The Problem with Narratives

The book’s premise is : most established narratives about India are fiction masquerading as fact. Despite having one of the world’s most impressive statistical architectures—Census enumerators, National Statistical Office surveyors, the National Crime Records Bureau—Indians continue to build inaccurate narratives about how the country works. They assume vote-banks where none exist, imagine urban explosions with little reason, and decide they are middle class with little basis. These narratives, repeated enough times, become political fodder.

Numbers, she argues, can capture the nuance and humanity that pre-packaged narratives flatten out.

Belief in God, Marriage & Love

It’s claimed 97% of Indians believe in God, with Buddhists as the notable exception. Buddhist traditions do not promote belief in a creator god, focusing instead on ethical conduct and discipline to attain nirvana—the cessation of suffering. While rituals exist in many Buddhist schools, they are not central to liberation. Religion remains important to Indians: 60% say they pray daily. Education level doesn’t affect religious practice. Indians are largely indifferent to, and tolerant of, the religious practices of others.

The book examines patterns in vegetarian vs. non-vegetarian food consumption, and how food habits intersect with upward mobility. It shows that modern India remains largely conservative—more orthodox in religious practice. It explores dietary choices, alcohol consumption, and the types of alcohol preferred. Foods like poultry, eggs, fish, fruits, and legumes—often more expensive—reveal distinct consumption patterns across income groups.

Indians overwhelmingly marry within their caste. The average age gap between husband and wife is around five years. The poorest 40% of women tend to marry before 18. Richer, better-educated women marry later. Over 90% of marriages in India are arranged by families. Love marriages are more common among richer, better-educated people, and among Christians and Muslims.

Work, Money & Leisure

The book explores how Indians earn, how much they earn, and how they spend on leisure. Enjoyment varies by caste, class, gender, and geography. Most women still aren’t paid for household labor. Nearly 40% of Scheduled Castes work as wage laborers—mostly in casual roles.

Riding motorbikes and singing chants are favourite leisure activities. Rich and upper-caste groups spend more time on religious practice and have more access to media. Inter-religious marriages are seen as acts of rebellion.

Fewer than 20% of women have their names on house papers; half have a bank account in their name; only 10% can make primary purchase decisions. For women working all day, talking to someone is the most meaningful leisure—because no one listens to them.

Crime Statistics: A Cautionary Tale

One of the book’s most striking revelations concerns crime data. Rukmini’s investigation of 600 rape cases in Delhi’s district courts revealed that a significant portion were not sexual assaults as commonly understood, but cases of consenting couples whose families had filed complaints to thwart inter-caste or inter-religious relationships. The FIRs followed informal scripts—”moving cars” that abducted young women, “sedative-laced cold drinks” that rendered victims unconscious. None of it stood up in court. The cold drink bottle was the smoking gun that never appeared.

This isn’t unique to sexual crime. Her investigation of Mumbai’s mephedrone cases found that police knowingly used wrong sections of law to arrest pedlars. The result: 100% acquittal rate, with nearly 150 young people spending over a year in jail on charges the police knew were legally unsound.

The takeaway: India’s crime statistics begin from a point of significant under-reporting, and states with higher reported crime might actually be doing a better job of ensuring full reporting rather than being the most unsafe.

Human Rights, Media & Voting Preferences

There are inferences that media exposure benefits the ruling BJP more than Congress, which performs better among those with low media access. Half of Indians vote based on caste. Many are open to strong leaders and tolerate media bias, discrimination, and segregation based on caste and religion.

Human rights and freedom of expression aren’t widely prioritized. From fans to cult followers, the idea of a fair judiciary or honest elections ranks low. Yet 70% still trust their state government. Media continues to reinforce bias. Among urban graduates and postgraduates, 66.6% lean toward ethnic nationalism and majoritarian views. Ghettoisation of minorities—especially Muslims—is rampant, from physical segregation to anti-Muslim rhetoric in mass media.

