Critical Techniques and Ethics in Generative AI

Description

This experimental unit, replacing the traditional Faculty of Arts capstone, immerses students in cutting-edge research on the effective use of Generative AI in academic contexts. Through discussion, experiential learning, and hands-on in-discipline application, students critically engage with prompting techniques, the fundamentals of large language models, and their nuanced differences. The unit emphasizes ethical considerations and develops students' critical judgment in applying these tools to achieve academic goals.

Adopting an intensive experiential learning approach, the unit demands extensive and nuanced use of Generative AI each week. This practical experience is paired with discipline-specific tasks tailored to different streams:

1.       History students compile a comprehensive 300-source annotated bibliography on the changing perceptions of Caligula across time and cultures.

2.       Politics and International Relations students participate in and create geopolitical wargames, exploring the impact of AI on global dynamics.

3.       Philosophy students explore creating and deconstructing propaganda, examining the philosophical implications of Generative AI on truth and democracy.

Throughout the unit, students engage in peer mentoring and reverse mentoring, providing valuable feedback on effective AI use and contributing to the development of future AI-integrated curricula. This collaborative approach fosters a dynamic learning environment where students not only learn about AI but also actively shape its integration into academic practice.

By combining theoretical knowledge, practical application, and critical reflection, this unit prepares students to be at the forefront of AI integration in their respective disciplines, equipping them with skills crucial for future academic and professional endeavours in an AI-enhanced world.

Learning Outcomes

• Apply effective prompting techniques and AI tools to conduct comprehensive research across various humanities disciplines, demonstrating proficiency in both technical skills and critical thinking.

• Evaluate the ethical implications, biases, and safety risks associated with using generative AI in academic research and professional contexts, drawing on philosophical frameworks and contemporary debates.

• Synthesize insights from AI-assisted research and peer mentoring to develop innovative strategies for integrating AI tools into academic workflows while maintaining scholarly integrity.

• Critique the role of AI in shaping contemporary discourse in humanities and social sciences, articulating well-reasoned arguments supported by evidence from diverse sources and independent research.

• Create discipline-specific projects (such as annotated bibliographies, simulations, or analytical essays) using AI tools, demonstrating the ability to leverage technology for advanced humanities research.

• Analyse the impact of generative AI on research methodologies and knowledge production in the humanities, identifying both opportunities and challenges for future academic practices.

Learning Design

Delivery details: This experimental unit is delivered on-campus at Macquarie University as part of the Faculty of Arts capstone program. It involves collaboration with AI experts and industry professionals to provide cutting-edge insights into generative AI applications in humanities research.

Volume of Learning: 150 hours (75 hours of learning and 75 hours of assessment tasks)

Activities: Interactive Seminars, Hands-on AI Tool Workshops, Guided Research Sessions, Self-Directed Online Learning, In-Class Discussions and Debates, Collaborative Project Work, Reflective Journaling, AI-Assisted Role-Play and Simulations,

Collaborative Grimoire Building, Ethics Debates