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Our Algorithm Knows What We Want Before We Do. That is the Problem.

What 42 Indian high school students taught me about AI, and what a sociologist’s warning about McDonald’s has to do with it

Dr. Vijayakumar Parameswaran Unnithan

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AI and Critical Thinking: Better at Answers, Worse at Thinking?
Infinite paths, one door: personalisation narrows as much as it opens. Illustration: EdPublica

Between July and September 2025, I interviewed 42 high school students as part of ongoing research into career aspirations and problem-solving. One pattern kept recurring, and it unsettled me more each time I saw it.

Students who regularly used AI tools gave curiously superficial answers to everyday problems. They would address the obvious aspect of a question, then stop, almost as if waiting for a “next suggestion” that never came. But when I asked simple follow-up questions such as “What other possibilities exist?” or “Is there an alternative perspective?”, something shifted. They began weighing trade-offs, generating options, thinking out loud in ways they hadn’t a moment before. The capacity for deeper analysis was clearly there. They just weren’t reaching for it on their own.

AI and Critical Thinking: What Studies Reveal

This pattern aligns with what researchers call cognitive offloading, one of the more quietly consequential effects of living alongside AI. The term describes our long-standing habit of delegating mental tasks to external tools like notebooks, calculators, and calendars to lighten cognitive load. But AI changes the nature of the offload. A calculator stores a number. AI generates the finished thought. When a tool not only holds information but produces the answer itself, students can begin expecting ready-made solutions rather than exercising their own problem-solving capacity. What is meant to scaffold learning risks becoming a crutch that quietly atrophies the very skills it was meant to build.

This is not a fringe worry. A 2025 mixed-methods study of 666 participants across age groups found a significant negative relationship between frequent AI tool use and critical thinking performance, with cognitive offloading identified as the mediating mechanism, and the effect most pronounced among younger, heavier users. My 42 interviews cannot establish that kind of statistical relationship on their own, but they offered a close-up view of the same mechanism in action, most visibly in that pause where a student seemed to be waiting for a “next suggestion” that never came.

A 2026 study on generative AI and learner agency distinguishes between two very different modes of AI use, dependent offloading, where the tool substitutes for a student’s own thinking, and autonomous offloading, where AI scaffolds thinking without replacing it. The dependent form threatens autonomy by making choices on the student’s behalf, even when it may feel helpful. A parallel systematic review frames the same divide as amplification versus substitution, where guided, metacognitively aware AI use extends a student’s cognitive reach, while passive, unreflective use displaces the mental effort deep learning actually requires. My follow-up questions seemed to pull a few students from dependent mode into autonomous mode. The capacity for deeper analysis was clearly still there. They just were not reaching for it on their own.

From McDonald’s to the Algorithm

Thirty years ago, sociologist George Ritzer described what he called McDonaldization, the spread of fast-food logic, efficiency, calculability, predictability, and control, into hospitals, universities, even relationships. It was a troubling process, but at least it was visible. We could see the golden arches multiplying, see the assembly line replacing the artisan.

What we are living through now is harder to see, because it inverts the logic. Call it AI-zation. Where McDonaldization imposed visible uniformity, AI-zation offers something that feels like the opposite — personalisation. Our search results are tailored to us. Our feed reflects our interests. Our recommendations are, supposedly, uniquely ours.

This is the seduction of AI-zation. It feels personal while quietly manufacturing a new kind of conformity, not the visible sameness of a fast-food counter, but an invisible narrowing of thought, preference, and possibility. Recommendation systems are trained on existing patterns, so they inevitably steer people toward what is already popular, already “successful,” already proven. The menu looks infinite. The actual range of what people consume keeps narrowing.

Alt text: AI-powered robotic arm playing chess against a human on a chessboard.
An AI-powered robotic arm plays chess against a human, illustrating the growing role of artificial intelligence in decision-making and problem-solving. Credit: Pavel Danilyuk / Pexels.

I think of this as programmed spontaneity, the feeling of free choice operating inside an algorithmically constrained space. The pattern is easiest to notice somewhere trivial. Watch one dance reel, and the next fifty look almost identical to it. The platform has correctly identified what will keep you watching and, in doing so, has quietly narrowed the world to a single, endlessly repeated genre. Nobody decided this for us, exactly, and yet our options shrank the moment we engaged.

