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In the kingdom of ends everything has either a price or a dignity. What has a price can be replaced by something else as its equivalent; what on the other hand is raised above all price and therefore admits of no equivalent has a dignity.One of the fascinating features of the history of science is how often new ways of seeing preceded new insights. The achromatic-lens microscope in the early 19th century paved the way for germ theory, and X-ray crystallography in the early 20th century played a vital role in the later discovery of the structure of DNA. In the same way flows of data – for example, about how people move around a city, or how blood cells change – can prompt new insights.But how important is measurement to social change? Many people are attracted to metrics and indices of all kinds. But, as my colleague Mark Moore used to warn, ‘do you really think the leaders of the Civil Rights Movement were counting the placards or measuring the decibels of their cries for human rights?’ In social change, as in our own daily lives, measurement often feels inappropriate for the things that matter most.This chapter examines some of the history of social observation as a tool for public policy, social innovation and social change, and I suggest where it might lead in the future. Without some means of measurement, it can be hard to know if a social innovation is good. It may feel good to the beneficiaries – but still be less effective than an alternative. Or it may work well for one group but not another. And, even if it may not be appropriate to measure the passions of movements, once these ideas become part of the mainstream, and are transformed into the cool logic of laws, regulations and programmes, measurements do start to matter a lot, as the Civil Rights Movement discovered.A short history of measurementFor centuries, governments have sought to map and measure social phenomena in order to better exercise control over them. In the modern era these attempts can be traced back to figures like Sir William Petty in England and the cameralists in Prussia.

Technology is the answer, but what was the question? Introduction Many firms, charities and governments are in favour of more innovation, and like to side with the new against the old. But should they? A moment's reflection shows that it's not altogether coherent (whether intellectually, ethically or in terms of policy) to simply be in favour of innovation, whether that innovation is a product, a service or a social idea. Some innovations are unambiguously good (like penicillin or the telephone). Others are unambiguously bad (like concentration camps or nerve gas). Many are ambiguous. Pesticides kill parasites but also pollute the water supply. New surveillance technologies may increase workplace productivity but leave workers more stressed and unhappy. Smart missiles may be good for the nations deploying them and terrible for the ones on the receiving end.In finance, Paul Volcker, former head of the US Federal Reserve, said that the only good financial innovation he could think of was the automated teller machine. That was an exaggeration. But there is no doubt that many financial innovations destroyed more value than they created, even as they enriched their providers, and that regulators and policy makers failed to distinguish the good from the bad, with very costly results. In technology, too, a similar scepticism had emerged by the late 2010s, with digital social media described as the ‘new tobacco’, associated with harm rather than good, with addiction rather than help. Or, to take another example: when the US Central Intelligence Agency's venture capital arm, In-QTel, invested heavily in firms like Palantir, which then became contractors for the intelligence and military (a prime example of the ‘entrepreneurial state’), it was far from obvious how much this was good or bad for the world.The traditional justification for a capitalist market economy is that the net effects of market-led innovation leave behind far more winners than losers, and that markets are better able to pick technologies than bureaucracies or committees. But even if, overall, the patterns of change generate more winners than losers, there are likely to be some, perhaps many, cases where the opposite happens. It would be useful to know.

The 21st century has brought a cornucopia of new knowledge and technologies. But there has been little progress in our ability to solve social problems using social innovation – the deliberate invention of new solutions to meet social needs - across the globe. Geoff Mulgan is a pioneer in the global field of social innovation. Building on his experience advising international governments, businesses and foundations, he explains how it provides answers to today’s global social, economic and sustainability issues. He argues for matching R&D in technology and science with a socially focused R&D and harnessing creative imagination on a larger scale than ever before. Weaving together history, ideas, policy and practice, he shows how social innovation is now coming of age, offering a comprehensive view of what can be done to solve the global social challenges we face.

