Explore ethical challenges in AI, including algorithmic bias, professional ethics, and workplace diversity.
Explore ethical challenges in AI, including algorithmic bias, professional ethics, and workplace diversity.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Computing, Ethics, and Society Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
What you'll learn
Understand and identify algorithmic bias in machine learning systems
Analyze gender and racial implications in AI applications
Apply professional ethics codes in computing
Evaluate tech workplace culture and diversity issues
Assess ethical implications of emerging AI technologies
Skills you'll gain
This course includes:
6.8 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course examines ethical issues in computing systems and their societal impact. Students explore algorithmic bias in machine learning, focusing on gender and racial implications. The curriculum covers professional ethics in computing, workplace culture, and emerging challenges in AI technologies like facial recognition and generative AI. Through case studies and discussions, participants develop critical thinking skills to address ethical challenges in modern technology development and implementation.
Course Overview and Ethical Foundations
Module 1 · 4 Hours to complete
Algorithmic Bias
Module 2 · 10 Hours to complete
Gender and Race in Computing
Module 3 · 5 Hours to complete
Professional Ethics, including Gender and Race in the Tech Workforce
Module 4 · 8 Hours to complete
Generative AI and the Future of AI
Module 5 · 7 Hours to complete
Fee Structure
Instructor
Distinguished Leader in Computer Science and Education
Bobby Schnabel is a Professor and External Chair of Computer Science at the University of Colorado Boulder, where he also serves as the Faculty Director for Entrepreneurship in the College of Engineering and Applied Science. He previously held the role of CEO of the Association for Computing Machinery (ACM) from 2015 to 2017 and was Dean of the School of Informatics and Computing at Indiana University from 2007 to 2015. Schnabel was part of the Computer Science faculty at CU Boulder from 1977 to 2007, during which time he served as CS department chair from 1990 to 1995, associate dean for academic affairs from 1995 to 1997, founding director of the ATLAS Institute from 1997 to 2007, and vice provost for academic and campus computing and Chief Information Officer from 1998 to 2007. He is a co-founder of the National Center for Women & Information Technology (NCWIT) and remains active on its executive team. Additionally, he co-founded the AAAI/ACM Conference on AI, Ethics and Society and chairs the ACM task force on ethics in computing education.
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