Social Science Parks A new tool for public innovation
Paper prepared for the Summer School of the University of the Basque Country
14th July 2014
Adam Price
Introduction The world is confronted by an array of deep-seated, complex and seemingly intractable problems. Bringing our collective intelligence to bear in new ways to devise new solutions is imperative if we are to address these challenges in the 21st century. In this paper I propose a radical institutional innovation to help us achieve this goal. In the broadest terms its goal is to: Bring a talented, diverse group of some of our most engaged minds together under a common banner in an environment in which they can focus on problems that require innovative solutions in an atmosphere of free-flowing interaction across disciplines and institutional silos that encourages the development of practical solutions. The organising principle used here for this meshing of minds is that of a “social science park”. It’s a research park with a difference, based not on the ‘hardware’ of technology but the ‘software’ of human behaviour. The generic concept of a dedicated piece of university real estate where basic research is turned into practical applications, usually in the form of new technology for spin-out companies, will be a familiar one. A social science park translates this concept into the ‘social science’ context: if Bilbao and Singapore with their Social Innovation Parks are attempting to create the world’s first ‘social Silicon Valleys’i, then this is an attempt, to create a social Bell Labs or Xerox PARC, – a dedicated space for new ideas embodied in new applications but anchored in the those areas of human knowledge focused on society and the way it is organised: economics, sociology, political science, management, social psychology, criminology etc. The social science park is designed to be a catalyst of change, equipped with the infrastructure and the culture necessary to promote the development both of a more innovation-oriented social science and a more socially-oriented system of innovation. As such it is an experiment in social science as well as of social science. Its novelty, however, in no way detracts from its necessity. At a global scale society faces multiple grand challenges that require new forms of combinatorial creativity that fuses understanding and experience. Creating new spaces, new organisational forms and new tools for the practical application of knowledge is a societal imperative. Creating the world’s first social science parks – a new model for which there is no ready template - is a risk worth taking as the risks of failing to innovate are inordinately greater.
The New Age of the Academy Throughout human history we have created new spaces for the production of knowledge. This is because in general the creation of human knowledge – notwithstanding the Eureka moments of extraordinary individuals – is fundamentally a social process, an exchange of ideas which needs a forum, a context, a place in which to work, from the libraries and academies of classical antiquity and the monasteries of the Middle Ages to the universities of today.
These places of learning grew up primarily to provide a setting for the transfer and codification of knowledge. Their basic infrastructure, the pattern of cloisters and cells, dormitories and dining areas hasn’t changed much in a thousand years. Some argue the digital age threatens to shatter this age-old template. The promise of a truly global academy, with its universal and instantaneous access to the world’s best teachers together with the entire canon of accumulated knowledge, is seen by some as a threat to the continued survival of all but the leading centres of knowledge. But much more likely perhaps than some modern dissolution of the monasteries is a reinvented role for universities as sites for problem-solving and innovation. The ivory tower is being replaced by the agora of the new academy – engaged and relevant, dynamic and entrepreneurial. The goal of the universities’ Third Mission – alongside universities traditional focus on teaching and fundamental research – is to change society, a vision mirrored in an economic context in the Triple Helix of university-industry-government collaboration.ii This practical, and in the philosophical sense, pragmatic view of the role of the University and its relationship to society, has been echoed in other ideas: the concept of Mode 2 and Science IIiii; the Entrepreneurial Universityiv; national and regional innovation systemsv;the civic university and the new Public Social Science. This ethic of social accountability is also enshrined in the UK Research Excellence Framework’s new emphasis on the demonstration of social and economic impact, and in the EU Horizon 2020 programme’s narrative of grand challenges. This shifting paradigm means a parallel shift in the organisational and physical architecture of our universities. Innovation requires tacit knowledge, an interchange between two or more people, dialogue and debate, challenge and cooperation. This works best when people are in the same room, working on the same problem. They need to have developed a common language and some common understanding of the issue. Though they may bring to it to their own special insights and expertise, they need to be able to communicate. They need the ‘enabling space’ to engage in what has been described in the literature on economic clusters and city-regions as ‘social learning.’ It is the kind of learning where ‘facetime’ is essential. This explains why the death of distance has been somewhat exaggerated and why ‘place’ has become an important element in industrial policy.vi It also explains the creation of science parks as dedicated spaces for innovation attached to universities. Innovation, in John Kao’s words, needs a home.vii
