Ethical & Societal Implications of Artificial Intelligence

This self-paced, online course introduces university faculty to the fundamentals of artificial intelligence, including its origins, societal impact, and evolving role in higher education.

Module Outline

Course Description: The Ethical & Societal Implications of Artificial Intelligence online course is one of the self-paced online courses developed under the UNG-DETI's AI in Learning Certification Program as a professional development opportunity designed to equip UNG faculty with essential knowledge and skills to integrate artificial intelligence (AI) into their teaching practices.
Course Objectives:
By the end of this course, the participant will be able to:
CO1. describe the ethical considerations and risks associated with generative AI, including bias, misinformation, and surveillance.
CO2. analyze the implications of generative AI on society, such as job displacement, autonomy, and the reduction of human interaction.
CO3: compare and contrast global efforts to regulate AI, including legislation like the EU AI Act and U.S. voluntary frameworks.
CO4. apply ethical principles and regulatory insights to recommend best practices for responsible AI development.

Module 1- Introduction to the Ethical and Societal Implications of AI

This module will introduce the foundational ethical and societal concerns surrounding AI technologies. You’ll learn about how generative AI can amplify existing biases, compromise user privacy, and affect human autonomy. 

By the end of this module, the participants will be able to:

  • Learning Objective 1- LO1: identify key ethical concerns in AI such as bias, surveillance, and autonomy. (CO1)
  • Learning Objective 2- LO2: summarize how AI systems can influence employment, interpersonal relationships, and public safety. (CO2)
  • Learning Objective 3- LO3: recognize the importance of ethical frameworks and public engagement in addressing AI-related risks. (CO2)

Module 2- Deepfakes, Copyrights, and Privacy Concerns

This module will explore how generative AI tools are reshaping issues of identity, creativity, and data ownership. Deepfakes, AI-generated art, and synthetic voice tools challenge our current understanding of consent, authorship, and digital ethics.

By the end of this module, the participants will be able to:

  • Learning Objective 4- LO4: define deepfakes and explain their implications for identity security and misinformation. (CO1)
  • Learning Objective 5- LO5: describe the application of existing privacy and copyright laws to generative AI technologies. (CO4)
  • Learning Objective 6- LO6: evaluate scenarios where AI-generated content may infringe on intellectual property rights. (CO1)

Module 3- Regulation and Global Responses to Generative AI

This module will focus on how governments and organizations are responding to the rapid development of AI through regulation and policy. You'll explore key frameworks like the EU AI Act, Canada’s Artificial Intelligence and Data Act (AIDA), and U.S. voluntary codes of conduct.

By the end of this module, the participants will be able to:

  • Learning Objective 7- LO7: list key provisions and objectives of AI-related regulations (EU AI Act, AIDA, U.S. frameworks). (CO3)
  • Learning Objective 8- LO8: examine the challenges faced by governments in regulating dynamic and evolving AI technologies. (CO3)
  • Learning Objective 9- LO9: assess the trade-offs between innovation, regulation, and societal well-being in AI policymaking. (CO3, CO4)

Module 4- Responsible AI Development and Future Challenges

This module will prepare you to recommend best practices and apply ethical standards and legal considerations to real-world AI design and deployment scenarios.

By the end of this module, the participants will be able to:

  • Learning Objective 10- LO10: outline core principles for responsible AI development, including fairness, transparency, and accountability. (CO4)
  • Learning Objective 11- LO11: identify techniques used to mitigate algorithmic bias and protect user data. (CO1, CO4)
  • Learning Objective 12- LO12: recommend responsible AI practices by applying legal frameworks and ethical standards to given case studies or scenarios. (CO4)
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