An annual talk delivered by the President of Gresham College, The Rt Hon the Lord Mayor of the City of London.
Cities are networked networks of connectivity and information sharing. They create, often indirectly, communication, transportation, commercial, and intellectual networks. For the City of London, expanding and changing networks develop its strengths. Over 40 learned societies, 70 universities, and 130 research institutes surround the City of London, creating a network of knowledge connections among science, technology, engineering, arts, mathematics, and finance.
In this annual lecture, Professor Michael Mainelli, President of Gresham College, Honorary Life Fellow, and Lord Mayor of the City of London, will draw upon his more than two decades of research into smart and financial centres worldwide.
He will explain how the 2023-2024 Mayoral theme: “Connect To Prosper”, with its emphasis on multi-disciplinary networks, hopes to link forces to advance, just a bit, a few solutions to global problems.
After the talk there will be a discussion with Professor Julia Black, Professor Mark Birkin and Professor Michael Batty.
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This lecture was recorded by The Lord Mayor of the City of London Michael Mainelli, Professor Julia Black, Professor Mark Birkin and Professor Michael Batty on 20 November 2023 at The Old Library, Guildhall London.
The transcript and downloadable versions of the lecture are available from the Gresham College website:
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My theme for this evening is Connect to Prosper, the power of networks. I want to explore network theory and why it underpins my 695th mayoral theme, celebrating the knowledge miles of our square mile, the world's coffee house. Imagine you are in a coffee house surrounded by people from different backgrounds, professions, and interests. You strike up a conversation with a stranger and discover that you have something in common. Maybe you share a hobby, a passion, or a problem. You exchange ideas, opinions, and contacts. You feel inspired, energized, and connected. You come up with a solution to some global problem inspired by the other people in the coffee house. A little while later, after dinner, you drink a glass of port and dream of solving the world's problems just before bed. When you wake up to the smell of coffee the next morning, you begin doing the work. Congratulations, you have just experienced network theory. Now there are numerous books on a single theme, Cod, salt, nutmeg, all viewing the world as a network around one subject. I've often wanted to write a book on ledgers. Yes, I'm that exciting. But the ultimate connective book might be the book of networks. It could start with the intellectual networks and coffee houses. From 1660, the Royal Society and the Enlightenment leading to the technology networks of telegraphs, telephones, electricity, transmission, and computers. We are clearly moving rapidly to an age where everything will be networked. Now we shall touch swiftly on six points ahead of our group discussion. What are networks? Why do networks matter? Emergent properties of networks, London as a network, the network of global cities. And finally, the theme of connect to prosper. So let's start. What are networks? Well, networks are systems of interconnected things as simple as that. Networks are systems of interconnected things, but the concept has great depth. Networks can be found in various domains and contexts such as biology, sociology, ecology, chemistry, physics, and some examples of networks might be neural networks, networks of neurons that are connected by synapses, which are the junctions where signals are transmitted between the neurons. Neural networks can be used to study how we process information and perform cognitive functions. There are social networks, networks of people who are connected by social ties such as friendship, kinship, or collaboration. Social networks can examine how people communicate, influence and cooperate with each other. Food webs are networks, networks of organisms that are connected by feeding relationships such as predator, prey or producer. Consumer food webs can be used to study how energy and nutrients flow through an ecosystem and how it affects the population dynamics and biodiversity. And a final example, molecular networks, networks of molecules that are connected by chemical bonds such as covalent, ionic, or hydrogen bonds. Molecular networks can examine how molecules interact and form complex structures and substances. You can graph networks and thus network theory is to many. A subset of graph theory ER's solution of the seven bridges of konigsberg problem was an early proof in the history of the theory of networks. Now the basis of all networks are nodes and links. Some people prefer to refer to nodes as vertices and links as as as edges, but it's still the same thing. Dots and lines and connecting them up. Now from the start, this looks extremely simple, a series of dots connected by bylines. So let's try and connect some dots to give you a taste of some of the options first. Typically, nodes are objects such as cells, people, animals or atoms. Nodes can have one or many connections. Nodes can be restricted to a limited number of connections. Nodes can be points or have size or have many different sizes. Nodes can be abstractly located or have predetermined coordinates in two dimensions or many dimensions. The secondary is links. Links can be one way or two way or both. Links can be thicker or thinner, reflecting differing strengths or capacities. Third, the network can require some nodes to be linked, all nodes to be linked, or all nodes to be linked to each other. And finally, fourthly, nodes can restrict what they do and don't accept from other links. Links can restrict what they send from node to node and how much they will send from node to node. There are a lot of options and when designing a network, there's a constant tension of what roles should be given to nodes and what roles should be given to links. And just to make your head spin, you can invert networks completely, making all nodes, links, and vice versa. Now, in their very underlying structure, networks exhibit the tension between competition and cooperation over control and resources, and thus our fundamental to economics, which is the allocation of limited resources. So why do networks matter? Well, the they matter because they structure the nodal connections without a structure. Those would just be a pile beside or on top of one another, whatever they were a pile of people, a pile of objects links give nodes a structure. For example, restricting which node can talk to another node and so on. Information, resources, objects flow according to the structure of the links. You can get quite metaphysical about all this. Classification starts with division. So let there be light and there was light and he separated the light from the darkness calling the light day and the darkness night. Thus, we separate nodes from links and we begin to see the creation of the network structures the entire way that we look at the universe as you design networks. And we're going to be hearing from people who do it today, you rapidly realize how complex they are. You also realize that the separations of night and day aren't that crisp and clear. Maps, for example, are very ambiguous. Cities such as London can be defined by defensive walls, planning permission, authorities, taxation, worker location or dependence on a host of infrastructure, land and sea transportation, water, energy, waste, communications. Now obviously an English city has a cathedral well, except that London has two notable cities, Westminster and our city. And if a city is a node and a railway a link, what is the boundary of a city? Many cities, London and New York spring immediately to mind, have burst their boundaries and expanded by swallowing older villages and Burroughs. We have twin cities such as Budapest or the metropolitan area of Minneapolis St. Paul. Of course, the railway link is simple, not when building a computer simulation of British rail. In the 1980s, we had trains that started at Birmingham for London, gaining and losing coaches along the way, gaining and losing engines. Along the way, we had a circular train in the Midlands that never had the same engines or coaches in its daily loop. It just went on a circle, spinning off engines, putting them on, spinning off coaches and putting them on. Our solution was interestingly in a simulation of British rail to banish the word train. It was too confusing and we just specified a set of engines and coaches from one station to the next. Now of course, the station is simple, not <laugh>. Many stations had multiple railways, et cetera. Now, Ludvik Wittgenstein tried to apply exactness to language and its relationship with real objects. Later he abandoned this view. Words are imprecise fuzzy. They're meaning lies in the way people connect them to achieve goals. There's a quantum calculus zx, which states that only connectivity matters. And similarly in network theory, we try to organize fuzzy situations. Once we have expressed a system of interconnected things in a network diagram or simulation, we can begin to measure it. And people have used network theory to analyze any number of things from why groups of people do or don't work together. To how protest science, identify sister radical organization networks to the structure of political jokes about Obama, Trump, and Biden. We have creative ways of measuring networks. For example, centrality breadth, depth volatility, utilization, stress round trip time jitter, believe it or not, and gradients and of course one of my favorite areas, the use of fractal dimensions. Now practically speaking, Google's original search engine was based on a simple network measurement. And I quote, page rank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites. Now, some fun uses of network analysis began with Hungarian Regus Corinthians 1929 short story where he postulated six degrees of separation. This led on to the concept that mathematicians know well of Erdos numbers, the distance to the famous Hungarian mathematician, which led on to the website six degree degrees.com and later social link networks such as LinkedIn, as well as of course in the film world. We have the six degrees of bacon, uh, which isn't referring to breakfast sandwiches, but your distance as a performer to Kevin Bacon and 1 20 15 MIT network analysis. I loved identified people who were harbinger of failure, whose very purchase of products indicated a products likely flop. MIT marketing professor Catherine Tucker explains, if you're the kind of person who bought something that really doesn't resonate with the market, say coffee flavored Coca-Cola, then that also means you're more likely to buy a type of toothpaste or laundry detergent that fails to resonate with the market. So network analysis is useful and dynamic network theory goes further. It studies how networks change over time. Dynamic network theory in the social arena proposes eight social network roles. People can play goal striving, system supporting goal, preventing system negating, observing, system reacting, goal reacting and simply system ignoring, applying these eight rules to politics, for example, you get apathetic voters. Dynamic network theorists analyze the interactions and preferences of social media users for marketing, advertising and personalization. For instance, the diffusion of information and opinions on Twitter during US or UK presidential or ministerial, sorry, or uh, elections. So, um, what are some of the emergent properties of networks? Well, emergent property to me is actually a very pompous name for surprise. Networks often surprise us. Who would've thought that a bunch of neurons connect connected by synapses could become conscious? As a humorous example of an emergent property, my daughter Senia had a friend who created a WhatsApp group for her own surprise birthday party and then withdrew from the group letting her friends move along to surprise her later itself. So changing social social interactions now from networks often emerges unexpected order, responsiveness, reproduction, growth, regulation, evolution and homeostasis. When a network is greater than the sum of its parts, it tends to show emergent properties. Networks in fact tend to be coordinated, not controlled. And complexity emerges from networks. Bella Suki argues that biological complexity as we see it today, cannot have evolved without networks. Network systems have resilience. They're able to main stability, maintain stability, and return to original conditions after shocks. Now, quite a famous, uh, fellow in the networking field is Ross Ashby, a psychiatric cybernetic assist say that fast after breakfast. Um, but Ro Ashby coined something we today called Ashby's Law that for a system to survive and remain stable, it must match the complexity, diversity and variety of the environment that it is within. The internet was designed to be resilient, a communications network to withstand nuclear war. Resilience comes from diversity and redundancy, lots of variety within the links and notes and lots of links to get around interference or destruction. Some network systems show properties of robustness that is they're able to recover and thrive after a complete change in their environment. Raccoons, Japanese knotweed, fire ants or Irish pubs in every city on the planet, they survive wherever they're put. These are robust now in line with RV Jones Crabtree's Bludgeon, which goes no set of mutually inconsistent observations can exist for which some human intellect cannot conceive a coherent explanation. However, contrived basically humans will find order in anything that's linked up and connected. It's one of the things that always bothers me when I see these network diagrams and maps and people go, wow, isn't that fascinating? I go, it is. What does it show me? What does it tell me? I kind of knew they were all interconnected. And in fact, as we're talking AI a lot these days, my BT research friend Dr. Robert Cock, was once asked, what would it be like to live with ai? And he said, it's already here. It's like living with a small dog. And when we see a complex network in action, think about it, we tend to refer to it in human terms, we anthropomorphize it. So take something like a tractor, which is a complex networked system. The tractor, he seems cranky this morning, or boats, which I love the boat she seems to handle lightly today or we often say about bureaucracy, the system is against me. We anthropomorphize these very, very complex, interconnected sets of objects. Now networks are not on all Lloyd goods. Ian Angel in science's. First mistake delusions in pursuit of theory concludes that. So-called intellectual rigor is merely reinforced self-reference imposed by the power that comes with utility delivered by the self-reference. In other words, be careful. Networks are inherently self-referential, and we need to be cautious about observing what we want to see or confusing. Causation with correlation and networks are unfettered in many ways. There are limits. All of that interconnection though that we speak about consumes energy. It consumes time. Now, Dyson spheres, to go a bit extreme here, were first posited in the 1937 novel star maker by Olaf Stapleton, in which he described every solar system surrounded by a gauze of light traps, which focused the escaping solar energy for intelligent use. In other words, the planet solar, the, sorry, the star system solely went black as the civilization needed all the energy to handle the networks. Interestingly, uh, Freeman Dyson at Princeton took up the idea scientifically in 1960 and some astronomers today seek evidence of these artificial structures capturing much of a star's energy just to power the information system networks that the planets is consuming and some claim that they've even found, uh, some tangential evidence that they might exist. So watch out for the solar system. Now, new value is created exponentially though from accumulated knowledge. So a lot of people have said, ah, well in the future, economics should no longer be about scarce resources, but about abundance. Uh, and they would even claim that as war destroys networks, then traditional warfare to grab productive land is of less value. Um, I might say I wish that were a little bit more true today, but that's another story. However, I would argue that there is scarcity and the people who say that there's an economics of abundance have missed a fundamental a point. Uh, it was Herbert Simon who said what information consumes is rather obvious. It consumes the attention of its recipients. Hence, a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. So I would argue, if anything we might move for an e from an economics of resources to one of attention, but there's still both about scarcity. And uh, Simone Vile said, attention is the rarest and purest form of generosity. Now, outside of biology, generative AI's, large language models such as chat, GPT, llama or Bard, jump up non-linearly in performance as they are fed more data. Memory is important, but very expensive. And this leads us to search for metrics, for example, of network decay. How can we achieve the same results more efficiently with a smaller, more efficient network, consume less energy use, use less memory? We also want