what happens in the past when technologies have been deployed in ways— where did things that weren’t predicted happen that had negative effects, etc.? So we want all of the students coming out We’re not saying don’t work with governments or don’t work with companies or do work with— we’re saying understand it so you can make your own choices in the right way, the way you would about any other powerful technology.

Speaker B: Jim Hendler, the author of Social Machines. Janet Adams, a geologist and former banker, is one of those who is a recent convert to AI. She is also the chief operating officer of SingularityNET, and like Professor Hendler, a big believer in the ethical conquering power of the new technology.

Speaker A: They need to reflect the whole beauty and the joy and the glory and the full diversity of humankind. So I think it’s really important for everybody to find some way of getting involved and that we grow our AIs in such a way that they are inclusive and of benefit to everyone, not just to the few.

Speaker D: That is going to be a terrible job though, isn’t it? Because a lot of people will say, hang on, there’s a lot of posturing going on here. We could say whatever we want, but these big companies are going to do whatever they want to do anyway, irrespective of what we say. So there has to be a framework that is developed that people adhere to.

Speaker A: That— you make a very good point. And there’s a global framework just recently has been introduced. But you make a very good point about the big companies. Companies, because at the end of the day, big companies are optimized for shareholder value, and the use of AI will be optimized for shareholder value. And this is where the decentralized movement comes into play, the blockchain cryptocurrency movement. And at SingularityNET, we’re a decentralized organization, so our AI is not optimized for the benefit of a few shareholders. Our AI is optimized, and everything that we do is optimized for our entire community of token holders. And, you know, I believe, and we believe at SingularityNET, that decentralized AI is mankind’s best hope for a really positive future with these technologies, so that we’re continually optimizing for the benefit of all, not just for the few.

Speaker D: Interestingly, to try to foster that movement, many people are calling for changes in economic practices. People are calling for changes in the way that companies set up so that it isn’t just shareholders that get the benefit from these things. For instance, 2 years or so ago, the American Roundtable said that businesses had to refocus themselves so that they were actually looking after the interests of society generally rather than just the interests of shareholders. But that’s, that’s going to be a difficult transition.

Speaker A: It’s going to be a difficult transition. And here’s where the decentralized movement and decentralization is really gathering power. You look at the audacity of cryptocurrency, look at the leadership of, you know, some of the great thinkers on the planet, great mathematicians on the planet such as Charles Hoskinson, who we work with. You know, our own CEO, Dr. Ben Goertzel, is a huge leading thinker in decentralization and beneficial, benevolent technologies for the benefit of all. So there are some there’s a strong movement taking place towards decentralization and towards a more community-focused, contribution-based, giving-back focus to business where the value that you bring or the value that an organization brings isn’t about profit. Of course, profit can be made. We’re not anti-capitalism, but the core and the strategic purpose always has to be having positive impact on as broad a range of people, industries, communities, societies, planet as possible, rather than just having some ESG program running on the side of a major organization, but putting that at the absolutely core strategic purpose of what we are about. And that is what we see as being mankind’s next great evolutionary step as artificial intelligence develops towards artificial general intelligence, which is where AIs can work with each other, communicate with each other, and ultimately artificial superintelligence, which where we have the potential for artificial intelligence to be smarter than us humans. The potential for eradicating world hunger, for managing planetary climate change, environmental issues, and for democratic distribution of wealth to everybody is there, and it’s there within our lifetime. So there is a very positive decentralized movement going on, and there are a lot of people working very hard to ensure that these technologies are applied for the higher benefit.

Speaker D: I mean, the thing that we need to do at the moment is to get tech into perspective, and we need to be in a position to be able to get tech into perspective in our lives and in our minds? That’s the issue, isn’t it?

Speaker A: Certainly, we do need to embrace tech because it’s— the speed of technological advancement is continuing to increase, and the pace of development of some of our AI systems is pretty rapid at the moment. We all need to accept that technology is here to stay, obviously, and is continuing to grow and has immense, immense power for good. You know, there’s a big AI for good movement, and get involved, get engaged, embrace the future, and have the confidence to bring our own unique contribution to the field.

