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  • Course Type: Breadth
  • Specialization: Computing, Ethics, and Society
  • Instructor: Dr. Bobby Schnabel, Professor of Computer Science, Department External Chair 
    • It is recommended that you take specializations in course order. Each course builds upon the prior course.

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Learning Outcomes

  • Describe the causes and prevention of algorithmic bias in machine learning algorithms.
  • Describe the main code of professional ethics in computing.
  • Identify key instances of algorithmic bias, including relations to gender and race.
  • Analyze issues in the culture of the tech workplace and reflect about how to address these in your career.

Course Content

Duration: 6 hours

In this introductory week, you will delve into the fascinating world of computing, ethics, and society. You will explore the fundamental concepts of ethics and ethical frameworks, providing a solid foundation for the entire course. You will gain insights into key ethical theories, including Kantianism, Virtue Ethics, Utilitarianism, and Social Contract Theory. Through interactive discussions and engaging resources, you will understand how these theories shape our moral decision-making processes and their significance in the context of computing technologies.

Duration: 10 hours

This week, you'll explore algorithmic bias, focusing on the ethical dimensions of facial recognition technology. The beginning of the week will be dedicated to an overview of algorithmic bias, its prevalence, and its consequences. Then, you'll examine real-world instances of algorithmic bias. Towards the end of the week, you'll focus on facial recognition technology by exploring its mechanics, addressing the concerning of racial bias, and the legal and regulatory challenges. 

Duration: 5 hours

This week you'll explore the intersections of gender, race, and algorithms. In the beginning of the week, you'll revisit algorithmic bias focusing bias related to gender and race. You'll explore the advantages and disadvantages of employing AI in hiring processes and unravel the complexities of predictive policing with AI, shedding light on its drawbacks and ethical implications. Then, you'll narrow focus to Gender and Race in Algorithms, specifically addressing the pervasive issue of racial bias in AI systems. Throughout this week, you'll gain a comprehensive understanding of the ethical challenges posed by AI in hiring and policing, as well as the broader implications of gender and race biases in algorithms, empowering you to critically assess and navigate these critical topics in the realm of technology and ethics.

Duration: 8 hours

This week is dedicated to professional ethics in computing and considerations of gender and race in the tech workforce. The first lesson will lay the foundational principles of ethical conduct in the computing industry, examining the ACM code of ethics as a guiding framework. Then, you'll explore the critical need for diversity in the workforce and the ethical considerations surrounding it. Finally, we'll spotlight real-world examples, including diversity and gender biases at tech giant Google, and delve into the compelling story of Timnit Gebru, shedding light on the challenges and opportunities in building a more inclusive and ethical computing workforce. Throughout this week, you'll gain a comprehensive understanding of the ethical dimensions of technology and the importance of diversity and inclusion in shaping the future of computing.

Duration: 7 hours

In this final week you'll explore the ethical dimensions of artificial intelligence. The beginning of the week will venture into the captivating yet challenging world of generative AI, unraveling the potential dangers of its applications while demystifying what generative AI truly entails. Then you'll look to the future of AI, where you'll navigate the complex ethical terrain that emerges as AI technologies continue to advance. Throughout this week, you will develop a profound understanding of the ethical concerns that accompany AI's evolution, equipping you with the knowledge to engage thoughtfully and responsibly with this transformative technology.

Duration: 3 hours

This module contains materials for the final project. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.


  • Cross-listed Courses: Courses that are offered under two or more programs. Considered equivalent when evaluating progress toward degree requirements. You may not earn credit for more than one version of a cross-listed course.
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