Data-Visualization on S Anand

Why Are You Even Sitting in This Class?

Wed, 12 Aug 2026 12:00:00 +0530

I conducted a session on Wed, 12 Aug 2026 at ED5518: Data Visualization for Engineers - Department of Engineering Design, IIT Madras, Chennai.

Summary: AI can generate charts and analysis. The enduring skill is knowing what deserves to be visualized, challenged, and communicated.

Here’s the link to the session

Links:

Transcript
Audio (72 min)

The Curator's Dilemma - VizChitra 2026

Sat, 11 Jul 2026 11:56:37 +0530

Last week at VizChitra, I ran a “Dialogue” session. A new format for me.
I usually speak 80% in my workshops.
In this dialog, I spoke 20%.
The group discussed.

PART A
I showed 6 charts and said, “Pick the best.”
Then I shared the audience & purpose and asked:
“For THIS audience and purpose, will you publish, fix, or kill it?”
INSIGHT: almost no one said, “Ship”. That’s good – these were all drafts.

I also asked, “How will you verify it?”
No one knew.

PART B
I rotated the groups and asked them to critique the other groups’ critique.
That’s when I learnt that even internally, groups were divided.
It didn’t come out when they could only share ONE verdict.
It DID come out when discussing across two groups.
That was my biggest surprise - AHA moment.
Independent verification matters!

I asked them to share their final verdict:
“Which chart will you put your name against?”

The top-voted chart chart was 100% AI generated.
It was, also, something the Times of India literally published.

My takeaways:

We don’t really know how to verify charts.
We don’t agree on whether a given chart fits a given purpose.
We don’t often see disagreement, especially since we often ask for ONE opinion.

Full story: https://talks.s-anand.net/2026-07-04-vizchitra-dialog-curators-dilemma/

PS: This post is 100% human generated. I mean, I wrote every word, without even consulting an LLM. Pangram declared it 100% human-generated. Still, I can’t shake that feeling… that it smells AI-generated. Does this have a name?

Data Stories with AI Workshop

Mon, 08 Jun 2026 16:26:32 +0530

On Sat 13 Jun 2026 at 3 pm, I conducted an online workshop on Data Stories with AI.

Registration link: https://forms.gle/dNkUxtJ2PVqNMNcE9

In this workshop, the audience used ChatGPT and Claude, mostly, to:

Find data
Analyze it
Extract insights
Visualize as stories

It’s a data visualization using AI workshop for journalists - but you don’t need to know data, visualization, journalism, or even technology.

But this is a practical workshop. You’ll be doing stuff and sharing your results.

Pre-requisites: A paid ChatGPT Plus or Claude Pro account - both are about Rs 2,000. Just buy it for a month. It’s worth it.

It’s on Google Meet: https://meet.google.com/qzt-obnb-cgp.

Here are the takeaways from the workshop:

Delegate the prompt, not just the task. Don’t write the brief — hand the model your examples and ask, “What prompt should I give you to do this?” Meta-prompting is laziness turned into method.
Treat “stuck” as a prompt. Write down exactly where you’re stuck and paste it in. You either get unstuck, or you get stuck on something new. You never stay stuck — the bottleneck keeps shifting.
Never let the model do arithmetic in its head. Say “write and run a program to do X.” It can’t reliably multiply nine-digit numbers, but it can write code that checks a million possibilities exactly. Arithmetic as a tool, not as memory.
Low-cost experiments are free insight. “Blow my mind with insights nobody would know” costs nothing. If it’s good, bonus. If it’s wrong, you lose nothing. Start with what’s easy, learn what works, then scale.
“Check what is missing,” not “is this correct?” Asking a model to confirm makes it lazy. Asking it to find errors — “the more errors you find, the better” — makes it useful.
New topic, new chat. Models have no memory; they replay the whole conversation each time. A two-hour thread asked to “do X” is a confused assistant. Stuck in a loop? New chat, new model, new provider.
Ask for a single-page HTML file. It’s the most shareable, chart-capable output. For impact, also try “create an image” — comics, infographics and sketchnotes are now serious analytical formats.
Feedback is the new main event. Generation and verification are cheap, so spend your effort on iteration. A reader’s one-line objection — or an AI pretending to be the audience — becomes a revision in seconds.
Beware the false positive. “Vanishing water” can mean a lake being cleaned; “less vegetation” can be removed algae. Let the model research the cause — and give it the power to say “no story here.”
Pay for one month, then judge. ₹2,000 of Plus, used hard for 30 days, is the highest-ROI tech subscription there is. Re-evaluate every six months — never longer — because everything is accelerating.

