Transcript
A (0:00)
Entitled an app that can save lives, brought by lse works and the lse complexity group. Our speakers tonight, we have three, we have a panel. Are our very own Eve Mittelton Kelly, who is founder and director of the Complexity Research Program at LSE and perhaps also most importantly, member of the World Economic Forum's Global Agenda Council on Complex Systems. Professor Middleton Kelly has worked previously in government and for since 1988, she has been an academic at the London School of Economics. She's a policy advisor in Europe and the USA to the European Commission to several UK government departments, and scientific advisors to the government of Australia, Brazil, Canada, Netherlands, Singapore and so on. She's developed a theory of complex social systems and an integrated methodology using both quantitative and qualitative tools and methods, and this theory is being used in teaching at universities around the world. Eve will be our first speaker. She will then be followed by Dr. Paul Lukovic, who is scientific lead of the EU project Socionical and Scientific Director of Embedded Intelligence, German Research center for Artificial Intelligence in Germany. And our final speaker tonight, who will be taking a policy maker's perspective, is Nestor Alfonso Santa Maria. Nestor is a lead in Business resilience for the City of London Corporation where he's part of the Security and Contingency Planning Group. Educated in Venezuela, he has experience that includes working with business protection with responsibility for business continuity, risk governance and information security for both HM Government and in other fields such as political risk analysis, violence prevention abroad. Nesta's work with international organizations in Latin America included helping communities deal with complex emergencies such as refugee crises complicated by flooding and human infectious disease outbreaks. Our three speakers are going to talk for about an hour. We have a detailed presentation and then there will be the opportunity for questions from the floor and there will be discussion across the panelists. So there will be an opportunity to engage with the work, but there's quite a lot to get through. So without further ado, can I open the session by inviting Eve to give her presentation? Thank you very much.
B (3:16)
What I would like to do is first of all to give you an outline of the socionic old European project, because all the work that we've done in this particular app that we will be talking about has in fact been developed as part of that project. So I'll give you a very brief outline of that, but I will focus very much on also the four different contexts within which it could be used. Then it will be the science behind the app will be provided by Paul and Nesta. Policymaker's Perspective socionical is a four year European project funded by the Future Emerging Technologies, 14 partners in 10 different countries. What the project has been funded to do is to look at evacuation following an emergency, but also at traffic flows. Now, the whole point is ambient intelligence technology to facilitate evacuation and traffic. This is where the app comes in, because your mobile phone is an ambient intelligence device. And Paul will in fact tell you all about that. But also is underpinned by complexity theory, which is where the LSE Complexity Research Group comes in. Because we've developed a theory of complex social systems, an integrated methodology. What our work is is to address apparently intractable problems by identifying the multidimensional problem space and creating what we call endogenous enabling environments that co evolve with a changing exogenous external environment. Now, we will not be talking about this. All I want to do here is to give you a little bit of context before we go onto the app. And the whole thing of course, is based on an analysis using the principles of complexity. These are some of the principles on the right. The main one I want you to look at is creation of new order, which is what distinguishes complex systems from complicated systems. The LSE Group's contribution in the project has been primarily working with policymakers in the UK and other countries. So we've conducted a set of face to face interviews with policy makers. The main thing we wanted to understand was what are their challenges in preparing and implementing contingency plans. If we're looking at evacuation after a disaster, this is precisely what we wanted to understand. How do they prepare plans and how do they implement them in practice? And we had workshops with all these organizations. Now you remember, I don't think anyone can forget 7, 7 in London and also 9. We started with these two events because they really were major disasters. And one of the things we found was that communication was absolutely key and at the heart of both incidents. Unfortunately, in both cases, communication was not what it could have been or should have been. The other thing we've done in trying to understand that background in that context was attempt exercises by the London Fire Brigade and local authority. But the thing that I will be concentrating more on is two trials that we organized to trial the app. Now, this app was not initially intended to be developed by socionical. Those of you who understand complexity theory, if I say it was purely emergent and self organized, will understand what I'm talking about. It happened that three of us, three partners, two technical partners who had the capacity and us in London who were able to work with policymakers, actually developed it and trialled it so it was trialed during both the 2011 and to 2012 Lord Mayor show in London and we were part of the control center during the 2012 Olympics. It was also trialled within the City of Westminster and we also trialled it during the West End Live Festival. In addition, after the 2011 trial at the Lord Mayor show, the show is very much organized by the City of London Police, or at least the control center is very much organized by them. They were quite pleased with their results and what we've done now is actually developed an app especially for the City of