Category: 2021

Data Science and Its Diversity Problems

Data Science, Discrimination, Gender Discrimination, Racial Discrimination

Author: Lauren Church, Carol Stabile; Publisher: Ms. Magazine; Publication Year: 2021. The following article discusses the issue of diversity in the data science field, which has adverse effects on the outcomes and range of issues…
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Ethical and Social Risks of Harm from Language Models

Access, Automation, Discrimination, Environmental Harms, Exclusion, Information Hazards, Language Models, Malicious Uses, Misinformation, Risks, Toxicity

Author: Laura Weidinger et. al.; Publisher: DeepMind; Publication Year: 2021. The following research paper helps organize the risk landscape associated with large-scale Language Models (LMs). To advance responsible innovation, a thorough understanding of the potential…
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Data Science Ethics – What Could Go Wrong and How to Avoid It

Accessible, Consent, Consumer Data, Consumer Privacy, Discrimination, Fairness, Fairness Accountability Transparency, Findable, Interoperable, Reusable, Transparency

Author: Kylie Ying; Publisher: freeCodeCamp; Publication Year: 2021. The following article discusses how the notion of informed consent quickly fades in a business setting, where it may be in fine print or even without our…
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A.I. Bias Caused 80% Of Black Mortgage Applicants To Be Denied

Artificial Intelligence, Fairness, Fintech, Home Ownership, Mortgage, Racial Bias

Author: Kori Hale; Publisher: Forbes; Publication Year: 2021. The following article describes a specific instance of an unethical artificial intelligence (AI) program where across the board minorities are being rejected from mortgage requests at higher…
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How to Promote Ethics in Data Science and Analytics

Ethical Constraints, Math, Training Data, Transparency

Author: Kirsten Hoogenakker Publisher: DataDrive Publication Year: 2021 Summary: The following article discusses how math has generally been thought of as a completely unbiased form of research. Numbers are numbers, how could they be biased?…
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Center for Applied Data Ethics suggests treating AI like a bureaucracy

Accuracy, Anthropological Assessment, Artificial Intelligence, Power Exchanges, Privilege

Author: Khari Johnson; Publisher: VentureBeat; Publication Year: 2021. The following article summarizes another paper about the danger of accepting the future of artificial intelligence (AI) as inevitable and potential power dynamics that can emerge that…
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Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers

Consent, Microsoft, Public Datasets, Unethical Data Removal

Author: Kenny Peng, Arunesh Mathur, Arvind Narayanan; Publisher: 35th Conference on Neural Information Processing Systems; Publication Year: 2021. The following research paper was done on how the most common method of removal of unethical data…
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Transphobia in Algorithms

AI Bias, Cissexism, Data Collection, Facial Recognition Systems, Gender, LGBTQIA+, Trans People

Author: Kelsey Campbell; Publisher: Gay TA Science; Publication Year: 2021. In the following talk, Kelsey explains how the cissexism present in society today impacts data science as a field. They give examples from real-life on…
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Sports Betting and Data Security: Cybersecurity, Data Protection, and Privacy Rights in Gaming Law Practice

Cybersecurity, Data Collection, Data Ownership, Data Privacy, Data Security, Sports Gambling

Author: Kathryn R.L. Rand, Steven Andrew Light; Publisher: American Bar Association; Publication Year: 2021. The following article describes how with the rise of legalized sports gambling, the authors point out the rise of data ownership,…
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