AI, Data Analytics & the Gig Economy

Inside the room

The programme opened online with identity, faculty expectations and the human purpose of the classroom. The second half introduced Ollama and installing local language models: bringing an AI model onto a laptop rather than relying only on a hosted conversational interface.

• What academic work would we like help with?
• What should remain a human responsibility?
• If AI explains a subject well, why come to the classroom?
• Introduced Ollama installation and choosing a local model suited to the laptop’s resources.

Inside the room

Saransh Dua’s session explored data beyond numbers: voice, text and continuous observations. Faculty then worked with prompting and prepared the tools for turning data into a working prototype.

• Revisited the opening questionnaire and discussed what counts as data.
• Read p27.md, a customer–AI-agent conversation, and drafted five questions ourselves before comparing them with ChatGPT’s questions.
• Distinguished count-based questions, categorisation and inference; explored role prompting and meta-prompting.
• Set up Codex and accounts for GitHub and Netlify; setup was a starting point, not a completed deployment.

Inside the room

The morning began with learning, reflection, gratitude and identity. Faculty recalled their earlier experience, wrote it down and used AI to shape a LinkedIn post. In the afternoon, that movement from experience to artifact continued through research tasks, skills and a website build.

• Discussed sleep and learning, retrieved the previous day’s experience, and shaped a learning log and creative LinkedIn post.
• Revisited identity, gratitude and courage, alongside physiology, emotion, feeling, thought, habit and performance. Living and observing were framed as the researcher’s own starting responsibilities.
• Mapped current research practice, then created recurring research tasks and reusable skills in Codex.
• Used p27.md to build an interactive representation, kept code versions in GitHub and served the result through Netlify.
• Set a follow-up challenge: create and publish a visual résumé.

Inside the room

The day opened by reviewing three faculty-created visual résumés. Their similar appearance led to a question: when everyone has access to the same tools, what makes the work distinctive? The discussion returned to taste, lived experience and observation, then to capturing those observations in a second brain. In the afternoon, faculty used the Codex → GitHub → Netlify workflow to make research and teaching topics interactive.

• Reviewed three visual résumés and discussed how taste and personal context can make similar AI-assisted outputs distinctive.
• Explored Roam Research and Obsidian as second-brain approaches, connecting captured notes through links and tags.
• Used Brownian motion and IoV’s systems examples to explore clickable, playable explanations; faculty worked on interactive versions of research or teaching topics.

Inside the room

Barinder Sethi led the final-day session on AI-enabled transformation. The photographs record him presenting to faculty at VIT on 5 October.