Generative AI in the Workplace: Policies, Ethics, and Risks
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Generative AI in the Workplace: Policies, Ethics, and Risks
This course is part of Navigating Disruption: Generative AI in the Workplace Specialization
Instructor: Josh Pasek
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What you'll learn
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
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There are 3 modules in this course
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.
This is the fourth course in “Navigating Disruption: Generative AI in the Workplace,” a course series on ways to respond to new advances in artificial intelligence in the workplace and our lives.
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!
What's included
2 videos4 readings2 discussion prompts
2 videos•Total 14 minutes
- Series Overview & Course Introduction•7 minutes
- Disruption Entails Risks •7 minutes
4 readings•Total 45 minutes
- Course Syllabus •10 minutes
- Pre-Course Survey•10 minutes
- OpenAI System Card•10 minutes
- GPT 4 System Card•15 minutes
2 discussion prompts•Total 30 minutes
- Risks of AI Integration in Your Workplace•15 minutes
- OpenAI System Card Reflection•15 minutes
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.
What's included
5 videos6 readings3 discussion prompts
5 videos•Total 44 minutes
- When Can You Trust an AI Output?•6 minutes
- Considerations When Deciding to Use AI•9 minutes
- AI & the Law•15 minutes
- How Can AI Do Harm?•8 minutes
- Transparency and Explainability•7 minutes
6 readings•Total 75 minutes
- Dangers Associated with Deepfakes•10 minutes
- Deepfakes Implications for Corporations•10 minutes
- Comparing AI Policies Across Nations•20 minutes
- AI and Copyright Law•10 minutes
- AI and Data Risks•10 minutes
- Explainable AI•15 minutes
3 discussion prompts•Total 45 minutes
- Reflection on Deepfakes & Trustworthy AI•15 minutes
- Reflecting on AI Policies•15 minutes
- Reaction to Explainable AI•15 minutes
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.
What's included
4 videos6 readings1 assignment1 discussion prompt
4 videos•Total 30 minutes
- Relying on Randomness & a Changing Platform•9 minutes
- The Risks of Overreliance•8 minutes
- Where is AI Going?•8 minutes
- Back to the Old Disruptive Technologies•5 minutes
6 readings•Total 50 minutes
- Understanding Out-of-Sample Errors (Part 1)•10 minutes
- Understanding Out-of-Sample Errors (Part 2)•10 minutes
- Understanding Out-of-Sample Errors (Part 3)•5 minutes
- Challenge of Insufficient Training Data•5 minutes
- End-of-Course Survey•10 minutes
- Continue your AI education with the AI Collection from Michigan Online•10 minutes
1 assignment•Total 20 minutes
- Reflecting on Your Concerns•20 minutes
1 discussion prompt•Total 10 minutes
- Lessons Learned from the Teachable Machine•10 minutes
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Reviewed on Feb 12, 2025
Excellent conclusion, with coverage of law and ethics, of generative AI.
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