In this chapter I turn to how social science can be adapted to the challenges and tools of the 2020s, becoming more data driven, more experimental and fuelled by more dynamic feedback between theory and practice. Social science at its grandest is the way societies understand themselves: why they cohere or fall apart; why some grow and others shrink; why some care and others hate; how big structural forces explain the apparently special facts of our own biographies. It observes but also shapes action, and then learns from those actions.Starting with the idea of social science as collective selfknowledge, I describe how new approaches to intelligence of all kinds can help to reinvigorate it. I begin with data and computational social science and then move on to cover the idea of social R&D and experimentation, new ways for universities to link into practice, including social science parks, accelerators tied to social goals, challenge-based methods and social labs of all kinds, before concluding with the core argument: an account of how social science can engage with the emerging field of intelligence design. This is, I hope, a plausible and desirable direction of travel.The rise of data-driven and computational social ScienceWe are all familiar with the extraordinary explosion of new ways to observe social phenomena, which are bound to change how we ask social questions and how we answer them. Each of us leaves a data trail of whom we talk to, what we eat and where we go. It's easier than ever to survey people, to spot patterns, to scrape the web, to pick up data from sensors or to interpret moods from facial expressions. It's easier than ever to gather perceptions and emotions as well as material facts – for example, through sentiment analysis of public debates. And it's easier than ever for organisations to practise social science – whether it's investment organisations analysing market patterns, human resources departments using behavioural science or local authorities using ethnography.These tools are not monopolised by professional social scientists. In cities, for example, offices of data analytics link multiple data sets and governments use data to feed tools using AI – like Predpol or HART – to predict who is most likely to go to hospital or end up in prison.

In the kingdom of ends everything has either a price or a dignity. What has a price can be replaced by something else as its equivalent; what on the other hand is raised above all price and therefore admits of no equivalent has a dignity.One of the fascinating features of the history of science is how often new ways of seeing preceded new insights. The achromatic-lens microscope in the early 19th century paved the way for germ theory, and X-ray crystallography in the early 20th century played a vital role in the later discovery of the structure of DNA. In the same way flows of data – for example, about how people move around a city, or how blood cells change – can prompt new insights.But how important is measurement to social change? Many people are attracted to metrics and indices of all kinds. But, as my colleague Mark Moore used to warn, ‘do you really think the leaders of the Civil Rights Movement were counting the placards or measuring the decibels of their cries for human rights?’ In social change, as in our own daily lives, measurement often feels inappropriate for the things that matter most.This chapter examines some of the history of social observation as a tool for public policy, social innovation and social change, and I suggest where it might lead in the future. Without some means of measurement, it can be hard to know if a social innovation is good. It may feel good to the beneficiaries – but still be less effective than an alternative. Or it may work well for one group but not another. And, even if it may not be appropriate to measure the passions of movements, once these ideas become part of the mainstream, and are transformed into the cool logic of laws, regulations and programmes, measurements do start to matter a lot, as the Civil Rights Movement discovered.A short history of measurementFor centuries, governments have sought to map and measure social phenomena in order to better exercise control over them. In the modern era these attempts can be traced back to figures like Sir William Petty in England and the cameralists in Prussia.

In this chapter I turn to how social science can be adapted to the challenges and tools of the 2020s, becoming more data driven, more experimental and fuelled by more dynamic feedback between theory and practice. Social science at its grandest is the way societies understand themselves: why they cohere or fall apart; why some grow and others shrink; why some care and others hate; how big structural forces explain the apparently special facts of our own biographies. It observes but also shapes action, and then learns from those actions.Starting with the idea of social science as collective selfknowledge, I describe how new approaches to intelligence of all kinds can help to reinvigorate it. I begin with data and computational social science and then move on to cover the idea of social R&D and experimentation, new ways for universities to link into practice, including social science parks, accelerators tied to social goals, challenge-based methods and social labs of all kinds, before concluding with the core argument: an account of how social science can engage with the emerging field of intelligence design. This is, I hope, a plausible and desirable direction of travel.The rise of data-driven and computational social ScienceWe are all familiar with the extraordinary explosion of new ways to observe social phenomena, which are bound to change how we ask social questions and how we answer them. Each of us leaves a data trail of whom we talk to, what we eat and where we go. It's easier than ever to survey people, to spot patterns, to scrape the web, to pick up data from sensors or to interpret moods from facial expressions. It's easier than ever to gather perceptions and emotions as well as material facts – for example, through sentiment analysis of public debates. And it's easier than ever for organisations to practise social science – whether it's investment organisations analysing market patterns, human resources departments using behavioural science or local authorities using ethnography.These tools are not monopolised by professional social scientists. In cities, for example, offices of data analytics link multiple data sets and governments use data to feed tools using AI – like Predpol or HART – to predict who is most likely to go to hospital or end up in prison.

The 21st century has brought a cornucopia of new knowledge and technologies. But there has been little progress in our ability to solve social problems using social innovation – the deliberate invention of new solutions to meet social needs - across the globe. Geoff Mulgan is a pioneer in the global field of social innovation. Building on his experience advising international governments, businesses and foundations, he explains how it provides answers to today’s global social, economic and sustainability issues. He argues for matching R&D in technology and science with a socially focused R&D and harnessing creative imagination on a larger scale than ever before. Weaving together history, ideas, policy and practice, he shows how social innovation is now coming of age, offering a comprehensive view of what can be done to solve the global social challenges we face.

Technology is the answer, but what was the question? Introduction Many firms, charities and governments are in favour of more innovation, and like to side with the new against the old. But should they? A moment's reflection shows that it's not altogether coherent (whether intellectually, ethically or in terms of policy) to simply be in favour of innovation, whether that innovation is a product, a service or a social idea. Some innovations are unambiguously good (like penicillin or the telephone). Others are unambiguously bad (like concentration camps or nerve gas). Many are ambiguous. Pesticides kill parasites but also pollute the water supply. New surveillance technologies may increase workplace productivity but leave workers more stressed and unhappy. Smart missiles may be good for the nations deploying them and terrible for the ones on the receiving end.In finance, Paul Volcker, former head of the US Federal Reserve, said that the only good financial innovation he could think of was the automated teller machine. That was an exaggeration. But there is no doubt that many financial innovations destroyed more value than they created, even as they enriched their providers, and that regulators and policy makers failed to distinguish the good from the bad, with very costly results. In technology, too, a similar scepticism had emerged by the late 2010s, with digital social media described as the ‘new tobacco’, associated with harm rather than good, with addiction rather than help. Or, to take another example: when the US Central Intelligence Agency's venture capital arm, In-QTel, invested heavily in firms like Palantir, which then became contractors for the intelligence and military (a prime example of the ‘entrepreneurial state’), it was far from obvious how much this was good or bad for the world.The traditional justification for a capitalist market economy is that the net effects of market-led innovation leave behind far more winners than losers, and that markets are better able to pick technologies than bureaucracies or committees. But even if, overall, the patterns of change generate more winners than losers, there are likely to be some, perhaps many, cases where the opposite happens. It would be useful to know.

This chapter is about evidence and whether we can, or should, know our impact, the effect we have in the world. It addresses the difficulties as well as the possibilities of evidence for innovators and politicians, civil servants and head teachers, charities and doctors. I also touch on the question at the level of daily life, the moral question of whether we help those around us to be healthier, happier and more prosperous. Knowing our own impacts is, I argue, as much a moral prerogative as the traditional philosophical injunction of knowing ourselves.The enlightenment storyMany of us imbibed from an early age what can be called the enlightenment story. In this story new knowledge is steadily accumulated, mainly in universities and from academic journals. Theories are invented, tested, refuted and then improved. Scepticism helps to refine them and, as Wittgenstein wrote, the child first learns belief and only then learns doubt. You could say that at school we learn knowledge, and then at university we learn to question that knowledge.Belief is strengthened precisely because it has already been knocked down. And so, accumulating knowledge shows that this medicine, that economic policy or this teaching method works and many others don’t. The successful method then spreads, because when you design a better mousetrap the world beats a path to your door. It spreads because people are rational and want to do better and are persuaded by evidence. And so, the world progresses. Light replaces darkness. Effective solutions displace failed ones.It's easy to mock the enlightenment story. The sociologists of science have shown a much messier pattern of change – full of barriers, wilful resistance and peer pressure. But the old enlightenment story contains a good deal of truth and is preferable to the alternatives. Because of intense pressures to act on evidence, and habits of doubt among maintenance staff and engineers, aircraft do not drop out of the sky. Smoking made the slow progress from evidence of harm, through taxes and warnings to full-scale bans, and millions of lives were saved.Experimental methods have been used for many decades.