to understand, when does a network exhibit involution? That's a term for a situation in which extra inputs particularly of data, no longer yield more output. How do we archive things in this world of ever expanding memory and data or even delete things permanently from the archive? This has long been a perennial problem for archivists who know that they can't store everything, but innovation networks are inevitably networks full of waste as explored dead end paths in search of novelty. If we knew what the answer was, we wouldn't need innovation. So some well trod paths also introduce things like paths dependency. We can't move to more efficient keyboards on our networks without displacing a lot of ti keyboards. I've just recently seen these new annoying device chargers. I'm sure they're better and they're more wonderful, but they have to displace a lot of embedded sockets before they take hold. So we can begin to see that the connectivity of the networks is important, but in other areas holds us back a little bit. Now you've heard people speculate that given enough time, 1000 monkeys on typewriters might produce the works of Shakespeare, Steve Wright muses. If you write the word monkey a million times, do you start to think you're Shakespeare and perhaps 1000 Shakespeares could produce the work of a monkey? Who knows? But interestingly, a lot of these evolving dynamic networks actually do need ways to incorporate more random inputs. I recall that in the early days of the internet, we hoped for serendipity. We thought the world would be a better, more inclusive place if we could instantly connect with an Indian farmer's wife and discuss life with her. We never really thought what the Indian farmer might think about a bunch of people from Cambridge talking with his wife. But it turns out of course, though that sadly networks can be divisive too. They can increase polarization as we have seen. We still don't quite know what makes a positive connection, nor whether all the various connections actually do amount to something positive. I though tend to be a bit of an optimist, and I'd like to start a campaign against conspiracies and for conspiracies seeking the positive results from connections. Now the Santa Fe Institute finds evidence of increasing returns to scale in city inventiveness and creativity increasing returns emerge from the fact that the value of connection rises with the number of participants in the network and show up as power laws in the concentration of petrol stations or the speed of information dissemination in a city. Each participant connecting to the network improves their individual productivity markedly, while also contributing to the productivity of those already connected. A thought experiment affirms the idea of network benefits. If there were two worldwide webs, wouldn't they be even more powerful if they were connected into one? So at the same time, though it introduces network dangers might therefore one web be more vulnerable. Now Jeffrey West at the Santa Fe Institute asks, why are large cities faster? Interestingly, people in cities do actually walk faster than country folk. In studies, there is a term the boltman cons, which relates particle energy to the temperature of a gas. Is there a boltman constant linking the energy consumption of a city to its social temperature or its pulse rate? It was a bit of fun. We at Gresham once used statistics to craft the best Gresham lecture title ever, the one that would pull the biggest crowd based on our history of lecture titles. What we got was London's century of modern imperial world war music, mathematics,<laugh>. And once somebody delivers it, they're going to have the biggest audience ever. What I'm trying to demonstrate though, is using statistics to evaluate global commercial centers is increasingly fraught too. We saw the difficulty with definition and the fuzziness of many of these things. Business travel falls, but tourism rises. Perhaps I frequently go on a business trip and a tourist trip at the same time people work from home. Yes, but not totally. Development teams now span the world. But what does endure is cities as networks of connections, cities create often indirectly communication, transportation, commercial and intellectual networks. Increasingly, uh, and despite my uh, degree, analysts are using chaos and complexity theory more to explore such networks. But where we're going is into realms that are very difficult to measure. How do we measure tolerance, diversity, innovation, resilience. I might suggest that one interesting measure particularly for us here in London is deal making. Large cities are faster because people have more interactions per unit as the city scales up. And in my day, uh, my day job, clients often plead at the end of a long day of comparative urban statistics. Please just give us one thing that will lead us to being a successful commercial center. And I often answer, there's a very simple answer, treat all comers fairly. More interactions lead to more deals, and therefore the requirement to have more structures to prevent cheating structures that promote trust, clarity of contract, certainty of delivery, robust enforcement. In short, the rule of law. And we in London pride ourselves on the rule of law as ultimately the base form of regulation for the entirety of all that we do. Deals pull in professional business and financial services, and thus professional business and financial services activity actually can serve as a good indicator of the strength of deal making and commercial temperature of the city. We turn to coffee houses. The history of coffee houses said to Israeli heir, the invention of clubs was that of the manners, the morals, and the politics of a people. The first coffee house in the city of London appeared according to legend in 1652 in Saint Michael's alley in Cornhill, just over the way it was run by Pasco Rose and partners. Now, coffee houses were temperance institutions different from taverns and ale houses. And to quote within the walls of the coffee house, there was always much noise, much clatter, much bustle, but decency was never outraged. By 1715, just to scan half century later, there were over 2000 coffee houses in London and they were clearly very popular and they were known as penny universities by virtue of a standard penny for admission. And they acquired an appropriate diddy, which goes so great a university. I think their na was any in u which you may a schooler be for spending of a penny. Obviously they meant spending a penny in a different way back then. And these coffee houses spawned numerous clubs and numerous business organizations. Off sighted are the London Stock Exchange and Lloyd's of London. The networks of coffee houses created communities and communities form strictly speaking, when people are prepared to be indebted to one another in a network, the links among a community are obligations. Debts are unsurprisingly. Coffee houses began to issue their own tokens, both solidifying their community and funding themselves on future coffee consumption. Now, global cities are a network of their own as well. In his 1999 essay, how to Get Rich Bio Geographer, Jared Diamond set out two principles for communities connectivity and coopetition. I'll just read what he said first, the principle that really isolated groups are outta disadvantage because most groups get most of their ideas in innovation from the outside. Second, I also derive the principle of intermediate fragmentation. You don't want excessive unity and you don't want excessive fragmentation. Instead, you want your human society or business to be broken up into a number of groups which compete with each other, but which also maintain relatively free communication with each other. And those I see as the overall principles of how to organize a business and get rich Connectivity on connectivity, I would go further than Jared towards intensity. Coral reefs, for example, are rich in biodiversity and competition, intense interfaces between the pelagic ocean and sun. Blessed in shore waters, they are boundaries between order and chaos. Opportunities to increase the intensity of interaction should always be seized. Airplanes, telecoms, bicycles, mobiles, Uber, all raise intensity. And even those much detested electric scooters are probably worth a try. Equally on coopetition, I would emphasize what Jared says. Society has many ways of resolving problems. Many of them are neither pretty nor progressive military rule. Communism, legal prescription. The roads to serfdom as they're often called cities have a mutual interest in showing that competitive commercial centers can cooperate and self-regulate to deliver policies that society wants on sustainability, et cetera, all