Photo of Katherine Harrison

Katherine Harrison

Associate Professor, Docent

How do material technical constraints and social norms intersect in the design and development of digital media technologies? Exploring how our practices, assumptions and norms shape these technologies, and the consequences for lives and bodies.

How are bodily and identity norms re/produced in the code and content of digital media technologies?

Does it matter if you don’t find your sexual preferences represented in a dropdown menu on a dating site? What happens when decisions about what constitutes “valid” data to be captured are based on technical limits to processing power or standardized algorithms? How might social or organizational assumptions about use and users exclude some people in the development of innovative digital technologies?

In my research I combine my personal fascination with digital media technologies with my political commitment to examining critically the impact of such technologies on bodies and lives. My work sits at the intersection of Science & Technology Studies, media studies, and feminist theory, bringing critical perspectives on normativity and knowledge production to studies of different digital media technologies.

Smart cities and companion (ro)bots are just two areas where technological development has important implications for recognition and livability. Technologies like these make big promises, but also have big consequences for how we can all live our lives. I develop material-discursive approaches rooted in interdisciplinary collaborations in order to explore these consequences.

New research projects

I am currently engaged in two research projects that build on and significantly develop my previous experience and knowledge:

Operationalising ethics for AI: translation, implementation and accountability challenges

The most acute issues in AI development today can be mapped to three “gaps” in negotiating ethical and moral considerations: translation, implementation and accountability. Mired within the translation gap many technologists struggle to recognize whether and how something may be or may become an ethical issue. Even where these issues are recognized and discussed as potentially ethically problematic, the implementation gap makes it difficult to address them in practice and in code because there is a proliferation of tools but few clear routes to action. Finally, the problem of the accountability gap manifests in a lack of a clear accountability framework within companies and organizations producing technologies as well as among the stakeholders commissioning, implementing and using it. Operationalising ethics for AI brings together an experienced interdisciplinary team to address these three gaps.

Financed by the Marianne and Marcus Wallenberg Foundation

Robotic care practices: Creating trust, empathy and accountability in human-robot encounters

No longer a science fiction, robots are starting to enter our daily lives, performing different kinds of care for us and our children. This project examines attempts to program educational robots and recruitment assistant robots to produce relations of trust, empathy and accountability with humans. These relations are necessary for forming good social interactions with humans, upon which the successful long term adoption of these cognitive companions depends. Understanding how trust, empathy and accountability are created in these interactions thus represents both cutting-edge research and an important part of the perceived solution to a global shortage of workers prepared to carry out the time and labour intensive work of care. This project brings together developers from the Social Robotics Lab, Uppsala University, FurHat company in Stockholm, and social sciences researchers from Linköping University with an international advisory board specialised in human-robot interactions. Through ethnography, developer interviews and video analysis of intra-actions with robots, we critically interrogate a tension between emotion and accountability in human-robot relations that stems from fundamentally different understandings of emotions, and which has wide-ranging consequences. At regular joint learning seminars during this four year project we will work together to develop nuanced, interdisciplinary understandings of emotion that can refine practical applications of robotic care.

Financed by the Marianne and Marcus Wallenberg Foundation

Short lecture: How to teach a robot to care?

Katherine Harrison, senior lecturer in gender studies, talks about three different robots that we may encounter in society: the teaching robot in school, the impartial interviewer and the robot in elderly care. Recorded on October 21, 2020 at Linköping University.


Research projects and networks

Completed projects

Behind the Science: the invisible work of data management in Big Science

Some of the largest quantities of data produced in today’s data-dominated world occur as the result of experiments taking place at Big Science facilities. These are facilities where cutting-edge scientific discoveries take place, changing our understandings of the universe and promising the answers to some of society's most pressing problems. The data produced during experiments at these facilities is the basis for such scientific breakthroughs. However, both historically and today, Big Science has tended to ignore how the collection, processing and storage of experimental data at these facilities shapes this new knowledge.

The production of high-quality, reliable data is fundamental to the advancement of scientific knowledge, but the nature of data collection and management is changing. Indeed, the very nature of Big Science is changing.

This book tells the story of a unique research journey following the people responsible for designing and implementing data management at a new Big Science facility, the European Spallation Source (ESS) in Lund, Sweden. It addresses a gap in the scholarly literature by highlighting the role of data management within the broader landscape of changing scientific experimentation. It draws on insights from critical data studies to understand how this data is framed by the context in which it is conceived of and generated.

Funded by Marcus and Amalia Wallenberg Foundation, and Riksbankens Jubileumsfond.

Latest publications


Katherine Harrison, Giulia Perugia, Filipa Correia, Kavyaa Somasundaram, Sanne van Waveren, Ana Paiva, Amy Loutfi (2023) The Imperfectly Relatable Robot: An Interdisciplinary Workshop on the Role of Failure in HRI COMPANION OF THE ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, HRI 2023, p. 917-919 Continue to DOI
Katie Winkle, Donald McMillan, Maria Arnelid, Madeline Balaam, Katherine Harrison, Ericka Johnson, Iolanda Leite (2023) Feminist Human-Robot Interaction: Disentangling Power, Principles and Practice for Better, More Ethical HRI Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, p. 72-82 Continue to DOI
Katherine Harrison, Ericka Johnson (2023) Affective Corners as a Problematic for Design Interactions ACM Transactions on Human-Robot Interaction, Vol. 12, Article 41 Continue to DOI


Maria Arnelid, Katherine Harrison, Ericka Johnson (2022) What Does It Mean to Measure a Smile?: Assigning numerical values to emotions Valuation Studies, Vol. 9, p. 79-107 Continue to DOI
Desirée Enlund, Katherine Harrison, Rasmus Ringdahl, Ahmet Börütecene, Jonas Löwgren, Vangelis Angelakis (2022) The role of sensors in the production of smart city spaces Big Data and Society, Vol. 9, Article 20539517221110218 Continue to DOI