Hands-on Data Science
AI Ethics for Public Sector Leaders
Adrian Dunkley
Adrian Dunkley is the founder and CEO of StarApple AI, Jamaica's first AI and Data Science company, he has a background in fintech, tourism, and sports science. He's held leadership roles in multinational corporations and is the President of the Jamaica Technology and Digital Alliance. Adrian aims to establish a Caribbean Space Agency and is a Data Scientist and A.I Engineer with 15+ years of experience. He holds a double major in Mathematics and Physics and a Masters in Enterprise Risk Management.
2 Days
Duration-
500Per Person
Individual -
200Per Person
Groups of 5+ participants
Course Description:
This 2-day course is dedicated to exploring the ethical dimensions of AI in the public sector. We’ll discuss how to navigate the complex ethical landscape of AI, covering issues like algorithmic fairness, transparency, and accountability. Our AI ethics experts will guide you through real-world case studies, providing practical strategies for addressing ethical dilemmas. You’ll leave equipped to lead ethically conscious AI initiatives in your organization.
Syllabus:
- Foundations of AI Ethics: Introduction to the ethical principles relevant to AI applications in the public sector, including fairness, transparency, and accountability.
- Algorithmic Fairness and Bias: Exploring the challenges of bias in AI algorithms and strategies for mitigating these issues to ensure fair outcomes.
- Transparency and Explainability in AI: Importance of making AI systems transparent and understandable to stakeholders, including methods for achieving this.
- Accountability and Governance of AI: Establishing frameworks for AI governance that ensure accountability for decisions made by or with the support of AI systems.
- Case Studies and Practical Strategies: Analysis of real-world case studies to illustrate ethical dilemmas in public sector AI projects, with discussions on practical strategies for ethical decision-making.
Prerequisites:
- There are no prerequisites for this course.
Grading Policy:
- 2 exams
- 1 capstone project
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