#FactCheck - Fake Quote Attributed To Manoj Tiwari On Rupee-Dollar Value Goes Viral Online

Introduction

‍
You ask an app for directions to a street you've driven down a hundred times. You let autocomplete finish your sentence before you've decided what you meant to say. You take a photo of a document instead of reading it, trusting the summary a model hands back. None of these moments feel like a loss. Each one is, on its own, a reasonable trade of effort for convenience. But add them up across a year, a career, an industry, and you start to wonder what exactly we've been trading away. Every technology wave produces its own founding myth. For AI, the myth is that intelligence can be manufactured at scale, bottled into a model, and dispensed on demand - cheaper, faster, and eventually better than the human original. It's a seductive story, and one we've been telling ourselves so uncritically that we've stopped noticing what it costs.

The casualties of this bet are rarely dramatic. Nobody announces that a skill has quietly atrophied, or that a habit of independent judgement has gone unused long enough to weaken. These losses don't show up as headlines; they show up later, as gaps, when the system that was supposed to think for us turns out not to have been thinking at all. Ford Motor Company's recent decision to rehire around 350 veteran engineers, after leaning heavily on AI-driven quality systems, is a small but telling data point.¹ The lesson isn't that automation failed outright — it's that a process can be automated without the judgement that made the process work ever being captured in the first place. That distinction between automating a task and actually preserving the human expertise behind it is the real subject of this AI moment.

‍

How Organisations Are Using AI in Decision-Making

‍

More organisations are now leaning on AI not just to execute tasks, but to help shape decisions. Deloitte's 2026 Global Human Capital Trends survey found that 60% of executives now regularly use AI to support their decisions, and the same report cites Gartner's projection that by 2027, half of all business decisions will be augmented or automated by AI agents. Companies like Netflix and Amazon are often pointed to as examples of this working well using AI to enhance recommendations and logistics while keeping people involved in the interpretation, generating significant value in the process. Elsewhere, results have been more mixed: MIT's "State of AI in Business 2025" study found that 95% of generative AI pilots showed no measurable P&L impact within six months, often because this initiative failed to integrate feedback or adapt to context rather than because the underlying model was flawed. Critics have noted the study used a narrow definition of success (six-month, bottom-line ROI), so the figure may understate the value AI creates in ways that aren't captured on the P&L. Notably, this is not an argument against using AI. It is an argument about how we use it and why the human-in-the-loop principle, keeping people actively involved in judgement rather than passively rubber-stamping outputs, is not a compliance checkbox but the thing that determines whether automation actually works. That distinction, between automating a task and preserving the human expertise behind it, is the point of contention.

‍

Finding the Balance

‍

The lesson isn't to use AI less, it's to be deliberate about where it sits in the process. The strongest results come from pairing AI's speed with human judgement, not swapping one for the other. That means keeping a clear owner for important decisions, checking that the model is optimising for the right goal, and treating its output as a strong first draft rather than a final answer. Used this way, AI doesn't replace thinking, it gives good judgement more room to work.

‍

Two Framings We Should Retire

‍

Conversations about AI adoption keep falling into two lazy framings. The first is AI versus humans, as if technology and workforce are locked in a zero-sum contest for relevance. The second is AI versus jobs, reducing every discussion to headcount and displacement. Both are legitimate concerns, but they crowd out a more urgent question: as AI gets embedded deeper into how decisions are made, what happens to the quality of the decisions themselves? This is not a question about whether AI is useful and it plainly is. It is a question about what gets quietly outsourced along with the task, and whether anyone notices before it matters.

‍

Why “Wisdom of Crowds” Does Not Automatically Apply to AI

‍

A comforting analogy often gets reached for: surely, with millions of people using the same models, errors will average out, the way independent forecasters tend to converge on accurate estimates.² That analogy breaks down where it matters most. The wisdom-of-crowds effect depends on independent thinking, genuinely diverse information, and an aggregation mechanism that does not distort the signal. When millions of people query the same underlying model, those conditions collapse. Everyone draws from the same statistical engine, trained on overlapping data, tuned toward similar “safe” answers. The apparent agreement is not corroboration, it is an echo. This creates a genuinely new risk: AI can be confidently, fluently, and uniformly wrong across an entire organisation at once, without the friction that would normally surface an error in a single person's judgement.

