Frequently asked questions
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?
The Alan Turing Institute is interested in research which tackles the big challenges in data science with lasting effects for science, the economy and the world we live in. Core areas of our research range from data-centric engineering, high-performance computing and cyber-security, to smart cities, health, the economy, government and data ethics.
Our initial research priorities were established through a major research process undertaken in 2015/16. The research process, which involved more than 1000 individuals from a range of disciplines and backgrounds, and over 40 workshops and summits, are summarised in our Scoping Workshop report.
How will The Alan Turing Institute contribute to the debate on data ethics?
Understanding the societal implications of big data 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 Fairness, Transparency and Privacy interest group, led by Turing Fellow 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.
Turing Lectures by Professor Luciano Floridi, ‘Ethics in the Age of Information’, Professor Helen Margetts, ‘The Data Science of Politics’, and Ben Shneiderman, ‘Algorithmic Accountability’, provide a useful introduction to the topics around data ethics which the Turing will explore.
How can I get involved?
We run regular Turing Lectures featuring guest speakers discussing the latest trends in data science. We host workshops and seminars for researchers. Events are free and open to all. Sign up for newsletter mailing list to be kept informed.
We regularly advertise for talented researchers, students, data scientists, engineers and operations staff to join our team. We also run regular calls for Visiting Researchers and students to join the Institute and support our research. Look out for these on our Opportunities page.