Explainability

AI has a Dangerous Bias Problem — Here’s How to Manage It

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Author: Thomas Macaulay, Alejandro Saucedo; Publisher: The Next Web; Publication Year: 2022. The following article discusses how almost all artificial intelligence (AI) algorithms are inherently biased as they do exactly what us the programmers tell them to do and we are all inherently biased ourselves. This resource is an interview with Alejandro Saucedo, Chief Scientist at The Institute for Ethical AI, who discusses his main points of what needs to be…

Australia’s Artificial Intelligence Ethics Framework

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Author: N/A; Publisher: Australian Government; Publication Year: 2022. The following guidelines provided by the Australian Government has a list of 8 items that make up their data ethics framework. These include: 1). Human, societal and environmental wellbeing, 2). Human-centered values, 3). Fairness , 4). Privacy protection and security , 5). Reliability and safety , 6). Transparency and explainability , 7). Contestability, and…

Making It Easier to Compare the Tools for Explainable AI

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Author: Surya Karunagaran; Publisher: Partnership on AI; Publication Year: 2022. The following article focuses on how Partnership on AI, inspired partially by Google Model Cards and Microsoft’s Datasheets for Datasets, has developed documentation on explainable artificial intelligence (AI) in the form of the XAI Toolsheet. Explainable AI comes from the desire to have more human-interpretable AI models, with better…

Ethical AI Governance Framework

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Author: N/A; Publisher: Saidot; Publication Year: 2021. The following article outlines 6 building blocks of an ethical artificial intelligence (AI) governance framework. These include strategy and values (acceptable use of AI in alignment with business strategy); people and culture (human competencies and cultural capabilities to enable and support the development and use of AI in an ethically sustainable…

Preventing Harmful AI Bias With Fairness Through Awareness

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Author: Rik Chomko; Publisher: Forbes; Publication Year: 2022. The following article describes how, from an equity standpoint, artificial intelligence (AI) transparency is vital for preventing bias that has the potential to penalize protected classes or negatively impact a person’s well-being. From a business standpoint, it is becoming just as important. Across the nation and the globe, standards and legislation are…

What is AI Ethics?

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Author: Phaedra Boinodiris; Publisher: IBM Technology; Publication Year: 2021. The following article discusses how artificial intelligence (AI) is making decisions that directly impact all of us. People assume that because AI is a machine, the AI is unbiased and creates a “correct” decision. There are 5 pillars to earning trust in an AI decision. The first pillar is fairness. Is AI fair to everyone? In particular, is AI being proper for historically…

SAM: The Sensitivity of Attribution Methods to Hyperparameters

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Author: Naman Bansal, Chirag Agarwal, Anh Nguyen; Publisher: N/A; Publication Year: 2020. The following article provides examples and an accompanying talk that illustrates how in many classification machine learning systems, even more explainable models, not black box, are highly susceptible to manipulation and silly mistakes. These models, which seek to show how they classify or recognize an image, can give vastly different results with…

What You Need to Know About AI Ethics

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Author: John Edwards; Publisher: Information Week; Publication Year: 2022. The following article discusses how artificial Intelligence (AI) is becoming more popular as tech continues to grow, but with that, the number and intensity of concerns with the use of AI is growing, too. The major concerns this article discusses are issues of bias, explainability, data handling, transparency on data policies, systems capabilities, and design…

What Do We Do About the Biases in AI?

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Author: James Manyika, Jake Silberg, Brittany Presten

Publisher: Harvard Business Review

Publication Year: 2019

Summary: The following article discusses how artificial intelligence (AI) can help identify and reduce the impact of human biases. But it can also make the problem worse by baking in and deploying biases at scale in sensitive areas. In Broward Country, Florida, an algorithm mislabeled African-American defendants as “high risk.” Bias can creep into algorithms in…

AI Ethics (AI Code of Ethics)

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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 make ethical decisions regarding the use and implementation of artificial intelligence. The 4 ethical challenges surrounding AI are explainability, responsibility, fairness, and misuse. For AI to be ethical it…