Voter turnout is around two-thirds, with more women voting than ever. The surge in female voters reflects growing participation. Ironically, the poor vote because it’s their right, while the non-poor vote for material benefits or out of a sense of duty.

Indians are on the move—especially from states like UP, Bihar, and Bengal. Migrants often can’t vote. In 2015, Janagraha, a Bangalore-based trust working in the areas of urban infrastructure and citizenship, reported that 11% of voter addresses couldn’t be found, 21% had moved, and nearly 50% couldn’t find their names on Delhi’s voter list. Pollsters and journalists often frame voting as driven by caste, religion, leaders, or development—but the reality is more nuanced. After the CAA protests, Muslims voted for AAP (not Congress), even though Congress supported the agitation—because AAP was more likely to defeat BJP. Notably, BJP has no elected Muslim representative.

The Data Imperative

The book’s conclusion carries urgency. Indian official statistics are not lying to us, Rukmini argues, but they are being silenced. A combination of neglect, discredit, and dismissal makes deficiencies seem too fatal to fix. When inconvenient data is suppressed, the narrative shipped to op-ed pages is that official statistics miss too much, so we’re better off without them.

This is dangerous. For 75 years, this data has shaped policy and driven change—debates about liberalisation, poverty lines, welfare states, affirmative action, rising Islamophobia. Access to this data has empowered ordinary citizens to engage with and agitate against the State. Without it, we hollow out democracy.

Final Thoughts

First published in 2021, the datasets referred in some cases may appear dated requiring an update, however the book is an interesting read for those who are curious about modern India—and essential for anyone who wants to engage critically with the narratives we’re fed.

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Kevin spent more than five years of his life in prison before becoming a professional hacker. As a child, he was fascinated by magic, enjoyed imitating others, and performed above average in his studies. Blessed with a good memory, a knack for impersonation, and a deep curiosity about technology, Kevin developed skills that eventually made him an exceptional hacker. In his later years, he became a security consultant, founded his own consulting company, and ultimately getting paid for the very hacking skills that once landed him into trouble .

/social engineering/ Kevin had known how to manipulate people since he was a child. A smooth talker, 12-year-old Kevin once asked a bus driver where he could buy a ticket-punching device. He then searched for unused tickets in a dumpster near the bus yard. Growing up in Southern California, he spent his spare time traveling all around the county by punching his own bus tickets while his mother was at work .

Kevin had remarkable insight into social engineering techniques—people naturally trust those who can establish credibility, such as someone posing as an authorized company employee. His approach to social engineering was surprisingly simple and straightforward. Kevin would meticulously research the target company, gathering details about its departmental structure, business units, operations, employee hierarchy, senior management, and the industry-specific lingo and terminology. Armed with this knowledge, he would execute his hacking attempts with precision.

/phreaking out/ Kevin was attracted to technology and communication devices. At the age of thirteen, he built a ham radio and took the exams to obtain an Federal Communications Commision (FCC) license. Kevin learned about telephone switching and networks. He social engineered his way through the employees and security staff and entered the premises of telecom company Pac Tell in his area and collected sensitive information that would allow him to set up call forwarding & monitoring. He could dial phone numbers by manipulating tones to make free calls or access restricted lines . He started hacking the nearest McDonald’s radio & messing around with customer orders. Kevin became a member of the phone hacking community or phreakers as they were known .

/cracking the code/ Kevin was no longer interested in attending school, and at 16, he opted to complete the GED instead of pursuing a regular high school diploma. He was teaching himself about computers alongside his hacker friends. At one point, he persuaded a school administrator to share his password, allowing him to use these credentials to dial into external phone lines via a modem attached to the computer. Kevin began visiting university campuses to access free computer lab time, as this was before the era of personal computers. He later went on to hack into systems at DEC, PacBell, Motorola, Sun Microsystems, Novell, and many other companies. Kevin would befriend, cajole & pretext employees and also trespass physical premises to retrieve system admin passwords. Once inside company network, Kevin would find vulnerable systems that were not adequately patched. He then installed phishing applications, cracked passwords, and collected sensitive information from banks and the Department of Motor Vehicles (DMV), as well as source codes for operating systems.