London Police. It's primarily for the city business community and the residents, but it also has a special warning inform fixture that can be activated in case of an emergency. And we intend to have a future seminar with the City of London Police to actually describe it. Going back to socionical, this is very much part of what we are doing. We're looking very much at the impact on human decision making and social dynamics. And that's part of what I will be talking about. Again, the LSE leads on two deliverables. One is seminars for policymakers and we had several of those and then a set of guidelines and recommendations for policymakers. We've also organized and edited volume to be published by Springer in the spring of 2013. So you will actually have a lot of that work available quite soon. Okay, let's look at the Socionical app. The socionical app is for iPhones. That was primarily in 2011, but this year it was also made available for Android. Now what it does is it does at least two things. One is it provides users with information about the event. And in the Lord Mayor show, it provided transport advice on how to reach the location, information on the float. And that was particularly attractive this year because you could just hold up your phone to the float and it would give you all the information about the float as it was passing. And it could also tell you where different floats were along the route. Historic buildings in the immediate location, location of Lewis and St. John's Ambulance. And the two ones I've starred were the ones that were most popular. Now this is for the benefit of the users of the app for the organizers and the emergency services. What it provides is a heat map. And again, Paul will show you what it looks like, a heat map superimposed on a Google map. So you have an actual map and superimposed on that you have a heat map which shows the density of the crowd, it changes color. It's a heat map in the sense that as it becomes More crowded. The colors change from blue to green and yellow to red. So red is where most of the crowd is the greatest density of the crowd and you can see quite clearly the movement and direction of the crowd. So this is the information that you have live in front of a screen in the control center. So if there is to be an incident or if there is to be too much of a crowding in a particular area, the app can actually send what is called a location specific advice. So this is quite different. It's not like most apps that broadcast the information to everyone who has the app. It can actually send it very specifically to to those with a device in a particular location. As you can imagine, it would have a lot of ethical issues. So we were very, very strict about the ethical guidelines. So the app was only active during the day of the event and only during a geographic boundary around the event. There was a very clear explanation of the purpose of the app, saying, this is part of scientific project, your data will be used for this purpose, and so on. It was always purely anonymous. We have no access to the identity of the users. We only know that a particular device has the app. All data were amalgamated and of course we observed European Commission regulations, we were cleared by our own socioeconical ethics committee and so on. So we organized the trials. We're part of the control center. But the most important thing is that we discussed impact with policymakers by conducting face to face interviews. However, in addition to all that, we also had a survey. So after the end of the show of the Lord Mayor show, we sent through a request for people to fill in a survey and then we also asked them if. If they would wish to participate in an anonymous, very short telephone interview that gave us a lot of insights into why people would use it. And I will give you some of that information in a moment. But first of all, I want to give you some findings on the app by policymakers. The way they see it is that the purpose of crowd monitoring is to provide information, the density and movement of a crowd, to use the information to enhan security and safety. That's the key to enhance security and safety of those taking part in the event and obviously to help with the appropriate deployment of resources. Resources, as we all know, are getting scarcer and scarcer and it's very important to deploy them appropriately, but also to identify abnormal patterns in movement or density that may become critical. So it's, as I said, a live assessment of what is happening. At the same time, there are CCTV cameras and there are Stewards and marshals that are walking the routes. So we're getting constant updates as to what is happening, both from humans and from the CCTV cameras. But what neither can do is give us a complete overview of exactly what is happening throughout the course of the event. And it's, of course, you know, assistive vikamera cannot do that. It was particularly valuable during the. During the fireworks display, because during the fireworks display, CCTV cameras don't actually work. And it was the first time that the City of London police could actually have a clear overview of the entire route around the Thames where people were standing to watch the fireworks, and they could actually see where the greatest density were. That meant that the following year they could plan where the stands were, et cetera, much more effectively. One of the things they also said was that using the heat map was intuitive and did not need any training. However, the important thing is that it needs a trained officer to actually identify potential critical issues and take appropriate action. And this is one of the quotations from one of the. The policy makers actually using it. He said, it's one of those pieces of kit that you do not realize its true potential until you actually use it. And I think that really says it all. It does have two weaknesses. It does not provide actual numbers because everything is amalgamated. So all we see is the crowd as a whole. But we cannot say X numbers are in that particular location. And of course, the heat map only reflects the number of users and only those with an active app.
