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Course
- AI
Adversarial AI: Ethics and Impact
Understand the ethical implications and real-world impact of adversarial AI. This course explores the financial, legal, and societal consequences of adversarial attacks and provides frameworks for responsible AI development.
What you'll learn
As adversarial AI moves from research labs to real-world systems, understanding its broader implications becomes crucial for responsible implementation. In this course, Adversarial AI: Ethics and Impact, you'll learn to navigate the complex ethical, financial, and societal challenges posed by adversarial machine learning. First, you'll explore how to quantify the financial impact of adversarial attacks on organizations and make data-driven security investment decisions. Next, you'll examine the ethical and legal questions around responsibility and liability when AI systems fail due to adversarial manipulation. Finally, you'll analyze real-world adversarial incidents like deepfakes and learn what these cases tell us about emerging threats. When you're finished with this course, you'll have the knowledge and frameworks needed to address technical aspects of adversarial AI, its business implications, ethical challenges, and societal impacts.
Table of contents
About the author
Dr. Goran Trajkovski is a seasoned professional with over 30 years of experience in AI, data science, and learning design, focused on innovative strategies and effective leadership.
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