ISBN: 9780262055703 - algorithmic realism: data science practices to promote social justice (30 resultados)

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Paperback. Condición: new. Paperback. A bold new vision for data science-and a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world? What practices should data scientists follow to achieve this goal?In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"-the steps that characterize the algorithm development process-he offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Taschenbuch. Condición: Neu. Neuware -A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. 282 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. 282 pp. Englisch.…

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Taschenbuch. Condición: Neu. Neuware -A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world.…

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Taschenbuch. Condición: Neu. Neuware - A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world.…

Condición: New. Ben Green is Assistant Professor of Information and Public Policy at the University of Michigan and a Faculty Associate at Harvard&rsquos Berkman Klein Center for Internet &amp Society. He is the author of The Smart Enough City (MIT Press).A.

Paperback. Condición: new. Paperback. A bold new vision for data science-and a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world? What practices should data scientists follow to achieve this goal?In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"-the steps that characterize the algorithm development process-he offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Softcover/Taschenbuch. Condición: Neu. A bold new vision for data science?and a practical, step-by-step guide for how data scientists can contribute to social justice. The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world? What practices should data scientists follow to achieve this goal? In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the ?data science workflow??the steps that characterize the algorithm development process?he offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science?s potential to foster a more equitable world. Sprache: Englisch Gewicht in Gramm: 352.…

Taschenbuch. Condición: Neu. Neuware -A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world.Easy Access System Europe Oü, 16879218, EU GPSR Authorised Representative, 282 pp. Englisch.…

Paperback. Condición: new. Paperback. A bold new vision for data science-and a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world? What practices should data scientists follow to achieve this goal?In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"-the steps that characterize the algorithm development process-he offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condición: Neu. Algorithmic Realism | Data Science Practices to Promote Social Justice | Ben Green | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2026 | The MIT Press | EAN 9780262055703 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware -A bold new vision for data scienceand a practical, step-by-step guide for how data scientists can contribute to social justice.The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good, algorithms regularly produce injustice in practice. Given these persistent harms, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world What practices should data scientists follow to achieve this goal In Algorithmic Realism, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the "data science workflow"the steps that characterize the algorithm development processhe offers a practical, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions, the book reveals a vision for a renewed, but realistic, optimism about data science's potential to foster a more equitable world. 282 pp. Englisch.…