The Web Science Institute which was established in 2013 brings together world-leading interdisciplinary expertise to tackle the most pressing global challenges facing the World Wide Web and wider society today. It is necessarily interdisciplinary – as much about social and organisational behavior as it is about the underpinning technology.
The web breaks down barriers between the human and the machine, enabling the evolution of so-called social machines that comprise both digital and human components – Wikipedia, Google, Facebook, Twitter and more recently Uber and AirBnB are all examples of social machines. We will see many more emerge as the Web continues to evolve.
The web breaks down barriers between the human and the machine, enabling the evolution of so-called social machines
Wikipedia demonstrates the power of collaborative intelligence, as communities identify and solve their own problems. This collective problem solving can be applied across society in health, transport, policy and city governance. For example, the Open City application aims to harness citywide participation in shared problems, exploiting common open data resources.
Substantial research needs to be devoted to engineering layers of trust and provenance into Web interactions. The coming together of our digital and physical personas presents opportunities for progress, such as the integration of financial, medical and educational services. But it is also an opportunity for cyber crime. Web science can help enhance the good and remove the bad.
Increasingly, companies are viewing positive social impact as good for their business and, with encouragement from government and business leaders, the concept has become mainstream. The Web contributes to this by increasing companies’ transparency through online platforms and social networks. This encourages dialogue between the company, suppliers, customers, government and society. It’s all about trust.
Innovative firms need long-term finance. Recently, there have been attempts at providing such patient finance via the SBRI programme—a good idea that needs to be linked to government procurement policy to make more impact. The UK also lacks a dynamic public bank focused on innovation and scale up for small firms. The lack of patient finance acts as a brake on the UK tech sector. One, often overlooked, factor in the history of the UK tech sector is the BBC—its catalytic role, and the resulting spillovers, have been critical to the sector’s success.
As I argued in evidence to the BEIS inquiry, what we need are mission-oriented policies, of the scale of the moon shot programme, that catalyze innovation across many sectors addressing major technological and social challenges. Sectoral policies cannot achieve this but missions around ‘green’ and ‘care’ could drive innovation across many sectors.
We need mission-oriented policies that catalyze innovation across many sectors addressing major technological and social challenges
The key lesson from Silicon Valley is the need for a decentralized network of public actors, across the entire innovation chain, interacting dynamically with the private sector. In my book I called this ‘The Entrepreneurial State’. This includes funding linkages between basic and applied science, patient finance for innovative firms, and demand side policies enabling full diffusion and deployment of new technologies across the economy.
Because they create most of the jobs – OECD research shows that young, or growing, companies produce 100% of the net new jobs across Europe. So making sure that our ecosystem is conducive to companies that are growing is super important, particularly given that large companies, on average, are shrinking. Probably even more important, though, is that job satisfaction levels are found to be much higher in scale-up companies than other categories of companies (small, medium, or large companies, or professional services firms).
Young and growing companies produce 100% of net new jobs across Europe -so making sure our ecosystem is conducive to companies that are growing is super important
First and foremost they can buy stuff from them! Second, they can make sure that others can identify them, so that the scale ups can more easily attract the people they need to hire, and the finance they need to expand overseas.
Finding people with the right skills to hire, and selling to large corporates.
That’s the wrong question. Scale-ups don’t need or want ‘support’. They want the barriers that prevent them from achieving their ambitions removed, starting with an adequate talent supply and access to people who have ‘been there done that’.
Entrepreneur First invests in top technology talent to help them build world-class, deep technology startups from scratch in London and Singapore. We are the world’s leading company-builder and we co-invest in our companies with a £40m fund. Since 2011, EF has created over 100 startups worth over $400m, including Magic Pony Technology which exited to Twitter for $150m, Tractable, StackHut, Pi-Top, OpenCosmos, Status Today and Cloud NC.
Google’s Eric Schmidt said that machine learning will be basis of ‘every huge IPO’ in the next five years. The most important thing for an AI startup is being clear what real world problem they are solving and for which market. Just having cool tech is not enough. However, the opportunities are endless. We see AI and machine learning companies disrupting every sector, from fintech to manufacturing.
We see AI and machine learning companies disrupting every sector, from fintech to manufacturing
For each cohort we conduct a worldwide search for the best talent across multiple continents. Typically, 50% of applicants come from outside the UK. Our data tells us that our reach spans over 200 university research departments and some of the biggest business ecosystems in the US, Europe and Asia.
While our operational HQ remains in London, we spend a lot of time in other regions where there is a high concentration of engineering talent. Within the UK we continue to build our presence in Edinburgh, Cambridge, Oxford and Bristol.