The Science Park Phenomenon Science parks emerged in the 1950s in the US, at Stanford University in California and the Research Triangle of North Carolina, as industrial parks for academic entrepreneurship based on the commercialisation of their scientific knowledge. The take-up of the idea was initially quite limited; Cambridge Science Park founded in 1970 is the oldest in the UK but was initially slow to develop. By the 1980s, however, science and technology parks began to proliferate and there are now well over 100 in total in the UK alone. These innovation spaces vary considerably in form, in scale and in the way they are managed. They include the vast technopole
and science city projects that began in France and Japan in the 1960s and 70s; to smaller-scale incubators and accelerators like the St John’s Innovation Centre in Cambridge; to inter-disciplinary atelier-style workshops such as the MIT MediaLab; and lastly the more conventional science, technology or research park. The empirical evidence base for science parks’ effectiveness as a policy intervention is sparse, mixed and contradictory, though most of the research tends to suggest some degree of positive impact on at least one of the indicators chosen. A series of studies in the 1990s led by Paul Westhead showed that firms on science parks in the UK had a greater survival rate than comparable firms located off-park, though there didn’t appear to be any other statistically significant benefits.viii A later study in 2003 of UK science parks did demonstrate a greater relative research productivity.ix International studies have also shown evidence in the case of technology-based firms based on science parks of greater patenting activityx; greater patenting productivityxi; better research linkages with universitiesxii; greater relative employment growth based on presence in the parkxiiiand based on proximity of the park to an universityxiv;greater survival ratesxv; and a higher likelihood of attracting industrial research labs based on the location of a science park locally.xvi At a broader level the most celebrated examples of science park success can point to some strong indicators of economic impact. The Cambridge Technology Cluster has produced 11 $1 billion plus companies in the last fifteen years. Beijing’s Zhongguancun Science Park developed China’s presence in the semi-conductor market from the late 80s onwards, seeding the eventual success of Lenovo. But the simplistic “field of dreams” strategy followed by many regional development agencies – for example, the Welsh Development Agency’s failed Technium programme – based around building new real estate to accommodate firms together with the offer of some financial incentives does not appear to have been particularly successful.xvii Recent research in the UKxviii does suggest that knowledge spill-overs – for which there is strong evidence of benefit in the context of economic clusters – are more likely to happen between firms within the same sector rather than across sectors i.e. innovation is more likely to happen in Steven Johnson’s “adjacent possible”xix. An explanation for this can be found perhaps in Harry Collins and Robert Evans’ work on the role of interactional expertise – the ability to have a meaningful conversation about a subject area without actually being an expert in it substantively.xx A software engineer may have a meaningful exchange and offer new insight to an expert working on another aspect of IT, but may find it difficult to interact with a biochemist. Science parks like innovation districts writ large may tend to work best when they exhibit what economic geographers have dubbed ‘related variety’ – a diversity of approaches built around a common core. That common ground has to be built on pre-existing foundations. Science parks cannot be conjured out of thin air, and have to relate to the resources to hand in the innovation system and the regional knowledge base – in other words we need to adopt a policy of ‘smart specialisation’.
Stanford was successful because of Silicon Valley not the other way round. Similarly Zhongguancun worked because of its proximity to a number of top Chinese universities as well as the research centre of the Chinese Academy of Sciences.
The Knowledge Triangle and the Quadruple Helix New concepts of how knowledge is produced are challenging even the relatively new paradigms of the Third Mission and the Triple Helix, and the social science park will need to reflect these new networked, non-linear ideas of knowledge production. The idea of the Third Mission carried within it a sense of discrete worlds of research, learning and innovation in a linear process beginning at the workbench and ending in ‘technology transfer’ or commercialisation. This compartmentalised world-view was perhaps reflected in the physical location of science parks in offcampus, often in pretty remote, and impersonal locations. The new concept of the Knowledge Triangle (see figure) stresses the many synergies between the three missions that bind them together. The Triple Helix, in similar vein, has also now become the Quadruple Helix, as the fourth pillar of people – individuals and groups of end-users and citizens – are incorporated in a spirit of open innovation.xxi A social science park is not therefore a gleaming hi-tech version of the ivory tower. Indeed it is the place where the towers, the silos and even the walls must come down. The park is a platform for