Monday, 19 December 2016

Prof Backhouse participates in the DBSA Urban Safety Dialogue

Prof Judy Backhouse was invited to be a panelist at the Development Bank of South Africa's recent Infrastructure Dialogue on Urban Safety. This Dialogue, held on the 16th November, was subtitled: Safety in our public spaces: Can infrastructural or technological interventions save us, and in what balance?

Students Nalukui Malambo, Lizalise Myataza, Letlotlo Kothane and Bonolo Motsepe joined the discussion and took the opportunity to share information about their research during the round-table discussions. 

Below is the text of Prof Backhouse's input to the panel discussion:

Critical perspectives on the pros and cons of technology as a solution to safety in public spaces

At Wits I have been running a project titled “Information Systems for Smart Cities in Africa” for the past three years.  I've been asked to consider the questions: Can smart city projects provide a city or regional solution to address development and infrastructure problems? Or is Smart City a catchy buzzword used for corporate profit-making with limited benefits for government and the public? My answer to both these questions is a typically South African: yes, and no.

Now it is very cruel to ask an academic to speak for ten minutes. What I want to do in this very short time, is to introduce you to two analytical devices or frames for thinking about these questions. The first is helpful in trying to understand what a smart city is and the second is useful for understanding different information systems that could help in solving city problems.

So, let's start with the question: What is a Smart City? We found that no-one really agrees. But we were able to identify two different kinds of understandings and an easy way to think about them is in terms of definitions of the word smart.

Some definitions of Smart include: “polished, fashionable, indicative of wealth”, “clean, tidy and well-dressed” or “fashionable and upmarket”. So we find that for some the idea of a smart city is a city that is wealthy, successful, clean and with good infrastructure, or modern. With this understanding of a Smart City comes a focus on supporting business (often high-tech and international business), attracting talent to work in those businesses, and improving infrastructure.

Other definitions of the term Smart are: “having quick-witted intelligence” or a device that is “programmed so as to be capable of some independent action”. Such definitions of smart lead to an understanding of smart cities as places where intelligence (both human and machine) is applied to solve city problems. Projects that support research to better understand city problems and the application of technologies in collecting and analysing data to inform solutions emerge from this sense of a smart city. 

So we have these two understandings: one about appearance and wealth and the other about intelligence and understanding. Try to guess which one I favour.

One of the problems with a lot of smart city projects is that they are exclusionary. My colleague Ms Malambo spent time in Nairobi looking at the Khonza City development that is taking place there. This is an initiative to build new cities, on the outskirts of Nairobi, that are intended to be smart cities. These cities are designed with good infrastructure and services, and are promoted as places that are safe, clean and better than Nairobi itself. They clearly target highly-skilled individuals and international business. While there is some benefit for the poor and small or informal businesses in servicing these projects, their needs are not being considered directly. These projects are driven by large international construction and information technology companies and serve their interests. This kind of approach to smart cities is likely to lead to increasing inequality and divert resources away from projects with more equitable goals. 

But if we consider the second understanding of smart city as the application of intelligence to better understanding and solving city problems, we find that information technologies do offer interesting possibilities for addressing the problems of rapid urbanisation.

Now the problem we are particularly interested in today is that of urban safety.

There are many ways that we can apply intelligence (both human and machine) to improve urban safety. Technology enables us to collect information about crime, about how people behave. We can observe what is happening using a range of different kinds of data – visual, audio, and indirect (for example, what phone calls someone makes or the tracking data that results from someone carrying a cellphone or wearing a bracelet). We can collect enormous quantities of data and store it, have special analytical tools that enable us to delve into this data and find patterns in it that increase our understanding. Note that these technology solutions have to be used in conjunction with human intelligence to design, operate and interpret the information that results and to assign meaning and decide on actions that result. 

At this point I want to introduce the second analytical device for our discussion. Recall that the first was the distinction between two ways of looking at smart cities. This second is about two kinds of technology solutions. We have central, top-down technology solutions that are centrally implemented and controlled and we have diffuse, bottom-up technology solutions that are devised and implemented by a range of different stakeholders.