based on market economies. But I would add a third point to Jared's, and that's about deriving order from chaos. The Wizard of Oz sees smart cities as a super connected, super centralized system in which the mayor hides behind a green curtain, seeing and controlling everything. The hippie entrepreneur, on the other hand, believes that smart cities give free access wherever possible so that a thousand innovative flowers can bloom. If cities are co-created by everybody, then great metropolises are about everyone's contribution. And thus, as much about accident as designed, the haphazard and serendipitous in cities creates opportunities for positive change. I support the hippie entrepreneur or to remember Terry Pratchett's advice in the eternal war between order and chaos. Chaos always wins because it's better organized. So my theme connect to prosper. In closing, I wanted to just give you a glimpse of it. Really, an analysis shows you something you might not have thought about the city, particularly given the way that we market it. We have over 40 learned societies, 70 universities, 130 research institutes, and 24,000 businesses right here around the city of London. It's a community speaking some 300 languages, creating a network of knowledge, connections as much or more science and tech, media and culture as finance. Out of our workforce, which is 615,000, we have 100,000 working in banking and finance. So ask yourself what the other 515,000 are doing all day. Uh, and it is a huge and wide variety of things. We are rightly known for our prowess in financial and professional services, but we're also the biggest center for tech in the country with scientists, engineers, and technicians, as well as the bankers, insurers, lawyers, accountants, and actuaries. So connect to Prosper, hopes to shine a spotlight on these other areas of strength. What I have decided to call the square miles knowledge Miles. And we're hosting an online series of lectures with talks from city figures on topics from artificial intelligence to fusion to quantum with, I might say, uh, the enormous help of the Gresham Society. The way I look at it is that our client and modestly here in London, our client, the world, sat down a decade ago and hammered out and shared 17 big problems that need solutions. You know, them as the un sustainable development goals and connect to prosper with its emphasis on multidisciplinary networks. Solving global problems has a defined goal, make positive connections in aid of these SDGs. So our square mile is a hub of dynamic networks that foster innovation, collaboration, and diversity. The coffee house culture of the 17th and 18th centuries spawned the London Stock Exchange and Lloyd's the new learning and natural philosophy gatherings of Gresham College and later the Royal Society spawned science, engineering and the Industrial Revolution. So the challenges and opportunities of dynamic networks in the 21st century include how can we balance competition and cooperation, foster creativity and resilience, and leverage dynamic networks to solve global problems such as climate change, poverty, or health. Tonight I am joined by three eminent panelists who will provide a response to my remarks and engage with you on the topic of networks. Professor Michael Batty, an expert on modeling cities to improve planning. Professor Julia Black, who is particularly interested in the regulatory aspects of networks and knowledge networks. Professor Mark Birkin with longstanding interests in urban and regional systems. So in closing, dynamic network theory is a powerful tool that can help us understand and improve our social systems. It can also inspire us to create and innovate, to collaborate and compete and to connect and prosper. Our square mile is a living example of dynamic network theory in action, and we are all part of it. We are the natural hub to provide global solutions. So let's make the most of it. Let's be curious, open-minded and tolerant. Let's be dynamic networkers. I look forward to our discussion. Thank you. Now, I promised the panelists that they could have a first right of rebuttal before we move to you. And so if I could, I'd like to start with Julia, for your thoughts on the power of networks. Well, Michael, that was an incredible talk. Um, huge range, enormous breadth. Um, and to be honest, to respond to it, I think we'd be here probably, you know, for some days to come. Um, so I just want to pick up on just a few of the themes that you talked about and connect them to the world that I live in, in this, in the spirit of, of connecting knowledge. So my own, my own world is, is one of connection. So I work, uh, as a, as a law professor at, at the LSE. So somebody said, you know, that that study of chaos theory is particularly possibly well placed there. Um, but I also work, so I work as an academic. Um, I also work as a, as a policymaker. I work as a regulator, in fact. Um, and I work in a very interdisciplinary area. I'm head of one of those learn 40 learner societies, the British Academy, which is the learning society for, uh, social sciences and the humanities. And for me, the thing that does actually connect all of those things is around knowledge. It is around the connection of knowledge and thinking also about the, from my perspective, the social system. So I love, I take that, um, the analysis of the social systems, and if I play that into the regulatory arena, then, um, took then first of all, in those who are being regulated, who are in a highly complex environment, never like the idea that complexity needs to be met with complexity. So that never really goes down particularly well. But I did know a regulator who did divide up their regulated population bit as you did in relation to the, uh, analysis of different actors in complex networks, which, and the categories included, they were just, they were unofficial, but they included the champions, uh, the criminals, the clueless and the comatose, uh, in terms of their own response to regulation. But one of the things that really for me, I think is incredibly powerful of what you're talking about is that connection of knowledge. The connection of knowledge in this context to solve incredibly challenging, important immediate challenges. And if we look at the timeline that was originally given to the SDGs, then actually that's approaching a downside quicker than the solutions. But I think what is really both important in that connecting knowledge, but also challenging is are two things. The first are, as it were, the creations of the conditions for serendipity. Now, we try to do this in universities. We try to also connect, uh, across different, uh, different areas of social systems. We try to connect the academic with the industry with policy makers, et cetera. And we know that that never really quite works. It doesn't always quite work, and there are multiple different reasons for that. But we know when it does work, then you can produce the most incredible solutions. So we have, um, we have a little what sort of campaign or set of examples running on the British Academy website at the moment called Connected Knowledge. And you'll see there's some examples of where people working in different disciplines in different areas have come together to create solutions. So that might be, uh, those working in music and dance, working with physiotherapists to help those who've had falls actually do their physio rehab exercises by setting them to music, by creating that dynamic, which then saves the NHSX hundred x million pounds, et cetera. Or my other current favorite at the moment, which is sea grass. So sea grass is a big absorber of CO two. Uh, so what do we need to do now? We need to, we need more sea grass, okay? So, but normally we're used to paying countries to take out their natural resources and sell 'em off. And this time we want them to keep their natural resources, but somehow get an income stream from that. So we need to think about, well, how are we going to restructure our financial instruments so that you get an income from actually keeping a natural resource in place and in fact growing it more rather than cutting it down and extracting it. So we have to have those, that connected knowledge. But what is really difficult are two things. One, the pacing of different institutional structures. Different institutional structures have different rhythms, different expectations. But the second is actually a concept of trust and truth, because when you bring different disciplines together, they actually have different concepts of what is valid knowledge, what constitutes valid knowledge. So if you are, and what is a valid perspective, is it valid in a scientific discussion or an issue which has a scientific