The same logic operates in domains that matter far more than reels, and it does not require any AI to appear at all. As a professor who has placed students in internships across dozens of organisations, I have watched a version of this play out for years. A student’s developmental need is exposure to something unfamiliar; if they have already worked in one area, the internship that would serve them best is often in a different one entirely, so they build range rather than repetition. But host organisations want the opposite. If a student has prior exposure to, say, employee engagement work, an organisation wants exactly that student, because they arrive already useful and need less onboarding. The organisation optimises for efficiency, minimum ramp-up, and maximum immediate output. The student needs breadth; the system rewards depth in a single, already-proven groove. Multiply that logic across a career, and a person can end up highly efficient at one narrow thing and never discover the other things they might have been.

This is the same tension recommendation algorithms formalise and accelerate, not invent. Efficiency, for any system, means doing more of what has already worked. Development, for a person, means doing something not tried yet. AI-zation is what happens when that older institutional logic gets encoded into infrastructure that operates continuously, at population scale, and largely out of sight.

Consider a career platform’s job suggestions, or a course recommendation engine, operating on the same principle as the internship market. It is optimising for patterns it has already seen. If your interests do not fit an existing category, the system is unlikely to help you find your way there, and the more you see what “people like you” are doing, the more that pattern starts to feel natural rather than constructed.

Why This Should Worry India Specifically

India has long been a civilisation organised around multiplicity, languages, philosophical schools, and ways of solving problems coexisting, often in productive tension. That diversity was never just decoration. It was, and is, epistemological, made of different ways of knowing and different definitions of a life well lived.

AI-zation threatens this precisely because it operates through standardisation disguised as personalisation. Search algorithms are globally standardised. Ed-tech platforms structure content around what optimises engagement metrics, not around pedagogical diversity. Jugaad, the distinctly Indian capacity for improvisation, depends on encountering a problem the “official” system has not already solved, and then building a workaround. But if an algorithm is always ready with the “right” answer before a student has fully sat with the question, where does that improvisational instinct come from?

This is not a case for rejecting technology. Digital tools have brought genuine benefit, access to information, connection, and efficiency gains that matter enormously in a country still building out infrastructure

This is not a case for rejecting technology. Digital tools have brought genuine benefit, access to information, connection, and efficiency gains that matter enormously in a country still building out infrastructure. The distinction that matters is between technology that augments human capability and technology that quietly programs human behaviour. Increasingly, we are getting more of the latter than the former.

The Illusion of Control

Defenders of algorithmic systems often point out that users retain control, that you can adjust settings, opt out, switch platforms. This misses something important. When algorithms mediate access to jobs, credit, education, and healthcare, individual opt-out becomes practically impossible for most people. And the “preferences” we express are themselves shaped by prior exposure. You keep choosing certain content partly because the algorithm keeps showing it to you. The system trains you as much as you train it.

The same illusion holds for the reasons AI systems offer when they do explain themselves. Research on explainable AI has repeatedly found that these explanations are often generated after the decision, plausible stories rather than faithful accounts of how the system actually arrived at its answer, and that even explanations carrying no real information can produce as much user trust as genuine ones. Demanding explanations from algorithms is necessary, but it is not sufficient. A system can learn to produce a persuasive explanation without that explanation being true.

Scale up the pattern from my student interviews and ask what happens when algorithms do our remembering (search), our navigating (maps), our reading choices (feeds), and increasingly our writing (generative AI). Each instance looks helpful in isolation. Together, they add up to something closer to the outsourcing of cognition itself.

What Can Actually Be Done

Four responses seem worth taking seriously, none of them rejecting technology.

First, algorithmic literacy needs to become collective, not just individual. When people understand that their “personalised” experience is shaped by hidden, profit-driven choices, they can begin to question the pattern rather than simply live inside it. For educators specifically, this means treating AI tools as objects of critical scrutiny in the classroom, not just productivity aids, and explicitly teaching students to pause and probe past the first answer, the way my follow-up questions did in those interviews.

Second, we need to protect spaces of deliberate non-optimisation. Not everything should be made efficient. Deep learning requires struggle. Creativity requires wandering. We need to consciously build and defend spaces, in classrooms, in workplaces, where algorithms do not intrude by default.

Third, India already has a structural alternative worth naming directly. The Open Network for Digital Commerce (ONDC) is public infrastructure built on the same logic that made UPI transform payments, an open protocol that keeps any single company from owning the whole stack of app, algorithm, and data. It has scaled fast, past 500 million transactions by mid-2026. Adoption is still uneven outside metro cities, but this is what building alternative infrastructure looks like in practice.