So, for example, we know that safety in public places depends on there being other people around to observe activities. Technology offers us new kinds of “eyes” in the form of  surveillance technologies that have been deployed to increase safety. One example is CCTV cameras that are installed in public spaces. These may be a good idea, but at the moment research into whether these technologies actually reduce crime is inconclusive. Some studies show that crime decreases, in some specific locations like parking lots, but not in city centres (Welsh and Farrington, 2009) others show no change and some even report increases in crime as people feel more secure and take fewer precautions or because crime is displaced to areas that are not monitored (Cerezo, 2013). But these technology solutions depend on people to be effective, so for example one study shows that surveillance systems reduced crime only when there were also effective enforcement activities (Piza, Caplan and Kennedy, 2014). In addition, it is often difficult to conclusively attribute changes in crime levels to the surveillance tools. 

Surveillance cameras are an example of what researchers call a top-down or centralised information system. That is an information system that is designed and run by a central authority, for the benefits of others. But technology also provides bottom-up or decentralised solutions, in which more people participate and shape what the information system is and does.

On this side of the spectrum are apps that help individuals take care of their safety by allowing their friends and family to track their whereabouts and receive emergency signals should the individual feel in danger. The Android apps Personal Safety Panic Alarm and bSafe are examples. The first has been downloaded 50 000 times and the latter 500 000 times and research shows that they give people a greater sense of safety. Such apps are examples of bottom-up approaches to security, where the "eyes" are friends and family members, although in one study of mobile safety apps (in Ireland), people said they would be happy to have police monitor their safety apps, despite privacy concerns (McCarthy, Caulfield and O'Mahoney, 2016). 

Even without apps, people use their cellphones to increase their safety by telling a friend where they are going and asking for a call if they have not checked in by an agreed time. These individual uses of information technology are informal information systems and are also important features of a Smart City.

Bottom-up solutions are designed by a wide range of stakeholders, including residents and small businesses, and so they bring more brains (and other resources) to bear on the problem; they may also make people feel empowered, be more effective and cheaper to implement than top-down solutions, but research in these areas is lacking, so we don't know for sure.

A smart city that wants to make use of bottom-up smart solutions would enable it's residents to be smart by enabling their use of technology. People own cellphones, but they need the skills to use them, and they need to have access to networks in order to be able to use safety solutions or to invent their own. Smart cities in Africa face the problem of getting people connected before they can make use of bottom-up solutions.   

So, I have given you two analytical devices for thinking about smart cities and their possible contribution to urban safety. First to distinguish between a smart city as wealthy and posh or as intelligently seeking understanding. There I unashamedly favour the latter. Second to think about solutions in terms of top-down and bottom-up. Here I favour both, since both have their uses. 

I want to end with three questions for discussion:

  1.  How do we ensure that whatever technology solutions we introduce, the interests that are served are inclusive and not elite?
  2. What are the challenges in deploying effective central, top-down technology solutions for urban safety?
  3.  Can we make better use of distributed, bottom-up systems designed by more stakeholders?

Cerezo A. (2013). CCTV and Crime Displacement: A Quasi-experimental Evaluation. European Journal of Criminology, 10(2), 222–236.
McCarthy O.T., Caulfield B. and O'Mahoney M. (2016). How transport users perceive personal safety apps. Transportation research part F: Traffic psychology and behaviour, 43, 166–182.

Piza E.L., Caplan J.M. and Kennedy L.W. (2014). Analyzing the Influence of Micro-level Factors on CCTV Camera Effect. Journal of Quantitative Criminology, 30(2), 237-264.

Welsh B.C. and Farrington D.P. (2009) Public Area CCTV and Crime RPevention: An Updated Systematic Review and Meta-Analysis. Justice Quarterly, 26(4).

Thursday, 1 December 2016

Writing retreat 2016

Research writing is difficult, especially for students to master. Students on the Smart Cities project recently enjoyed a week-long writing retreat where they worked on their final research reports alongside staff who were working on research articles. Students had completed their data collection and analysis and were putting the results into their final reports.

