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Cambridge Digital Humanities

Cambridge Digital Humanities course timetable

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Tue 14 Jul 2020 – Mon 1 Feb

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July 2020

Tue 14
(Critical) Machine Vision for the Humanities [remote delivery] new (10 of 10) Finished 15:00 - 17:00 Cambridge Digital Humanities Online

Leonardo Impett, Cambridge Digital Humanities

Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020.

This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision.

Learning outcomes

By the end of the course, students should be able to:

  • Understand the basic tasks of machine vision, such as Image Classification, Object Detection, Image-to-Image Translation, Image Captioning, Image Segmentation etc.
  • Understand the fundamental technical operations of image processing and machine vision: the pixel encoding of images, Gaussian and convolutional filters,
  • Explore critical aspects of machine vision in a technically-informed way: e.g. the problems in algorithmic bias brought about by featureless convolutional networks
  • Develop and run their own simple machine vision and image processing pipelines, in a visual programming language compiling to Python
  • Understand the potential synergies and limitations of machine vision applications in humanities research and cultural heritage institutions
Wed 15
Game Design: an introduction for researchers [remote delivery] new (4 of 4) Finished 16:00 - 17:00 Cambridge Digital Humanities Online

Emma Reay is a third-year PhD researcher at the University of Cambridge and an associate lecturer at Anglia Ruskin University. Her current project explores depictions of children in videogames, and her research interests include representation studies, children's digital media, gaming and education, and playful activism.

Adam Dixon is a game designer and writer who makes both physical and digital games. He has worked on everything from big public games that involve running around cities to narrative video games about learning scientific skills. Much of his work has involved working with museums and research organisations such as the Wellcome Trust, Science Museum, Nottingham Trent University and the V&A. This has included designing games, using play for public research engagement and most recently, teaching teenagers to create digital games for Wellcome Collection’s Play Well exhibition. Outside of that he works and releases his own games including roleplaying games, LARPs and interactive fiction.

Applications https://www.cdh.cam.ac.uk/file/cdhgamedesign201920applicationdocx-0 should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Wednesday 10 June 2020. Successful applicants will be notified by 15 June 2020.

This online course will introduce participants to the practice of game design. It will explore the different ways that digital and analogue games are designed, particularly how you can design with intent to communicate a mood, theme or message. Participants will learn game design skills - such as boxing-in, design documents and prototyping – alongside opportunities to test them out by creating their own short games. Examples will focus on game design in research-related contexts, including using games as part of your research process and to communicate research outcomes to diverse audiences.

The sessions focus on game design, how to shape mechanics and play experiences, so no technical skills are needed. Participants will create their short games using both non-digital tools and simple, free software that will be taught in the sessions.

Topics covered:

  • Game design basics
  • A chance to play and consider thoughtful games
  • Boxing in
  • Planning games
  • Making games
  • Bitsy and Twine
  • Playtesting and iteration

Format

The course will be delivered online, with live teaching sessions taking place on Zoom.

  • Weds 17 June, 4pm BST: Introduction (45 minutes)
  • Weds 24 June, 4pm BST: Game play feedback (45 minutes)
  • Weds 1 July, 4pm BST: Game design seminar (45 minutes)
  • Weds 15 July, 4pm BST: Final session (60 minutes with break)

A CRASSH blog post was created for the originally scheduled session which may be of interest to read and can be found here: http://www.crassh.cam.ac.uk/blog/post/Play-as-Research-Practice

Wed 29
The Transkribus Guided Project new (1 of 2) Finished 16:00 - 16:30 Cambridge Digital Humanities Online

We introduce the Transkribus software system that can be taught to read handwriting from images of documents and rapidly convert it into useful digital formats. This guided course provides basic training by practical immersion in this software, which requires only basic IT skills. Transkribus was developed by READ under the Horizon 2020 funding framework and is now a co-operative. It had 20,000+ users in 2019, and is becoming a standard research tool for mass transcription of archival sources. Participants will transcribe anonymised data from pre-loaded scans of forms filled out for the French national census of 1999 in Transkribus's downloadable software interface. These manual transcriptions will help train a handwritten text recognition (HTR) model to automatically transcribe many more of these forms later. In fact, the model will eventually allow the creation of one of the largest data sets ever attempted from manuscript sources. This course is a collaboration with Transkribus and Cambridge Digital Humanities. It is funded by a Cambridge Humanities Research Grant.

August 2020

Wed 5
The Transkribus Guided Project new (2 of 2) Finished 16:00 - 17:00 Cambridge Digital Humanities Online

We introduce the Transkribus software system that can be taught to read handwriting from images of documents and rapidly convert it into useful digital formats. This guided course provides basic training by practical immersion in this software, which requires only basic IT skills. Transkribus was developed by READ under the Horizon 2020 funding framework and is now a co-operative. It had 20,000+ users in 2019, and is becoming a standard research tool for mass transcription of archival sources. Participants will transcribe anonymised data from pre-loaded scans of forms filled out for the French national census of 1999 in Transkribus's downloadable software interface. These manual transcriptions will help train a handwritten text recognition (HTR) model to automatically transcribe many more of these forms later. In fact, the model will eventually allow the creation of one of the largest data sets ever attempted from manuscript sources. This course is a collaboration with Transkribus and Cambridge Digital Humanities. It is funded by a Cambridge Humanities Research Grant.