/on the run/ Kevin did all of this for fun, for the thrill of it, and not to steal or destroy. As a juvenile, he was once certified by a counsellor as being addicted to hacking. Hacking was a way for him to let off steam and prove a point. Kevin collected passwords and source codes as trophies. He did all this in the 1980s & early 90’s, when the law had not caught up with the tech yet. Kevin spent several years in federal prison, first as a juvenile and later for about 5 years from 1995 to 2000. Kevin had a difficult childhood, however a doting mom & a grad ma, who stood by him during his incarcerations. Kevin also received grassroot support as his hacking abilities were hyped by the media & people rallied together for a “Free Kevin” movement, urging a fair trial while he was in prison. Kevin died of pancreatic cancer at the age of 59 in 2023.

/to trust is human/ Kevin’s story is one of a person constantly on the run, with the FBI always on his tail. In many ways, it’s a story of humans' willingness to trust one another, and then being taken for a ride for just doing that !

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All these frameworks though are referenced in various industries they have few things in common .

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Why are frameworks required ?

As technology advances it increases the complexity and the need for various actors, partners, suppliers and customers to collaborate. As the ecosystem grows it becomes extremely difficult to communicate with various entities involved. Then there are regulatory frameworks companies are expected to abide by in the countries they are operating in .

First, it helps to establish a common vocabulary & definition of terms, that establish a common understanding within the community of professionals and industry practitioners. Often the lines are blurred between the myriad of technological complexities professionals have to deal with today. A framework helps in establishing a baseline understanding of concepts, terminologies and the intricacies . Framework provides a structure to the discussion when people from various departments, backgrounds and experiences meet to discuss an industry solution .

Second, it helps drive best practices, documentation and standardisation of processes. Business processes are the lifeblood of any organization. It is through processes people within various groups, teams and departments understand how an organization delivers value to its customers. These are also useful in driving continuous improvements, corporate governance and formulating industrial policies for the regulators and governing authorities.Organizations of medium size and above have to maintain a sizable amount of documentation.

Third, it sets the benchmark to evaluate maturity of the organizations. Based on these benchmarks auditors conduct reviews and issue certifications. Hence, helping the industry recognise those compliant within the crowd & setting them apart. Capability Maturity Model Integration or CMMI is one such process improvement framework that helps organizations improve their performance by standardising best practices for effective processes.Its purpose is to assist organizations in building and maintaining high-quality, efficient processes that drive consistent project success.

In summary, frameworks help in establishing a common language, practices and standards that industry choose to abide by - and for the overall progress of the ecosystem by facilitating interaction, integration and interoperability .

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As an AI research engineer specializing in voice processing, Kai-Fu Lee’s team developed early voice recognition/interface technologies (such as PlainTalk, Casper, and GalaTea) that were integrated into Apple’s products and R&D during the 1990s—long before voice recognition became mainstream.

The Comparison

In his book AI Superpowers (2018), Mr. Lee compares the relative strengths and weaknesses of the U.S. and China. He uses the principle of duality—or yin and yang—to help readers understand that there is a deep difference in the cultures, organizations, and policies of these two nations.

That one nation prizes innovation, while another made its mark in manufacturing by imitating.

One promotes mission-driven entrepreneurship, while the other shaped its entrepreneurship to suit market demands. One wants to solve problems, the other has a tendency toward wealth creation. One is egocentric and bullish, the other favors mercenary or guerrilla tactics. One is driven by a lofty mindset of abundance and seeks to transform the world, while the other plays for survival, given the scarcity experienced by earlier generations. For one, originalitymatters; for the other, reverse engineering suffices. One relies on hard work, the other is extremely hard-working. While one is keen to localize, the other believes one size fits all.

Other important differentiators include product design, decision-making, subscription models, hiring and promoting local talent, and doing the legwork.

