By Dennis Kennedy
This spring, at Michigan State University College of Law and the MSU Center for Law, Technology & Innovation, we launched the “LegalRnD AI Studio,” a mini-course series designed to enhance law students’ AI literacy. Here’s how you can replicate this successful model and provide your students with the essential AI literacy they need.
Session 1: Prompting 101
The first session laid the foundation for understanding generative AI. Students were introduced to AI capabilities and tools, learning the art of crafting effective prompts. Key components included:
- Ethical and Responsible AI Use: Emphasized the importance of data privacy and compliance with university guidelines. Students were reminded to be cautious about what they input into third-party AI applications.
- Introduction to Generative AI: Explained the basics, including large language models (LLMs), temperature settings, and the significance of tokens versus words.
- Crafting Effective Prompts: Taught students to create clear, specific prompts to guide AI outputs.
Session 2: Advanced Prompting
Building on the basics, the second session delved deeper into AI prompting. We explored advanced techniques like iterative refinement, chain of thought, RAG, personas, and prompt chaining. Highlights included:
- Advanced Prompt Examples: Provided structured prompts and hands-on practice to enhance AI interaction skills and achieve desired outputs.
- Enhancing Conversational AI Interactions: Demonstrated techniques for refining AI responses through memory refreshing and conversational styles.
- PCRO Approach: Used Dennis Kennedy’s PCRO model (Persona, Context, Request, Output) for crafting detailed and structured AI prompts.
Session 3: What Employers Expect
The final session focused on bridging the gap between academic learning and professional expectations. Students gained insights into what legal employers seek in new hires, especially regarding AI literacy. Key elements included:
- Industry Insights: Discussed research findings on employer expectations regarding AI proficiency.
- Practical Exercises: Engaged students in scenario-based activities simulating real-world legal tasks.
- Future Steps: Shared strategies for continuing AI learning and staying competitive in the job market.
- Comprehensive Handout: We provided a detailed handout as both a course guide and a future reference.
Key Takeaways for Professors:
1. Ethical Considerations: Emphasize ethical AI use, data privacy, and compliance with university policies.
2. Interactive Learning: Blend lectures and hands-on practice to ensure students grasp both theoretical concepts and practical applications.
3. Progressive Skill Building: Start with basic prompting techniques and gradually introduce more advanced concepts.
4. Focus on Prompting: Effective prompting is crucial for generative AI success.
5. Real-World Relevance: Engage students in practical exercises simulating tasks they might encounter in their careers.
6. Continued Learning: Offer strategies for ongoing AI education and staying competitive in the job market.
7. Feedback and Practice: Provide regular feedback and practical assignments to help students refine their skills.
8. Stay Flexible: Be prepared to adapt your course as AI technology and industry needs evolve. Incorporate segments where students can share their AI experiments and discoveries.
9. Collaborate: Reach out to tech companies, employers, and other departments, like MSU’s Center for Teaching & Learning Innovation. There is no need to go alone.
Challenges to Consider:
- Ethical Considerations: Navigating ethical implications of AI, especially for law students without prior professional responsibility training.
- Balancing Depth and Breadth: Focusing on core skills without overwhelming students who might be new to AI.
- Time Constraint: Selectively covering essential topics effectively within the available sessions.
- Keeping Up with AI Advancements: AI is changing quickly!
Why This Course Matters?
The “AI Studio” approach reflects that using generative AI is both an art and a science, learned best through hands-on practice. By implementing a similar course, you can create a successful AI literacy course that equips your students with the skills needed to thrive in the modern landscape. The response from students has been overwhelmingly positive. They appreciate the practical skills and feel more confident in navigating the world of AI.
The mini-course is an important step in addressing the tech skills gap in legal education. It provides a solid starting point and sparks an interest in further learning. It’s also an approach that can be effectively applied to other disciplines.
Dennis Kennedy is the Director of the Michigan State University Center for Law, Technology & Innovation and teaches a course in AI and the Law at the MSU College of Law. Email: kenne514@msu.edu.