Artificial Intelligence

A 20-Year Community Roadmap for Artificial Intelligence Research in the U.S.

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Author: Y. Gil and B. Selman; Publisher: Computing Community Consortium (CCC) and Association for the Advancement of Artificial Intelligence (AAAI); Publication Year: 2019. The following paper touches on such a broad spectrum of societal facets artificial intelligence (AI) affects and should be considered more closely. The different areas stimulated ideas such as highlighting the AI Open Knowledge network need. Currently the major tech companies have access to a majority of this resource so it is imperative to open…

Theories of AI Liability: It’s Still About the Human Element

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Author: William A. Tanenbaum, Kiyong Song, Linda A. Malek; Publisher: Reuters; Publication Year: 2022. The following article outlines the 2 basic theories/ideas regarding who is responsible or liable for the actions taken and decisions made by an artificial intelligence (AI). The first argument is that the organization that utilizes the AI is solely responsible for the effects of its outcomes. The second contends that those developed the AI should have to…

The Role and Limits of Principles in AI Ethics: Toward a Focus on Tensions

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Author: Jess Whittlestone et al.; Publisher: Conference on AI, Ethics, and Society; Publication Year: 2019. The following research article argues that there are tensions between common principles guiding ethical decision-making about artificial intelligence (AI). They explain 4 key tensions: service quality versus privacy, accuracy versus fair treatment, personalization versus solidarity, and convenience versus dignity. By analogy with bioethics, the authors also argue…

Ethics of Artificial Intelligence and Robotics

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Author: N/A; Publisher: Stanford Encyclopedia of Philosophy; Publication Year: 2020. In the following article, Dr. Müller at Stanford discusses why artificial intelligence (AI) system scandals are covered differently in the media. For a problem to qualify as a problem for AI ethics would require that we do not readily know what the right thing to do is. In this sense, job loss, theft, or killing with AI is not a problem in ethics, but whether these…

Three Ways to Avoid Bias in Machine Learning

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Author: Vince Lynch; Publisher: TechCrunch+; Publication Year: 2018. The following article discusses how bias in artificial intelligence (AI) can cause problems both because AI outputs are often blindly trusted, so any missed human bias could be spread, and because AI used in automated functions could spread bias without knowledge. The article names 3 ways to avoid bias in machine learning. 1). Choose the right…

The Key Concepts of Ethics of Artificial Intelligence

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Author: Ville Vakkuri, Pekka Abrahamsson; Publisher: IEEE Xplore; Publication Year: 2018. The following article seeks to find out what the reoccurring themes are in artificial intelligence (AI) ethics discourse as a way of understanding the current state of AI ethics as well as determining a direction for AI ethics going forward by using these themes to create a framework. 1062 papers were analyzed and 37 reoccurring keywords words related to AI…

Handling Data Bias

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Author: Vidhi Chugh; Publisher: Medium; Publication Year: 2021. The following article describes how as a data scientist, if you want the product you are working on to be “[artificial intelligence (AI)] for good,” then it is inevitable to encounter some situations such as biased data, biased models, or biased implementation. This article illustrated forms of what data bias can be and there is no one solution for all. But…

It’s Never too Early to Get Your AI Ethics Right

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Author: Veronica Irwin; Publisher: Protocol; Publication Year: 2022. The following article discusses how startups, especially early-stage ones, are focused on making evangelical sales to large enterprises. Even with good intentions, it is easy for founders to think of cutting corners, which can have bad consequences. If investors do not trust the team or the product, the startup can be in deep trouble. If the artificial…

Locked Out by Big Data: How Big Data, Algorithms and Machine Learning May Undermine Housing Justice

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Author: Valerie Schneider; Publisher: Columbia Human Rights Law Review; Publication Year: 2020. The following article is a very granular deep dive into how artificial intelligence (AI) can lead to discrimination in housing and how this relates to Fair Housing Act “disparate impact” jurisprudence. The motivation for the article was a proposed rule from HUD that would have immunized landlords using algorithms from disparate impact fair housing claims…

Data Ethics, AI and Responsible Innovation

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Author: University of Edinburgh; Publisher: edX; Publication Year: N/A. The following online class was created by the University of Edinburgh which is available for free on edX. The course is 7-weeks long and requires only 3-4 hours of work per week, but the course covers a large variety of material relating to data ethics, artificial intelligence (AI), and responsible innovation. The course focuses on educating the student on…