While the U.S. tends to operate on a laissez-faire model for economic policymaking, the Chinese government has adopted a hybrid approach to capitalism—offering subsidies, low-rent spaces for startups, facilitation centers, "guiding funds" invested through local governments, and delegating support functions to mayors or regional authorities.

According to Kai-Fu, the most valuable product to emerge from China’s copycat era wasn’t a product at all—it was the entrepreneurs themselves.

Through Compassion

While the central theme of the book is the advancement of AI, Kai-Fu discusses one of the most important yet often overlooked aspects of modern life—the human experience and the loneliness that the quantified world can create. Especially in a hyper-competitive, winner-takes-all environment where the premium is placed on maximizing value or profits.

Kai-Fu Lee makes a case for a more humane approach to AI. He advocates a shift—from emotionally draining, self-centered, attention-seeking uses of AI—to a technology that serves the needs of society. Not exploitative, but synergistic, emotionally fulfilling, and enabling shared progress through mutual understanding and collective prosperity.

By his own admission, this realization came after his near-death experience with cancer. The act of writing a will, spending time with a monk, and receiving love, care, and support from his family during recovery brought this side of life into focus. While not entirely oblivious to it earlier, he had approached it more as a calculated exercise.

As an engineer who once couldn’t resist being present at a product demo on the day his daughter was born—and known as an “Ironman” by his team—Kai-Fu came to realize that life is more than a value-maximization equation. It's ironic that someone who liked to discuss what his tombstone might say had to confront his own mortality after being diagnosed with lymphoma in the gut, and told he had only a few more years to live.

In essence, Kai-Fu Lee is pitching for a more compassionate world, built on the foundation of love.

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Given the AI hype, trends across social media, and widespread news coverage, almost everyone today has heard the term AI or used its most visible application, ChatGPT.

However, when it comes to what lies under the hood, there's more to it than meets the eye. With all the corporate jargon, marketing clichés, and technical terms, it can be overwhelming — even for those with a technical background — to make sense of the underlying technology.

The Takshashila Institution, a Bangalore-based policy think tank, has published an AI Primer for policymakers. Founded in 2009, it is an independent, non-partisan think tank in India. Its funding comes from individual donors, including Rohini Nilekani as the establishment donor, and from organisations such as the Shroff Family Charitable Trust, the Jamnalal Bajaj Foundation, Rohini & Nandan Nilekani Philanthropies, and the Infosys Foundation.

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/AI Primer/

AI requires specialized hardware to perform efficiently. At the heart of processing are chips fabricated in hardware foundries such as TSMC. These chips, made from silicon wafers, are known as ASICs (Application-Specific Integrated Circuits).

While the resource is intended for policymakers, it offers a clear overview of the key terms involved, helping almost anyone — especially those with an engineering background — get oriented.

It explains what AI is, outlines the training process and its inefficiencies, highlights the role of data, and discusses hardware components in detail. The primer covers terms such as GPU, CUDA, TPU, memory, networking, modes, and more. It also introduces the software ecosystem, including frameworks, programming languages, and algorithms.

Link to AI Primer .

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There are two modes of learning—methodical, procedural, and conceptual on one side, and intuitive, practical, and creative on the other. Barbara Oakley, in her book A Mind for Numbers, refers to these modes as the focused and diffusion modes. The focused mode of learning is step-by-step, allowing time for contemplation and mastering the fundamentals. In contrast, the diffusion mode is about learning through examples, memorising patterns, and relying on intuition or the gut.

Scientists, researchers, and academics tend to be more attuned to the focused mode of learning. On the other hand, entrepreneurs, politicians, and athletes often rely on the diffusion mode. These two seemingly opposing methods represent the yin and yang of human learning. One is reflective, thoughtful, and contemplative, while the other is about thinking on one's feet, getting the job done, and being action oriented.