solution to think about values, interests, economic distribution, et cetera. If we look at the clean air debate, for example, it's very, very clear science. And yet the debate, if we, if we really don't, if we only focus on the scientific element to that, then we can see what happens there. We miss the register of others who are talking in a different register. So we have to think about the fact that even the science will meet the values and the interests. But even within the science, in fact, you have the multiple sciences, and we saw this a little bit, uh, in covid. We saw many things in Covid. Um, but when the knowledge as it were that were coming outta the qualitative social scientists in terms of behaviors, in terms of reactions, et cetera, were being rejected by those Mitre binder working, for example, in the medical sciences because we weren't testing things using randomized control trials because it has more difficult to do in a social context. So it's then to really understand, well actually what is your truth claim? And how can we really accept that what you say coming out of your discipline, your perspective is actually valid, is good, is something we can rely on so that we can then work together and we can progress. So we need trust in these networks, and we also need that facilitation of that institutional, um, as they say in, in one area of regulatory theory. It's not so much social engineering or social gardening. So it's xenia, it's setting it out, creating those infrastructure, creating that trust, then withdrawing and letting it happen. Lovely. Thank you. Thank you. Mark your thoughts. Yeah, thanks. So I, I mean, four things that I'd like to pick up on very briefly. Um, so you, your first on the question of collaboration again, and I mean, I think at, at a very broad level, um, I mean, one of the reflections I had, you know, hearing the talk, uh, a couple years ago, I had the, the, the pleasure of going to, to Boston as part of a group from the, the city of Leeds. It was actually part of a regional economic accelerator program. And without going into the detail of it, the one thing that actually struck me about Boston, which I think was number 12 or something on your list of most successful cities, was they had absolutely fabulous spaces for collaboration. You know, big warehouses that they repurposed, bringing together entrepreneurs, academics, uh, students, you know, all all kinds of people. And so I think that you're thinking about the later part of your talk where you're talking about the, the actual, you know, the kind of positive steps that you're looking to, to bring people together to collaborate. You know, I think that's, you know, I think that's bang on track and, you know, thinking about your theme of connecting to prosper, you know, anything that can help to connect people together a little bit more strongly, I think that's gonna move you in the right direction. And and I really, um, applaud that. I think that's bang on. Um, you talked a little bit about AI in, in, in a few places, and, uh, so one of my, um, uh, positions of responsibility is as, uh, a program director for Urban Analytics at the Chewing Institute, the National Institute for for AI and Data Science. I mean, I, I think, uh, may, maybe we should talk more over dinner, but I, I think the thinking could go a bit a a bit further in relation to, to ai. You know, I mean, I I I do think that, you know, I mean, you touched on large language models and that kind of thing, which are already playing havoc with all kinds of university systems and essay writing and, and all the rest of it. But, you know, that kind of technology, I think it is gonna transform our understanding of many things including network science. So I think, for example, you know, you talked about the, the different kind of social media usage typologies, you know, which are probably, most of these things are based on kind of, you know, theoretical judgments, perceived wisdom, you know, a little bit of data, the odd focus group, that sort thing. Again, you touched on data, but you know, the kinds of data that we're gonna start to absorb about the way that people really do behave you a much more dynamic way in these, in these sorts of environments coupled with the kind of the technologies that people are starting to think about is really gonna be quite transformative. And in, in my own research, we've seen some of that in relation to, you know, things like consumer behavior, the way that we can, you know, look at people's transaction patterns in supermarkets or their behaviors on transport infrastructure or all kinds of things. So I, I do think that that's gonna be very transformational, but not may, maybe, um, maybe not completely within the next year. So perhaps you'll be, uh, uh, it may be down to one or two of your successes to push that forward as well. Uh, thirdly, very briefly, um, I mean, one of the properties of, of, of, of networks that you, that you didn't really talk about was, was the idea of, of hierarchies. And I mean, I was thinking a little bit about that in the, in the, in the Kevin Bacon thing, but at one or two other places, and again, one could go into, into, into greater detail on that. I mean, again, a kind of a not terribly intellectual sort of point I wanted to make about that was, but it was interesting when you started talking about your world cities, um, where it was very noticeable that there were to me, as someone who coming from Leeds, so they wanted to be British cities, um, on there. And, um, you know, one of the other things I was thinking about, you, you talk about the city of London as a, as a center for tech. Um, I was actually with a group this morning who would, would who were, um, selling me the, um, uh, giving me the sound Paddington Basin as kind of a, a bit of a technology hobo. Well, they actually, they weren't, but you know, they kind of mentioned you're coming together there, you, you've got Marks and Spencer's visa, Microsoft, a few others, you know, and, and of course, you know, cheering at the British Library, you know, we've got, um, you know, deep mind and the British library itself and the crick and and so on and so forth. So I, so I think, again, thinking about your hierarchy or relationships as they are locally, regionally, and, and how all that connects into that, you know, that sort of world, that that, that world scale piece is something that, that, that I think is interesting. And as the kind of honorary northerner or, uh, regional representative on, uh, certainly on the platform, I thought I should probably say that. And then finally, um, in interesting, I I probably should comment on the thing about, about cities, and it was interesting that at one point you were talking about cities very close to your discussion about, uh, trains and, and railways and, and so forth. And I, I did, you know, I did kind of wonder whether we should be applying the same logic and think if we're talking about cities, you know, maybe we need to cross out the word cities and think about actually, you know, a lot of the people, for example, who, you know, who, who work in the city of London, who have that important you who help to shape it, you know, are not necessarily, well, you know, you know, the, the vast majority of 'em won't be resident here, for example. Um, and you know, one can think of it as a, you know, kind of more broadly as a network of connections and, and all that sort of things. Uh, but also I think, um, well, a couple other things, you know, thinking about, you know, those sustainable development goals, for example, you know, all those things go beyond beyond cities. Um, I noticed in Balter and Luxembourg in a couple of your centers as that would then phrase the major centers, you know, not, not cities. And, and also just finally, um, you're very interesting in your interest, in your comments about your kind of the pulse rate of cities or however we define these things. You know, I do think if you then start thinking about those sustainable development goals about sustainable cities, you know, in some ways we're gonna have to slow cities down. Um, you know, and so we do need to think about, you know, how, how, how energy get transformed maybe into other things that, that, that maintain that, that, that dynamic. Because I think, you know, that that's inevitable is that we have to go through some of those kinds of transformations. Mike. Yeah, tha thanks very much. Um, I'd like to explore this relationship between computing and, uh, connectivity and networks in some sense, because, uh, although, um, uh, much of what you said was mainly looking at networks, uh, links and nodes and so on, in this particular particular context, some of the basic ideas about networks really