For law schools
Bring a credit-bearing AI course to your NLU
Computational Thinking & AI for Lawyers is a 16-hour, hands-on course built for National Law University students — rigorous enough for academic credit, India-first and current, and designed to slot in through your own academic council without disturbing the BCI core.
Why adopt it
What this gives your students
Six reasons the course earns its place in the curriculum — each grounded in real cases, statutes, and the tools already in Indian practice.
Future-Proofs Your Graduates
AI is already in Indian courtrooms and firms: the Supreme Court runs SUPACE, SUVAS, and TERES, and firms like AZB and Shardul Amarchand use Harvey. This 16-hour course teaches students to prompt AI, read its output critically, verify it, and know where law forbids relying on it — turning AI anxiety into a professional competency.
Protects Students From Career-Ending Mistakes
In 2026 the Supreme Court of India held that citing AI-fabricated case law is professional misconduct (Gummadi Usha Rani v. Sure Mallikarjuna Rao). The Bombay HC imposed a Rs 50,000 cost order for phantom precedents, and a US court sanctioned a lawyer in Mata v. Avianca. The whole course is, in effect, how not to be the lawyer in Mata: a documented duty to verify before anything ships.
A Distinctive, Memorable Pedagogy
The course is built on the Mirror Move (ON US -> IN THE MACHINE -> LIVE AI -> THE SKILL) and commit-then-reveal live polling. Students experience a bias on themselves, see the same failure in an LLM, watch it live on a real chatbot, then take away a concrete skill — anchored in real cases, statutes, and judgments, not abstractions.
Routes Computational Thinking Through Legal Reasoning
The intellectual hook is that legal reasoning IS computational thinking: IRAC is decomposition, analogy from precedent is pattern recognition, extracting the ratio decidendi is abstraction, applying a legal test step-by-step is algorithm design. Students learn to wield AI with skills they already have — no quantitative background assumed.
Two Tracks: Law WITH AI and Law OF AI
Students learn AI as a tool (research, drafting, review, discovery) and AI as a subject of law (algorithmic bias and due process, AI-fabricated evidence, IP in training data, the DPDP Act 2023, the EU AI Act, the SC White Paper). The law-of-AI strand is itself a growing practice area NLU graduates are expected to be literate in.
Models Modern Academic Integrity
Students are required to use AI — that is the point — but must disclose and verify. Grading rewards judgment, verification, and process, not raw model output. The course models the very norms of disclosure and verification it teaches, giving NLUs a reflexive, defensible answer to the AI-in-assessment question.
Why it earns credit
A clean fit for the National Credit Framework
The course maps cleanly to the UGC/NEP National Credit Framework. Under the NCrF, 1 credit = 15 hours of lecture/teaching (or 30 hours practical), with roughly 30 hours of out-of-class work toward a ~45-hour total learner engagement. The course delivers 16 contact hours plus labs, readings, and assignments (~30+ out-of-class hours via the Hallucination Audit, Legal Prompt Portfolio, and capstone), giving roughly 45 learner-engagement hours — a clean 1-credit course. It is positioned under NEP as a Value-Added Course (VAC) / Skill Enhancement Course / multidisciplinary elective. These categories let NLUs approve it WITHOUT disturbing the BCI core curriculum: the BCI governs the LL.B. core, not value-added electives, and approval runs through each NLU's own academic council. For NLUs wanting a fuller elective, a scaled 2-credit variant (~30 contact hours) is available on request. The course is rigorous enough for credit, with eight defined programme learning outcomes, graded assessment (participation/polling 10%, Hallucination Audit 20%, Legal Prompt Portfolio 20%, group AI-assisted exercise 20%, capstone 30%), and rubrics emphasizing correctness of verification, soundness of prompt strategy, awareness of bias and sycophancy, ethical handling, and reflective insight.
