Cambridge Digital Humanities course timetable

Join our Methods Fellow, Amira Moeding in a workshop which introduces methods of historical enquiry into the development of digital technologies and digital data. How can we do the history of technology today? What are the limits of historical enquiry; what are its strengths? Moreover, what can we learn from historical narratives about technologies? More concretely, what can the history of “Big Data” tell us about artificial intelligence today? What were, for example, seen as the pitfalls and problems with biases early on in the development of data-driven applications?

Together with you, Amira will think through and employ methods of historical enquiry and critical theory to gain a better understanding of the origin of ‘data-driven’ digital technologies. Therein, the workshop attempts to bring about both an understanding of the statistical or data-driven methods by asking how they came about and why they became attractive to whom. The workshop thus links technologies back to the interests and contexts that rendered them viable. This line of enquiry will allow us to ask what ‘technological progress’ currently is, how stories of ‘progress’ are narrated by industry actors, and what ‘risks’ become apparent from their perspective. By providing this contextualisation and recovering early interests that drove developments in artificial intelligence research and ‘Big Tech’, we will also see that progress, and the promises for the future that it holds, are not ‘objective’ or ‘necessary’ but localised in time and space. We will raise the question to what degree digital humanities cannot only use digital methods to aid the humanities, but how historical and philosophical methods can be employed to provide a basis for criticising and theorising ‘the digital’ and putting the methods so-called ‘artificial intelligences’ are based on into perspective.

Convenor: Dr Giulia Grisot (Cambridge Digital Humanities)

This workshop will delve into the intricacies of sentiment analysis using R, offering participants a comprehensive understanding of this text mining technique and a chance to gain hands-on experience with sentiment scoring methodologies and advanced sentiment visualisation. Designed for intermediate R users, this session aims to equip attendees with the requisite skills to extract nuanced insights from textual data through the lens of R programming. You will need your own laptop.

It is often said we live in a society saturated with data. Visualisation methods can play a crucial role in helping to cut through the information overload. Badly designed charts, graphs and diagrams, on the other hand, can confuse or deceive. This session will introduce and contextualise graphical communication practices historically and culturally, helping you to think more critically about your own work and that of others.

We will focus on graphical display as an interpretative and persuasive practice which requires as much attention to detail as writing. A hands-on collaborative exercise using historical data will give you the chance to put your visualisation skills to work. Coding skills are not required for this workshop but a basic familiarity with creating graphs and charts will be helpful. If you need to refresh your skills before the session, please use this open access workbook: https://docs.google.com/document/d/1wtwqIsWVGcsQ6rvXAzdpfNL5f7mUqV5k_Rr7ZrQCnbo/edit. (if the link doesn't work from UTBS, please copy and paste into your browser).