Cooperative ownership is a related, distinct model, workers or citizens owning the platform itself. Europe’s Smart cooperative serves over 100,000 freelancers; Switzerland’s MIDATA lets citizens govern their own health data. New York’s Drivers Cooperative is the cautionary case. Launched as a driver-owned Uber alternative, it now struggles because collective ownership has to compete with venture capital willing to lose money for years to win the market. Whether India’s cooperative tradition can extend into education technology or data governance, alongside infrastructure like ONDC, remains an open question.

Fourth, algorithmic systems that affect access to opportunity need to be explainable and challengeable. This requires regulation, but it also requires organised public demand, because voluntary transparency from platforms whose business model depends on opacity is not something to wait for.

The Stakes

Mahatma Gandhi’s idea of swadeshi, self-reliance rather than dependence on external systems, has an obvious digital-age analogue, something like cognitive sovereignty, the capacity to think, choose, and imagine outside the boundaries an algorithm has already drawn. In education specifically, this means treating AI as scaffolding to be gradually withdrawn, not a permanent support to lean on.

“We are not choosing between technology and tradition. We are choosing who controls the cognitive infrastructure young people grow up inside.” — Dr Vijayakumar Parameswaran Unnithan

We are not choosing between technology and tradition. We are choosing who controls the cognitive infrastructure young people grow up inside, and whether that infrastructure preserves the messy, effortful, sometimes inefficient work of actually thinking something through. My conversations with those 42 students suggested the capacity for that kind of thinking has not gone anywhere. It just needs to be asked for.

EDITOR’S FACT-CHECK

Key claims independently verified against primary sources: Gerlich (2025), Societies 15(1):6, on cognitive offloading and critical thinking (n=666); Zhu et al. (2026), Frontiers in Psychology, on dependent vs. autonomous cognitive offloading; ONDC’s 500-million-transaction milestone (reported July 2026); Smart cooperative’s membership figures; and the trajectory of New York’s Drivers Cooperative.

Dr Vijayakumar Parameswaran Unnithan is a Career Architect and Director of Research at CareerTotus Consultants Pvt. Ltd, India. As a researcher, he works at the intersection of career development, employability, and organisation development.

Society

Marshall Islands: Why the US Nuclear Legacy Is Back Before the UN

Between 1946 and 1958, the United States conducted 67 nuclear tests in the Marshall Islands, exposing communities to radioactive fallout and forcing repeated relocations. Decades later, health concerns, restricted access to ancestral lands and demands for U.S. nuclear test archives remain unresolved.

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Aerial view of a coastal community in the Marshall Islands, with turquoise waters, sandy beaches, homes, roads and green vegetation along the shoreline.
An aerial view of a coastal settlement in the Marshall Islands, where communities live along narrow strips of land surrounded by the Pacific Ocean. Image credit: Mohamed Sarim/Pexels

The people of Bikini Atoll left their homes in 1946 after the United States selected the atoll for nuclear weapons testing. They were told the move would be temporary. More than seven decades later, most of their descendants still do not live on Bikini. That displacement was the beginning of a much larger nuclear testing programme across the Marshall Islands.

Between 1946 and 1958, the United States carried out 67 nuclear weapons tests in the islands, which were then under U.S. administration as part of a United Nations trust territory. The tests took place mainly at Bikini and Enewetak atolls, although radioactive fallout reached communities elsewhere.

For Marshallese communities, the consequences were not limited to the two testing sites. People were moved between islands, exposed to radiation, separated from traditional lands and, in some cases, later moved again when returning home proved unsafe. The most consequential test came on March 1, 1954.

Castle Bravo and the Fallout

At Bikini Atoll, the United States detonated Castle Bravo, a thermonuclear device that became the country’s largest nuclear test. The explosion was much more powerful than expected, and radioactive fallout travelled beyond the planned danger zone.

Rongelap and Utrōk atolls were among the inhabited areas affected. Residents were eventually evacuated, but some were later returned to their islands. Concerns about continuing radioactive contamination subsequently led to further relocations.

The effects were recorded in the health of exposed populations. Studies and U.S. government programmes have documented elevated risks of certain cancers and thyroid disease among people exposed to radiation. Health concerns also extended to reproductive outcomes and other conditions associated with radiation exposure.

The testing programme also changed the physical basis of life on the islands. Much of the Marshall Islands consists of small, low-lying atolls where communities have traditionally depended on limited land and marine resources. When an island became contaminated or was designated for testing, relocation meant more than moving houses. Communities lost access to food sources, burial grounds, customary lands and places associated with family histories. Bikini illustrates the problem particularly clearly.

Residents were allowed to return in the 1970s, but they were removed again in 1978 after radiation concerns, including contamination of locally produced food, made permanent resettlement unsafe. The original Bikini community has never fully returned.

What Happened After the Tests Ended?

