Search

This article discusses fairness in artificial intelligence (AI) based policing procedures using facial recognition as an example. Algorithmic decisions based on discriminatory dynamics can (re)produce and automate injustice. AI fairness here concerns not only the creation and sharing of datasets or the training of models but also how systems are deployed in the real world. Quantifying fairness can distract rom how discrimination and oppression translate concretely into social phenomena. Integrative approaches can help actively incorporate ethical, legal, social, and economic factors into technology development to more holistically assess the consequences of deployment through continuous interdisciplinary collaboration. Dieser Beitrag diskutiert Fairness in auf künstlicher Intelligenz (KI) basierenden Verfahren der Polizeiarbeit anhand des Beispiels der Gesichtserkennung. Algorithmische Entscheidungen, die auf gesellschaftlichen Diskriminierungsdynamiken beruhen, können Ungerechtigkeiten (re-)produzieren und automatisieren. KI-Fairness betrifft dabei nicht nur die Erstellung und das Teilen von Datensätzen oder das Training von Modellen, sondern auch die Art des Systemeinsatzes in der Realwelt. Die Quantifizierung von Fairness kann davon ablenken, wie Diskriminierung und Unterdrückung sich konkret als soziale Phänomene niederschlagen. Integrative Ansätze können hier dazu beitragen, durch kontinuierliche interdisziplinäre Kollaboration ethische, rechtliche, soziale und wirtschaftliche Faktoren aktiv in die Technikentwicklung einzubeziehen und die Folgen des Einsatzes ganzheitlicher einzuschätzen.

In this article, we reconsider elements of Agre’s critical technical practice approach ( Agre, 1997 ) for critical technical practice approach for reflexive artificial intelligence (AI) research and explore ways and expansions to make it productive for an operationalization in contemporary data science. Drawing on Jörg Niewöhner’s co-laboration approach, we show how frictions within interdisciplinary work can be made productive for reflection. We then show how software development environments can be repurposed to infrastructure reflexivities and to make co-laborative engagement with AI-related technology possible and productive. We document our own co-laborative engagement with machine learning and highlight three exemplary critical technical practices that emerged out of the co-laboration: negotiating comparabilities, shifting contextual attention and challenging similarity and difference. We finally wrap up the conceptual and empirical elements and propose Reflexive Data Science (RDS) as a methodology for co-laborative engagement and infrastructured reflexivities in contemporary AI-related research. We come back to Agre’s ways of operationalizing reflexivity and introduce the building blocks of RDS: (1) organizing encounters of social contestation, (2) infrastructuring a network of anchoring devices enabling reflection, (3) negotiating timely matters of concern and (4) designing for reflection. With our research, we aim at contributing to the methodological underpinnings of epistemological and social reflection in contemporary AI research.

Building on concepts from Science & Technology Studies, Simon David Hirsbrunner investigates practices and infrastructures of computer modeling and science communication in climate impact research. The book characterizes how scientists calculate future climate risks in computer models and scenarios, but also how they circulate their insights and make them accessible and comprehensible to others. By discussing elements such as infrastructures, visualizations, models, software and data, the chapters show how computational modeling practices are currently changing in light of digital transformations and expectations for an open science. A number of inventive research devices are proposed to capture both the fluidity and viscosity of contemporary digital technology.

The present study aims at evaluating how YouTube users understand, negotiate and appropriate science-related knowledge on YouTube. It is informed by the qualitative analysis of post-video discussions around visual scenarios of sea-level rise (SLR) triggered by climate change. On the one hand, the SLR maps have an exemplary status as contemporary visualizations of climate change risks, beyond traditional image categories such as scientific or popular imagery. YouTube, on the other hand, is a convenient media environment to investigate the situated appropriation of such visual knowledge, considering its increasing relevance as a navigational platform to provide, search, consume and debate science-related information. The paper draws on media practice theory and operationalizes digital methods and qualitative coding informed by Grounded Theory. It characterizes a number of communicative practices of articulated knowledge appropriation regarding climate knowledge. This includes “locating impacts,” “demanding representation,” “envisioning further,” “debating future action,” “relativizing the information,” “challenging the reality of anthropogenic climate change,” “embedding popular narratives,” “attributing to politics,” and “insulting others.” The article then discusses broader questions posed by the comments and related to the appropriation and discursive negotiation of knowledge within online video-sharing platforms. Ambiguity is identified as a major feature within the practice of science-related information retrieval and knowledge appropriation on YouTube. This consideration then serves as an opportunity to reconsider the relationship between information credibility and knowledge appropriation in the age of the digital. Findings suggest that ambiguity of information can have a positive impact on problem definition, future imagination and the discursive negotiation of climate change.

Handelte es sich bei dem Beitrag des Präsidenten der Freien Universität Berlin Günther M. Ziegler “Die Bedeutung der Verlage wandelt sich” wieder nur um ein “Loblied auf “Open Access" als Zukunft des wissenschaftlichen Publizierens”? Diesen Vorwurf jedenfalls machte Wolfgang Sander dem Präsidenten in seinem kurzen Kommentar vom 12. Juni 2019. Doch nicht in jeder Kürze liegt immer auch Würze: Die von Sander vorgetragenen, aber kaum näher begründeten Vorbehalte gegen Open Access sind, wie im Folgenden ausgeführt, nicht stichhaltig. Auf das von Ziegler beschriebene und kritisierte Geschäftsmodell wissenschaftlicher Verlage geht Sander mit keinem Wort ein. Stattdessen werden - wie so oft in der Debatte um Open Access - pauschal die Langzeitarchivierung und die Frage der Publikationskosten als ungelöste oder gar unlösbare Probleme angeführt. Die Autor*innen dieser Erwiderung nehmen im Folgenden zu diesen Fragen Stellung.