The first approach is more relaxed, while the second is dynamic and active. However, thinking that one is superior to the other would be misleading. It’s equally important to recognise that both methods have their inherent limitations. Those who rely on a diffusion mode of learning are application-oriented and may excel at acquiring practical skills without deeply understanding the fundamentals. Meanwhile, focused learners are more analytical and logical, but their theoretical approach can sometimes make it challenging to solve real-world problems. The key lies in finding a balance between analytical and practical approaches.

The diffusion method involves learning from already memorised patterns—much like how chess grandmasters, who might not have exceptional IQs, can distinguish between various patterns they’ve learned through practice and apply successful combinations to outmanoeuvre their opponents. Magnus Carlsen, for instance, has 10,000 endgames in his memory and can recall the year and players of a match just by seeing the positions of pieces on the board.

Conversely, conceptual learners rely on deep thinking and the core concepts they’ve studied in a classroom setting. Not grasping logical proofs or derivations hinders their ability to understand analytical problems. However, those who can easily solve numerical and analytical problems with a pen and paper, may struggle to apply their classroom knowledge to real-life scenarios.

Both methods of learning are interconnected. In pre-modern times, skills were often acquired through apprenticeships under skilled masters or family elders. Japan still follows this system in areas requiring master craftsmanship, like sushi-making.

While there are undeniable benefits to linear and logical thinking, reflection, and contemplation, it’s equally important for learners—especially students—to develop memory structures, frameworks, and patterns over time. These help in recalling and applying knowledge for effective problem-solving.

In conclusion, there’s a need to bridge the gap between theoretical concepts and practical application—a learning system that harmonizes these differences and aligns with the professional skills needed for success in fields like technology, business, and policymaking.

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Investors

Ola Electric shares made their public debut on Indian bourses on August 9th. The issue price was INR 76, which saw strong subscriptions, closing at INR 91.20 on the first day of listing. Within just two weeks, by August 19th, the stock reached a high of INR 157.40, more than doubling its market cap. However, it closed slightly lower that day at INR 146.38. Since then, it’s been a volatile ride. As of November 8th, the share price has fallen below its initial listing price to INR 72.2. The price has been on a consistent decline since reaching its high, losing 27% following the public spat on October 6th.

Customers

The Central Consumer Protection Authority (CCPA), an Indian government body, has received 10,644 complaints against Ola e-scooters since September 2023. Complaints include service concerns and delivery delays. Many customers have shared disappointing experiences at Ola Electric service centers, often providing specific request numbers. Reported issues include scooters catching fire, motor malfunctions, and denial of service. Some customers have waited over two months for repairs. Amid this chaos, an Ola service center in Virar (Mumbai) reportedly hired bouncers to handle irate customers, while at a center in Kalaburgi, Karnataka, frustrated customers set fire to the Ola Service Center.

Engineers

Electric vehicles, including scooters, consist of both hardware and software components. The hardware includes the motor, battery, and inverter. In the absence of an internal combustion engine and traditional drivetrain components, power and drivetrain control are managed by a Vehicle Control Unit (VCU). Additional functions, such as Battery Management System, Regenerative Braking Control, and Torque Vectoring, are also performed by the VCU. These hardware and software systems require complex integration that may also require periodic firmware update. Engineering—whether systems or manufacturing—requires timely attention to customer feedback, essential for its engineers to resolve bugs, malfunctions, and performance issues in future product releases. Furthermore, the entire supply chain must meet rigorous standards.

Conclusion

Automotive production relies on skilled internal resources, a dependable supply chain, and a robust partner ecosystem. Product engineering, design, and development follow a structured lifecycle. Excellence in manufacturing demands consistent customer focus, process adherence, and a commitment to quality throughout the value chain. Senior management's focus on top-line revenue at the expense of addressing customer complaints can only worsen the situation. Circumventing processes, implementing quick fixes, and dismissing customer grievances will not help Ola Electric achieve global brand recognition for delivering value.

Sources : Photo : x.com, Share Price : NSE

{Originally written : November 2024}

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