The United States stopped nuclear testing in the Marshall Islands in 1958. The relationship between the two countries changed substantially in the following decades, culminating in the 1986 Compact of Free Association.

The agreement included provisions dealing with the consequences of the nuclear testing programme. The United States established programmes for medical surveillance and treatment and environmental monitoring, while compensation arrangements were created for nuclear-related claims. Those measures have not resolved every issue raised by the testing programme.

Health care remains a major concern because exposure occurred across different communities and generations, while long-term monitoring is needed for diseases that may emerge decades after radiation exposure. Environmental questions also remain around the safety of returning to contaminated islands and the reliability of food grown or gathered there. There is another problem: access to information.

Why the Archives Matter

The Marshall Islands has sought greater access to U.S. government records concerning the nuclear tests, radiation exposure and the decisions made during the testing period.

Those records could help answer questions that remain important today. What information did U.S. authorities have about radiation risks at different stages of the testing programme? What did they tell Marshallese communities? Why were some communities returned to affected islands? How were decisions about evacuation and resettlement made?

For researchers, historical records can also complement health and environmental data collected over subsequent decades.
The UN has previously raised concerns about gaps in access to information relating to the nuclear programme, including records that were incomplete, redacted or otherwise unavailable to Marshallese authorities. That makes the latest UN intervention more than a call to preserve historical documents.

Why the Issue is Being Raised Again

The UN human rights body has now called on the United States to take additional steps to address the nuclear legacy in the Marshall Islands. The recommendations include stronger healthcare support for people affected by the testing programme and the release of classified archives.

The timing matters because the population directly exposed to the tests is ageing. At the same time, their children and grandchildren continue to live with the consequences of displacement, health monitoring and restrictions on access to some ancestral islands.

The Marshall Islands is also dealing with a practical problem that did not exist in the same form when the first tests were conducted: much of its population is now spread across different islands and overseas communities. Questions about land, health records, compensation and historical documentation therefore affect families who may no longer live in the places where their relatives were exposed.

The nuclear tests ended in 1958. The programmes created to deal with their effects have continued for decades. The latest UN report points to two areas where the organisation says further action is still required: medical care and access to information. For Marshallese communities, both are connected to the same history. The medical record explains part of what exposure did to people. The archives could help explain how decisions were made that exposed them in the first place.

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Society

India Has Robots. So Why Does Manual Scavenging Still Put Workers in Sewers?

India has recorded at least 662 sewer and septic-tank deaths in 10 years, despite a legal ban on hazardous sanitation work and growing use of robotic cleaning. EdPublica examines why manual scavenging persists—and what it will take to end dangerous human entry into sewers.

Vaishnavi V S

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Manual scavenging: Three sanitation workers manually clean a garbage-filled, polluted waterway while standing and crouching in contaminated water, illustrating the hazardous conditions faced by workers involved in manual scavenging and sanitation work.
Manual sanitation work can expose workers to direct contact with human waste and contaminated environments. India has prohibited manual scavenging and hazardous sewer and septic-tank cleaning, while government programmes now promote mechanisation and safer sanitation practices. Representational image. Image credit: Soubhagya Maharana/ Pexels

Around 10 pm on 30 September 2025, a worker went down into the septic tank of a hotel in Kattappana, in Kerala’s Idukki district, to clean it. He became trapped. Two colleagues went in to pull him out and were trapped too.

The manhole was too small for rescuers to enter. The fire force brought in an earthmover to break open part of the structure, and after a rescue operation of about an hour and a half the three men were taken to hospital, where they could not be saved. They were Jayaraman, from Cumbum in Tamil Nadu’s Theni district, and Sundara Pandian, 36, and Michael, 23, both from Gudalur in the Nilgiris. The Idukki District Collector’s report later attributed the deaths to inhalation of toxic gas in a tank with critically low oxygen, though the gas itself was not identified. It recommended a multi-department inquiry and compensation for their families of the dead involved in manual scavenging.

Kerala is the state where this is least expected. In the dataset used for this report, it recorded three sewer deaths in the decade to 2025: two in 2016, one in 2017, and none since. The men of Kattappana do not appear in that count. Nor does Joy, a sanitation worker who drowned in a waste-choked canal in Thiruvananthapuram in July 2024. Every figure in this story is a minimum.

Between 2016 and 2025, the National Commission for Safai Karamcharis (NCSK) recorded 662 deaths across India in connection with hazardous sanitation work. India banned the employment of manual scavengers in 1993. The 2013 Act went further, barring anyone from being employed to clean sewers and septic tanks hazardously, that is, without the protective gear and safeguards its rules prescribe. Yet sanitation workers still enter through narrow openings, sometimes with only basic protective equipment, to clear blockages and clean spaces where sewage, toxic gases and human waste accumulate. The work can take hours; in the wrong conditions, it takes lives.

