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010 a| 2023032900;

020 a| 9780197693025q| (hardback);

020 a| 9780197693032q| (paperback);

020 z| 9780197693056q| (epub);

020 z| 9780197693049;

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050 00 a| QA76.9.D343b| W375 2023;

082 00 a| 006.3/122| 23/eng/20230810;

100 1 a| Washington, Anne L.?| UNAUTHORIZED;

245 10 a| Ethical data scienceh| [electronic resource] :b| prediction in the public interest /c| Anne L. Washington, PhD.;

260 a| New York, NY :b| Oxford University Press,c| [2023];

300 a| 172 pages ;c| 25 cm.;

490 0 a| Oxford technology law and policy;

504 a| Includes bibliographical references and index.;

505 0 a| Prologue: Tracing ethics in the prediction supply chain -- Source : data are people too -- Model : dear validity, advice for wayward algorithms -- Compare : no comparison without representation -- Optimize : data science reasoning -- Learn : for good -- Show us your work or someone gets hurt -- Conclusion: Prediction in the public interest.;

506 a| Available only to authorized users.;

538 a| Mode of access: World Wide Web;

650 0 a| Data miningx| Moral and ethical aspects.=| ^A408868;

650 0 a| Predictive analyticsx| Moral and ethical aspects.?| UNAUTHORIZED;

650 0 a| Machine learningx| Moral and ethical aspects.=| ^A145211;

655 0 a| Electronic books.=| ^A491897;

710 2 a| Oxford University Press.=| ^A636469;

856 40 z| Full text available from Oxford Scholarship Onlineu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Facademic.oup.com%2Fbook%2F55143;

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Ethical data science prediction in the public interest / Anne L. Washington, PhD.

Author/creator	Washington, Anne L.
Other author	Oxford University Press.
Format	Electronic
Publication Info	New York, NY : Oxford University Press, [2023]
Description	172 pages ; 25 cm.
Supplemental Content	Full text available from Oxford Scholarship Online
Subjects	Data mining--Moral and ethical aspects. Predictive analytics--Moral and ethical aspects. Machine learning--Moral and ethical aspects.

Series	Oxford technology law and policy
Contents	Prologue: Tracing ethics in the prediction supply chain -- Source : data are people too -- Model : dear validity, advice for wayward algorithms -- Compare : no comparison without representation -- Optimize : data science reasoning -- Learn : for good -- Show us your work or someone gets hurt -- Conclusion: Prediction in the public interest.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2023032900
ISBN	9780197693025 (hardback)
ISBN	9780197693032 (paperback)
ISBN	(epub)

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Library	Location	Call Number	Status	Item Actions
	Electronic Resources	Access Content Online	✔ Available

Ethical data science prediction in the public interest / Anne L. Washington, PhD.

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