AI Literacy as Disciplinary Practice
Venue: Jadavpur University One Day Hands-on Workshop & Roundtable
Proposed by GreenAI Services Pvt. Ltd. (DPIIT-Recognised AI Startup · Kolkata · Mumbai) in academic collaboration with the School of Cognitive Science, Jadavpur University
Large Language Models produce fluent, confident, well-structured text. This fluency is precisely what makes them dangerous in academic settings. A paragraph that reads well is not necessarily a paragraph that reasons well — and this distinction is the central intellectual challenge that generative AI poses to every department in the university.
This programme equips faculty to critically evaluate what AI produces, identify where it fails within their own discipline, and make sovereign decisions about when, whether, and under what conditions to deploy it in research, teaching, and institutional governance.
Mandates integration of emerging technologies into faculty development with disciplinary rigour and verified outcomes.
Calls for critical AI literacy — the capacity to evaluate, interrogate, and responsibly deploy AI, not mere tool familiarity.
Not merely referenced but taught — a dedicated session on compliance obligations that directly affect academic AI use.
Recommends experiential, project-based learning embodied throughout the day's facilitated sessions.
Three parallel tracks — STEM & Formal Sciences, Social Sciences & Economics, and Humanities, Arts & Philosophy — within a single cohort. Every hands-on exercise, prompt template, and critique methodology is calibrated to the epistemic norms of each field.
Most AI workshops foreground prompt engineering — how to get better outputs. This programme inverts that emphasis. The core competence developed is critical verification: the ability to identify what an AI has misrepresented, whose knowledge it has erased, and what epistemic assumptions it has silently imported.
Data protection is not relegated to a compliance footnote. A dedicated session unpacks the DPDP Act as it directly affects faculty who use AI in research, teaching, and student assessment — covering consent architectures, data fiduciary obligations, and cross-border data flows to LLM providers.
Demonstration of autonomous, multi-step AI workflows that can execute complex academic tasks such as literature synthesis across 50 papers, systematic data extraction, multi-source fact-checking etc.
The workshop goes beyond conversation: participants draft discipline-specific AI use statements that can be used as a feed for framing institutional policy.
All participants attend the same plenary sessions and panel discussions, but hands-on exercises are customised by track. This respects the epistemic diversity of JU's faculty without fragmenting shared intellectual experience.
Conducted entirely live and on campus. Click any session to expand details.
This programme brings together faculty members and experts from STEM, Social Sciences, Humanities, Law, and Computer Science, drawn from some of India's foremost institutions.
A unified, DPDP-compliant interface integrating multiple frontier LLMs under a single academic login. Compare outputs across models — making bias, variation, and failure modes visible in ways no single-model experience can.
Complimentary token allocation included · Isolated per-participant data vaults · Full DPDP 2023 compliance · On-premise deployment option available
Upon completion, participants will demonstrate the ability to: