What is data science?
Billions of gigabytes of data are generated globally every day. Data science is the drive to turn this data into useful information, and to understand its powerful impact on science, society, the economy and our way of life.
The study of data science brings together researchers in computer science, mathematics, statistics, machine learning, engineering and the social sciences.
In this film we asked a range of Turing researchers, together with industry and government thinkers about what data science means to them – and why it is important to all of us.
What is artificial intelligence?
There is no accepted definition of artificial intelligence or ‘AI’ but the term is often used to describe when a machine or system performs tasks that would ordinarily require human (or other biological) brainpower to accomplish, such as making sense of spoken language, learning behaviours or solving problems. There are a wide range of such systems, but broadly speaking they consist of computers running algorithms, often drawing on data.
In popular culture artificial intelligence is often viewed as sentient machines, thinking and behaving like a human.
In reality, much AI is computers which are trained to perform tasks independently and which are already present in much of our lives. For example, there has been much publicity about the use of AI in decision-making, for example in the legal system. The AI in this example is driven by machine learning tools, which have taught a computer to make decisions based on the data presented to it.
What is machine learning?
Machine learning is a branch of artificial intelligence that allows computer systems to learn directly from examples, data and experience. The Royal Society's recent report on machine learning provides more background.
How do data science, machine learning and artificial intelligence overlap?
Many of the foundational tools and methods of data science underpin machine learning and artificial intelligence.
Data science, AI and machine learning require many of the same skills in mathematical modelling, computer science, statistics, mathematics.
They are all long-standing areas of science which have experienced a major resurgence (in the case of AI and machine learning) or emergence (in the case of data science) thanks to increases in computer power, the ability to capture and make sense of data, theoretical break-throughs, and investment.
They are all set to have a major impact on the world we live in, and provoke important ethical and societal questions.
What research does The Alan Turing Institute undertake?
Research at the Turing is channelled around a number of ambitious challenges which represent areas in which AI and data science can have a game-changing impact for science, society, and the economy.
Find out more about our challenges, programmes of research, projects, and interest groups and the core capabilities which underpin them.
How did the Institute shape its research agenda?
Ahead of the launch of the Institute in 2015/16, more than 1000 people from a range of disciplines and backgrounds took part in a scoping exercise to define our initial research priorities. The outputs from this exercise are summarised in our Scoping Workshop Report.
In 2018 we launched a set of eight research challenges, which were devised in consultation with partners and researchers. These challenges are representative of broader areas of applied science which the Turing works in, and will not be led by the Turing alone, but depend on significant collaboration and partnerships.
How does The Alan Turing Institute contribute to the debate on data ethics?
Understanding the ethical and social issues arising from the use of data science and artificial intelligence is one of The Alan Turing Institute’s key research priorities.
The members of our Data Ethics Group lead our research in this area. The group work in collaboration with the broader data science community, support public dialogue on relevant topics, and makes calls for participation in workshops and public events.
The ethical expertise concentrated in the Data Ethics Group complements a wider group of researchers in the Institute exploring issues of fairness, transparency and privacy in data science. The interest group in fairness, transparency, privacy, led by Programme Director for AI Adrian Weller, includes experts in machine learning, security, causal inference and algorithm design. The group aims to develop new technical approaches to managing these ethical challenges, and to inform a broader discussion.
Find out more about our work in data ethics, and the Turing's own Ethical Advisory Group which ensures that research conducted across the Institute confirms to high ethical standards.
How can I get involved?
Visit our Learn, Explore and Participate (LEAP) page to discover all the different ways you can engage with the Turing.
We run regular Turing Lectures featuring guest speakers discussing the latest trends in data science. We host workshops and seminars for researchers and technical audiences, as well as more general events open to all. Sign up for our newsletter mailing list to be kept informed.
We aim to engage with as many researchers as possible with an interest and expertise in artificial intelligence and data science. This page lists opportunities available to researchers from across the UK (and in some cases the globe), whether you’re early in your career or a senior researcher.
We also regularly advertise for talented researchers, students, data scientists and business operations staff to join us at the Turing. Look out for these on our opportunities page.