Category: Code of Ethics
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4 Principles of Responsible AI and Best Practices to Adopt Them
Data Access, Data Classification, Data Encryption, Fairness, Representation in Training Datasets, Responsible Artificial Intelligence, Synthetic Data, Training Data, Transparency, Usage RestrictionsAuthor: Cem Dilmegani; Publisher: AI Multiple; Publication Year: 2022. The following article explores 4 principles for responsible AI design and recommends best practices. The 4 principles, along with best practices, include: 1). achieving fairness by…
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Bias in AI: What it is, Types, Examples & 6 Ways to Fix It in 2022
Artificial Intelligence, Automation, Debiasing, Decision-Making, Diversify, Human-Driven Processes, Multidisciplinary, Representation in Training Datasets, Third-Party, Training Data, TransparencyAuthor: Cem Dilmegani; Publisher: AI Multiple; Publication Year: 2022. The following article describes how in the imperfect world, AI can’t be expected to be completely unbiased. However, there are various ways to minimize bias by…
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Data Feminism
Binaries, Context, Data Collection, Hierarchies, Indigenous Peoples, Intersectionality, Power Distribution, Power StructuresAuthor: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. In the following book D’Ignazio and Klein present a new lens for thinking about data science and ethics. Their ideas are based on…
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What Gets Counted Counts
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. The following book chapter considers how within data science, practitioners are used to seeing the world in 1s and 0s – in fact,…
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The Numbers Don’t Speak for Themselves
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. The following book chapter discusses how context is everything. Numbers are just numbers and cannot speak for themselves. Future data scientists need to…
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On Rational, Scientific, Objective Viewpoints from Mythical, Imaginary, Impossible Standpoints
Author: Catherine D’Ignazio and Lauren Klein Publisher: MIT Press Publication Year: 2020 Summary: The following book chapter from “Data Feminism” can be beautifully summed up by words from Black feminist sociologist Patricia Hill Collins: “Neither…
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Design for Data Ethics
Author: Cat Drew; Publisher: Royal Society Publishing; Publication Year: N/A. Summary: The following visual provides a clear framework and flow chart for data ethics in design practice. This resource has more general data ethics framework…
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The CARE Principles for Indigenous Data Governance
Author: Stephanie Russo Carroll et al.; Publisher: The Data Science Journal; Publication Year: 2020. The following article discusses how Indigenous Peoples have been oppressed in numerous ways, and with the growth of big data and…