“Nobody Is Ever Alone”: The Use of Social Media Narrative to Include the Viewer in SKAM

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Ways of knowing with data visualizations

Data visualizations combine numeric data with visual representation, and these modes allow them to express certain kinds of knowledge more easily than others. This chapter uses examples of historical data visualizations in order to examine what ways of knowing they privilege. What is the difference between the spatial organization of tools in prehistoric homes and a photograph or bar chart showing information about the same tools, in terms of the kinds of knowledge they enable? How do the systems for gathering and visualizing data during the 18th and 19th centuries shape our understanding of the world? How do data visualizations make us feel that they are objective? How do they shape our ideas of what is possible?publishedVersio

Algorithmic failure as a humanities methodology: Machine learning’s mispredictions identify rich cases for qualitative analysis

This commentary tests a methodology proposed by Munk et al. (2022) for using failed predictions in machine learning as a method to identify ambiguous and rich cases for qualitative analysis. Using a dataset describing actions performed by fictional characters interacting with machine vision technologies in 500 artworks, movies, novels and videogames, I trained a simple machine learning algorithm (using the kNN algorithm in R) to predict whether or not an action was active or passive using only information about the fictional characters. Predictable actions were generally unemotional and unambiguous activities where machine vision technologies were treated as simple tools. Unpredictable actions, that is, actions that the algorithm could not correctly predict, were more ambivalent and emotionally loaded, with more complex power relationships between characters and technologies. The results thus support Munk et al.'s theory that failed predictions can be productively used to identify rich cases for qualitative analysis. This test goes beyond simply replicating Munk et al.'s results by demonstrating that the method can be applied to a broader humanities domain, and that it does not require complex neural networks but can also work with a simpler machine learning algorithm. Further research is needed to develop an understanding of what kinds of data the method is useful for and which kinds of machine learning are most generative. To support this, the R code required to produce the results is included so the test can be replicated. The code can also be reused or adapted to test the method on other datasets.publishedVersio

Machine Vision: How Algorithms are Changing the Way We See the World

Humans have used technology to expand our limited vision for millennia, from the invention of the stone mirror 8,000 years ago to the latest developments in facial recognition and augmented reality. We imagine that technologies will allow us to see more, to see differently and even to see everything. But each of these new ways of seeing carries its own blind spots. In this illuminating book, Jill Walker Rettberg examines the long history of machine vision. Providing an overview of the historical and contemporary uses of machine vision, she unpacks how technologies such as smart surveillance cameras and TikTok filters are changing the way we see the world and one another. By analysing fictional and real-world examples, including art, video games and science fiction, the book shows how machine vision can have very different cultural impacts, fostering both sympathy and community as well as anxiety and fear. Combining ethnographic and critical media studies approaches alongside personal reflections, Machine Vision is an engaging and eye-opening read. It is suitable for students and scholars of digital media studies, science and technology studies, visual studies, digital art and science fiction, as well as for general readers interested in the impact of new technologies on society.publishedVersio

Speculative Interfaces: How Electronic Literature Uses the Interface to Make Us Think about Technology

In a study that traverses more than half a century – going from e-lit precursor Christopher Strachey’s M.U.C. Love Letter Generator (1952) to Michael Joyce’s experimental hypertext afternoon: a story (1990) to Kate Pullinger’s data-driven touchscreen work Breathe (2018) – Rettberg situates experimentation with digital interfaces in a longer tradition of innovation in literary and scholarly production. She also argues for the central importance of such experimentation in the ongoing development of both electronic literature and the digital humanities, suggesting that speculation in the design of digital interfaces can help preserve and extend the interpretative and intuitive aspects of Western literary and scholarly traditions, while also bringing the limitations and exclusions of such knowledge systems into focus.publishedVersio

Seeing Ourselves Through Technology

Cultural and Media Studies, New Media and Digital Media, Media and Cultural Theory, Popular Cultur

The Data Sprint Approach: Exploring the field of Digital Humanities through Amazon’s Application Programming Interface

This paper documents the results of an intensive "data sprint" method for undertaking data and algorithmic work using application programming interfaces (APIs), which took place during the Digital Method Initiative 2013 Winter School at the University of Amsterdam. During this data sprint, we developed a method to map the fields of Digital Humanities and Electronic Literature based on title recommendations from the largest online bookseller, Amazon, by retrieving similar purchased items from the Amazon API. A first step shows the overall Amazon recommendation network for Digital Humanities and allows us to detect clusters, aligned fields and bridging books. In a second step we looked into four country-specific Amazon stores (Amazon.com, Amazon.co.uk, Amazon.fr and Amazon.de) to investigate the specificities of the Digital Humanities in these four countries. The third step is a network of all books suggested for the Electronic Literature field in the four Amazon stores we searched, which offers a comparison to the field of Digital Humanities.publishedVersio

Ask Rosa – The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer

Objective: We aimed at developing a pilot version of an app (Rosa) that can perform digital conversations with breast or ovarian cancer patients about genetic BRCA testing, using chatbot technology, to identify best practices for future patient-focused chatbots. Methods: We chose a commercial chatbot platform and participatory methodology with a team of patient representatives, IT engineers, genetic counselors and clinical geneticists, within a nationwide collaboration. An iterative approach ensured extensive user and formal usability testing during the development process. Results: The development phase lasted for two years until the pilot version was completed in December 2019. The iteration steps disclosed major challenges in the artificial intelligence (AI)-based matching of user provided questions with predefined information in the database, leading initially to high level of fallback answers. We therefore developed strategies to reduce potential language ambiguities (e.g. BRCA1 vs BRCA2) and overcome dialogue confusion. The first prototype contained a database with 500 predefined questions and 67 corresponding predefined answers, while the final version included 2257 predefined questions and 144 predefined answers. Despite the limited AI functionality of the chatbot, the testing revealed that the users liked the layout and found the chatbot trustworthy and reader friendly. Conclusions: Building a health chatbot is challenging, expensive and time consuming with today’s technology. The users had a positive attitude to the chatbot, and would use it in a real life setting, if given to them by health care personnel. Practice implications: We here present a framework for future health chatbot initiatives. The participatory methodology in combination with an iterative approach ensured that the patient perspective was incorporated at every level of the development process. We strongly recommend this approach in patient-centered health innovations.publishedVersio

Mining the Knowledge Base: Exploring Methodologies for Analysing the Field of Electronic Literature

This is a work-in-progress report from an exploration of the intersection between the fairly conventional digital humanities method of creating a database - specifically, the ELMCIP Electronic Literature Knowledge Base (http://elmcip.net/knowledgebase) and the digital methods strategy of directly analysing online, digital content. We are testing out different methods of analysing data about conference series harvested from the Knowledge Base, using social network analysis to visualise the connections between people, events and works and tag analysis