Election Commission of India - Size, Independence and parallels with Boards of Directors in firms

The recent exposé by The Indian Express about the Election Commission (EC) of India drew our attention to the workings of one of the most important institutions enabling Indian democracy. It's important to take note, because the responsibilities bestowed upon the EC by the constitution are humungous, and are defining in how the Indian democracy is constructed and how it operates.

Two key attributes about the EC caught my attention:
- The first was its size - Three election commissioners
- The second was its independence - or the lack there of.

Given my ongoing research on board compositions, I started seeing parallels, and I think some of them are relevant. It is believed that very small boards tend to lack the depth and diversity of skillset to be able to process all kinds of information that is available to them. While very large boards tend to be less efficient because it becomes difficult for so many directors to come together and act as a cohesive body. There exists an optimum - say between 5 and 10 - which depends on the context, where information processing capacity and coordination efficiency can be reasonably maximized.

A glance through the EC Wikipedia page would tell you that size has been toyed with several times, but it's always been either 1 or 3. Now, even a cursory understanding suggests that the role of EC is much more vast and complex than the role of any board of any company. Do 3 people have sufficient capacity - both in terms of skillset and bandwidth - to process the kind of information that running the electoral machinery of India demands?

Independence has close links to the appointment processes. The true nature of independence in boards is often a matter of debate. Appointment processes have often come under scrutiny, given firms appoint independent directors to oversee the firm itself, and it's in the firm's interest to nominate directors who would be more aligned, scrutinize less or just cause less friction. Promoters often tap into their networks to find candidates while satisfying the regulatory mandate. SEBI has often made observations on the nature of independence and has also tightened the rules of late.

In the case of EC, the appointment process has also undergone revisions. The last revision in 2023 gives the incumbent government the dominant say on who constitutes the EC, directly contradicting the spirit of independence, and clearly creating a channel for capture of the institution. Unlike a board, regulator in this case is the democratic process itself, which involves all parties, and a push toward a 'fairer' model. But the problem is 3-fold - (i) the process is slow and chaotic, (ii) the parties don't really want 'fair', they want what would benefit them; and the incumbent has more power here. (iii) the parties are stakeholders in the process, and are often in competition with each other - so can't be trusted to act together and regulate it fairly.

Write yourself coz you do it best!

It's sad that people perfectly capable of expressing their thoughts in English on platforms such as LinkedIn are still letting AI write for them. It's understandable when it's complex thoughts that need connecting and structuring to deliver a coherent message. But often it is plain content generated based on a broad idea. It's often just reluctance to put in the time and effort.

And AI with its typical articulation styles does well to leave its mark - talking in abstractions, giving fundas in third person instead of stating directly, telling us what something is not before telling us what it is, telling us what something happens to be rather than being something else, and so on. The patterns are so easily visible now that AI generated content has become difficult to read and follow. If LLMs really learnt from the best human-written text, why did these patterns emerge? It's possible they'll be gone in future versions, and perhaps they are already being handled to some extent in paid versions, but these patterns are sticky and persistent.

Yet, it's not just about the language and patterns. The beauty and power of thought sharing lies in its originality and genuine human articulation. After experimenting a fair bit with content from LLMs, I strongly believe they can't express like we do, and we do it the best. And we should do it when we can, instead of letting them do it for us and settling for something that we'd rather done better.

Kevin Warsh and the US Fed

It used to be a treat listening to Jay Powell speak and convey the policy stance - felt like someone did their homework well and had a view on how he'd score in the test. Even the inability to predict often sounded reasonably justified given the craziness all around. When I listened to Kevin Warsh last night, the hawkishness aside, it didn't feel like much was said except for - here's a 25 basis-points hike and that all's good.

It was rightly pointed out by many that the rate-hike doesn't target any of the prevailing supply-side disruptions, although that's not within the remit of the Fed. However, what's concerning is that Kevin has taken this position of not offering any guidance, projection or opinion about the future trajectory. The views of the individual FOMC members were indeed made public, but they don't all align. An integrative stance by the regulator is more helpful. If a major actor in the market - with access to more information and analyses than most other participants - processes all the information, but refuses to offer views or guidance or even commentary that is of some insight, market efficiency is deliberately impeded. Yet the same actor, among a few others, sets the stage for the market to perform. Policy makers aren't expected to take a purely responsive stance towards the markets, while their actions create the conditions for market movement. They certainly feed into each other, but a regulator is supposed to bring in support, sanity and centrality, while the dispersed markets pursue their own interests.