Honour's students Kundai Mutseyekwa, Brian Opheelwane and Letlotlo Kothane make the hard work look easy
The pleasant surroundings and good food, away from campus, helped to keep everyone motivated and energised, while supervisors were present to answer questions, read and give input along the way. All of the honour's students on the project have since completed and submitted their research reports.

Tom Grace, Bonolo Motsepe, Kundai Mutseyekwa and Prof Jason Cohen enjoy lunch under the trees.

Thursday, 17 November 2016

Presenting at the African Cyber Citizenship Conference

Shado Masilela presented a paper at the 2016 African Cyber Citizenship Conference held in Port Elizabeth on the 31st October and the 1st November. The paper, titled "Using personas to understand city residents' information needs and evaluate city information services" was based on the work that Shado completed for her honours during 2015.

Based on interviews with city residents, she developed a set of five personas of typical Johannesburg residents and their information needs. She then used these needs and the profile of each individual to evaluate the City's web site to see how well it was meeting the needs of the different types of residents. She identified several ways for the city to offer better information services to residents.

The paper also investigated the usefulness of the persona method for understanding information needs and provision.

The paper has been published in the conference proceedings and a copy can be downloaded here:


Students at the Joburg Smart City Day

Students Bonolo Motsepe, Letlotlo Khoathane and Kundai Mutseyekwa took advantage of the Joburg Smart City Day on the 20th August to collect data from various smart city stakeholders for their research projects. 

Joburg Smart City Day formed part of the Fak'ugesi Festival and was focussed on innovative technology developments in Johannesburg. It was held at the newly-opened Tshimologong precinct in Braamfontein.

Monday, 22 August 2016

Prof Cohen responds to Prof Wall, Chair in Economic Development in the City of Johannesburg

On the 5th May this year, the School of Economic and Business Sciences (where this project is housed) welcomed Prof Ronald Wall to the (new) Chair in Economic Development in the City of Johannesburg. Prof Wall presented a lecture titled: Glocal Competitor: Boosting Johannesburg’s Power within the Global Economic System.

Prof Jason Cohen, principle researcher on the Information Systems for Smart Cities in Africa project, responded to Prof Wall's presentation as follows: 

Honourable guests, ladies and gentleman.

Professor Wall, congratulations and thank you for an excellent lecture. And welcome again to Wits and to the Faculty.

Professor Wall’s work brings to the fore the simple but powerful idea that we need to understand cities not as separate territories but rather as nodes within a global network, and importantly that what happens within cities is then connected to what happens between cities. Professor Wall thus argues and demonstrates in his work that the characteristics of a city node influence its position (or what he calls its prestige) in the network.

Professor Wall’s work is a stellar example of the promise of big data, the value of cutting edge applications of data visualization, and of how interrogating large datasets with network and cluster analysis allows us to arrive at fresh insights.

And when you have the sorts of hard data that Professor Wall is providing, we see just how important policy choices by cities are to the outcomes that we observe.

And as with all good research, the quality of Professor Wall’s work is evident also in the additional questions and debates that can arise from it. I’d like to kick-start the discussion process by raising some brief points, I have about 5 minutes and 5 points.

Let me say that I offer my perspectives in the spirit of an inter-disciplinary engagement. I am not an economist, but my work into smart cities and ICT driven innovation within cities has many touch-points with Ronald’s work. So I believe we are dealing with a shared problem of how we can develop a better City that is not only more economically competitive but also addresses the problem of inequalities and in which where residents can enjoy higher quality of life. 

My first question is about how we balance interests in the process of developing the attractiveness of the city to FDI. Ronald spoke of tensions between wealth and wellbeing.

We can infer from Ronald’s work that to attract a mass of investment, a city needs to match investor demand for city characteristics with the supply or provision of the relevant infrastructure, services and amenities (i.e. urban competitiveness). For me, this raises a question as to whether the properties of a City most likely to attract foreign investment are always and necessarily compatible with the properties of a City reflective of the needs of residents.

