We have argued here that AI needs Good Data. The four pillars of good data: community, rights, usability and politics are at the forefront of a just digital society and economy. Good Data situates genuinely ethical AI within communities and collectives, rather than individuals or large organisations.
Furthermore, ethical AI principles such as fairness, accountability, transparency judge only the information systems within which AI is installed, without ...
Feb 15, 2021 · In this chapter we argue that discourses on AI must transcend the language of 'ethics' and engage with power and political economy in order to constitute 'Good ...
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Artificial intelligence poses a lot of ethical risks to businesses: It may promote bias, lead to invasions of privacy, and in the case of self-driving cars, ...
To navigate data privacy, security, and ethics, it will be crucial for business leaders to understand how ethics and AI mesh, the challenges of implementing AI.
This book brings together critical interrogations of what constitutes AI, its impact and its inequalities in order to offer an analysis of what it means for AI ...
In this article, we'll touch on issues like data bias, legal fault, and consumer privacy, as well as the regulations that may or may not exist in the AI space.
Accuracy - The data used in AI should be up to date and accurate. And there needs to be ways to correct it. Data should also be handled, cleaned, sorted ...
Oct 15, 2020 · An operationalized approach to data and AI ethics must systematically and exhaustively identify ethical risks throughout the organization.
Sep 26, 2024 · UNESCO's first-ever global standard on AI ethics – the 'Recommendation on the Ethics of Artificial Intelligence', adopted in 2021, is applicable to all 194 ...