Research Mastery: From AI to Follow-up with Traditional Skills (On-Demand)

Course Description

Research Mastery: From AI to Follow-up with Traditional Skills explains how generative AI can jump-start legal research but must be followed by disciplined verification. The presentation begins by treating AI as an efficient entry point for issue spotting, rapid synthesis, and drafting a preliminary research plan. It then examines why lawyers and students over-trust AI—fluent language, cognitive ease, and automation complacency—and why those human factors require guardrails. The ethics segment ties AI use to professional duties of competence, diligence, confidentiality, supervision, and candor, emphasizing recurring failure modes such as hallucinated citations and outdated or jurisdictionally incorrect rules.

Worked examples demonstrate that AI outputs are often directionally helpful but can be wrong in the details, making validation essential. The presentation then pivots to “traditional mastery”: using platform ranking, West’s Topic & Key Number system, and high-quality secondary sources (treatises, ALR, restatements, encyclopedias) to confirm leading authorities and ensure completeness. It closes with a safe workflow: use AI to start, but rely on traditional research skills to finish.

Syllabus

1. Generative AI as the entry point
2. Why we trust (and over‑trust) LLMs
3. Ethics and professional responsibility (+ failure modes)
4. Case studies: testing AI outputs
5. Verification workflows with traditional methods
6. Secondary sources as validators
7. Free resources
8. Key takeaways / safe workflow (new)