This chapter is about evidence and whether we can, or should, know our impact, the effect we have in the world. It addresses the difficulties as well as the possibilities of evidence for innovators and politicians, civil servants and head teachers, charities and doctors. I also touch on the question at the level of daily life, the moral question of whether we help those around us to be healthier, happier and more prosperous. Knowing our own impacts is, I argue, as much a moral prerogative as the traditional philosophical injunction of knowing ourselves.The enlightenment storyMany of us imbibed from an early age what can be called the enlightenment story. In this story new knowledge is steadily accumulated, mainly in universities and from academic journals. Theories are invented, tested, refuted and then improved. Scepticism helps to refine them and, as Wittgenstein wrote, the child first learns belief and only then learns doubt. You could say that at school we learn knowledge, and then at university we learn to question that knowledge.Belief is strengthened precisely because it has already been knocked down. And so, accumulating knowledge shows that this medicine, that economic policy or this teaching method works and many others don’t. The successful method then spreads, because when you design a better mousetrap the world beats a path to your door. It spreads because people are rational and want to do better and are persuaded by evidence. And so, the world progresses. Light replaces darkness. Effective solutions displace failed ones.It's easy to mock the enlightenment story. The sociologists of science have shown a much messier pattern of change – full of barriers, wilful resistance and peer pressure. But the old enlightenment story contains a good deal of truth and is preferable to the alternatives. Because of intense pressures to act on evidence, and habits of doubt among maintenance staff and engineers, aircraft do not drop out of the sky. Smoking made the slow progress from evidence of harm, through taxes and warnings to full-scale bans, and millions of lives were saved.Experimental methods have been used for many decades.

The 13 methods featured are: Accelerator programmes Anticipatory regulation Challenge prizes Crowdfunding Experimentation Futures Impact investment Innovation mapping People Powered Results: the 100 day challenge Prototyping Public and social innovation labs Scaling grants for social innovations Standards of Evidence

The 13 methods featured are: Accelerator programmes Anticipatory regulation Challenge prizes Crowdfunding Experimentation Futures Impact investment Innovation mapping People Powered Results: the 100 day challenge Prototyping Public and social innovation labs Scaling grants for social innovations Standards of Evidence

The 13 methods featured are: Accelerator programmes Anticipatory regulation Challenge prizes Crowdfunding Experimentation Futures Impact investment Innovation mapping People Powered Results: the 100 day challenge Prototyping Public and social innovation labs Scaling grants for social innovations Standards of Evidence

This book is about the many ways in which people are creating new and more effective answers to the biggest challenges of our times: how to cut our carbon footprint; how to keep people healthy; how to end poverty. It describes the methods and tools for innovation being used across the world and across the different sectors – the public and private sectors, civil society and the household – and in the overlapping fields of the social economy, social entrepreneurship and social enterprise. It draws on inputs from hundreds of organisations around the world to document the many methods currently being used. In other fields, methods for innovation are well-understood. In medicine, science, and business, there are widely accepted ideas, tools and approaches. But despite the richness and vitality of social innovation, there is little comparable in the social field. Most people trying to innovate are aware of only a fraction of the methods they could be using. This book provides a first mapping of these methods and of the conditions that will enable social innovation to flourish.

This book is about the many ways in which people are creating new and more effective answers to the biggest challenges of our times: how to cut our carbon footprint; how to keep people healthy; how to end poverty. It describes the methods and tools for innovation being used across the world and across the different sectors – the public and private sectors, civil society and the household – and in the overlapping fields of the social economy, social entrepreneurship and social enterprise. It draws on inputs from hundreds of organisations around the world to document the many methods currently being used. In other fields, methods for innovation are well-understood. In medicine, science, and business, there are widely accepted ideas, tools and approaches. But despite the richness and vitality of social innovation, there is little comparable in the social field. Most people trying to innovate are aware of only a fraction of the methods they could be using. This book provides a first mapping of these methods and of the conditions that will enable social innovation to flourish.

This volume – part of a series of methods and issues in social innovation – describes the hundreds of methods and tools for innovation being used across the world, as a first step to developing a knowledge base.