interaction, a space for collaboration and knowledge co-creation by researchers, students, citizens, customers and stakeholders. Where traditional science parks often have felt like corporate gated communities, a social science park has to be social: a public square of open interaction, at the heart of social life, an innovation hub in a wider system. Now knowledge is acknowledged to be more widely distributed, gathering and generating new knowledge requires us to deepen collaboration with a wider range of actors: firms, academics, public agencies, regions and cities, people and citizens. This new model of shared value creation, can in the words of one author range from “research to market and a new focus on innovation-related activities, such as pilots, demonstrations, test-beds, living labs”.xxii The role of the universities is thus shifting from that being the monopoly producer of knowledge to the orchestrator of “regional innovation ecosystems operating as test-beds for rapid prototyping of many types of user-driven innovation: new products, services, processes, structures and systems, which need to be transformative and scalable in nature.”xxiii Orchestration is a method for coordinating a diverse network of actors without top-down direction – by designing spaces, creating a culture and developing incentives which seed co-operation and channel activity along broadly agreed lines. According to Markku Markkula of Aalto University this task of orchestration requires a multiplicity of new elements: new networks and alliances, new concepts and new tools, but also new physical, virtual and mental spaces.xxiv This shared environment is critical to the building of a successful innovation eco-system:
“Once actors are able to find each other, communicate effectively and understand each other’s questions and needs, trust and mutual respect can grow. Collaborative learning becomes possible and the investment of time, effort and attention participants need to make in order for collaboration to be successful can begin to pay off. Support infrastructures, methodologies, technologies, tools, activities and shared spaces –both physical and virtual meeting and co-working spaces – are important to facilitate communication and to build shared understanding.”xxv
Social Scientists as Social Innovators Science has long dominated our concept of innovation. But in reality technological innovation has always had its social analogue. Over a century ago sociologists at the University of Chicago were referring to social technology, social invention and, somewhat more problematically perhaps, social engineering. Writing in the 1960s Peter Drucker and Michael Young popularised the term social innovation that has now become a mainstream term for practitioners worldwide. It is this same logic – that lies behind the proposal for a social science park.xxvi Social innovation, can “be regarded as the interface point between sociological reflection
and social action because it requires reflection on societal problems and targeted action" with a key role for social scientists – largely untapped to "be visibly involved in public debate and practical societal contexts" and to act "as a supporter of social innovation" xxvii. The Social Science Park seeks to give this process an institutional setting and a physical home. For Stuart Conger, the great Canadian social innovator, one of the greatest obstacles to social progress was social scientists’ wariness of getting involved in the process of innovation. For much of the Twentieth Century certainly the social scientist has seen him-and-herself more in the role of critic than inventor. The social scientist “was not interested in making the world a better place” as William Ogburn claimed emphatically in an influential address to the American Sociological Society in 1930.xxviii Social science has as a result tended to prioritise analysis over the trial-and-error of practical application. The Park is a conscious attempt to create a new active social science – imaginative and experimental, with researchers moving from a position of passive observation of society to being actively involved in its transformation. It links back to earlier periods when science has been strongly linked to social reform - the Enlightenment in Europe, the Progressive Era in the United States, – and strongly represented in certain, more heterodox disciplines e.g. criminology during the Twentieth Century.xxix It chimes with a wider shift towards a more action-oriented philosophy of science, the move from Mode 1 knowledge to Mode 2 referenced earlier, Mode 1 being the curiosity-driven desire to understand the world and Mode 2 motivated by the desire to use our knowledge to change the world for the better. In a sense the absolute integrity of critical detachment is being traded for the positive influence of the socially engaged. Research is becoming more relevant and resulting in innovations for society, whether in the form of new products or new policies, with universities morphing into “innovation-promoting knowledge hubs.”xxx The social science park though is still a place for genuine science. Indeed in some ways it represents a paradigm shift towards a more rigourous use of scientific methods. As a number of social scientists have argued in a recent ‘manifesto’: “The combination of the computational approach with a sensible use of experiment will bring social science closer to establishing a well-grounded link between theory and empirical facts and research.”xxxiInnovation and the new experimentalism mean the social sciences are at one and the same time, more socially useful and more scientifically robust.
