Category: Education & Training
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Conscientious Classification: A Data Scientist’s Guide to Discrimination-Aware Classification
Author: d’Alessandro B, O’Neil C, LaGatta T.; Publisher: National Library of Medicine; Publication Year: 2017. The following article describes discrimination in the context of machine learning. The authors discuss how models can be biased even…
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Data Ethics
Artificial Intelligence, Automation, California Consumer Privacy Act, CCPA, Data Analysis, Data Collection, Data Dissemination, Data Generation, GDPR, General Data Protection Regulation, Personal Data, TransparencyAuthor: N/A; Publisher: Cognizant; Publication Year: N/A. The following glossary entry defines and expands on the concept of data ethics. The entry defines data ethics as a branch of ethics that evaluates data practices—collecting, generating,…
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Bias in Machine Learning
Algorithms, Discrimination, Feedback Loop, Inequality, Machine Learning, Machine Learning Lifecycle, Miro, Unconscious BiasAuthor: N/A; Publisher: Miro; Publication Year: N/A. The following visualization highlights the impact of bias in several aspects of the machine learning lifecycle. One point discussed frequently is the patterns of bias and discrimination baked…
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Synthetic Data Generation
Amazon, American Express, Data Protection, Google, Insufficient Representation, Synthetic Data, Training Data, Underrepresented CommunitiesAuthor: Christian Schitton; Publisher: Medium; Publication Year: 2022. The following article discusses how synthetic data is a less well-known area of data science. Synthetic data addresses issues of insufficient representation in data. For example, models…
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Principles for the Safe and Effective use of Data and Analytics
Author: N/A; Publisher: New Zealand Government; Publication Year: 2018. The following document contains a list of principles developed for the safe and effective use of data and analytics. The first principle states that any organization…
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Why the Ethical Use of Data and User Privacy Concerns Matter
Author: Charlie Fletcher; Publisher: Venture Beat; Publication Year: 2022. The following article investigates the importance of data privacy and ethics in a world of rising cybercrime. The author argues that now more than ever, data…
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Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults
Accessibility, Ageism, Digital Ageism, Discrimination, Fairness, Harms of Allocation, Harms of Representation, Older Adult Populations, PrejudiceAuthor: Charlene Chu et al.; Publisher: The Gerontologist, Volume 62; Publication Year: 2022. The following paper explores the impacts of ageism and technology. They define “digital ageism” as the repercussions of bias against older individuals…
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Standards of Practice Handbook
Author: N/A; Publisher: The Chartered Financial Analyst (CFA) Institute; Publication Year: 2014. Summary: The following handbook discusses regulation in relation to ethics of financial analysts. It covers how to keep privacy of data, to transfer…
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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…