This week, we’ve added a glossary to The Alan Turing Institute’s website, with 24 definitions of key terms in data science and artificial intelligence (AI), including algorithmic bias, digital twin, neural network and synthetic data.
There is a lot of jargon in data science and AI, so our aim is to create an accessible resource for non-specialists who want to find out more about these topics without having to navigate the technical language. We’re hoping that we can counter some of the misinformation and lead the conversation around these topics, and provide some clarity to the terms that people hear in everyday life – algorithm, deepfake, robot – while also introducing them to new concepts, like deep learning, natural language processing or the Turing test. We’re also hoping that it will be a useful resource for journalists and policy makers, as well as researchers in areas that intersect with data science and AI.
A is for algorithm: Why we created a data science and AI glossary | The Alan Turing Institute
