Kate Crawford

Bio: Kate Crawford is an academic researcher from Microsoft. The author has contributed to research in topics: Social media & Big data. The author has an hindex of 36, co-authored 92 publications receiving 9547 citations. Previous affiliations of Kate Crawford include University of New South Wales & University of Sydney.

Critical questions for big data

Abstract: 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 costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people. Significant questions emerge. Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements? Or will it be used to track protesters and suppress speech? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means? Given the rise of Big Data as a socio-tech...

Datasheets for Datasets

Abstract: The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every component, no matter how simple or complex, is accompanied with a datasheet that describes its operating characteristics, test results, recommended uses, and other information. By analogy, we propose that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses, and so on. Datasheets for datasets will facilitate better communication between dataset creators and dataset consumers, and encourage the machine learning community to prioritize transparency and accountability.

Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability

Abstract: Models for understanding and holding systems accountable have long rested upon ideals and logics of transparency. Being able to see a system is sometimes equated with being able to know how it work...

Six Provocations for Big Data

Abstract: 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 costs of analyzing information from Twitter, Google, Verizon, 23andMe, Facebook, Wikipedia, and every space where large groups of people leave digital traces and deposit data. Significant questions emerge. Will large-scale analysis of DNA help cure diseases? Or will it usher in a new wave of medical inequality? Will data analytics help make people’s access to information more efficient and effective? Or will it be used to track protesters in the streets of major cities? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means? Some or all of the above?This essay offers six provocations that we hope can spark conversations about the issues of Big Data. Given the rise of Big Data as both a phenomenon and a methodological persuasion, we believe that it is time to start critically interrogating this phenomenon, its assumptions, and its biases.(This paper was presented at Oxford Internet Institute’s “A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society” on September 21, 2011.)

Following you: Disciplines of listening in social media

Abstract: This paper develops the concept of listening as a metaphor for paying attention online. Pejorative terms such as ‘lurking’ have failed to capture much detail about the experience of presence online. Instead, much online media research has focused on ‘having a voice’, be it in blogs, wikis, social media, or discussion lists. The metaphor of listening can offer a productive way to analyse the forms of online engagement that have previously been overlooked, while also allowing a deeper consideration of the emerging disciplines of online attention. Social media are the focus of this paper, and in particular, how these platforms are changing the configurations of the ideal listening subject. Three modes of online listening are discussed: background listening, reciprocal listening, and delegated listening; Twitter provides a case study for how these modes are experienced and performed by individuals, politicians and corporations.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

Experience and Education.

Abstract: Preparing the books to read every day is enjoyable for many people. However, there are still many people who also don't like reading. This is a problem. But, when you can support others to start reading, it will be better. One of the books that can be recommended for new readers is experience and education. This book is not kind of difficult book to read. It can be read and understand by the new readers.

The archaeology of knowledge

Abstract: We may not be able to make you love reading, but archaeology of knowledge will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In this case, more books you read more knowledge you know, but it can mean also the bore is full.

Critical questions for big data

Abstract: 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 costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people. Significant questions emerge. Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements? Or will it be used to track protesters and suppress speech? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means? Given the rise of Big Data as a socio-tech...