have come outta computing, uh, and in some respects, um, the two are really in parallel. I mean, there's, um, if you know anything about the history of computing, then there are all sorts of laws in computing. There's Moore's Law, for example, that, uh, suggests that every 18 months, uh, and this is always under debate every 18 months or so, uh, a computer chip gets twice as much memory. It runs, um, twice as fast, basically. Uh, and it's half the size basically. And that's been going on for about 40 or 50 years. And the reason why we have AI all around us at the moment, uh, talk about that, is largely because of that. Language models are basically a product of laws law. But there's another law, which is called Metcalf's Law, that, um, in the, um, in the early 1980s, there was, um, a group in, uh, Palo Alto in Silicon Valley, uh, set up by Xerox called Xerox Park, and it was basically a skunk work. Xerox were getting into the business of thinking about building computers and so on. Uh, and there's all sorts of apocryphal stories. Apparently Steve Jobs from Apple basically visited Xerox Park, uh, and, uh, stole the ideas about the Macintosh and so on. But, but, uh, uh, there was a, a scientist, um, in, um, uh, in, in Xerox Park of Palo Alto, uh, called Bob Metcalf, and he was the person who put together computers and networks. The first ethernet, the link between your, um, your PC or your Mac, basically. Uh, and a printer basically, probably these days is using some kind of, uh, ethernet related, probably using wifi. But, um, if you're in an institution, basically be using an ethernet, well, they invented this at, at Xerox Park, and, uh, he coined the law, or rather the law was coined, coined after him that, um, the power of, uh, uh, the power of a network really, uh, depends not on the number of nodes in the network, but on the square of the number of nodes. So if you've got 10 computers in a network, uh, then the, the power of that network, uh, is basically not 10 computers each one added together. It's actually the links between them. And you can apply that to just about everything. You applied it, Michael, to all sorts of things. I mean, if you look at a small village versus a town, basically, uh, what Jeff West was saying at Santa Fe and so on, uh, about scaling, basically that big cities are more than proportionately, uh, more wealthy, more diverse, and so on, uh, because there is more than proportion of connectivity in a big city in that sense. So, so this is really very important. I remember when we came to London in, um, uh, about 30 years ago, we came, I, I was living in the United States for a few years before that, uh, and in my area of, uh, applying computers to cities, basically, uh, uh, very much related to what you've been talking about, mark, uh, in that particular context, applying computers to cities, we were very interested in beginning to map things back 30 years ago, it was quite hard to actually map things, but GIS geographic information systems are on the cards. And so one of the things we did in our group at UCL, uh, was to begin to map out, uh, many of the features that we already knew that, uh, in big cities, for example, the density of the population was higher than on the edge and so on in this sense. And so what we did is we had a data set of, uh, internet, uh, protocol numbers, basically all the internet connections, uh, in the uk. We had this data set and we thought we were plotted out. And what we would expect to see was a big spike, uh, in London, um, and smaller spikes in Manchester and places like this. In terms of the, uh, of this activity, what actually emerged was that the spike in central London here in the city was absolutely enormous. Now, this was 1996, cast your mind back to then, most people didn't really know about the internet, and they were just beginning to learn about it. Tim burners Lee had put the front end, the graphical front end on the worldwide web and so on, but most people, um, didn't know about it in that context. So it was very surprising to us that, that you got this incredible density of, of, of locations, of internet protocol numbers here in the city. You could, we could locate it right down to these individual points, but of course, the real power of this network is actually the square of it. So what we were seeing was just the tip of the iceberg quite literally in that particular context. So I think there's, there's all sorts of very interesting things that Mark referred to, Julie referred to in terms of the power of networks, the power of all of these things to actually create, uh, to create wealth in some sense and create diversity. And that's exactly what you were talking about, connectivity to prosper in that sense, I believe the provinces, uh, kindly volunteered to, uh, organize the questions from the audience. I think we're gonna be taking them in a very swiftly in a group of three. Is that correct, Martin? Yeah, I, um, would like to know what, um, measures you have, um, taken in case, um, climate change happens With climate change. Yeah. Yeah. Okay. Okay. Um, and the next one, so we stick on the same row, we've got three here in a nice row. I, I was going to ask about the unconnected, I think in mind, the disadvantaged, maybe the red wall, and then also the elderly who are not connected to the internet, nowhere near a bus route. Hi. Hi. Thank. Can you hear me? Hi. I think this question is, uh, both for the law mayor and for Professor Julia Black. Um, so how can we use knowledge, uh, networks to build opportunities for city workers? And I'm quite interested, uh, ju uh, professor Julia Black, uh, had really an interesting story about what you are doing, uh, at the British Academy around your networks and how you use, how you use knowledge coming from different people coming together to resolve issues that they might not be able to, to resolve by themselves. The, the direct question would be, have you do the demographics of your participants, because what I can, I always unfortunately find that academia has this really great ideas, but we never, we're not able to transfer them in the real world business and so on. How can you make it more accessible? So climate change, the first one, second one. Kick off on the first one, Julie. Sorry, on the last one, I think On the last, yeah, so I'll happily, um, I'll happily try. Okay, on the last one. So on the, um, so I think there are a couple of things there in relation to how to create different forms of networks, and then how to mobilize that knowledge so that it then goes and has a public benefit. Um, so the first is that what we do within the British Academy is we do two core things. One is we convene, and the other is we fund. Um, and so we are funding, um, funding interdisciplinary work. We're also funding people to go from academia into, uh, either into business or into public policy roles or from, or vice versa, so that we have that mobility and that connectivity. Um, we're also starting to build a network of knowledge connectors, so those who are themselves interested in connecting knowledge, um, we know it's quite, it's a difficult thing to do. Um, the what we, what in the social context, you know, those APIs aren't quite as seamless. Um, those translators, uh, have to have a very particular skill to be able to actually translate from one subsystem or one network, one part of a, a network to another to try to create those links. So to try and to do that. And then finally in the, in the context of actually mobilizing that knowledge so that academic work gets out there into the real world, then, um, I actually lead a, a network of about 40 universities in the uk, uh, and across the EU to try and do that. So there's a number of different things. Um, working hard, it's going to take some time, but working absolutely with the city, and I absolutely, totally love the, the connected knowledge to prosper, uh, because that is exactly, exactly what we're doing. So delighted. Great. Thank you. I two questions about climate change. You want climate change? Yeah, I mean, uh, in, in relation to climate change, probably the, you know, the, the main thing I would say, again, I, I think yeah, encouraging, you know, changes in behavior patterns and the way we do things. I'm thinking particularly, for example, uh, our group is doing, uh, quite a lot with an organization called Active Active Travel England at the moment, who are, you know, promoting some of it, some of this is about your interactions between health and mobility, but it's also very importantly about, um, your different, you know, different patterns of mobility and how they can become more, you know, kind of more sustainable, more effective. So, you know, some of that, for example, is about, um, you know, how