Laboratory of Laboratories As the social sciences begin rediscover the power of experimentation, in some ways they are beginning to converge with the natural scientists. And just as chemistry would be unthinkable without lab space – the same is increasingly true for social scientists and social innovators too. In the last few years about 170 social science labs have sprung up in various guises conducting wide-ranging experiments in diverse fields: experimental economics and finance (e.g. auction and market design, trading strategies), behavioural science (learning, social competence, inter-cultural
understanding), voting behaviour, network phenomema, decision-making , game theory etc. This approach is becoming increasingly influential. Two of the last Nobel Prize winners in economics, for example, were experimental economists. The first tier of lab-like activity is represented by laboratory settings on site. This usually includes facilities to allow volunteers, usually university students, to participate in experiments simultaneously, usually involving the use of a network of computers in a controlled environment e.g. the US’s biggest wireless experimental lab at UC Berkeley’s X-Lab in California or the 25 partitioned workstations available for use at Nuffield College, Oxford’s Centre for Experimental Social Sciences. Other ESS laboratories are more virtual, availing themselves of the power of the Internet to deliver massive online experiments at scale. Others, drawing on psychology’s longer history of experimental work, involve much larger facilities for face-to-face experiments in e.g. the 1,200 m2 of specially designed observation and group interaction spaces at the world’s biggest Behavioural and Social Science Lab in Bremen’s Jacob University. A different kind of lab is represented by the change, innovation, co-design or social labs which have sprung up in companies, in Government and in civil society over the last few years.1 These are dynamic settings in which the experimentation is in the form of the rapid prototyping, rapid cycles of trialling and testing and constant iteration. The approach draws upon post-war insights about group dynamics and systems thinking from the Tavistock Institute and Kurt Lewin, blended with ideas from design thinking, creative problem-solving, innovation management and the agile movement in software development. Leading practitioners of the approach include the Danish Government’s in house MindLab, the UK consultancy Participle, the American design firm IDEO, and Stanford University’s d-school. These are places in the words of John Kao, author and former HBS professor, where ‘opportunities for new solutions to emerge as people meet, interact, experiment, ideate and prototype.” He compares the innovation lab with the atelier of the artist – an open environment where creativity is at the centre. Ethnographic observation – bringing back field data about real users in real contexts is a key tool in any change lab. ‘Getting the whole system in the room’ – a phrase which harks back to Kurt Lewin’s British protégé and co-founder of the Tavistock Institute, Eric Trist – is also acknowledged as central to any large-scale process. A more expansive version of the lab concept, so-called living labs, were first invented at MIT in 2003 but since then have begun to spread throughout the private sector (e.g. Philips Research Experience Lab) and in higher education. They can vary from temporary or permanent from small-scale immersive developmental environments setting to real settings within the community to the macro-level wehere a whole city can be used as a living lab. The basic principle is one of students, professors, experts, practitioners and researchers developing new professional and scientific knowledge in concert with living lab partners (companies, 3rd sector bodies, public sector etc) and end-users in an actual living environment. 1
See Zaid Hassan (2014) The Social Labs Revolution
The Proximity Principle At the heart of the park is the idea of co-creation: people working together across disciplines and across professional boundaries to study, learn about and also to solve some of the most pressing problems we face. The first necessary condition for successful collaboration is physical proximity. Thomas J. Allen’s famous discovery in MIT in the 1970s, the so-called Allen curve, demonstrated an exponential relationship between distance and the regularity of communication between engineers: someone six feet away from you was four times more likely to talk to you regularly as someone sixty feet away, and someone on a different floor was unlikely ever to speak to you, and someone in a separate building you probably never met at all.xxxii Proximity influences not just the quantity but also the quality of interactions. Isaac Kohane’s work examining the effect of distance between the authors of 35,000 academic papers showed much greater impact, as measured by the frequency of citation, the closer the authors were based. Geographic proximity creates trust but also a greater likelihood of non-regimented conversations outside the parameters of organised meetings which are more likely to generate random, creative connections.xxxiii The best cauldrons of creativity all involve physical proximity, a meeting of minds which is the engine of innovation.xxxiv There is a special quality of thought when people are physically present with each other, attuned and mentally engaged with a shared focus. Co-location means it’s easier to establish contact and exchange knowledge.xxxv Casual conversations, overhearing others, exposure to the buzz and atmosphere of a place creates constant flow of knowledge spillovers. Tacit knowledge and the building up of trust which is the foundation of collaborative working requires face-to-face engagement. There are other forms of proximity which are equally important, however. Common values, attitudes, emotional disposition and a shared commitment are also important too.xxxvi Ensuring these other proximities -cognitive, social, institutional and organisational – are in place will be critical in avoiding the park simply becoming an empty shell. Just putting up a building is never enough – which explains perhaps the failure of the Technium Project.xxxvii Two people sitting in the same room or two organisations located in the same space does not guarantee learning or innovation: “The first and most essential condition is that the actors who are involved in learning are able to understand each other i.e. use a ‘common interpretative scheme’.” (Markusen, 1996). As well as this cognitive proximity, sharing a high-level strategic sense of common purpose will be a critical ingredient to success. This includes sharing the same vision but also following a similar organisational logic. An appropriate umbrellalike organisational structure for management of the Social Science Park should allow a shared setting of norms and values to develop among a wide variety of tenants.