Speaker B: SingularityNET’s Janet Adams Professor Michael Manelli, a computer scientist and businessman, chairman of the commercial think tank ZYN, and emeritus Gresham Professor of Commerce at Gresham College, has a more pragmatic view. Being ethical, he says, is being simply driven by information. Artificial intelligence itself is making some of the decisions for you because it’s processing the information that you are you’re basing your decisions on. For, as Professor Minelli points out, with so much information to plough through in our everyday lives, we will simply find it easier to use a machine learning-based selection tool to pull up the information that we want. And yet there is yet another factor. Our reach for people to work with is now enormous because of the web. We can literally work globally. Meaning that, for instance, ethical services which might have come at a premium in London can be very affordable if bought from someone who has slashed the costs and opted to live in Bali. Indeed, as is the case in the Philippines, which has exploited the internet to provide office workers and remote support staff working during the night, many countries are suddenly aware that they can make a good income relative their home economies. As Manelli says, the AI world is flat and choice is global, so ethics may not be as expensive as it has been.

Speaker E: Well, when you go onto the web as an insurer and you want to find a claims manager, you want to find a lawyer, you want to find clients, the, the net is really quite flat. We tend to go through a search engine, typically Google, which is about 70% of what Most people do when they find something, they Google it and they go and they drop in on it. So you don’t know that your claims adjuster is near you physically or not near you physically. You don’t care. On the net, it’s all flat. So you could be talking to a claims adjuster halfway across the world, you know, in Kazakhstan, because to you, that all looks the same. That’s in a geographical sense. You’ve also got in the business sense. If I drop in on the insurance sector, your insurance company, I see just your company. Warren Mutual, that’s all I see. But actually I could drop in now and see, well, there’s Warren Mutual and he’s next to a few other businesses that compete with him. And there are a few accountants in there and some lawyers and they must specialize in insurance or they wouldn’t be near him, if you see what I mean. So we would have many different potential geographies. Well, if you believe that that’s going to be big, and I happen to believe it will be growing over time. We are doing more and more online. All of that is going to be driven by effectively artificial intelligence. A human being can’t sustain those types of geographies. And so the machinery will be creating the landscapes in which we ourselves are making our decisions. And I think that is potentially a fundamental change to capitalism in terms of determining who is near you, who are your stakeholders. There’s been a lot of well, frankly, foggy model thinking on the stakeholder argument, which I don’t want to go into in this, but I do believe that the landscape is going to change and it will be the machinery that is making that landscape.

Speaker D: So what you’re essentially saying is that because you can become involved with a lot more people, you can become— you can choose your partners more effectively because there are more partners available and you can choose the ones that will work better with you. And you can do that because you are online and because you can engage with people, that that will mean that your business will therefore become better?

Speaker E: Your business will become more complicated, and I think that simplicity is going to be one of the biggest issues in this space. It’s how does a human being keep their head around all of this that’s happening. You know, I began my life years ago as a scientist who was doing a tremendous amount of programming, and I used to think code of a few hundred lines was pretty large. And now when you look at the code for building just about any application, you’re bringing in enormous libraries, the libraries that handle all of your internet connections, your video connections, your sound connections, your voice connections, the sheer scale of software that’s being delivered right now, to let the two of us interact here is just mind-boggling. It is truly millions and millions of lines of code.

Speaker D: That’s the issue, isn’t it? Because the issue is that you cannot have overview of that. You said that this technology has been— lots of technology has been around for 50 years and that we’re using algorithms from the ’70s. When ENIAC first started, it did calculations in 30 seconds that would have taken human beings 24 hours to do, and apparently immediately rendered 3,200 people redundant because they weren’t needed to do those calculations. So that was the first mainframe computer, or the alleged first mainframe computer. Now, as you say, the software is so huge the ability for a human to have overview of that is just, just not there. And so essentially it’s that though we’re getting to a situation where we all get into cars, we don’t know very much about the mechanics of metals and the metallurgy that goes into making a car, but we still get in the car and use it. You’re sort of saying that we’re getting to that point.

Speaker E: We’ve gotten well beyond that point, I think, in many respects. It’s It’s fly-by-wire aircraft. It’s systems that control, you know, the distribution of viruses. It’s, sorry, vaccines. You know, you’ve got— we are very, very dependent on technology in its many manifestations. And the only tools that we’re now talking about in terms of controlling that technology are more technologies. So we’re in the— if you remember that old, I think it was Mad Magazine, Spy/Counter-Spy, where Everybody is effectively in constant warfare. And that, in a way, goes back to my earlier example about the lawyers, that you’re seeing people going, I don’t understand what I’m going to do with 5 million emails. I don’t have a lifetime to spend on one court case. But I think I’ve got an idea of a way to automate it. And then the other side is doing something equally similar.