Manual scavenging: Horizontal bar chart showing recorded sewer and septic-tank deaths by state between 2016 and 2025. Tamil Nadu recorded 93 deaths, followed by Maharashtra with 84, Gujarat with 83, Uttar Pradesh with 81, Haryana with 69, Delhi with 65 and Kerala with 3.
Tamil Nadu recorded the highest number at 93 between 2016 and 2025, while Kerala recorded three in the dataset. Kerala is shown for contrast and does not include deaths that fall outside the official classification. Source: National Commission for Safai Karamcharis (NCSK).

The toll peaked in 2019, at 124 deaths. Tamil Nadu recorded the most over the decade, at 93, followed by Maharashtra (84), Gujarat (83), Uttar Pradesh (81) and Haryana (69); Delhi recorded 65. The five states named accounted for about 62 per cent of the deaths. Since the NCSK began counting in 1993, it has logged 1,361 such deaths, 264 of them in Tamil Nadu and 13 in Kerala.

Official series differ by source and date, because states report late. Replies in Parliament have put the toll for 2019 anywhere between 116 and 133, and a reply in March 2026 that counted from 2017 onwards ranked Uttar Pradesh first (86), ahead of Maharashtra (82) and Tamil Nadu (77). The pattern is consistent even if the totals are not.

A note on terms also matters here. The government draws a legal line between “manual scavenging”, which the 2013 Act defines as lifting human excreta from insanitary latrines, and the “hazardous cleaning” of sewers and septic tanks. It has told Parliament that no deaths have been reported from the first, while counting those in the second. Campaigners treat both as the same caste-bound labour. This report uses “manual scavenging” for the wider practice and “sewer deaths” for the deaths.

Behind the toll lies a harder question: if India has achieved significant technological advancement, why does manual scavenging still persist at all? What keeps people entering spaces they should never have to enter?

For Bezwada Wilson, national convenor of the Safai Karmachari Andolan (SKA) and a Ramon Magsaysay Award winner, the fight against manual scavenging has always been about more than sewers. Through the SKA, he helped document the practice, challenge official claims and take the issue to the Supreme Court. The Supreme Court’s 2014 judgment recognised the continuing problem, ordered the identification and rehabilitation of workers, and directed compensation of ₹10 lakh to the families of those who died in sewers, bringing dignity, equality and caste discrimination to the centre of the debate.

The Work Begins Long Before the Sewer

Wilson grew up in a community that has been tied to sanitation work for generations, and he has spent much of his life challenging the system that kept it that way. As a child, he says, he studied in a separate school near his settlement, where caste and language shaped where children from his community were sent to learn. He came to the movement against manual scavenging through an understanding of what prolonged contact with human excreta does to a person’s health and life.

People who come into contact with human excreta, he says in an interview with EdPublica, are exposed to deadly diseases. Their quality of life deteriorates. That, for Wilson, was reason enough to act. But the deeper problem is what happens when a community is identified with one kind of work for generations. Even education does not necessarily erase that association.

Wilson says government programmes aimed at upskilling members of sanitation-worker communities exist, but questions whether they are reaching people effectively. The Ministry of Social Justice and Empowerment told the Lok Sabha in 2022 that it had spent ₹266.16 crore on its self-employment scheme for the rehabilitation of manual scavengers since 2013-14; that scheme has since been replaced by NAMASTE. Students in these communities still face difficulties accessing education in many places.

Then there is discrimination. When people have been treated as inferior for generations, Wilson argues, a change in law does not automatically change the way society sees them. That matters because manual scavenging is not simply a story about a hazardous job. It is also a story about who is expected to do it.

The Number that Remains Visible

The 662 deaths recorded between 2016 and 2025 are a floor, not a full count. They are the deaths captured in the available dataset, and that distinction matters: the scale of the problem is larger than the deaths that make it into official or reported records. The NCSK says its figures draw on state governments’ reports, media reports and complaints it receives.

The gap between official and civil-society counts is wide. The Ministry told the Lok Sabha in August 2026 that 498 people died in hazardous sewer and septic-tank cleaning between January 2019 and June 2026, a toll that fell from 132 in 2019 to 47 in 2025. The SKA’s own tracking runs the other way, as the table shows. It has counted 113 deaths in the first seven months of 2026 alone; the government’s figure for the first four months is 52.

