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?

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 in the strategy?

The process to develop the Institute’s strategy was a collaborative one; we engaged with individuals from across the Turing community and our partner organisations through a series of workshops, meetings and co-design sessions, along with relevant stakeholders from the wider research landscape. We sought further feedback of the draft strategy through a consultation phase with our network, refining our thinking prior to full publication in March 2023.

Given the scale of resources that other nations can bring to bear, we took it as a basic organising principle that we needed to focus our efforts on areas where:

  1. There is a significant societal or economic challenge or opportunity to address
  2. The application of data science and AI could have a transformative impact on the domain
  3. The UK is positioned to build a sustainable advantage against global competitors – in turn built on either privileged assets or distinctive capabilities

Taking initial direction from the priorities of the Office for Science and Technology Strategy (now part of the Department for Science, Innovation and Technology) and applying the tests outlined above led us to select the following areas on which to focus the Institute’s science and innovation efforts:

  • Health
  • Environment and sustainability
  • Defence and national security

These areas form the foundation of our developing Grand Challenges and their associated Missions. Supporting these efforts will be our core capabilities. Collectively, our aim is to provide the end-to-end interdisciplinary pathway that will enable ideas to be taken through to impact and for data science and AI to solve problems of national and global significance.

 

COVID-19 advice

See our dedicated page here.

 

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.