Speaker D: But that then throws up this other issue, doesn’t it, which is that obviously in such a complex world, to introduce other equations and algorithms into that complex world, you’ve got to make sure that they don’t cause your entire complex world to come crashing to a stop. So you’ve got to have some software agency which says, yes, you are allowed to enter this into the fish tank because— and we know that you’re not going to poison the water. That’s almost an inevitability, isn’t it?

Speaker E: Well, that’s certainly one approach. And it’s, you know, it’s very similar to the walled garden discussion on the internet all the time. The contrast typically between an iPhone where Apple walls off and authorizes software to a much greater degree than Android, which allows you to download more freely apps. It’s not that there’s no control there either, but it is much freer. And this is the constant tension. Is it going to be a kind of a Wild West of the most competitive survive, a kind of a Darwinian type approach? Or is it going to be a top-down, regulated approach. And, you know, we can see signs of that in the various democratic discussions we’re having. So we’ve got on the one hand, and throw in a non-democratic discussion in the sense of China, which has its Great Firewall and is determined that it wants to control at least geographically the internet within its zone. We’ve got on the other hand, the American model, which has been in a fairly free and easy, to the point that we believe our privacy is being destroyed. We’ve got the EU which has taken a kind of slightly different rights-based approach, which I happen to be a big fan of the EU GDPR, but you can see these three very different type of structures in terms of just controlling the privacy element of it. You then move that into the safety element. You move that into age element, which, you know, what ages should people be allowed to use what type of software and what type of decisions? And it’s going to keep increasing like that, our constant debate for the next next few hundred years is going to be, as it really has been for the last 50. How do we control technology?

Speaker B: That was Professor Michael Mannelli. There is also, though, one factor that we have not really delved into, and as we mentioned with the case of the billionaire Ronald Perelman, it is one that in its highly documented 2-year history has redefined companies: COVID. And in Perelman’s case made his life more complicated by jeopardising his fortune. As we now all know, COVID has ushered in the world of remote work, accelerated the demise of the high street, and meant that many of us have suddenly realised that we do not have to commute to work. In the case of James Bailey, author of Culture Redefined and a successful small business Remote working ironically brought him closer to his workforce, and in the process, he learned more about them than he’d known before. Something that led to him deciding to sell his business to his staff because of his belief in ethical business. According to Bailey, part of that decision was due to the fact that the employees were the business.

Speaker G: The real reason, the main catalyst, Peter, was COVID-19 and the fact that the majority of the team had been furloughed. At the back end of March 2020. For a period of a couple of months when most employees were on furlough, I had weekly checkups with them via Zoom just to make sure that everybody was okay. We talked a little work, but more, it was more a case of checking in on them on their wellbeing. And it was at that stage when I personally realised as a business owner how much the company actually meant to the employees, as in it was, they treat their role and their job much more than a 9 to 5. It was— they treat it as an extension of their families. Because I’ve been running the company, it was coming up to 5 years old and it had grown relatively rapidly, and a lot of the team had been there from the early days of growth. It just seemed a logical way of being able to reward the entire team within the business.

Speaker B: Okay, so what, what is an employee ownership trust?

Speaker D: How does that work?

Speaker G: So an employee ownership trust, for me, it’s It’s the, it’s the better way. There’s many dynamics to an employee ownership. You can look at the cooperative as a model, John Lewis Waitrose, the John Lewis partnership as a model. What makes employee ownership trusts quite unique is a secondary company. So in my former company, Wave Limited, it also had a Wave EOT that set up. The trust owns, so the trust company owns the shares. Individuals do not own the shares, the trust owns the shares on for the benefit of the employees. So when people choose to leave the business, they lose any rights that they had to the shares. And when somebody joins the business, after a 12-month probationary period, they become full-time members. There’s a probationary period quite simply due to bonus payments. There would be a danger of recruiting somebody at the right time but the wrong time in terms of bonuses and them joining for the wrong reasons. Now the EOT, the Employee Ownership Trust model, has been around since 2014, and there’s distinct advantages to the seller.

Speaker E: So this—

Speaker G: the sale of the business is free from— or the sale of the shares is free from capital gains tax. But more importantly for the employees, the first £3,600 of any bonus can be paid free from income tax. So the employee or members of the trust only have to pay the appropriate level of National Insurance. So that’s the big benefit for me for an employee ownership trust. You can form an employee ownership trust from either the trust owning a minimum of 51% shares up to 100%. I initially sold 85% of the shares along with my wife, and 12 months later, December just passed, when we exited the business formally, we sold the remaining 15%.

