This year’s Web Science Summer School provided a great opportunity to learn about the theme of Artificial Intelligence (AI) from a diverse range of perspectives. In the usual spirit of Web Science, we were presented with a well-rounded selection of talks and workshops covering the social, technical and ethical issues surrounding AI technology. It was fantastic that these sessions came directly from some of the leading experts in the respective fields.
For the social perspective, several of the talks addressed the academic and managerial implications of new forms of data and computational methods presented by AI. Professor Susan Halford emphasised the importance of reflecting on these new developments from a social science angle. The message was reinforced from an industry perspective by JP Rangaswami, who spoke of AI being embedded in a cultural environment that requires more discernment by organisations that exchange data. Themes of trust and values also came up in Dr Kieron O’Hara’s talk about the ethical dimensions of AI. Each of the speakers presented concrete suggestions for shaping the discussion and implementation of AI technology across academia, industry and the public sector. There was an underlying message of responsibility and empowerment, showing how we are in a position to positively shape the ways in which AI technology develops in our society.
A more technical perspective was covered by a series of practical workshops where we learnt how AI technology can be implemented to analyse various kinds of data. In Dr Adriane Chapman’s tutorial, we learnt about the process of applying machine learning methods. We also visited the impressive Data Observatory at Imperial College London, where Professor YiKe Guo discussed their visualisation of complex data. His student, Senaka Fernando then taught us about software for visualising data on a map. Although it was not possible to produce much work during the short length and technical challenges in these tutorials, they provided useful guideposts for pursuing advanced analytic techniques in our own time.
The remaining sessions focused on actionable ways of applying our newly gained knowledge to advise different kinds of stakeholders on current issues related to AI. Professor Mark Nixon gave a fascinating talk about AI biometrics and their applications in security. This was followed by a workshop where we got a chance to participate in a hypothetical scenario requiring us to provide guidance on the possible implementation of facial recognition technology at a university. Another workshop from the Office for National Statistics gave us the opportunity to learn about how ethics are handled in a government organisation, where the measurement of social issues increasingly makes use of AI technology. Lastly, there were the group projects, which encouraged us to think carefully about using Open Street Map data and AI in different scenarios. Having this practical element every day provided a good structure to reflect on everything that we were learning.
Overall, the Summer School was a very interesting, challenging and stimulating experience for learning about AI. I hope that similar events happen here in future and I would highly recommend the Web Science summer schools to anyone interested in current technology.