Manual scavenging in India: Bar chart comparing government and Safai Karmachari Andolan (SKA) counts of sewer and septic-tank deaths from 2022 to 2025. The government recorded 88, 65, 54 and 47 deaths, while SKA recorded 93, 102, 116 and 121 respectively, showing a widening gap.
The government and Safai Karmachari Andolan recorded increasingly different numbers of sewer and septic-tank deaths between 2022 and 2025. Sources: Lok Sabha reply, August 2026; Safai Karmachari Andolan.

The two series cannot both be right, and the difference is not only about counting. It is also about classification, since the government counts hazardous cleaning but not “manual scavenging”. Even among the deaths that are recorded, accountability is slow: the NCSK says compensation has been paid in 1,206 of the 1,361 cases logged since 1993, with 101 still pending.

Vimal Govind M K, founder and CEO of Kerala-based Genrobotics, came to the problem from the technology side. His company turned its robotics towards sewer cleaning, he says, after the founders came across a newspaper photograph of a man who had died inside a sewer in Kozhikode, Kerala. The image changed the direction of their work.

“We decided to pivot the technology we were developing towards a completely different problem—to prevent people from entering sewers and doing this dangerous work manually,” Govind said.

That decision eventually produced Bandicoot, a robotic system designed to clean manholes without sending a person inside. Genrobotics says it was first deployed in Kerala in 2018. But the existence of a machine does not mean people stop entering sewers.

A Robot Exists. So Why are People Still Entering?

Genrobotics says it has trained more than 3,000 workers and has around 400 robots operating in India. Its public figures have varied: a March 2026 press release spoke of more than 275 deployments, while earlier interviews cited 300 and 350 robots. Govind says a task that can take three to four hours when done manually can be completed in around 20 minutes using the technology. Operating one robot takes two workers, he says.

Manual scavenging: Genrobotics’ Bandicoot robotic system positioned over manholes during sewer-cleaning operations, with a sanitation worker operating the robot in the daytime image and the robot deployed at night in the second image.
Robotic systems such as Genrobotics’ Bandicoot are designed to clean manholes without sending sanitation workers inside. The system is operated from outside the manhole, allowing hazardous sewer-cleaning work to be mechanised.

Figures from the field point the same way. Chennai’s water board has been reported to have cleaned more than 5,000 manholes in the first year of deployment, and a company case study lists 1,111 manholes cleaned by two robots for Mumbai’s civic body between September 2024 and March 2025. Both figures come from the company or from secondary reports.

On paper, the logic seems straightforward: if a machine can enter a sewer, a human being should not have to. But India’s sanitation infrastructure does not operate on paper. Municipalities and water boards buy machines, yet many of the deadliest jobs are commissioned by someone else. Kattappana was a hotel’s tank. This week in Mumbai’s Santacruz East, Santosh Kashate, 50, died and Ajay Thakur, 30, was hospitalised after they allegedly entered a municipal sewer manhole while cleaning a housing society’s drain. Police were registering a case of death by negligence against the contractor, and said society members could also be booked for hiring private workers without informing the Brihanmumbai Municipal Corporation.

Some facilities need specialised cleaning only occasionally. Private establishments have little reason to invest in technology for a task they might need once a year, or once in several years. Govind points to another problem: safety enforcement.

In India, confined-space management and workplace safety remain uneven, he says. In countries such as Singapore and the UAE, workers require safety training and permits before undertaking such work, with safety procedures built into the job itself. India’s problem is therefore not simply a shortage of machines. It is also a shortage of systems that make entering the sewer unacceptable.

The courts have pushed in that direction. In October 2023, in Dr Balram Singh v Union of India, the Supreme Court raised compensation for sewer deaths from ₹10 lakh to ₹30 lakh. In January 2025 it barred manual sewer cleaning in six metropolitan cities, and in July 2026 it issued show-cause notices on contempt to the chief secretaries of five states. After two contract workers died in a Tiruchirappalli manhole on 22 September 2025, the corporation announced ₹30 lakh for each family and filed a complaint against the contractor. Compensation and complaints now follow such deaths. Prevention still lags.

When Protective Equipment is not Enough

For years, the response to hazardous sanitation work has often included protective equipment—masks, gloves and other safety gear. But Govind says equipment alone does not necessarily change behaviour. He says workers who have spent years entering sewers can become accustomed to the practice, and that even after being provided with protective equipment, some continue to enter because that is how the work has traditionally been done.