This needs to be done with a deft touch. Sharing some degree of common interests or a common language is critical to success, but too much similarity can also be counter-productive. Hybridity and serendipity are crucial to the innovation process; the park must be a place where different skills and knowledge bases mingle in a common home which strikes a balance between proximity with heterogeneity. Too much cognitive distance – say between practitioners and researchers - means people won’t be able to understand each other but too little mean they will have nothing new to say to each other, and no new ideas will flow. By the same token as most relevant knowledge is contained outside the confines of the Park sophisticated ways of co-ordinating with the wider world will need to be constructed.
The Architecture of Innovation An open, free-flowing, transparent ethos will be the central organising principle as a social science park is engineered to encourage network-building and informationsharing in contrast to the competitive and proprietorial attitudes associated with more traditional ideas of Intellectual Property. The design of the physical space of the park itself may help or hinder the innovation process, and care will need to be taken in this regard. Drawing on the experience of innovative work-spaces worldwide (the St. Luke’s advertising agency, London; MIT Media Lab, Cambridge MA; Pixar Studios in Emeryville, California; Google’s various headquarters) the following common themes emerge:xxxviii
Visibility: workspaces and meeting places are open and transparent: Collision spaces: the design of shared facilities/resources – cafes, kitchen areas, roof terraces and community gardens etc creates multiple, informal, unpredictable, serendipitous interaction – the apocryphal water-cooler moment Opt-outs: alcoves, pods, etc are also important to create areas for private conversation and quiet contemplation Erosion of status: people work together and share facilities without visible symbols of rank Blurring work and play: bright surroundings, recreational areas , comfortable furniture and the development of a strong work-based social life are all important in fostering creativity, cohesion and a sense of belonging Narrative: the form of the building itself – and in the case of an existing building, its history – represent a key element in the self-concept of the organisation and the image it wishes to project Overflow: room to grow organically nearby or raw, empty space within the existing building will be important to retain a sense of the park being in a continuous state of evolution: and at a practical level to accommodate new centres, projects and businesses
While physical proximity is a necessary component, the design of the social and institutional architecture of the park is at least as important as the design of the space itself. In some ways because of its emphasis on solving grand challenges
rather than micro-spin outs, the spirit of the park is closer in some ways to the classic research parks of the 20th century: the war-time Manhattan Project and Bletchley Park, the post-war quasi-public corporate research campuses Bell Labs, Xerox PARC, and the RAND Corporation. The Park is not a disparate collection of loosely affiliated organisations but a concentration of minds, open to the world but cohering around a common set of tools, of values and purpose.
Putting Research (back) into Practice It is a strange feature of academic life, as Jonathan Shepherd pointed out, that, with the exception of the consultant staff of university medical schools, few academics who teach public service professionals continue to practice. The park will be designed as an environment for a new breed of practitioner-academics to prototype ideas based on their research findings, working with other practitioners in the field to assess the effectiveness of new approaches. This could involve active partnership with service providers e.g. a network of experimental schools, an echo of John Dewey’s idea of a Laboratory School at the University of Chicago at the beginning of the 20th century which spread throughout the Unites States. Another important element would be to support practitioners in the field in strengthening their own research capabilities. One means of doing this is to mainstream basic research methods, particularly self-directed action research, into professional education. Another is by adopting the Learning by Developing approach adopted at Aalto University. This builds research and innovation into learning by incorporating real-world R&D projects with external partners into mainstream under-graduate and post-graduate study. Building up programmes and methodologies of ‘interactive social science’ which involve engagement with users, practitioners, etc as active participants in the research process – not just as research subjects or consumers of the final product – will also help build bridges between research and practice. In the most advanced cases this could involve embedding social science researchers on the frontline by building a Researcher in Residence programme throughout the public services. This chimes with the idea of ‘flipping academics’ recently proposed by the Canadian innovation theorist Alex Bruton as a new breed of researcher that: “informs first and publishes later;….seeks “the truth” and “usefulness” together….[and] works where they need to work”.