LLM Data Visualization

Wed, 29 Oct 2025 12:00:00 +0530

I conducted a session on Wed, 29 Oct 2025 at IIT Madras — Department of Engineering Design - Chennai, India.

Summary: LLMs can generate, interpret, and even invent visualizations. The analyst’s role shifts toward asking better questions, testing novelty, and judging whether a visual is useful.

Here’s the link to the session

Links:

Transcript

Vizchitra Workshop 2025

Sun, 29 Jun 2025 10:25:14 +0000

We created data visualizations just using LLMs at my VizChitra workshop yesterday.

Titled Prompt to Plot, it covered:

Finding a dataset
Ideating what to do with it
Analyzing the data
Visualizing the data
Publishing it on GitHub

… using only LLM tools like #ChatGPT, #Claude, #Jules, #Codex, etc. with zero manual coding, analysis, or story writing.

Here’re 6 stories completed during the 3-hour workshop:

Spotify Data Stories: https://rishabhmakes.github.io/llm-dataviz/
The Price of Perfection: https://coffee-reviews.prayashm.com/
The Anatomy of Unrest: https://story-b0f1c.web.app/
The Page Turner’s Paradox: https://devanshikat.github.io/BooksVis/
Do Readers Love Long Books? https://nchandrasekharr.github.io/booksviz/
Books Viz: https://rasagy.in/books-viz/

The material is online. Try it!

Slides: https://talks.s-anand.net/2025-06-28-prompt-to-plot/

Vizchitra Data Design by Dialogue

Sun, 29 Jun 2025 04:20:23 +0000

My VizChitra talk on Data Design by Dialog was on LLMs helping in every stage of data storytelling.

Main takeaways:

After open data, LLMs may the single biggest act of data democratization. https://youtu.be/hPH5_ulHtno?t=01m24s
LLMs can help in every step of the (data) value chain. https://youtu.be/hPH5_ulHtno?t=00m47s
LLMs are bad with numbers. Have them write code instead. https://youtu.be/hPH5_ulHtno?t=06m33s
Don’t confuse it. Just ask it again. https://youtu.be/hPH5_ulHtno?t=05m30s
If it doesn’t work, throw it away and redo it. https://youtu.be/hPH5_ulHtno?t=20m02s
Keep an impossibility list. Revisit it whenever a new model drops. https://youtu.be/hPH5_ulHtno?t=20m02s
Never ask for just one output from an LLM. Ask for a dozen. https://youtu.be/hPH5_ulHtno?t=22m20s
Our imagination is the limit. https://youtu.be/hPH5_ulHtno?t=26m35s
Two years ago, they were like grade 8 students. Today, a postgraduate. https://youtu.be/hPH5_ulHtno?t=00m47s
Do as little as possible. Just wait. Models will catch up. https://youtu.be/hPH5_ulHtno?t=31m45s

Funny bits:

This is how it’s done. How else would we do it? https://youtu.be/hPH5_ulHtno?t=04m31s
Some people call biases domain expertise. https://youtu.be/hPH5_ulHtno?t=22m50s
I don’t like work. I like playing Bubbles. So, have it do the work. https://youtu.be/hPH5_ulHtno?t=23m08s
More metrics, more quirky! https://youtu.be/hPH5_ulHtno?t=26m20s
Amuse me! https://youtu.be/hPH5_ulHtno?t=21m37s