In our Information Systems for Smart Cities in Africa project work, we define city smartness in terms of the improvements city initiatives bring to the satisfaction and quality of life of city residents. And we have spent some time eliciting and mapping residents’ priorities, and determining which initiatives are most important to their satisfaction. How then might a more relativist and resident-centred view of important city characteristics clash with (rub up against) those characteristics of a city found most necessary for FDI attractiveness?

How do we balance and prioritize the needs of residents within the city against those of outside investors? Whose interests are advanced in the process? And what are the consequences of mismatches. Ronald’s work thus leads us to this recognition that our work on cities is not just about data, but is as much about values, and our study of cities must inevitably engage us in important social choice debates – about the investments we want to attract, into what sectors, and the consequent implications for city characteristics. 

My second question is about preference and trade-off.

If we are to convince firms from across key targets sectors, and individuals, that they are better off in Johannesburg than in competitor cities then we need to know not only what characteristics of cities make them more attractive but also why those factors matter. And to know why they matter, do we not then need to probe certain fundamental questions of firm behaviours and individual preferences. If we argue that we are actually dealing with a bundle of city characteristics then we need to uncover the trade-offs that people and firms are prepared to make across infrastructure, services, amenities etc. 

As an example, in our work with COJ residents, we have found a sample of COJ residents prepared to trade faster broadband and a more efficient public transportation infrastructure for better individual safety and more affordable housing. So there may be value in thinking about the attractiveness of cities from these base principles of utility and trade-off with a focus on identifying those bundles of city characteristics that match the preferences of investors, firms and individuals. A similar argument has been made by Michael Storper in his book on Keys to the City[i] when discussing the growing attractiveness of the southern US sunbelt states over the north-eastern US (which we saw as those huge spikes in Ronald’s visual).

My third question is about kick-starting new patterns of global investment.

We learned from Ronald that COJ is 6th in total African FDI. Ronald’s analysis shows us that city-level characteristics matter for FDI attraction. But which is the chicken and which is the egg?

Investment especially in greenfield FDI can lead to the economic development and smartness of cities (including increases in employment, labour productivity, skills, technology transfer – under certain conditions). But we’ve also seen that FDI is more likely to be attracted into cities with certain characteristics that in themselves already reflect a particular level of development. For example COJ’s ‘betweenness’ strength may be a function of the strength of our institutions. So the determinants of FDI attraction may also be the outcomes of FDI attraction. If the relationship is indeed cyclical, how can it best be kick-started? How do we ensure that existing patterns of global investment do not simply reproduce? 

My fourth question is about different approaches to gaining glocal knowledge of cities.

One approach is to pursue the major shared determinants of network centrality (FDI attractiveness). Here, the construction of parsimonious models that provide for the best possible explanations are favoured. Yet, another approach would focus on obtaining richer pictures where the lived experiences of people within the city can be teased out and appreciated, including how city characteristics have influenced and been influenced by investor actions. Here, the focus is on the unique attributes of a city, the focus is on differences rather than on those shared determinants. Proponents of such approaches might argue that the unique conditions and characters of our cities cannot simply be relegated to the noise and error terms of a parsimonious model. So how can we combine the contributions of both research groups into our conclusions and recommendations on the city? I ask this question in particular because Ronald has mentioned his interest in the potential of qualitative work. 

My fifth and final question is a longer-term and perhaps classic question for those interested in the development of cities.

Are we inevitably going to see the end of cities? We are already seeing electronic commerce, telehealth, telework, online education, technology-enabled business process outsourcing, and other technology and ICT-enabled advances breaking down traditional assumptions of how and why cities need to organize. Will technology lead us to the point where density in metropolitan areas disappears? In other words, will technology make the flow of goods, people and information so easy and seamless that we no longer need to cluster in cities?

Professor Wall, thank you once again for your thought provoking and insightful analyses, and I look forward to the exciting work that will come from your Chair.

[i] Storper, M. (2013). Keys to the City: How Economics, Institutions, Social Interaction, and Politics Shape Development, Princeton University Press.