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Ghost fictions (Guided project) new Mon 26 Oct 2020   14:00 Finished

'Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 13 October 2020. Successful applicants will be notified by 15 October 2020.

This CDH Guided Project series which also includes a Methods Workshop will explore the generation of ‘synthetic’ texts using neural networks.

The release of OpenAI’s GPT-2 and GPT-3 language models in 2019 and 2020 has shown that predictive algorithms trained on very large general datasets can generate ‘synthetic’ texts, perform machine translation tasks, rudimentary reading comprehension, question answering and summarisation automatically without needing large amounts of task-specific training. These ‘ghostwritten’ texts have provoked wide attention in the media.

Researchers have experimented with prompting GPT-3 to write short stories, answer philosophical questions and apparently propose potential medical treatments -although GPT-3 had some difficulty with the question “how many eyes does a horse have?”. The Guardian ‘commissioned’ op-ed from GPT-3.

Through interactive hands-on sessions and demonstrations we will explore synthetic text production and look at how ideas about the distinction between ‘fact’, ‘fiction’ and ‘non-fiction’ are shaping the reception of this emerging technology. Our aim is to stimulate deeper critical engagement with machine learning by humanities researchers and to encourage more public debate about the role of AI in culture and society.

We invite applications from early career researchers and others at the University of Cambridge to join a small project team for four online sessions during the Guided Project phase in Oct-November. Participants will need to commit to joining the live sessions and to set aside at least 3-4 hours work on a small-scale individual project during the course. We are interested in assembling an interdisciplinary group of researchers drawing on insights from across humanities, social science and technology disciplines .Prior knowledge of programming, computer science or Machine Learning is not required.

Interaction with Machine Learning new Mon 1 Feb 2021   10:00 Finished

Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Thursday 7 January 2021. We will review applications on a rolling basis and applicants will be notified at the latest by the end of Monday 11 January.

This CDH Guided Project aims to provide humanities, arts and social science researchers with an overview of current theory and practice in the design of human-computer interaction in the age of AI and equip the participants with analytical tools necessary for a critical investigation of contemporary design with AI/ML. Looking closely at interactions between humans and emerging AI systems, the workshop will also explore the potential for interaction between humanities scholars and computer scientists in the process of development and assessment of new solutions.

Lectures and practical research design sessions in Interaction with Machine Learning taught by Professor Alan Blackwell and Advait Sarkar (Microsoft Research) as part of an optional course for Part III and MPhil Computer Science students will form the anchoring element of the Project. These will allow researchers without a Computer Science background to explore how key challenges in AI design are being addressed within the field of interaction design, as well as identify areas in which humanities methodologies and approaches could be adopted to improve the production process, by making it more fair, critical, and socially-aware.

Participants will also take part in three workshops specifically tailored to humanities and social science researchers and will be supported in developing a mini research project investigating how humans interact with systems based on computational models. The projects may include:

  • probing an already existing dataset, system, or user interface from a critical perspective
  • developing an idea for new interaction design based on critical applications of ML/AI.

Please note: no prior practical experience or knowledge of programming is required to take part in the Project, however some awareness of how AI systems work will be beneficial.

Minimum time commitment:

  • 8 weekly online lectures led by Professor Alan Blackwell (Computer Science and Technology) and Advait Sarkar (Microsoft Research). Weekly from 26 January, 2-4pm (with the last hour as an optional session for Guided Project participants).
  • 3 x 1.5 hour specialist workshops for humanities and social science participants led by Tomasz Hollanek and Anne Alexander (CDH)
  • 1.5 hour project showcase and final discussion

Participants are encouraged to set aside additional time to work on their projects between sessions. A Moodle email forum and drop-in ‘clinic’ style support sessions will be available during the Guided Project.

Lecture topics and dates

  • Current research themes in intelligent user interfaces (26 January, 2pm)
  • Program synthesis (2 February, 2pm)
  • Mixed initiative interaction (9 February, 2pm)
  • Interpretability / explainable AI (16 February, 2pm)
  • Labelling as a fundamental problem (23 February, 2pm)
  • Machine learning risks and bias (2 March, 2pm)
  • Visualisation and visual analytics (9 March, 2pm)
  • Research presentations by Computer Science Students (16 March, 2pm)

Workshop themes

  • AI critique, humanities methodologies and user interface design (1 February, 10-11.30am)
  • Recommender systems (1 March 10-11.30am)
  • Machine vision (8 March 10-11.30am)
  • Project presentations and discussion (15 March 10-11.30am)

Objectives By the end of the course participants should:

  • be familiar with current state of the art in intelligent interactive systems
  • understand the human factors that are most critical in the design of such systems
  • be able to evaluate evidence for and against the utility of novel systems
  • be able to apply critical methodologies to current interaction design practices
  • understand the interplay between ML/AI research and humanities approaches