Building the Policy Test-Bed There is an increasing consensus in policy and academic circles that studying the ‘natural experiments’ thrown up by society’s independent evolution is insufficient when seeking to understand our underlying problems. There is increasing interest in introducing into social policy the same rigour that the randomised field or control trial represents in medicine. Geoff Mulgan has suggested we could be. The American author Jim Manzi has written about its use by business, most notably the credit card company Capital One’s attempt to turn itself into a scientific laboratory for business, conducting thousands of mini-experiments every month on
aspects of customer behaviour and business strategy.xxxix The Social Science Park could be a platform for the development of a parallel test-bed environment for the public sector. The use of randomised control trials in a more social context dates from the 1960s. Large-scale social experiments were subjected to rigourous evaluation but the disappointing results led to a loss of interest on the part of politicians. Since the early 1980s, however, there has been something of a resurgence of experimental social science. The global figure for social RCTs conducted continues to rise year on year – though they still number only a few thousand in total. The RCT – though it is not without its detractors - is increasingly seen as the best method to evaluate specific social interventions. MIT’s Poverty Action Lab, for example, has conducted wide-ranging RFTs related to poverty reduction, education and health in developing countries; Harvard economist Ronald Fryer’s Ed-Lab work on the US school system; and Chicago sociologist John A.List’s work on racial discrimination are among the other key examples. The work of the Behavioural Insights Team in the UK has also shown that RCTS needn’t be expensive and can be run in multiple short cycles of iteration as part of existing systems of data collection and management. The EU is actively promoting the adoption of policy experimentation through the SPARK (Social Policy Analysis for Robust Knowledge) network. While the term ‘experimental government’ still poses some difficulty, in practice, as Geoff Mulgan has argued, we are poised on the cusp of a new era ‘“where governments are willing to test their ideas out – to run RCTs and embed continuous learning and feedback into everything they do.”xl
From Big Data to Deep Understanding Computational social science is an emerging academic field at the intersection of social science, computer science and statistics which promises to revolutionise our understanding of complex social systems and provide an unprecedented opportunity to address some of the major challenges we face. Traditional social science enquiry lacked the ability to conduct massive social observation and simulation at the level of granular detail that is now possible. Three things have come together to enable this:
Hardware: cheap processing power, supercomputers and distributed computing make execution of large-scale heterogeneous programmes feasible Large-scale data-sets: new types of massive user-generated data made available through ICT applications e.g. mobile phone records, social networks, commercial transactions, geo-located, minute-by-minute, which can be used to model the complex, interdependent dynamics of human behaviour at a societal scale New methodologies: agent-based modelling, machine-learning, advanced data mining, decision trees, case-based reasoning engines, modern Bayesian methods, clusters and support vector machines
This combination of Big Data, new techniques and new computational capacity mean that generative explanations about how people think , inter-relate, create wealth, govern themselves and reproduce their cultures can be developed in virtual computational social worlds, analysed and experimented with and then tested empirically using real world data. This has far-reaching implications for vast areas of human activity. It also provides the core social sciences - economics, sociology, political science, anthropology - with a set of new instruments on a par with the birth of quantitative social science a century ago. Such is its usefulness computational social science also has relevance to the wider human sciences and humanities: psychology, organisation and management, linguistics, geography, communications, law etc. CSS means that social science is no longer limited to talking about averages; it dissolves the difference between the micro and the macro and removes the need for aggregation. It provides a snapshot of society in high resolution allowing us to see the big picture without losing any of the detail. CSS is a truly inter-disciplinary and still emerging field. But what is exciting about it is its ambition to be a true science, producing explanatory models of social phenomena and predictive rules of a non-obvious nature i.e. it promises to help turn social science into an applicable tool that can inform decision-making about major policy issues and grand challenges. These range from financial and economic instability, epidemiology and demographics, socio-economic and inter-ethnic division, governance, crime and new problems arising from the use of technology itself. CSS makes it possible for the first time to simulate complex inter-dependent social processes at a massive scale, and therefore to provide policy-makers with usable information about optimal policy options. A new Institute which brought together social and behavioural scientists with computer scientists, together with statisticians, cognitive scientists, agent theorists, complexity and network scientists, mathematicians and physicists working side-by-side to produce innovative theoretically grounded and empirically tested models of human behaviour could become a world leader, a sort of CERN for understanding the ‘social’ universe. This will require the building of a novel setting that is beyond the current state-of-the-art in computational and in organisational terms e.g. the development of easy-to-use programs and techniques just as mass market CAD software revolutionised engineering in the 1980s, there is a need to foster commercially available CSS tools. A trans-disciplinary and multi-sectoral social science park would be the perfect arena in which to forge this new toolkit.