October 2020

Mon 12
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (1 of 7) Finished 11:00 - 11:45 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (2 of 7) Finished 12:00 - 13:00 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Tue 13
Humanities Data: a basic introduction new Finished 10:00 - 11:00 Cambridge Digital Humanities Online

This CDHBasics session will explain what data is, and what ‘humanities data’ looks like (via a behind-the-scenes tour of the Digital Library). This session covers good practice around file formats, version control and the principles of data curation for individual researchers.

Mon 19
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (3 of 7) Finished 11:00 - 11:45 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (4 of 7) Finished 12:00 - 13:00 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Mon 26
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (5 of 7) Finished 11:00 - 11:45 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (6 of 7) Finished 12:00 - 13:00 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Ghost fictions (Guided project) new (1 of 4) Finished 14:00 - 15:30 Cambridge Digital Humanities Online

'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.

Tue 27
Sorting things out - why metadata matters new Finished 10:00 - 11:00 Cambridge Digital Humanities Online

This CDHBasics session focuses on the importance of metadata (‘data about data’), examining the crucial role played by classification systems and standards in shaping how scholars interact with historical and cultural records.

November 2020

Mon 2
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project) new (7 of 7) Finished 11:00 - 13:00 Cambridge Digital Humanities Online

Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020.

Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Mon 9
Ghost fictions (Guided project) new (2 of 4) Finished 11:30 - 13:00 Cambridge Digital Humanities Online

'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.

Ghost fictions (Guided project) new (3 of 4) Finished 14:00 - 15:30 Cambridge Digital Humanities Online

'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.

Tue 10
Re:search new Finished 10:00 - 11:00 Cambridge Digital Humanities Online

This CDHBasics session looks at how searching and finding technologies structure scholarship. It also covers

  • an introduction to search engines, both for web search and custom search functions within collections;
  • discussion about OCR errors and blindspots in digital search in historical collections
  • problems of fragmentation of the source text, and the legacy of pre-digital formats such as microfilm.
Mon 23
Ghost fictions (Guided project) new (4 of 4) Finished 14:00 - 15:30 Cambridge Digital Humanities Online

'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.

Tue 24
Digital Research Design and Data Ethics new Finished 10:00 - 11:00 Cambridge Digital Humanities Online

This CDHBasics session explores the lifecycle of a digital research project across the stages of design;

  • data capture
  • transformation
  • analysis
  • presentation and preservation

it also introduces tactics for embedding ethical research principles and practices at each stage of the research process.

December 2020

Mon 7
Automated writing in the age of Machine Learning new (1 of 2) Finished 11:30 - 13:00 Cambridge Digital Humanities Online

Computer programmes which predict the likely next words in sentences are a familiar part of everyday life for billions of people who encounter them in auto-complete tools for search engines and the predictive keyboards used by mobile phones and word processing software. These tools rely on “language models” developed by researchers in fields such as natural language processing (NLP) and information retrieval which assign probabilities to words in a sequence based on a specific set of “training data” (in this case a collection of texts where the frequencies of word pairings or three-word phrases have been calculated in advance).

Recent developments in machine learning have led to the creation of general language models trained on extremely large datasets which can now produce ‘synthetic’ texts, answer questions, summarise information without the need for lengthy or costly processes of training for each new task. The difficulties in distinguishing the outputs of these language models from texts written by humans has provoked widespread interest in the media. Researchers have experimented with prompting GPT-3, a language model developed by OpenAI to write short stories, answer philosophical questions and apparently propose potential medical treatments -although GPT-3 did have some difficulty with the question “how many eyes does a horse have?”. Meanwhile, The Guardian ‘commissioned’ an op-ed from GPT-3.

This Methods Workshop will explore the generation of ‘synthetic’ texts through presentations, discussion and demonstrations of text generation techniques which participants will be encouraged to try out for themselves during the sessions. We will also report back from the Ghost Fictions Guided Project, organised by Cambridge Digital Humanities Learning Programme in October and November this year. The project looks at how ideas about the distinction between ‘fact’, ‘fiction’ and ‘nonfiction’ are shaping the reception of text generation methods and aims to stimulate deeper critical engagement with machine learning by humanities researchers.

Prior knowledge of programming, computer science or Machine Learning is not required. In order to try out the text generation techniques demonstrated during the course you will need access to Google Drive (accessible via Raven login for University of Cambridge users).

Automated writing in the age of Machine Learning new (2 of 2) Finished 14:00 - 15:30 Cambridge Digital Humanities Online

Computer programmes which predict the likely next words in sentences are a familiar part of everyday life for billions of people who encounter them in auto-complete tools for search engines and the predictive keyboards used by mobile phones and word processing software. These tools rely on “language models” developed by researchers in fields such as natural language processing (NLP) and information retrieval which assign probabilities to words in a sequence based on a specific set of “training data” (in this case a collection of texts where the frequencies of word pairings or three-word phrases have been calculated in advance).

