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Responsible AI: Transparency, Accountability, Explainability and Privacy

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Responsible AI: Ethical Implications and Societal Impact

Dive into the ethical, social, and political dimensions of artificial intelligence (AI) with our Responsible AI course. Explore how AI technologies influence fairness, privacy, bias, democracy, and social justice. Through engaging case studies, dynamic discussions, and practical hands-on exercises, students will gain a deep understanding of the ethical challenges and societal implications of AI. Learn to develop a comprehensive framework for designing, developing, and deploying AI systems responsibly, ensuring fairness, transparency, and accountability.

Join us on this transformative journey to shape the future of AI responsibly.

Course Highlights:

  • AI and ethical implications, bias, and societal impact.
  • AI privacy, safety, security, and data protection.
  • AI frameworks and tools for bias mitigation, transparency, and privacy.
  • Ethical considerations during the AI development lifecycle.
  • AI governance and regulatory landscapes.
  • Algorithmic fairness, bias, and surveillance.
  • Overview of tools and techniques to reduce AI-based bias and improve transparency.

Learning Outcomes:

By the end of the course, students will learn about:
  • Critical Analysis: Ability to evaluate AI systems for ethical implications, bias, and potential social harm.
  • Frameworks and Tools: Develop an understanding of various responsible AI frameworks and tools for bias mitigation, transparency, and privacy.
  • Empathetic Design: Integrate ethical considerations throughout the AI development lifecycle.
  • Policy Awareness: Be conversant in regulatory landscapes and policy discussions regarding AI ethics.
  • Societal Impact: Analyze and articulate the broad societal impact of AI developments.
  • Effective Communication: Successfully communicate ethical AI considerations to technical and non-technical audiences.

Course Typically Offered: Online during Summer and Winter quarter. 

Prerequisites: Basic understanding of business and technology and an interest on the impact of AI on business processes and transformation. A bachelor's degree or equivalent experience in any field is desirable.

Next steps: Upon completion of this class, consider enrolling in other courses in the Machine Learning Methods Certificate.

More information: Contact unex-techdata@ucsd.edu to learn more about our programs in Data Science.

Course Number: CSE-41402
Credit: 3.00 unit(s)
Related Certificate Programs: Machine Learning Methods

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