A small, rusted circular manhole cover set into a concrete surface, illustrating the narrow openings through which sanitation workers may be expected to access sewers and confined spaces.
A narrow manhole can leave barely enough space for a person to enter. Such confined openings can make sewer cleaning and rescue operations difficult, particularly when workers enter hazardous spaces containing toxic gases and low oxygen. Representational image. Image credit: Magda Elhers/Pexels

Official figures show the limits of the equipment route. Under the government’s NAMASTE scheme, 89,915 sewer and septic-tank workers had been validated by August 2026, and about 87,000 protective kits had been distributed by the scheme’s third anniversary in July. The Lok Sabha was also told that 52 people died in hazardous cleaning in the first four months of 2026. The figures do not say who the dead were or whether they had been profiled. They do show that distributing equipment has not, by itself, ended the deaths.

Changing that, Govind says, requires training and a cultural shift. That observation brings the technology debate back to Wilson’s argument. If caste has historically determined who performs sanitation work, and if generations of workers have been conditioned to see hazardous cleaning as part of their occupation, then a robot can solve only one part of the problem. It can keep a person out of the sewer. It cannot, by itself, determine what happens to that person afterwards.

What Happens to the Worker When the Robot Arrives?

This may be the most important question in the mechanisation debate. Automation is often discussed in terms of machines replacing people. In sanitation, however, the better outcome is different: workers moving from hazardous manual entry to safer, skilled roles.

Genrobotics says sanitation workers are trained to operate its technology and become part of its teams. The company said in January 2025 that more than 1,000 of the workers it had trained had become robot operators. It says the transition removes direct interaction with sewage from their work. A worker who once entered a manhole could instead operate a machine from outside it.

The job remains. The danger does not have to. Those numbers are the company’s own, though. What would settle the question is what operators earn, who employs them and whether the jobs last. The model also depends on municipalities and other employers actually investing in mechanisation, training workers and enforcing the rules.

Govind says budget allocation remains one of the major barriers to adoption. Government programmes and funds can support mechanisation, but ultimately policymakers and local administrators have to decide to spend the money. The government’s main programme is NAMASTE, launched in July 2023 with an outlay of ₹349.73 crore over three years to 2025-26 across more than 4,800 urban local bodies. It profiles sewer and septic-tank workers, provides protective kits and health insurance, and offers capital subsidies of up to 50 per cent for sanitation machines and enterprises. An extension to rural areas, with an additional outlay of about ₹498.73 crore for 2026-27 to 2030-31, has been reported.

The Geography Tells Another Story

The deaths are not evenly distributed across India. Kerala, by comparison, recorded three deaths in the dataset, two in 2016 and one in 2017, with none from 2018 to 2025.

That contrast is worth examining, but not celebrating too quickly. A decline in reported deaths does not, by itself, prove that hazardous sanitation work has disappeared. Differences in reporting, infrastructure, enforcement and the kinds of sanitation work carried out in each state can all affect the numbers. Kattappana and Joy’s death in Thiruvananthapuram sit outside Kerala’s count.

Govind says Kerala has stronger safety practices than many other states, while acknowledging that enforcement and investment remain challenges nationally. Genrobotics first deployed Bandicoot in Kerala in 2018, the year the zero run begins. The timing is suggestive, not proof, and Kattappana shows what a municipal robot does not reach: a private tank behind a hotel.

The more useful question, then, is not simply which state has the fewest deaths. It is what is different about the systems that keep workers out of hazardous spaces.

Besides the Number 662

India’s response has increasingly moved towards mechanisation. The government has also introduced programmes aimed at eliminating hazardous sanitation work, rehabilitating workers and creating safer sanitation systems.

The experiences of Wilson and Govind point to two requirements for the same goal. One is technological: make it possible to clean a sewer without sending a person inside. The other is social: make sure the person who no longer enters the sewer has the education, income, skills and social acceptance to move into safer work. Neither can replace the other. A third, the law, is meant to hold them together.

A robot can pull a worker away from toxic sewage. A law can prohibit an employer from sending that worker back in. A rehabilitation programme can offer another livelihood. But unless all three work together, the prohibition remains vulnerable to the same pressures that created the occupation in the first place.

Govind predicts that the sanitation industry could become almost completely automated within the next five to six years, with very little human involvement in hazardous work. It is an ambitious prediction. Against more than 4,800 urban local bodies, the company’s own count is a few hundred robots.

The technology may arrive before the social transformation does. And that is the real test for India. Not whether it can build a robot capable of entering a sewer. But whether it can build a system in which no human being has to.

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Society

Who Cares for India’s Older People?

On International Day of Older Persons, a HelpAge India study highlights gaps in healthcare, income, family care and social support facing older people in India, including added risks from climate-related hazards.

