Tag: Inclusivity

Systemic Data Ethics Framework: A Stable Foundation for Responsible Innovation

Accountability, Agency, Application, Compliance, Consequences, Fairness, Inclusivity, Infrastructure, Integral Theory, Materials, Strategy, Sustainability, Transparency

Author: Peter Brownell; Publisher: Systemic Data Ethics; Publication Year: N/A. The following article and visualization establishes a framework for data ethics that can be mapped visually in a number of ways. At its core, the…
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How to Stop the Metaverse from Becoming the Internet’s Bad Sequel

Accessibility, Inclusivity, Metaverse

Author: Micaela Mantegna; Publisher: TED; Publication Year: 2022. The following talk features Micaela Mantegna who is a video games lawyer who is an advocate for ways to improve the metaverse. She explains in this video…
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AI & Data Fairness & Bias

AI Bias, Algorithms, Fairness, Inclusivity

Author: Kathleen Walch, Ronald Schmelzer; Publisher: AI & Data Today; Publication Year: N/A. The following podcast focusses on how building frameworks can help avoid the pitfalls associated with bias and fairness in artificial intelligence (AI).…
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AI Ethics (AI Code of Ethics)

Artificial Intelligence, Explainability, Fairness, Inclusivity, Misuse, Responsibility

Author: George Lawton, Ivy Wigmore; Publisher: Tech Target; Publication Year: N/A. The following definition discusses how an artificial intelligence (AI) code of ethics is important because it is able to provide guidance to stakeholders to…
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Ethical Issues Surrounding Research of AI in Health Care

Accountability, Artificial Intelligence, Autonomy, Equity, Inclusivity, Public Interest, Sustainability, Transparency, World Health Organization

Author: F. Lisa Murtha, Pralika Jain and Kiyong Song; Publisher: Reuters; Publication Year: 2022. The following article discusses the controversy around artificial intelligence (AI) in healthcare has become a barrier to using AI to better…
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How Inclusive Machine Learning Can Benefit Your Organization

Decision-Making, Fair Algorithm, Fair Training Data, Inclusivity, Machine Learning

Author: Christopher Tozzi; Publisher: ITPro Today; Publication Year: 2022. The following article discusses how businesses have started putting more of an “inclusive” focus on machine learning models to avoid bias and error while creating models.…
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The Numbers Don’t Speak for Themselves

Context, Data Collection, Inclusivity

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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