Category: Diversity, Equity & Inclusion

Algorithmic Bias in Data-Driven Innovation in the Age of AI

Algorithmic Bias, Data Driven Innovation Phases, Data Driven Process

Author: Shahriar Akter, Grace McCarthy, Shahriar Sajib, Katina Michael, Yogesh Dwivedi, John D’Ambra; Publisher: International Journal of Information Management; Publication Year: 2021. The following paper provided a thorough framework for algorithmic biases in data driven…
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Artificial Intelligence in Education: Addressing Ethical Challenges in K-12 Settings

Algorithms, Educational Outcomes, Human Bias, K-12, Systematic Bias

Author: Selin Akgun, Christine Greenhow; Publisher: AI and Ethics; Publication Year: 2022. The following article discusses the current and proposed uses of artificial intelligence (AI) in promoting educational outcomes for K-12 students. It asserts that,…
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How Biased Are Our Algorithms?

Artificial Intelligence, Biased AI, Racial Bias

Author: Safiya Umoja Noble; Publisher: TEDx Talks; Publication Year: 2014. The following video initially discusses how the speaker is not the same skin tone as her white mother. She then goes into discussing the cultural…
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Locating ethics in data science: responsibility and accountability in global and distributed knowledge production systems

Accountability, Data Science, Ethical Implications, Participative Management, Responsibility

Author: Sabina Leonelli; Publisher: The Royal Society; Publication Year: 2016. The following article talks about the challenges produced in data science around the responsibilities and accountabilities of individuals in the industry. The author advocates a…
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Responsible AI: Data Science and Ethics with Dr. Rumman Chowdhury

Artificial Intelligence, Biased Data, Ethical Data Culture, Ethical Implementation, Fairness

Author: Rumman Chowdhury; Publisher: Accenture Technology; Publication Year: 2019. In the following video, Dr. Ruman Chowdury explains how “[artificial intelligence (AI)] is information about people meant to understand trends about human behavior.” There are 2…
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A Guide for Ethical Data Science

Accountability, Data Management, Data Science, Harm Avoidance, Human Oversight, Implementation, Professional Competence, Project Planning, Trustworthiness

Author: Institute and Faculty of Actuaries; Publisher: Royal Statistical Society; Publication Year: 2019. The following article is a very well designed code of ethics that revolves around its defined 5 major themes of data ethics:…
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Chris Olah on What the Hell is Going on Inside Neural Networks

Black Box Algorithms, Data Interpretability, Google, Neural Networks

Author: Robert Wiblin, Keiran Harris, Chris Olah; Publisher: 80,000 Hours; Publication Year: 2021. The following podcast episode features Chris Olah, a researcher at Google focused on data interpretability, specifically as it relates to neural networks…
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The Ethics of Smart Cities and Urban Science

Anticipatory Governance, Data-Driven Urbanism, Dataveillance, Epistemology, Geosurveillance, Smart Cities, Software-Enabled Technology, Urban Big Data, Urbanism

Author: Rob Kitchin; Publisher: The Royal Society; Publication Year: 2016. The following article talks about how software-enabled technologies and urban big data have become essential to the functioning of cities. Consequently, urban operational governance and…
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Critics Raise Alarm Over Big Tech’s Most Powerful Tools

Algorithms, Dark Patterns, Google, Reinforcement Learning

Author: Richard Water; Publisher: Financial Times; Publication Year: 2021. The following article discusses how big tech companies are using “Dark Patterns” in order to nudge their userbase into certain patterns of behavior. In a “race…
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