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Rutgers University

AI Ethics in Business

Rutgers University via Coursera

Overview

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Learning Outcomes: This introductory-level course combined theoretical knowledge with actionable insights for real-world business scenarios, making it ideal for learners looking to integrate AI into the social ethics strategy. By the end of this course, you will be able to: • Understand AI Basics • Explore Ethical Dimensions • Grasp Regulatory Environments • Address Privacy and Fairness: • Practical Insights This course covers an Intermediate knowledge of AI technology and its current application in the business field. It also covers foundational topics of ethics and regulatory frameworks relevant to AI issues. The course also provides real-world case studies and future projections. This course integrates AI technology with business applications and social ethics, providing a unique and comprehensive learning experience. Participants will gain practical skills for implementing AI solutions responsibly and in compliance with regulations. The course connects theoretical concepts to actual business and ethical scenarios through case studies and real-world examples. Discussions on future AI trends and ethical dilemmas further prepare learners to lead in their fields. This Intermediate-level course is designed for students and professionals in various fields, including business managers, IT specialists, policymakers, and those aspiring to integrate AI into their career paths. To be successful in this course, you need to have a background in fundamental business operations and basic knowledge of AI (common AI applications in business and basic algorithms).

Syllabus

  • Foundations of AI Ethics
    • Module 1 of this course offers a foundational exploration of Artificial Intelligence, emphasizing its practical applications and ethical implications. Learners will understand the distinctions between different types of AI, such as Strong and Weak AI, and the importance of ethics in AI development. Through targeted readings, videos, and interactive assignments, this module prepares participants to navigate the evolving landscape of AI technology and its societal impacts.
  • Understanding AI and Ethical Implication
    • Module 2 investigates how AI is currently implemented in different fields. It also emphasizes the importance of responsibility in AI usage and explores how to establish moral frameworks when robust legal and social guidelines are absent. This module provides learners with critical insights into the ethical challenges AI poses and how to navigate them effectively.
  • Core Ethical Challenges in AI
    • This module focuses on Artificial Intelligence's core ethical and operational challenges, covering fairness, privacy, transparency, and accountability. The module also discusses the contexts and mechanisms of AI decision-making, underscoring the critical roles of human oversight.
  • Regulatory Frameworks and Case Studies
    • This module explores the regulatory framework for artificial intelligence, offering a comprehensive look at various regulatory approaches and their impacts on society and AI development. Learners will examine how different regulatory frameworks affect AI applications across sectors, including AI's role in human resources and the real-world outcomes of automation in hard labor. Through a mix of theoretical concepts and case studies, the module provides deep insights into the complexities of AI regulation.
  • The Future of AI and Ethical Considerations
    • This final module assesses how AI implementation impacts society, highlighting the importance of vigilant monitoring and regulation. It explores the limitations of unchecked AI, proactive regulatory strategies, and the dual roles of AI in enhancing and risking sectors like robotics and autonomous transport. The module concludes with a comprehensive review of critical lessons from the course, urging a balanced approach to AI governance to safeguard societal and technological futures.

Taught by

Steven Katz

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