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Older people receiving assistance while navigating uneven steps at a public site
Older people receive assistance as they navigate uneven steps, highlighting the importance of accessibility and support in later life. Representational image. Image credit: Krepesh Chandra Sarker/Pexels

Growing older can change something as ordinary as getting medicines, visiting a doctor or managing a difficult day alone. For many older people, the question is not simply whether help exists, but whether someone is close enough and able to provide it when it is needed.

A recent HelpAge India study of 2,224 older people across 20 districts in 10 states offers a picture of the support systems on which they depend. It found that 94% of older people who needed care received it from family members. But that support is not equally available to everyone.

Thirteen percent of those surveyed lived alone, 33% were widows and 28% were aged 80 or above. Nearly half reported a long-term impairment, including mobility and vision difficulties. These circumstances matter because everyday care often depends on another person being physically present.

When Family is not Nearby

India’s older population continues to rely heavily on family for care. But migration for work is changing household arrangements. In the HelpAge study, 18% of households reported that a family member had migrated for work. Sons accounted for 76% of those migrants.

For older people living alone, neighbours often fill part of the gap. Thirty-eight percent depended on neighbours for care, while 20% relied on family members living elsewhere. Sixteen percent said they received no care.

Older people and their welfare
Living arrangements among older people, with 42.1% living with a spouse and children and 13% living alone. Source: HelpAge report

Distance does not necessarily mean that families stop supporting older relatives. Financial assistance and regular communication can continue. But some needs cannot be met remotely: taking someone to a hospital, collecting medicines, helping them move around the house or responding when they suddenly fall ill. This distinction becomes particularly important during emergencies.

Health Harder to Manage

The study found that 52% of respondents could not afford medicines. Public facilities were an important source of healthcare, with 51% using primary health centres and 49% government hospitals.

Climate-related events exposed some of these existing difficulties further. Seventy-eight percent of those surveyed had experienced at least one such hazard in the previous three years, with heatwaves the most common.

Among those who experienced heatwaves, 74% said illness increased and 44% said existing health conditions worsened. One-third reported difficulty accessing healthcare. These figures are less about the hazard itself than about what happens when an older person already managing health problems has fewer options for care.

“Older persons are among those most at risk from rising climate shocks, particularly those living alone or with impairments, yet they remain largely invisible in climate response efforts,” says Rohit Prasad, CEO, HelpAge India. “Climate impacts extend beyond physical hazards, affecting health, income, housing, care and social wellbeing.”

Prasad says age-related physical, financial and social challenges can limit older people’s ability to prepare for, withstand and recover from climate events. He calls for ageing to be integrated into climate adaptation, climate financing, elder-centric disaster risk reduction and social protection policies.

Income Constraint

Healthcare is only one part of financial insecurity in later life. Pensions were the main source of income for 49% of respondents. Sixteen percent had neither work nor income, while others continued to work in agriculture, agricultural labour or other forms of employment.

The ability to pay for medicines, travel to healthcare facilities, household repairs or basic necessities depends heavily on this income. Work also changes with age. The HelpAge study found that the proportion reporting no work or income rose from 11% among those aged 60–69 to 21% among those aged 80 and above.

For people who have spent much of their lives in informal employment, growing older can therefore mean entering a period with limited savings, little employment protection and greater healthcare needs.

The Problem of Access

Government schemes can provide important support, but knowing about a benefit does not always mean being able to obtain it. The study found relatively high awareness of the Public Distribution System, pensions, subsidised healthcare and housing schemes. Yet access was more difficult for people with poor health, those severely affected by climate hazards, people without formal education and those from lower socioeconomic groups.

Respondents also reported delays, difficulties with digital access and a lack of assistance with applications. For an older person with limited mobility, poor eyesight or little experience with digital services, even a relatively straightforward application can become difficult without help.

Ageing Needs More Than Family Care

India’s ageing population is growing, while the family structures that have traditionally provided care are changing.

UNFPA estimates that the number of Indians aged 60 and above could approach 193 million by 2030. That growth will increase the need for healthcare, financial support and forms of care that do not depend entirely on whether an older person’s children live nearby.

The answer is not to replace family care, which remains central to the lives of many older people. It is to ensure that those who do not have family nearby, cannot afford private care or need support beyond what relatives can provide are not left without alternatives.

Ageing policy therefore needs to look beyond longevity. It has to account for who provides care, who pays for healthcare, how older people access public services and what happens when the person they depend on is no longer close by. For many older Indians, these are not future questions. They are questions of everyday life.

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