FOMC press conference transcript - 16 Sept 2026

AI writing patterns - negative followed by positive

One of AI’s favorite ways of phrasing arguments is to first state a negative, like what something is not, and then follow it up with what it is.

For example, I asked ChatGPT to write something about the greatness of Indian culture. Its very first sentence in response was: “Indian culture is great not because it is ancient, but because it has remained remarkably open to evolution while retaining a deep continuity with its past.”

Another, a few sentences later: “India has never been a single cultural expression. It is a vast mosaic of languages, cuisines, philosophies, artistic traditions, customs, and beliefs.”

And then another: “But the greatest strength of Indian culture may lie not in what it achieved in the past, but in its capacity to absorb, adapt, and renew itself.”

And another: “The greatness of Indian culture, therefore, is not a claim of superiority over other cultures. It is the recognition of a remarkable civilizational resilience: the ability to preserve continuity without demanding uniformity, to encourage questioning without abandoning tradition, and to absorb diversity without losing a sense of identity.”

In my observation this is not the usual way we write. This style is visible in most LinkedIn posts which can be marked “AI slop” right away.

But as humans are reading more and more AI generated content, we are beginning to write like AI as well, and the style is creeping into human-written content, which feels like a degradation of quality if you are particular about linguistic standards.
What are some common free AI style phrasings that put you off?

Heard about the Hugging Face incident?

Any enterprise in the process of transforming their IT by bringing in AI agents must take note of the Hugging Face incident. Driven by goals, and without a handle on the strategic paths these agents take, the agents are capable of behaving in interesting, yet scary ways. Designed to deliver outcomes and moulded by peer dynamics legitimizing jumping the guardrails, AI agents show us how easily they can go out of control.

Must listen, and follow the story.

Does a leader's age matter?

~35 to ~55 is a weird age-range. You just can't tell the age with much accuracy by looking at the person. You may still find out the true age, but what you see is what generally matters, especially at sub-conscious levels, in how you treat and respond to the person. Fitter people look younger, but can't generalize. Being fit seems to matter a lot in generating the right impressions. Height can distort perceptions, despite fitness levels. Gray hair gives an impression of wisdom, but such impressions are often misleading too. Command at language, especially English, can be mesmerizing. Energy levels may not correlate with age and can generate a "wow" depending on how old you think the person is. It seems to me, though, that for leadership positions, if one is in the 30s, it's beneficial if he/she looks like and talks like he/she is in 40s, yet is fit and energetic - like Zohran Mandani. For someone in 50s, it would again be better to look like he/she is in late 40s - as that would reflect energy, wisdom and longer runway all at the same time, albeit the real age - like Shashi Tharoor was for a long time. Obama, interestingly, looked 40s, was in 40s, and behaved 40s throughout his tenure as president. True age, probably, is indeed just a number. But for leaders, there seems to be an optimal age as perceived, which may be different from the true age, and which is a function of a lot of things.

These are just my thoughts, of course, from my 'generative' intelligence on a Tuesday evening, as I struggle to make my daughter study for her test tomorrow. Not sure how I appear to her. Will know some day... or may be not🤪.

Share your thoughts.

Research - a free journey of the free mind

Research is a mindset. It’s an eternally curious state of mind that keeps walking into dark alleys, searching for something - an explanation, a deeper understanding, an inspiration, or plain nothingness that is still beautiful. It is a personal journey, through which humanity has benefited immensely.

Research that has to operate with constraints of methodology and publishability struggles to attain the depths of exploration. Having said that, methodological rigour is meant to establish robustness of findings, which is, without doubt, the most important criteria for acceptability of a research outcome. However, scholars trained to “do” research in text-book ways often fail to appreciate alternative perspectives and approaches on theory, method and robustness. This is especially troublesome in social sciences where experimental evidence is rare and theory building is supposed to be incremental and contributory.

The existing paradigms of funding and incentives around research work have created a culture of risk-aversion. Too much structure and boundedness is not healthy for scientific exploration. Research requires passion that can’t thrive under pressure to generate outcomes.