The Shock of the Old Like every new idea, the idea of a “social science park” can boast deep roots and a few false starts. The first mooted attempts to build a fully-fledged “social science park” stem from the early 1990s. The London School of Economics in 1992, under its then Director John Ashworth, proposed to move from its Aldwych campus to the former County Hall building on the South Bank in in order to create what Ashworth described as a “social science park” including the development of
research centres and spin-off firms, especially in the area of economic forecasting in which the LSE had particular expertise, plus a Civil Service training institute modelled on the French ENA. Despite support from the then Trade and Industry Secretary Michael Heseltine and a lengthy legal challenge, the site was sold in the end to the highest bidder, a Japanese developer who turned it into a hotel. The LSE invested the cash instead in the purchase of The George IV pub and Dickens’ Old Curiosity Shop. Also in 1992 John Hopkins University commissioned a feasibility study for the United States’ first “social science research park” in an ambitious plan to redevelop a venerated former major-league baseball stadium in North-East Baltimore. The university’s property advisors concluded there was a market need and a good fit with their existing strengths but the distance from the ‘primary market’ in Washington DC was a significant constraint. The Stadium was demolished and a retirement home now stands on the northern end of its outfield.
Social Innovation at Scale These failures have not prevented the new momentum to create for the social sciences the kind of infrastructure that science and technology has developed as a platform for innovation in the latter half of the Twentieth Century. Speaking at the turn of the Millennium the Canadian sociologist, and long-term president of Canada’s Social Sciences and Humanities Research Council argued thus: “To fulfil our needs as researchers, but also to fulfil the needs of society, we have to build the necessary infrastructure which will service to efficiently collect, transmit and make use of knowledge….The social sciences have an unprecedented winter of opportunity to shape the tools – both intellectual and technological – that will structure the reality of the future….To meet the demands of that future, we are called upon to ‘reinvent’ the social sciences in some pretty fundamental ways. We must be able not only to move beyond traditional [….] boundaries. We must also build new capabilities and reflexes of coordination, collaboration and communication – including among researchers, […..] and also between researchers and people from other walks of life”xli To paraphrase, it might be said that the time of the social science park has finally come. Throughout the world in recent years we have seen the rise of social labs. Social labs are platforms for addressing complex social challenges that have three core characteristicsxlii: 1. They are social, bringing together diverse participants drawn from different sectors of society, such as government, civil society, and the business community. 2. They are experimental. The team doing the work takes an iterative approach to the challenges it wants to address, prototyping interventions and managing a portfolio of promising solutions.
3. They are systemic. The ideas and initiatives developing in social labs, released as prototypes, aspire to be systemic in nature. This means trying to come up with solutions that go beyond dealing with a part of the whole or symptoms and address the root cause of why things are not working in the first place.
These principles are mirrored in the mission statement for one putative social science park which is ‘to generate economic, environmental and social value through co-developing innovative and effective solutions to societal problems’. In some very literal sense a social science park is a social lab on a very big scale. That scale means that the breadth of its social innovation:
Social technology: technological innovations related to social problems Social invention: the development of new tools, policies and practices capable of delivering large-scale social change Social enterprise: new start-up organisations with explicitly social goals Social commerce: commercial products or processes based on social science insights
can cover a multiplicity of dimensions.
A Park is (almost) Born Given the strong fit between need and opportunity the idea represents, it should come as no surprise that leaders and staff in a number of universities have recently floated the idea of a social science park , UPF in Barcelona and the Universities of Lincoln and Southampton in England among them. Only two universities so far, however, have gone further in developing concrete plans for social science parks. Turkey’s Medenyiet University, a relatively new institution, has unveiled a proposal to create what it calls SocioPark, a social science based research park, in Istanbul: Some of the key principles behind the proposal were summarised following discussions at a foundational conference in March this yearxliii: •
It will be a new facility similiar to the University’s existing technopark and biopark but based on the social sciences
•
Its objective is to help society benefit from the knowledge and research ability of the university. This principally achieved by: i.
Creating solutions for social problems at both national and international levels
ii.
Supporting collaboration in interdisciplinary common research projects
iii.
Presenting the concrete results of the research to policy makers
•
The Park to be managed by the university, but free financially and not dependent on bureaucacy. Other universities, NGOs, outside entrepreneurs may open offices in SocioPark.