Recent developments in machine learning have led to the creation of general language models trained on extremely large datasets which can now produce ‘synthetic’ texts, answer questions, summarise information without the need for lengthy or costly processes of training for each new task. The difficulties in distinguishing the outputs of these language models from texts written by humans has provoked widespread interest in the media. Researchers have experimented with prompting GPT-3, a language model developed by OpenAI to write short stories, answer philosophical questions and apparently propose potential medical treatments -although GPT-3 did have some difficulty with the question “how many eyes does a horse have?”. Meanwhile, The Guardian ‘commissioned’ an op-ed from GPT-3.

This Methods Workshop will explore the generation of ‘synthetic’ texts through presentations, discussion and demonstrations of text generation techniques which participants will be encouraged to try out for themselves during the sessions. We will also report back from the Ghost Fictions Guided Project, organised by Cambridge Digital Humanities Learning Programme in October and November this year. The project looks at how ideas about the distinction between ‘fact’, ‘fiction’ and ‘nonfiction’ are shaping the reception of text generation methods and aims to stimulate deeper critical engagement with machine learning by humanities researchers.

Prior knowledge of programming, computer science or Machine Learning is not required. In order to try out the text generation techniques demonstrated during the course you will need access to Google Drive (accessible via Raven login for University of Cambridge users).

January 2021

Mon 18
Methods Workshop: TEI workshop new (1 of 2) Finished 10:00 - 11:30 Cambridge Digital Humanities Online

The TEI (Text Encoding Initiative https://tei-c.org/) is a standard for the transcription and description of text bearing objects, and is very widely used in the digital humanities – from digital editions and manuscript catalogues to text mining and linguistic analysis. This course will take you through the basics of the TEI – what it is and what it can be used for – with a particular focus on uses in research, paths to publication (both web and print) and the use of TEI documents as a dataset for analysis. There will be a chance to create some TEI yourself as well as looking at existing projects and examples. The course will take place over two sessions a week apart – with an introductory taught session, then a chance to work on TEI records yourself, followed by a review and discussion session.

Mon 25
Methods Workshop: TEI workshop new (2 of 2) Finished 10:00 - 11:30 Cambridge Digital Humanities Online

The TEI (Text Encoding Initiative https://tei-c.org/) is a standard for the transcription and description of text bearing objects, and is very widely used in the digital humanities – from digital editions and manuscript catalogues to text mining and linguistic analysis. This course will take you through the basics of the TEI – what it is and what it can be used for – with a particular focus on uses in research, paths to publication (both web and print) and the use of TEI documents as a dataset for analysis. There will be a chance to create some TEI yourself as well as looking at existing projects and examples. The course will take place over two sessions a week apart – with an introductory taught session, then a chance to work on TEI records yourself, followed by a review and discussion session.

Tue 26
Privacy, information security and consent: a guide for researchers new Finished 10:00 - 11:00 Cambridge Digital Humanities Online

This CDH Basics session will see discussion on how to assess the impact of relevant legal frameworks, including data protection, intellectual property and media law, on your digital research project and consider what approach researchers should take to the terms of service of third-party digital platforms. We will explore the challenge of informed consent in a highly-networked world and look at a range of strategies for dealing with this problem.

February 2021

Mon 1
Interaction with Machine Learning new (1 of 4) In progress 10:00 - 11:30 Cambridge Digital Humanities Online

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
Doing Qualitative Research Online new (1 of 2) Finished 14:00 - 15:00 Cambridge Digital Humanities Online

What happens to practices of qualitative research when interactions between researcher and research subject are largely mediated? From observations of users’ interactions on social media platforms, to interviews conducted through WhatsApp or Skype, digital communications offer both opportunities and challenges for qualitative research in a wide range of disciplines across the Social Sciences and Humanities. This methods workshop will explore a wide range of topics including:

  • Establishing trust and credibility
  • Engaging with digital gatekeepers
  • Navigating blurred boundaries between ‘private’ and ‘public’
  • Re-conceptualising ‘researchers’, the ‘research field’ and ‘ research subjects’
  • Identity, anonymity and visibility - implications for research practice
  • Mitigation strategies: from data parsimony to creative obfuscation
  • Self-care for researchers in online research
  • Embedding ethical research practice across the project lifecycle

The workshop will take place over two sessions, an introductory seminar and discussion led by Dr Anne Alexander on 1 February, after which participants will be asked to complete a short reflective piece of work assessing their own research design and identifying areas where they feel they need further help and advice. The second session on 8 February will be participant led including small group and plenary discussions exploring strategies for dealing with challenges identified by participants.

Participants should set aside around 1 hour between the two sessions to complete and submit their self-assessment.

Participants are strongly encouraged to attend the CDH Basics session Privacy, information security and consent: a guide for researchers with Dr Anne Alexander on 26 January in advance of the Methods Workshop.