For law schools
Bring a single-credit AI course to your law school
Computational Thinking and AI in Law is a 16-hour, hands-on course: 8 sessions × 90 minutes (60 taught, 30 hands-on), 2 Conversations with Experts and a 60-minute evaluation. India-first, current, purpose-built for law students, and designed to pass through your own academic council without disturbing the BCI-governed core.
- 16 contact hours
- 8 sessions + 2 expert conversations + evaluation
- Single credit
- BYOD · phones as clickers
- Built for law students
Why adopt it
What this gives your students
Future-proofs your graduates
AI is already in Indian courtrooms and firms: the Supreme Court runs SUPACE, SUVAS and TERES, and large firms are deploying legal-AI tools. This 16-hour course teaches students to prompt AI well, read its output critically, verify it, and know when it cannot be relied on. It turns AI anxiety into professional competency.
Protects students from career-ending mistakes
Indian courts already impose consequences for AI-fabricated case law: the Bombay High Court ordered ₹50,000 in costs for citing a non-existent judgment (Deepak v. Heart & Soul, 2026); the ITAT Bengaluru recalled an order built on fictitious citations (Buckeye Trust); a US court sanctioned the lawyers in Mata v. Avianca. In July 2026 the Supreme Court of India held that citing unverified AI-generated judgments is misconduct for an advocate (Pooja Ramesh Singh, 2026 INSC 668), having first observed as much in a pending matter, Gummadi Usha Rani v. Sure Mallikarjuna Rao. The whole course is how not to be the lawyer in Mata.
Half taught, half practised
Each 90-minute session is 60 minutes of instruction and a 30-minute guided lab on the students' own laptops, with a timed run of show, a fixed deliverable and a verification checklist. The taught hour is a mirror (an experiment on the class, then on a real model) or a build-along (the class builds the prompt, workspace or pipeline with the presenter). Everything taught is then practised.
Computational thinking, taught through reasoning students already do
Decomposition is issue-spotting; pattern recognition is analogy from precedent; abstraction is extracting the ratio; algorithm design is applying a legal test. No quantitative background is assumed; every technical idea arrives through an experiment on the class or a build-along, and a demonstration on a real model.
Purpose-built for law students
Every example, experiment and assessed piece of work is drawn from legal education and practice. Sessions 1–6 build the toolkit for thinking clearly about AI and verifying what it produces; Sessions 7–8 apply it to legal research, practice and the professional duties that govern it, with two Conversations with Experts alongside.
Models modern academic integrity
Students are required to use AI, and required to disclose and verify it. Grading rewards judgment, verification and process over raw output. The course models the norms it teaches, giving an institution a 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: 1 credit is about 15 hours of teaching plus roughly 30 hours of out-of-class work, around 45 hours of learner engagement. This course delivers 16 contact hours (eight 90-minute core sessions of 60 taught plus a 30-minute lab, two 90-minute Conversations with Experts, a 60-minute evaluation) plus readings and graded work of about 30 out-of-class hours. It can be offered under NEP as a Value-Added Course, Skill Enhancement Course or multidisciplinary elective, approved through the institution's own academic council, without disturbing the BCI-governed LL.B. core. Eight defined learning outcomes, a dedicated in-class evaluation and a rubric-based graded scheme (see Assessment) make it rigorous enough for credit.
What it does for employability
The junior firms and the bench now want
Firms and the bench want AI-competent, verification-disciplined juniors. AI is already embedded in Indian practice (the Supreme Court runs SUPACE, SUVAS and TERES), so graduates must operate these tools, and operating them badly is now sanctionable: Indian courts have imposed costs and recalled orders over AI-fabricated citations, and the Supreme Court has held that citing unverified AI-generated judgments is misconduct for an advocate (Pooja Ramesh Singh, 2026 INSC 668). Employers need juniors who can prompt effectively, match tool to task, interrogate output, and verify every citation to source with a documented trail. The course produces graduates who treat verification as a professional duty, understand confidentiality limits (never paste privileged data into public LLMs), and pair human judgment with machine speed. The Hallucination Audit, a seeded memo verified to source with a repeatable trail, is itself a portfolio piece.
What it needs
Light to host
No specialised computer lab. Bring-your-own-device, one standard room, Wi-Fi, and a presenter tool stack we provide.
Devices (BYOD)
Students use their own laptops for the labs and their own phones for live polling; there is no lab or hardware to provision. They already have the devices, and they need to operate the tools themselves.
Room
One standard room with a projector. A cohort of 30–60 works well and scales with teaching assistants. No computer lab required.
Connectivity
Wi-Fi enough for students to run AI tools on laptops and vote on phones. Because Wi-Fi and model variance can disrupt live demos, the presenter pre-tests every prompt and keeps fallback screenshots.
Presenter tool stack
Live AI demonstrations run on a chatbot and real legal-research tools from the presenter's laptop, on the projector. Polling uses the course's hosted commit-then-reveal app (computationalthinking.ai/live: yes/no, scales, multiple-choice, numeric and word-cloud questions, with a Group A/B split for the anchoring experiment) on students' own phones; a hosted third-party polling tool is an accepted fallback.
Lab tooling
Default stack: a generalist model (Claude/ChatGPT/Gemini) plus free Indian Kanoon and, where available, trial access to one grounded legal-research tool, so students can compare a generic chatbot against a grounded, citator-backed engine.
Delivery schedule
16 contact hours: eight 90-minute core sessions (60 taught + 30 lab), two 90-minute Conversations with Experts, a 60-minute evaluation. Delivered weekly (one core session a week; conversations and evaluation scheduled into the sequence) or as a four-day intensive. Dates and fee are set with the host.
Expert conversation speakers
Each Conversation with Experts is an instructor-led conversation with a practitioner, tied to material already taught: 'Inside the firm — what AI actually does to legal work' (Sessions 1, 3 and 6) and 'Building with AI in-house — harnesses, tooling, workflows' (Sessions 4–5 and 7). Speakers are confirmed with the host, which is welcome to propose practitioners from its own network.
How to start
Start small, or go all in
- 01
Single-session guest lecture
A standalone 90-minute session from the course: the mechanism hour (Session 2: the Ladder of Misinference, anchoring run live on the room, the cautionary cases) or the research workflow (Session 8: the four-step authority check). A low-commitment way to show the live experiments and AI demonstrations to one class or seminar.
- 02
Full single-credit course
The complete 16-contact-hour course for academic credit: eight 90-minute core sessions, each with live experiments and a 30-minute lab; two Conversations with Experts; a 60-minute evaluation; a full assessment scheme with rubrics; and this companion website, packaged as a single-credit VAC for the academic council.
- 03
Train-the-trainer
Equip the institution's own faculty to deliver the course in-house: the syllabus, session decks, lab guides, assignment briefs and rubrics, the citation codebook and the live-polling app are handed over, so the institution can run and re-run the course.
Ready to map it to your credit framework?
Request the syllabus & a callFAQs
Questions your council will ask
Bring it to your law school
Request the syllabus & a call
The course exists so your students never file a fabricated case: the mistake that drew a sanction in Mata v. Avianca, a ₹50,000 cost order in the Bombay High Court, and the Supreme Court of India's July 2026 holding that it is misconduct. Bring it to them before the lesson arrives the hard way.
- 01
You enquire. A couple of lines is plenty.
- 02
We send the syllabus, the session plan, and the assessment scheme.
- 03
A call to map it to your credit framework and calendar.
We reply within one working day, and the syllabus is yours to evaluate with no commitment. Or write to [email protected].