As generative AI finds its place in contemporary organizational practices, it’s important for leaders and workers alike to understand the risk involved with using these systems. In “Generative AI in the Workplace: Policies, Ethics, and Risks,” you’ll consider the hurdles that need to be navigated for effective AI adoption. In this course, you will learn how to identify when uses of AI are appropriate, and better understand challenges in AI ethics and the law. You’ll also explore the transparency of AI algorithms and where the technology is headed in the future.
Generative AI in the Workplace: Policies, Ethics, and Risks
Ce cours fait partie de Spécialisation Navigating Disruption: Generative AI in the Workplace
Instructeur : Josh Pasek
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Expérience recommandée
Ce que vous apprendrez
Identify ways generative AI algorithms can lead to biases in decision-making
Anticipate implications of a lack of algorithmic transparency for decision-making
Plan proactively to protect data security and user privacy
Consider ethics at every stage of the generative AI decision-making process
Compétences que vous acquerrez
- Catégorie : Algorithmic Bias
- Catégorie : Transparency (Human-Computer Interaction)
- Catégorie : AI Copyright
- Catégorie : Generative AI
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novembre 2024
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Il y a 3 modules dans ce cours
Welcome to the course! In this module, we will begin with an overview of this fourth and final course in the Navigating Disruption series, Generative AI in the Workplace: Policies, Ethics, and Risks. After offering some your concerns related to AI adoption on your workplace, we’ll continue to discuss the inherent risks associated with AI adoption and how industry leading organizations are working to address such risks in their models. Let’s get started!
Inclus
2 vidéos4 lectures2 sujets de discussion
In this module, we'll explore the importance of trustworthy AI and how deepfakes threaten to undermine trust in generative AI. We'll then be joined by a guest speaker who will share with us perspectives about how the professionals in law are thinking about the products of AI. We'll close this module with an examination why it is important to ensure that AI models are transparent and can be explained, both for mitigating harms that can be produced and so that users can understand how their queries are being processed.
Inclus
5 vidéos6 lectures3 sujets de discussion
In this final module, we'll summarize the key concepts and ideas we've discussed throughout the course. In our final graded assignment, you will revisit you first discussion post in which you shared some of the risks you are concerned about related to AI adoption in your workplace, and offer some perspectives on how your thinking has changed through our course conversations.
Inclus
4 vidéos5 lectures1 devoir1 sujet de discussion
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Recommandé si vous êtes intéressé(e) par Business Essentials
University of Michigan
Board Infinity
Coursera Instructor Network
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