do we develop the sort of infrastructure that is gonna promote, you know, particularly groups that aren't, you know, 35 to 45 year old men in like her and, you know, so for example, getting greater, uh, diversity equality between the, the genders in terms of, um, you know, different, different modes of, of travel. You know, maybe we need less, um, you know, less kind of arterial routes for bikes and more, um, you know, kind of developing, uh, other routes along canals, this kind of thing. So yeah, active, active travel in England is producing plans at the moment for, you know, pretty much every local authority in, in the country. But connecting that to your behavior patterns, to the way that people respond to particular kind of initiatives, you know, how can we do that effectively? Um, and whether there's any way for the city of London to get involved in all of that, um, uh, I don't know, but I'm, I'm sure that there's a part that could be played there. Then our, our next question was about the unconnected. The unconnected. It's a very good question. The Unconnected, the unconnected is the dots actually in a sense, but, um, uh, there's a great story by em, em Foster called The Machine Stops, basically written in 1909, where he envisages a world where everybody is in their own little cocoon and there's no connection between them basically, in a sense, and this is put forward as being some kind of utopia, but of course, ultimately the machine stops in a sense. Um, uh, and that's really an unconnected world in one sense. Um, if we look at, uh, the modern world around us, basically there, there are both good and bad in terms of unconnected and connected in that sense that I think there are many, uh, failed states, for example, or failing states that, uh, could benefit enormously from new forms of connection in a global context. And equally well, uh, there are plenty of places that probably could do with some disconnection in some senses. So, and I think that's a very important point because I'm not particularly aware of anybody who's looked across a whole series of ideas in networks and has looked at both good and bad, disconnected, um, unconnected and so on, looked at that thing. And I think that would be a very useful thing to look at, because I think there are definitely things that we might do in terms of public policy, in terms of cities where we might disconnect a few things to actually improve them in that sense. Let's move to the back of the Hall for Change. Got one, two, and three. I can see. Hi. Hello everyone. My name is Harry from Speaker Leaders, and it's very interesting what, um, the story that you shared with us about the coffee shops and how these networking and this big network started, right? But today we live in a society that we telling to our kids don't talk to strangers, and there is a massive fear of public speaking and to build relationships. So from the educational point of view, what is your point in how can we empower our kids, our new generations that actually talk to strangers is good. Talk to strangers, come help you to build your net worth to create relationships, to span your business to, to get better resource at schools. So from the educational point of view, what can we put in place to empower or to teach some polling speaking skills so we can avoid the biggest fear that our junior generation face today? Uh, the panelists for amazing presentation, uh, because we in City of London, uh, I want to ask a question which relates to money and networks. Uh, we heard about the power of networking resources and people, and, um, I kind of thought that, you know, money Good. Could you speak up a bit? It's very difficult to hear you. Yeah, I just want to ask a question. First of all, thank you. The panelists for the presentation, and especially the Mike Minelli, uh, just because we're in city of London, I kind of talked about asking a question which relates to money and power of networks. We heard about the power of networks of, you know, capturing capacity needs and so on. Uh, I just was thinking that money involved for the last 5,000 years to compensate for the lack of connectivity in between expanding village and people, et cetera. And now we are living for the last 60, 70 years into, in extremely networked world. Uh, do you see any emerging, um, capacities of networks and so on? To provide facility for, uh, non-financial means for human sustainability, we organize ourselves without using the many as a means of our organization. Thank you. And last one, a little bit further over that way. Thank you. Yep. Thanks. Um, my name's Paul Atherton. I'm a fellow at the Royal Society of Arts, the greatest coffeehouse of all. Um, I was just interested in the nature of the corruption of a network, which we see quite often, especially in the internet space, where a single individual can dominate and control how the connections happen, how people are influenced in that space, and ultimately the outcomes of their behavior. Thank you. So they, they linked together thematically quite well. I think it's how does the networks do good? Um, came through from the first question and perhaps from the last one, the middle one, I didn't quite, quite so Well, Perhaps I could turn in. Mike, do you want to pick up on how networks do good? Do good? Yeah. Um, how do networks do good? The, the, my answer to this, I think, uh, assumes that, uh, it shouldn't, well, you shouldn't take my answer to assume that I believe that networks are all good, basically in that sense. Um, but networks can do good. I think by, uh, connecting, uh, and I, this related to the, my previous response, uh, by, by connecting, uh, things that would appear to benefit, um, uh, in this particular context, groups of people who might be benefit in some sense, uh, networks, for example, I think help in terms of reducing, um, uh, segregation, things of this sort. So I feel that there's a whole range of things, uh, in terms of how we could actually look at different networks. And of course we have to take spec. I'm not, I'm not suggesting there's a generic principle here in that sense, but we have to take each case, each aspect, um, in its own right in that sense. Uh, and that's why I think we would find that in certain circumstances, um, uh, connecting things would do good. In other circumstances, connecting things could do bad. I mean, I'm, I'm, I'm happy to have, happy to have a go. So think, to be honest, the term dual use is, is very much in, in vogue at the moment. And networks are dual use technologies, as it were. Uh, so yes, they can be used for greater enhanced connectivity. So you talked about, you know, kids should be invited to talk to strangers, you should look at their social media. Um, one of the challenges on there is it's that connectivity that was dreamed of Michael, you mentioned sort of talking to the, you know, the, the wife of the farmer in India. I'd be more interested what the wife had to think of it rather than a husband actually. But, but you know the point. So, so yes, it can absolutely can be used for the most enormous good. Um, absolutely can be used for the most enormous harm and part of that, but not only part of that is, is just us as humans, right? We're self-referential. Where do we go? We go to what we like, we go to where we know we seek confirmation bias. So we surround ourselves with things that we know, things that, things that are like us. Um, and so, and we know that no matter how much you talked about, more feeding, more data doesn't necessarily produce, uh, better outcomes. Actually. We know that just feeding more information doesn't change people's views. It just re entrenches them. So part of that is about behavior. Part of that is actually about design. So I talked about the institutional dynamics, uh, to play into the networks. And we know that in social media, we know exactly how those algorithms are geared'cause we know what the business models are. So I'm not, I would encourage us to be, um, quite realistic as to the social context, not only in which those networks are built and developed, but in which they're designed and deployed. Um, and to think of them absolutely, yes, as those dual use technologies, both in the technology sense and in the social sense. So I'm just gonna ask the last round of questions before I get Michael to summarize, and then, um, we will close. So we have a question down there. I think the first one, I'm Professor Christy. M uh, thanks for your great analysis. In terms of connection to prosper, I'm troubled by the social inequities that still exist in spite of our connectivity, in spite of technology and covid, if anything, expose this severely. We are people in ta, hamlets and the city, and we have people in Hackney and so close that