What Is Programming? And How To Get Started
January 28, 2025
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This course is part of Computing, Ethics, and Society Specialization
Instructor: Bobby Schnabel
Included with
(13 reviews)
Recommended experience
Beginner level
No prior background is required to complete this course.
(13 reviews)
Recommended experience
Beginner level
No prior background is required to complete this course.
Describe the causes and prevention of algorithmic bias in machine learning algorithms.
Identify key instances of algorithmic bias, including relations to gender and race.
Describe the main code of professional ethics in computing.
Analyze issues in the culture of the tech workplace and reflect about how to address these in your career.
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Computing systems and technologies fundamentally impact the lives of most people in the world, including how we communicate, get information, socialize, and receive healthcare. This course is the second of a three course sequence that examines ethical issues in the design and implementation of computing systems and technologies, and reflects upon the broad implication of computing on our society. It covers algorithmic bias in machine learning methods, professional ethics, and issues in the tech workplace.
This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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.
6 videos11 readings1 assignment1 peer review
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.
8 videos15 readings1 peer review2 discussion prompts
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.
4 videos5 readings1 assignment1 peer review1 discussion prompt
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.
8 videos8 readings1 assignment1 peer review1 discussion prompt
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.
4 videos6 readings1 assignment2 discussion prompts
CU Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Colorado Boulder
Degree
University of Colorado Boulder
Degree · 24 months
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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