| Description |
1 online resource (1 volume) |
| Summary |
As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C's) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today. |
| Subject |
Data mining -- Moral and ethical aspects.
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Big data.
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Machine learning.
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Quantitative research.
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Exploration de données (Informatique) -- Aspect moral. |
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Données volumineuses. |
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Apprentissage automatique. |
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Recherche quantitative. |
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Big data |
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Machine learning |
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Quantitative research |
| Added Author |
Mason, Hilary, author.
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Patil, DJ (Dhanurjay), author.
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