their life expectancy because of that social inequity draws by over 10 years. Thank you. Okay, the next one is the back and then one just here in the middle. Um, in, in light of the, uh, uh, quote by sir, uh, Herbert Simon, uh, about information consuming attention, um, are networks self-regulating in terms of the, uh, waste, uh, or, or, or the information generated from, uh, innovation and the information which it's able to consume? Uh, is there any self reg regulating mechanism there? Or is that, uh, un uncontrolled? Can it be, Thank you. And the last one here. Hello. Thank you Philip Ross. Uh, one of the, the, when we talked about what I've taken from your talk, Michael, was about communities prosper when there's connectivity in them. And actually, we talk a lot about garden cities, which you're talking about together. And Ebenezer Howard talked about the connected cities being a powerful place. I was looking at thinking when we talk about new communities, which we're building a lot of, now actually, instead of just houses, we need to create places for people to, to network and prosper together. I think I was gonna see what your take was on that. I was just gonna add that I think my most powerful personal network is actually the other parents are at my, at my, at my son's football team.'cause it throws together parents all sorts of different backgrounds and creates those interactions, which would have otherwise never happened. Yeah. So, so on the social inequity question, so, so, uh, I'm a geographer, so I'm very conscious of, you know, issues relating to accessibility and, you know, what's going on in the center of the cities and so forth. And as we kind of touched on, you know, there are gonna be o other issues there in relation to, you know, digital divides and those, those kind of questions. I mean, I would, would commend to you, if you've not come across it, a project called Born in Bradford, which is a group that we work with, you know, quite closely. One of the things that those people have done is, you know, they've been following a cohort of children over the last 15 years, and then on into their family relationships and, and, and so forth. And one of the things that they've started to do is to connect together different aspects of, um, inequality and lack of opportunity in very interesting and powerful ways. One of the examples they use, which always stay to me, is in relation to, uh, children's eyesight and their academic performance, because they start to link together health data, educational data, and finding very strong relationships there, particularly, again, within, for example, disadvantaged communities where there may be social attitudes or financial issues relating to the kids actually taking up their prescriptions. That kind, lots of other examples. But I think in relation to this conversation, one of the other things that's interesting there is, again, by connecting up the dots between education, health, crime, consumption of your healthy food, active travel, all these kind of questions. Then we do have, actually have, have some chances to, to get at these kind of deeper questions of social inequity in some interesting ways. Uh, let me, let me respond to the gentleman who asked the question about self-regulation. Again, I think that's a particularly, uh, interesting, uh, play on connectivity, on, uh, complexity, um, uh, on computing and all of these things. So, uh, and he mentioned, um, at Herbert Simon, who was the Nobel Prize winner in, um, in economics, I think psychology and economics, um, uh, in the eighties, who did a great deal of this. Uh, one of the points, um, and this is just tangential, I think to the question, but one of the points the question raises is the fact that Herbert Simon, and many people have said these things that we've been talking about tonight in different ways over and over again. I think you can go back to almost prehistory and find some of these sorts of points that we've been making. Basically, that's not necessarily a bad thing because I feel that, uh, they do have to be revisited. There are, they're important things. And the self-regulation question is interesting that can you have too much networking? Um, you know, and how do we, how do we actually proceed on that particular basis in that sense? Are there places that we can measure where there's too much networking in this particular context? Uh, and in that, in that context where we have situations which seem to be outta balance, then what does this say about, um, uh, about regulation basically? And self-regulation, of course, is a related, uh, concept in their con I can't personally point to any self-regulating networks. I guess that, that in some senses, personal networks around us. Uh, if one feels one's in equilibrium, then perhaps we, um, uh, are self-regulating in some sense. But I'm not really aware, I'm not the right person to ask about whether a lot of work has been done on this question of self-regulation, but it strikes me as important. Look, I'm really sorry we much as I know, we'd all love to go on asking questions all evening. We've sadly run out of time. I'm going to ask law Mayor to sum up now. It's Just a quick, quick reaction actually. Firstly, thank you very much for those very considered questions. Thank you very much to the panelists. Um, I love the idea of social gardening. I think Mark is absolutely right. Uh, we, we do need to start reconsidering what is a city and all of the definitions that we have are kind of crumbling at the edges. I'd pick taxation as a good example. We don't know where people are working, where the, what their firms are. And I think Mike's point very much about this is intimately entwined with our understanding of computing, which I think is a very good one. Um, I believe that networks enrich us, otherwise, we're back in the 1909 Forrester novel when the machine stops. Um, but I think there are dangers as in any sense of connectivity. Um, it was interesting as well, the question on self-regulation and climate change. Those aren't aware the city of London had the first Clean Air Act in 1953. We, uh, went to Johannesburg, uh, we went to Rio. We've been at every single one of the 27 cops, and I will be going to cop 28 in Dubai next month. So we're, we're very committed to the climate change thing. I think it's a very interesting reaction though to, uh, believe it or not, the, the idea of, uh, self-regulation. The proposal that Cop three in Kyoto in 97 was to self-regulate using markets. In other words, to price the externalities, which I think is also related to the idea of things consuming too much. Uh, and that's kind of why I put the Dyson spheres in there, futuristic and crazy. But that's kind of the inevitable conclusion. If you don't find ways of self-regulating, uh, which of course is inherently because, uh, network theory and systems theory are frankly intertwined around the computing. But I think moving towards the social gardening model is probably better. I just might close that. At the end of the day, if the proper study of man is man himself or herself, then clearly, uh, we should be studying networks all the time. And so it has been a study of millennia, and it's a study that will continue. And I think if you look at the world, sometimes through the lens of networks rather than cod or salt or something else, uh, hopefully it enriches your life and I hope that we explore it during this year. Thank you. I'd Like to, So I'd like to introduce, uh, Mr. Richard Smith, who is the executive director of Gresham College, who's going to wind up the evening for us. Um, I, I am afraid it is indeed my role, uh, to, uh, draw proceedings for close this evening. I do think we could have probably gone on for, for the rest of the night. And then some, uh, it, it is a, uh, fundamentally interesting topic. We've had a wonderful insight, uh, into the power of networks and the way they, they underpin development, innovation, collaboration, community prosperity, and even large parts, uh, of our humanity. That's particularly taken by Professor Black's. Uh, comment about the, the serendipity, uh, of knowledge and joining these things up. Uh, I must take the opportunity to say that if you're looking for serendipity of connection, uh, then, uh, Gresham College provides you with the opportunity for <laugh> for overlapping networks of knowledge, uh, and underpins equally the importance of integrity, uh, in a networks world. So do check out our website and our YouTube channel if you get the chance. However, um, I'd just like to conclude by thanking, uh, our panel this evening. Uh, Michael Batty, mark Birkin, uh, Julia Black, uh, and in particular our networker in chief. The, uh, the Lord Mayor Alderman, professor Michael Minnelli.