Cardiff University’s plans for a c.8,900m2 Social Science Park (SPARK) are somewhat more advanced with £40m allocated to the project as one of four key priorities in its new Innovation System. According to Cardiff University the core elements within SPARK include:
Co-location of existing centres of research excellence (e.g. WISERD, PPiW) alongside organisations from the private, public and third sectors (c.400 people). This includes Welsh, UK Government and EU-funded initiatives but also other privately-funded think tanks and foundations, e.g. in public sector outsourcing, strategy, policy and horizon scanning, big data, financial services, retail, media, computational social science social networks, and technology for social good. Innovation Academy: The SPARK will be a place for thinking differently, a training centre focusing on the management and delivery of innovation in various spheres. Executive education seminars, sabbaticals, internships and working visits will make the SPARK a knowledge hub for innovators, particularly in the public and social innovation fields. Computational Social Science institute: Activities in the CSSi would include: (i) Managed data collection, processing, exploitation, and dissemination resources; (ii) Establishing and nurturing a pool of talented software engineers and data analysts able to work across a platform of projects, share expertise and best practices, and work alongside social scientists in an inter-disciplinary context, and (iii) Driving innovation through “blue-chip” partnerships – industry, academic, and public sector – and enabling a vibrant computational social science research environment that sparks new questions that Big Data might help answer. BESS Behavioural and experimental social science lab: SPARK will develop a new model experimental social science lab. It will be a purpose-built facility designed to test cutting-edge hypotheses about cognition and human behaviour in business settings. The state-of-the-art facility aims to facilitate world-class behavioural research, provide a variety of services that support data collection for behavioural research on business-related topics, promote the development of a vibrant research community and enhance our teaching breadth and scope. Public Services Innovation lab: PSIL is a laboratory of social change; a space in which a diverse group of stakeholders can co-design innovative answers to society’s ‘wicked problems’. Like the SPARK itself, PSIL is an arena for collaboration (with researchers, practitioners, and other stakeholders) and a place for prototyping, but it swaps the scientific method for systems theory, creative problem solving and design thinking as its tools for solution building. Distinct labs could be developed in different thematic areas e.g. health, crime etc.
Dedicated space for the physical prototyping of new public purpose tech innovations developed in conjunction with the College of Physical Sciences and Engineering. For example, Welsh public procurement could be used to develop innovative solutions that could then be marketed on a global scale. There is also considerable potential working with colleagues in the biomedical and life sciences, for example in the take-up of clinical innovations. The park will act as knowledge broker between technology companies, practitioners and commissioners as part of a public-private initiative in health, welfare and learning. It will also seek to attract technology companies and their relevant research institutes to co-locate in the park to take advantage of the knowledge-spill overs and other agglomeration effects from the cluster of public and social innovation. An Institute of Advanced Studies (IAS), a cross-disciplinary centre of research excellence working on a rolling programme of research issues. The IAS will host visitors and staff on research leave, hold events, play a role in mentoring and developing staff and act as a ‘beacon’ for the research conducted at Cardiff. It will be the host to a Fellowship of internationally leading researchers and also to Honorary Fellows who are invited to spend time working in the park alongside Cardiff colleagues.
The Infrastructure of a Scientific Revolution Globally social sciences can be said to be on the cusp of a new golden age. Vast computational capacity coupled with Big Data means society can be observed in all its complexity like never before. Insights imported from other disciplines (neuroscience, evolutionary biology, game and network theory) have brought with them a new predictive power. Yet another source of convergence with the natural sciences is to be found in social scientists’ (re)discovery of the value of experimentation through virtual labs and randomised control trials. Of course, the potential lies not only in convergence with STEM (Science, Technology, Engineering and Mathematics) but the retention and development the unique insights from social science research. On the demand side also there is a new appetite for the knowledge that only social science can generate. There is a growing recognition among policy-makers and practitioners alike of the need for innovation in public services and a proper evidence base for policy. This is leading to a renewed focus on the role of Universities as part of the pipeline of production of evidence and as test-beds for policy evaluation and experimentation. Similarly the private sector – in a world increasingly defined by social networks, social media and social software – is focused on understanding the (social) science of human interaction like never before. But why a park? Classic work on innovation has long pointed to the importance of ‘third spaces’: environments where practitioners can collaborate with research scientists in the production of new knowledge. This has taken a variety of physical forms from the science park to the innovation campus or the open multidisciplinary experimental space (most famously represented by MIT Media Lab).
Could social science and the society it ultimately serves benefit, through better science leading to better practice, from this same approach? The creation of human knowledge is fundamentally a social process where knowledge spills over from one field to another, ideas are exchanged, theories challenged and new concepts born. Proximity is critical. Yet those who generate knowledge often operate in separate world to those who apply it. Meanwhile universities are striving for greater societal impact alongside their traditional roles of teaching and research and practitioners are struggling to find new ways of meeting the needs of a changing society. The Social Science Park brings the worlds of theory and practice together in new ways to spark the ideas that will lead to transformational change. Though the Park is a physical space, it is its soft infrastructure – its culture and its sense of common endeavour, its associative capacity and network capital - that will be the most critical factors in its success. If well-designed it will be nothing like the intellectual silos of old. It will be an open, inter-disciplinary, collaborative environment in which a “new renaissance” of social science can flourish, a perfectly-crafted tool for the problems of our time.
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