Live Behind data and algorithms

2022-06-16 10:26:04 CEST

Data and algorithms has been on the agenda for some time with studies of biased systems in terms of gender ethnicity and now also age. There is still a need for a socio-cultural approach to research on data and algorithms, by focusing on the actors and their culture(s) behind these technologies. Engineered by humans, data and algorithms embody rules, ideals and imaginations. They are encoded with human intentions that may or may not be fulfilled. Studying humans, logics and culture behind data and algorithms is therefore pivotal if we intend to have an informed discussion of power, and shifting relations of power, in contemporary data societies. In this seminar we therefore gather researchers exploring questions such as what logic, or combination of logics, informs the practices of designing and programming algorithms. And how the data that these algorithms base their calculation, is constructed?

Chair: Jakob Svensson

Speakers:

Janet Abbate
From Brain to Algorithm: The Politics of Metaphors For Automated Thought

Mike Ananny
Seeing Like an Algorithmic Error: How do algorithms make mistakes and why do they matter?

Elizabeth van Couveing
Platform Time: A Critique of Temporal Quality Criteria in Information Retreiva

Sara Suarez Gonzalo
Data domination: the effects of mass surveillance in neo-republican perspective

Anne Kaun
On robot colleagues and software stories: Cultural Techniques of knowing and unknowing the algorithm

Ulrike Klinger
The Power of Code: Women and the Making of the Digital World

Itzelle Aurora Medina Perea
Patterns in Practice – beliefs, values and feelings in practitioners’ engagements with data mining for drug discovery

Rivka Ribat
Materializing Privacy in Local and Global Developer Communities

Fernanda R. Rosa
Code Ethnography: An Application to the Border Gateway Protocol (BGP)

Andrea Rosales
Facing the ethical controversies of programmers.

Minna Ruckenstein
The feel of algorithms

Julia Velkova
Data centers and cloud ruinations: infrastructural frictions at the backends of datafication

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