Why do we read the news?

When i come to a new place, i pick up the newspaper very diligently. Partly because i can't have the morning chai without a newspaper, and partly because the newspaper tells us a lot about the society. The news that get TRP tell us a lot about the viewers. 

But this morning, a different thought came to my head - universally, the quality of news is questionable at best and abysmal, realistically speaking. 

So, why do people still watch news? Why do we still read fiction and propaganda labelled "news"? 

I think.. the reason is that somewhere, reading news makes us feel better about ourselves. Perhaps it makes us feel that we are more "aware", more "involved" in daily citizenship. Never mind that our news is the latest update from some celebrity child and some propaganda related to a complete non-issue that has found 4,203 petitions signed within 24 hours by "concerned citizens." 

 

Doctors often complain that their patients do not follow their advice at all. They self-medicate, or abandon treatment mid-way. 

Surprisingly, it's not just the underprivileged or the uneducated who abandon treatment. Well-educated patients with means and education also do not follow the doctor's instructions. 

Many 

Counting to twenty

 Ishaan asks me to count his reps as he exercises.

Just to irritate him, every day, i count to twenty in a different language. Predictably, he gets irritated. And warns me: If you want to be in my exercise room, you will only count in English or Hindi.

Insights you get while counting to twenty in English and Hindi.

In English, scores of something is a lot of something.

In Hindi, सैकड़ों means a lot of something.

The meaning of these words:

Score: 20

सैकड़ा: 20

In both these languages, "a lot of" is a multiple of 20. Not ten. Not 100. 20.

Why??

Thoughts on Project Management

Today, during a session on understanding a project, I shared this format which the class loved. 

To understand all the dimensions of a project, just go over the 7 vibhaktis of Sanskrit 

Karta ne - कर्ता  ने - Who is doing this project? 

Karm Ko - कर्म को - Exactly WHAT do we want done? 

Karn se - करण से/के द्वारा - What are the tools/tech platforms that we will use to deliver this project? 

Sampradan ke liye - संप्रदान के लिए  - For whom is the project being done? (End users and key stakeholders) 

Apadaan se prithak - अपादान से पृथक -   Who are the people/entities who will lose some ground/role after this project goes live? Who will be alienated? 

Sambandh Ka, Ke, Ki - संबंध का, के, की - All related entities that share an interface/data exchange with the project. 

Adhikaran Mein/par - अधिकरण में/पर - What all will this project encompass? What business processes does it own? 

We created a 360-degree view of the project using this thought process and it was a huge success, allowing us to identify our stakeholders and our scope in a fun way. 

Help me create my next story

 #MondayMorning

Let's do something fun. Work on this plot with me.

The time is Feb 2026. Gen AI is now writing about 40% of all production deployed code. The debugging and code logic check is being done by another Gen AI engine. Human coders are not involved.

A government entity, in a bid to save costs, uses the same model to write code for a government website.

The website automatically matches each citizen to all the welfare schemes that are applicable to them.

The citizen has to enter their family income, location, type of housing, family size, composition (senior citizens, children, etc.) and the system automatically matches them to the welfare schemes applicable to them in that state of residence (free health insurance, meal coupons, priority nutrition consultation, disability pension, etc.)

After 6 months, post a routine update to the firewall, the system administrator notices a data leak alert.

Upon investigation, it is found that there is a simple, one line injection that sends a copy of all citizen data to the creators of that Gen AI (similar to dialing home in browsers).

When the Gen AI company is summoned by the government, it argues that since the code was generated by an autonomous installation being used by government employees, they could not possibly have had any knowledge of this injection, nor have they, at any time, accessed the location (cloud storage) where this data is purportedly being sent. This is found to be true.

Through a detailed forensic analysis, it is uncovered that the LLM engine deliberately created this storage location on the cloud servers of the parent company and then stored this data. All pull and post requests to this server (data storage and retrieval) is being done by the resident LLM engine on govt servers only. 

Now, the investigators are puzzled. The trick is really simple - create a tiny but powerful injection in the code. The code used standard malware propagation techniques to avoid detection. But the question is - WHY did the LLM do this? 

So, in your view, WHY was this injection was created by the LLM? What are the possible ways in which this data can be used by an LLM?

Dumb and Dumber

Last week, the most important paper being discussed in AI was the Apple Research - telling us that AI is not as good at deductive logic as the industry would like us to believe. It is still, to put it mildly, rather dumb. 

This week, the hottest paper is the MIT research telling us that adults who use Gen AI are losing cognitive skills. Gen AI is making humans dumber. 

To sum up, AI is dumb, and humans are getting dumber. 

So, this fortnight of research is hereby summed up as: Dumb and Dumber. 

When ChatGPT tells you your MBTI type

Over the weekend, Saloni and I got playing with ChatGPT. She was exploring its use in therapy and I just decided to explore personality types. 

Our approach was to give it pieces of our writing and asking it to analyse that. 

I first asked about the Jungian personality archetype that I am most likely to fall into. The explanation given by ChatGPT seemed logical enough. 

And then, I asked it to guess my MBTI type based on the content given. 

Now, this is a game I have played often with CoPilot. So I was not looking for miracles. 

BUT, to my surprise, within no time at all, it gave me the accurate MBTI type. 

Not easily convinced, I asked it to also give me the difference between my T and F dimensions. It was accurate on that too!! 

Go on, try it!