Speaker D: Right, so you actually did sell your shares to the business in the first place. So as an owner, as the owner of the business, you did get a capital return on it?

Speaker G: I did get a capital return, and that came out— that just came out of the black, out of the company profits. Right, so there’s been no external debt financed upon the business. Me and my wife, we’re being paid out over the next 12 months of the final part of the income that’s coming our way.

Speaker D: Right, okay. Now you said that you decided to form the, the, this ownership trust because you became aware of how much the company meant to the employees. How much do the employees mean to the company?

Speaker G: Oh, for, for my former company, where the employees do and still should mean absolutely everything. We’re a professional services provider, so the company provides project management, technical design, technical support services to retail, to the retail sector specifically in refrigeration. So without a product to sell, as a professional services provider, a company is only as good as its people. But again, another advantage of an employee-owned business is the fact that the onus is actually on the employees. The more they put in, the more they get out. And although the team was already very committed before becoming an employee-owned, there was a distinct increase in levels of commitment. So in terms of similar to the levels that I as a founder had put into that business, which you wouldn’t normally expect from an employee who generally looks at a job being 9 to 5. They may give the very best during those hours, but they won’t look to go above and beyond. But from the inception of the EOT business, which was December 2020, we saw a mass increase. So financially, perspective, Peter, we sort of went from a turnover of £1.25 million to— and again, I’m out of the business now, but per calendar year That’s increased by just over £150,000 last year without increasing the number of overheads in the business.

Speaker B: The heartening story of businessman James Bailey, author of Culture Redefined and a self-confessed socialist who is now starting another business, this time in computer software. Here’s technology think tank ITIV’s Daniel Castro once more on why climate change is an easy ethical target for businesses.

Speaker H: It’s have you passed this low bar. I’m concerned that, you know, AI regulation and AI ethics will kind of end up in that same place. It becomes more of a have you met this standard versus what’s the best way to build this product.

Speaker D: So do you think that companies are becoming more ethical just because they’re, what, becoming a little more intelligent? The American Business Roundtable said in 2019 that the mission statement for the corporation had changed, that it wasn’t now just about delivering shareholder value, that it had a wider role in the society and the community.

Speaker H: Yeah, I mean, I think there are these kind of corporate responsibility officers who are thinking about these things. You have a lot of groups that are thinking about diversity, equity, and inclusion. Companies are thinking about more than just the profit numbers. But I don’t think all companies are the same. I think some are embracing that more than others. And some always have had more of some kind of political bent or ethical bent and others don’t. I mean, you can even think about the kind of Google do no evil. Even that phrasing, of course, is very different than do good. And I think a lot of companies, though, are more interested in doing good. Now, the extent to which they want to do good and how much that doing good comes at the expense of profits, that varies by company. But I think the idea of doing good is something that just generationally, as new workers come in, They’re interested in that and they want to see companies that are doing that. I think that will be reflected in technology companies, especially because they’re the ones that are often hiring a lot of these, you know, younger workers.

Speaker D: But this will be forced through. I mean, we’ve, we’ve got this big problem with climate change that seems to be gathering momentum right the way around the world. Fortunately, if everything is true. So, yeah, that’s going to give an ethical example to people that they’re going to have to follow. So, you know, there is this— these ideas that the polluter pays beginning to be pushed into company economics, which weren’t there before.

Speaker H: Yeah, absolutely. And I mean, I think if you look at a lot of tech companies, I mean, most have carbon neutral goals and they’ve pursued that. I think that ends up almost being the easiest one for companies, right? Because it’s measurable. Much easier to measure than saying, can you be carbon neutral versus democracy neutral? And nobody’s talking about how they can be democracy neutral or positive. And so that’s where, how do you measure the impact there? And how do you ensure that companies are doing what they need to to make sure that they’re fostering a vibrant society?

Speaker B: Daniel Castro of the think tank ITIF on the response of business to the ethical challenges now facing the world. That’s all for this month from Password on Resonance FM, produced by Blue Buffery and written and presented by me, Peter Warren. Tune in next month for more on the impact of technology on society, or if you can’t wait that long, go to our website www.futureintelligence.co.uk to find out more about the issues that we have presented to the European Union, the French Senate, and the UK Houses of Parliament, and that have, via our reports, gone viral on the internet. Thanks for listening and goodbye.

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