The Turing Podcast is an exciting new podcast from The Alan Turing Institute, the UK's national institute for data science and artificial intelligence.
How can AI help us understand breast cancer
In this episode hosts Jo Dungate and Rachel Winstanley speak to Andrew Holding, a Senior Research Associate at Cancer Research UK's (CRUK) Cambridge Institute and Turing Fellow. Andrew discusses how his research is using machine learning to understand the biology that underlies breast cancer to help improve treatments.
Palaeoanalytics: Using Data Science and Machine Learning to answer questions about Human Evolution
The hosts chat with to Professor Robert Foley, who works on Human Evolution at the University of Cambridge and is a Fellow of The Alan Turing Institute. The conversation takes a broad view of how our understanding of human evolution has changed in recent decades and focusses in on the Turing institute’s Palaeoanalytics project, which involves applying data science and machine learning methods to non-genomic data. Find out more about this project here: https://www.turing.ac.uk/research/research-projects/palaeoanalytics
How good is AI at detecting online hate?
AI is widely lauded as a way of reducing the burden on human online content moderators. However, to understand whether AI could, and should, replace human moderators, we need to understand its strengths and limitations. In this episode our hosts speak to the researchers Paul Röttger and Bertie Vidgen to discuss how they are attempting to tackle online hate speech, in particular through their work on HateCheck - a suite of tests for hate speech detection models.
Optimizing Policy for Sustainable Development
In an interview recorded last year, Jo & Ed are joined by Dr Omar A Guerrero, an Economist & Computational Social Scientist at The Alan Turing Institute & UCL Department of Economics, whose research focusses on economic behaviour and institutions from an interdisciplinary angle. The episode focusses on Policy Priority Inference (PPI); a technology developed in collaboration with the United Nations Development Programme. PPI is intended to be used to optimise government policy to meet sustainable development goals and identify the policy priorities that governments need to set if they are to adopt a specific development strategy. Read more about the research discussed in this episode here: https://www.turing.ac.uk/research/research-projects/policy-priority-inference
Covid lockdowns: which policies worked best?
This week on the podcast, the hosts are joined by Sören Mindermann & Mrinank Sharma who are PhD students from Oxford University. Mrinank works as part of Oxford's Future of Humanity Institute, whilst Sören is a member of Oxford Applied and Theoretical Machine Learning Group and the episode focuses on the research they've recently had published on inferring the effectiveness of government interventions against Covid-19, during the first wave of the pandemic in 2020. You can find the research article for this work here: https://science.sciencemag.org/content/371/6531/eabd9338
In conversation with Sue Black
In this episode the hosts were joined by Professor Sue Black to discuss her inspirational life story and career, as well as the initiatives she has set up to encourage more women into the tech sector and her hopes for the future.
Sue Black is a Professor of Computer Science and Technology Evangelist at Durham University, has set up initiatives such BCS women and the social enterprise Tech mums, to encourage more women into computing and has received an OBE for ‘Service to technology’. She was also instrumental in the campaign to save Bletchley Park.