What it does for employability
The verification-disciplined junior firms and the bench now want
Firms and the bench want AI-competent, verification-disciplined juniors. AI is already embedded in Indian legal practice — the Supreme Court runs SUPACE, SUVAS, and TERES, and firms like AZB and Shardul Amarchand use Harvey — so graduates must actually operate these tools. But operating them badly is now sanctionable: the SC held in 2026 that citing AI-fabricated case law is misconduct, and courts have imposed costs and recalled orders (Bombay HC Rs 50,000 cost; ITAT recall after reliance on fictitious case law). Employers therefore need juniors who can prompt AI effectively, match the right tool to the task (research engines vs. drafting vs. review vs. discovery), interrogate output, and verify every citation and proposition to source with a documented trail. The course produces exactly that: graduates who treat verification as a professional duty, understand confidentiality limits (never paste privileged data into public LLMs), and can pair human judgment with machine speed — the 'centaur' lawyer Susskind describes. The capstone — a verified AI-assisted work product with a verification trail and reflective essay — is itself a portfolio piece demonstrating this discipline to employers.
What it needs
Light to host
No specialized computer lab. Bring-your-own-device, one standard room, Wi-Fi, and a presenter tool stack we provide.
Devices (BYOD)
Bring Your Own Device: students use their own laptops for the hands-on AI labs and their own phones for live polling — there is no specialised lab or hardware to provision. NLU students already have the devices and, crucially, need to operate the AI tools themselves.
Room
One standard room with a projector. Cohort size of 30-60 works well for the labs and is scalable with TAs. No specialized computer lab required.
Connectivity
Wi-Fi sufficient for students to run AI tools on their laptops and vote on their phones. Because Wi-Fi and model variance can disrupt live demos, the presenter pre-tests all prompts and keeps fallback screenshots.
Presenter tool stack
Live AI demos run on a chatbot plus real legal-AI tools from the presenter's laptop via the projector. A commit-then-reveal polling app (yes/no, 0–10, and 0–100 inputs, with a Group A/B split for the priming demo) runs locally from the presenter's laptop; a hosted tool such as Slido or Mentimeter is an accepted fallback.
Lab tooling
Default lab stack: a generalist model (Claude/ChatGPT) plus free Indian Kanoon and trial access to one grounded legal-research tool, so students can compare a generic chatbot against a grounded, citator-backed engine.
Delivery schedule
8 modules x 2 hours = 16 contact hours, deliverable as 8 weekly 2-hour sessions or as an intensive over 4 days (two modules per day). Each module is ~70 min teaching/discussion plus ~50 min hands-on lab.
How to start
Start small, or go all in
A scaling offer — try a single class, run the full credit course, or have us equip your own faculty to deliver it.
- 01
Single-module guest lecture
A standalone session drawn from one module — for example the cautionary-case 'why' (Module 1/2: Mata v. Avianca, Gummadi Usha Rani, the Bombay HC cost order, and why the machine invents cases) or the 'verify' module (Module 4). A low-commitment entry point that showcases the Mirror Move and live AI demos for a single class or seminar.
- 02
Full credit course
The complete 16-contact-hour course delivered for academic credit — eight 2-hour modules with embedded Mirror-Move demos and hands-on labs, the full graded assessment scheme and rubrics, the capstone, and the course companion website, packaged as a 1-credit VAC (with a scaled 2-credit variant available) for submission to the NLU's academic council.
- 03
Train-the-trainer
Equip the NLU's own faculty to deliver the course in-house — handing over the syllabus, module decks, lab guides, assignment briefs and rubrics, citation codebook, and the live-polling app, so the institution can run and re-run the course sustainably.
FAQs
Questions your council will ask
Bring it to your NLU
Request the syllabus & a call
The course exists so your graduates never file a fabricated case — the mistake that drew a sanction in Mata v. Avianca and a misconduct finding from the Supreme Court of India. Bring it to your students before the lesson arrives the hard way.
You enquire — a couple of lines is plenty.
We send the syllabus, assessment scheme & rubrics.
A call to map it to your credit framework.
We reply within one working day. No commitment — the syllabus is yours to evaluate. Or write to hello@computationalthinking.ai.