Kate Crawford's research while affiliated with New York University and other places

Publications (14)

Chapter
The use of big data research methods has grown tremendously in both academia and industry. One of the most fundamental rules of responsible big data research is the steadfast recognition that most data represent or impact people. For some projects, sharing data is an expectation of the human participants involved and thus a key part of ethical rese...
Preprint
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NeurIPS 2020 requested that research paper submissions include impact statements on 'potential nefarious uses and the consequences of failure.' When researching, designing, and implementing systems, a key challenge to anticipating risks, however, is to overcome what Clarke (1962) called 'failures of imagination.' The growing research on bias, fairn...
Article
Currently there is no standard way to identify how a dataset was created, and what characteristics, motivations, and potential skews it represents. To begin to address this issue, we propose the concept of a datasheet for datasets, a short document to accompany public datasets, commercial APIs, and pretrained models. The goal of this proposal is to...
Article
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The use of big data research methods has grown tremendously over the past five years in both academia and industry. As the size and complexity of available datasets has grown, so too have the ethical questions raised by big data research. These questions become increasingly urgent as data and research agendas move well beyond those typical of the c...
Preprint
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The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and many others are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions. Diverse groups argue about the potential benefits and cost...
Article
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There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such disconti...
Article
We conducted a study of Australia’s media content regulation system in the context of three major Federal Government reviews of media law and policy (Australian Law Reform Commission, 2012; Department of Broadband, Communications and the Digital Economy, 2012; Finkelstein, 2012). The current system understands governance as the work of government a...
Article
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In this paper we explore development, gender and technology through a focus on mobile phones and examples of their everyday use by rural women in India. We introduce ways in which technologies might be thought about in terms of “meaningful mobilities” by discussing attachments, structures of labour, agency and specifically how mobiles are an active...
Article
Full-text available
The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and other scholars are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions. Diverse groups argue about the potential benefits and c...
Article
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Elközelgett a Big Data, az adatrengeteg kora. A számítástudósok, fizikusok, közgazdászok, matematikusok, politológusok, bioinformatikusok, szociológusok és más tudósok fennszóval követelik, hogy az embereket, dolgokat és ezek kapcsolatait leíró, folyvást termelődő hatalmas adatmennyiséggel dolgozhassanak. Fontos kérdések formálódnak meg. Hozzásegít...
Article
Full-text available
The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and other scholars are clamouring for access to the massive quantities of information produced by and about people, things, and their interactions. Significant questions emerge. Will large-scale search...
Article
Full-text available
The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and many others are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions. Diverse groups argue about the potential benefits and cost...

Citations

... On the one hand, the public acceptance and individual use of CTA may strengthen the factual forms of social cohesion that exist in a collective (67) or strengthen factors that are elementary for them (72,82), it may prevent negative consequences for forms of social cohesion that would have happened if CTA were not accepted and used (66), or open up possibilities for reimagining old and establishing new relationships (92). On the other hand, the acceptance and use of CTA may also have a negative impact on a society's forms of social cohesion: by threatening or undermining the forms of social cohesion that exist in a collective (83), by weakening factors that are elementary for them (75,77,(80)(81)(82)86), by reinforcing existing discriminations and worsening the situation for specific groups of people (38,75,90,91), or by using resources for the development and implementation of CTA that would have had more positive effects on the community if used in an alternative way (88,89). ...
... The ever increasing amount of big data in science, engineering, and society, including meteorological, hydrological, ecological, environmental, as well as various kinds of biomedical, manufacturing, e-commerce, and government management data, has fueled enormous optimism among researchers, entrepreneurs, government officials, the media, and the general public [1,2]. It is now hoped that by recording and analyzing the errors of all the components of a sophisticated machine, one can quickly diagnose and then fix its malfunctioning. ...
... The explanations include, for example, descriptions of training data, its machine learning model's training and prediction processes, and the model's performance indicators [53,54,66,74]. Practitioner-facing tools (e.g., Microsoft's HAX "responsible AI " toolkit, data sheets [24], model cards [46]) further boosted this approach's real-world impact. Experiments showed that AI explanations improved clinicians' satisfaction with DSTs and increased the likelihood of them taking the AI's advice [9,42,51,60]. ...
... To protect the identity of the individuals posting the videos and those commenting on videos, web addresses and channel names are not reported here (see, e.g. Zook et al., 2017). ...
... This demand to anticipate research impacts is not new in the modern academyespecially in the biomedical and social sciences, where Institutional Review Board (IRB) processes for research involving human subjects have been in place for decades (Abbott & Grady, 2011;Grady, 2015). However, the novel human scale, breadth, and reach of CSS research, as well as the new (and often subtler) range of potential harms it poses to impacted individuals, communities, and the biosphere, call into question the adequacy of conventional IRB processes (Metcalf & Crawford, 2016). While the latter have been praised a necessary step forward in protecting the physical, mental, and moral integrity of human research subjects, building public trust in science, and institutionalising needed mechanisms for ethical oversight (Resnik, 2018), critics have also highlighted their unreliability, superficiality, narrowness, and inapplicability to the new set of information hazards posed by the processing of aggregated big data (Prunkl et al., 2021;Raymond, 2019). ...
... The proprietary nature of much of the data used in CSS is important because it determines what information becomes available and to whom and what kind of analysis and intervention it can inform. It also, as predicted more than a decade ago, creates hierarchies amongst researchers and institutions, since access to data is a privilege to be negotiated (boyd & Crawford, 2012). This has meant that so far the CSS field has been mainly populated by high-status researchers from wellfunded institutions in high-income countries, who also tend to be male, white and connected to the well-funded academic disciplines of computer science, quantitative sociology and statistics or to policy interests that tend towards security, population management and economic development. ...
... The pivotal use of the mobile phone by women has continued to identify it primarily as a work tool. Household management, organization, caring, emotional support and expression, microcoordination (Ling, 2004), and remote mothering or grandmothering, have passed through the mobile phone both in industrialized countries (Fortunati & Taipale, 2012; Frizzo-Barker & Chow-White, 2012; L. F. Rakow & Navarro, 1993;Sawchuk & Crow, 2012) and also in developing countries (Stark, 2020;Tacchi et al., 2012). However, the mobile phone has also been a means of undoing gender, strengthening women's control of communication, reinforcing their personal autonomy and freedom, including at the political level (Stark, 2020), and making mobile housework and care visible in public space (Hjorth & Lim, 2012). ...
... In the following sections, this report will offer an overview of several digital governance mechanisms within and outside Europe. Grounded in the existing academic literature on technology governance (Brown and Marsden 2013;Crawford and Lumby 2013;Fountain 2007;Wagner 2016) as well as in wider theories of governance (Ackerman 2004;Barnett and Duvall 2005), the report seeks to improve our understanding of how the governance of digitalization processes currently functions, and how it might function in future. To achieve this goal, we will focus on a set of four examples chosen to illustrate the challenges of implementation and compliance in the digital age: ...
... According to McQuillan, we need to look beyond the questioning of data practices (Boyd and Crawford 2011) and examine "the nature of the material-political apparatus that connects data to decision-making and governance" (McQuillan 2015, p. 565). This material-political apparatus is "undergoing a significant shift in the system of relations at several levels: in architectural forms (forms of database structures), administrative measures (as algorithms), regulation (as algorithmic regulation) and laws (as states of exception)" (2015, p. 566). ...
... An example of a source of data widely used by those who intend on identifying social patterns through Big Data is twitter. As Boyd and Crawford (2012) notice: ...