Reframing ADM: concepts, Values, Alternatives

Many of the popular, technical, industry and government discourses of automation use the future tense. They simultaneously imagine and create a world in which the promises of technology are seamlessly realized in a frictionless world. Scholars of automation and digital media – from a wide range of (inter)disciplinary backgrounds – know differently. To paraphrase Raymond Williams (1921-1988), technologies are always introduced into old social forms/context, themselves populated by older technologies.

In this lecture, I will examine how we, as scholars of automation and digitalisation, can contribute constructively to the discourses, metaphors and imaginations that shape our technological cultures. For those less familiar with US popular and high culture, the title will be explained. 

Sally Wyatt is Professor of Digital Cultures at Maastricht University in the Netherlands. She is also one of the three national coordinators of the Dutch Digital Society Programme, a collaboration between all Dutch universities. 

Session 1: Dissecting AI Myths, Metaphors and Ideals – and moving on

• Stop and Start: How does automated decision making becomes accepted? The case of the traffic light 1912-1940 (David Moats, University of Helsinki)
• “Mobile information society” - techno-scientific imaginaries of the 90s’ in retrospect (Mika Pantzar, University of Helsinki)
• Language of Algorithms in the EU: Agency and Metaphors in Communication around Artificial Intelligence (Kaisla Kajava, Aalto University)
• The Commercialisation of Participation: Is FemTech a ‘win-win’ for public engagement and commercial interests in AI? (Michael Strange and Jason Tucker, Malmö University)

Session 2: Reclaiming Futures for Public Sector Automation

• Public service algorithm – imagining better media? (Kaarina Nikunen, Tampere University)
• Automation as an empty signifier: Interrogating automated work futures and their non-technologies (Martin Berg, Malmö University)
• Constraining context: Towards an actionable critique of public administration datafication (Lisa Reutter, Norwegian University of Science and Technology)
• Public Sector AI Governance: Discrimination Awareness in Swedish Public AI Development (Stefan Larsson, Charlotte Högberg, and Anne Kaun)

Break

Keynote by Malte Ziewitz : The Algorithmic Underground: Rethinking Due Process in a Data-Driven World

When people feel mistreated by an automated system, their options tend to be quite limited. For one, it can be hard to know when computationally generated judgments are at play. A loan denied, a job not offered, or a benefit reduced does not usually come with a detailed explanation. And even then, it can be virtually impossible to find an avenue for formal recourse—or what legal scholars call due process, i.e., the right not to be judged arbitrarily and to appeal an authoritative judgment. Instead, we have been seeing the emergence of a range of underground economies that promise unofficial forms of recourse and relief: self-help books that vow to change their readers’ lives with actionable strategies, YouTube videos that narrate tips and tricks for data subjects, and a new cast of marketing professionals who claim to optimize and curate data-driven reputations. In this talk, I shall take a closer look at this new “algorithmic underground” and explore the changing status of due process in a data-driven world. Drawing on ethnographic fieldwork with credit scoring systems, web search engines, and automated hiring platforms in the UK and the U.S., I examine the stakes of living in the shadow of the system and ask what it may take to rethink our analytic sensibilities along the way.

Malte Ziewitz is Associate Professor at the Department of Science & Technology Studies at Cornell University. An ethnographer and sociologist, he studies the changing role of governance and regulation in, of, and through digitally networked environments. His recent work has looked at the lived experience of credit scoring subjects, the search engine optimization (SEO) industry, and attempts at algorithmic regulation. At Cornell, he directs the Digital Due Process Clinic, a clinical research program that helps ordinary people cope with, understand, and challenge automated decision systems. 

Dinner in town TBA

Keynote by Helen Kennedy: Everyday Data Solidarities

Responding to the call of this conference to think about alternative conceptualisations of ADM and its constituent parts (data, AI, ML, algorithms and so on), in this presentation, I will propose that we can conceive of public perceptions of these technologies in terms of ‘everyday data solidarities’. I draw on empirical research from Living With Data and other projects, on which collaborators and I have found widespread concern about the potential for data-driven and automated systems to have negative consequences for people from disadvantaged and minority groups. We have found this, in part, because of our own alternative valuing and conceiving of ‘the public’ not as one, singular public, but as ‘diverse publics’. Hence, our research participants appear to be aware that data-driven systems and ADM can reinforce inequalities, and that some are more likely to do so than others. This awareness informs how people imagine data-driven and ADM futures, how they think about public-private partnerships in the development of these systems, and how they adapt to them. I argue that the concept of ‘everyday data solidarities’ helps us counter dominant discourses of publics as not knowing or caring about the data-AI-ML-ADM complex. 

Helen Kennedy is Professor of Digital Society at the University of Sheffield where she directs the Living With Data programme of research. She is interested in how digital developments are experienced and how these experiences can inform the work of digital practitioners in ways that overcome inequalities. She researches perceptions of and feelings about datafication and the possibility of data-related agency. She is interested in things like trust, equity, justice, and what ‘the digital good’ might look like. Other current projects include Generic Visuals in the News and Patterns in Practice: cultures of data mining in science, education and the arts. Recent books include Data Visualization in Society (Amsterdam University Press, 2020) and Post, Mine, Repeat: social media data mining becomes ordinary (Palgrave MacMillan, 2016). See full list of publications.

Session 3: Getting Concrete: Practices of Building and Maintaining ADM

• The humans doing the work: Re-humanizing algorithmic systems (Tuukka Lehtiniemi, University of Helsinki)
• Organizational enactments of the ethically “good” algorithmic decision-support system (Ida Schrøder and Helene Ratner, Aarhus University)
• Achieving intelligent material management: The case of the Helsinki public library (Juho Pääkkönen, University of Helsinki & Aalto University)
• One size does not fit all: Conceptualizing AI literacy for public sector workers (Marta Choroszewicz, University of Eastern Finland)
• Citizens’ digital afterlives in machine learning systems: Orchestrating the inclusion and exclusion of citizens’ data in the development of predictive algorithms for public administration
• (Helene Friis Ratner, Aarhus University & Nanna Bonde Thylstrup, Copenhagen Business School)

Session 4: Diving into the Human Experience for Alternatives

• Seeking breathing space amidst breathless epistemologies (Minna Ruckenstein, University of Helsinki)
• Scales of Human-Machine Relations: Reframing Trust in ADM (Sonja Trifuljesko, University of Helsinki)
• Between fragility and institutionalization?: ADM in the aftermath of socio-technical experiments
• (Julia Velkova, Linköping University)
• Caring for technology, caring for the body: anticipatory practices and algorithmic autonomy in health-related tracking (Sne Scott Hansen and Henriette Langstrup, University of Copenhagen)
• Human capabilities for a good datafied life? (Stine Lomborg & Signe Sophus Lai, University of Copenhagen)