‍

The Casualties, Named Plainly

‍

Several things erode quietly when organisations are not deliberate about integrating AI into decisions. Independent judgement is the first casualty of the willingness to form a view before checking what the model says. Verification effort follows: generative AI collapses retrieval and generation into one fluent output, and people invest less effort checking something that already sounds complete and well-reasoned. Diversity of thought narrows as more decision-makers lean on the same handful of models for research and drafting, quietly reducing the range of framings available when it matters most. Accountability becomes harder to trace when a recommendation generated by a model and passed along with minimal scrutiny creates a strange vacuum where a decision was made but nobody quite owns it. And informational anchoring sets in, where a signal becomes a coordination point simply because everyone is looking at it, regardless of its accuracy.

‍

Why Human-in-the-Loop Is a Design Requirement

‍

“Human in the loop” often becomes a rubber-stamp step rather than genuine scrutiny. That is a mistake, because the functions humans provide are structural, not decorative. Context that a model cannot infer  history, relationships, unstated constraints  shapes whether a reasonable-sounding answer is right in a specific situation. Domain expertise built over years lets someone recognise when a fluent answer is subtly wrong. Ethical judgement decides trade-offs a model has no standing to make on an organisation's behalf. Accountability means someone can be asked why a decision was made and answer from reasoning, not from “the system recommended it.” And the rarest function of all is the willingness to challenge a convincing answer and resisting the very fluency that makes AI output persuasive.

‍

What This Looks Like in Practice

‍

For organisations, the goal is not slowing AI adoption but being deliberate about where human judgement stays load-bearing. AI output should default to draft status until a qualified person has actively tested its logic against context the model lacks. Teams using the same AI tools for analysis should build in a step that actively seeks disagreement, rather than assuming convergence means correctness. Ford's decision to bring engineers back to lead design reviews is instructive: expertise, once encoded into a system, is not safe to let atrophy in the people who built it.³ Verification should be visible and required for decisions with real financial, legal, safety, or reputational consequences. And organisations should track which decisions were AI-assisted and who owned the final call, so accountability stays traceable rather than quietly disappearing.

‍

Conclusion

‍

Decades ago, management thinkers warned that automating a broken process only helps an organisation fail faster. The AI era raises the stakes on that warning: judgement itself, the hard-won capacity to reason well under uncertainty, can be automated away without anyone deciding to give it up. Machines already process information faster than any team of people. What they cannot yet do is originate the wisdom that comes from human experience, accountability, and the willingness to be told one is wrong. That capacity erodes not because AI is powerful, but because organisations stop deliberately exercising it. The real task ahead is not resisting AI, but ensuring that as it takes on more of the work of deciding, humans deliberately keep hold of the responsibility of deciding.

‍

References

‍

1. https://www.assemblymag.com/articles/100186-ford-rehires-veteran-engineers-to-improve-ai-vehicle-quality
2. https://finance.yahoo.com/technology/ai/articles/ford-rehires-veteran-engineers-ai-144332497.html
3. https://finance.yahoo.com/technology/ai/articles/ford-rehires-more-300-engineers-162210705.html
4. https://www.msn.com/en-us/money/other/ford-rehires-hundreds-of-engineers-after-ai-struggles-to-improve-quality/ar-AA26P4QB?ocid=BingNewsSerp
5. https://www.foxbusiness.com/technology/ford-rehires-experienced-engineers-after-ai-misses-mark
6. https://www.livemint.com/opinion/online-views/artificial-wisdom-of-crowds-jobs-crisis-ai-technology-automation-openai-model-11785009289768.html
7. https://www.deloitte.com/us/en/insights/topics/talent/human-capital-trends/2026/decision-making-with-ai.html
8. https://www.hpcwire.com/aiwire/2026/03/04/deloittes-state-of-ai-2026-why-enterprise-execution-is-falling-behind-adoption/ and Legal.io summary: https://www.legal.io/blog/5719519/MIT-Report-Finds-95-of-AI-Pilots-Fail-to-Deliver-ROI-Exposing-GenAI-Divide
9. https://www.marketingaiinstitute.com/blog/mit-study-ai-pilots

‍

Introduction

‍

“an intermediary, on whose computer resource the information is stored, hosted or published, upon receiving actual knowledge in the form of an order by a court of competent jurisdiction or on being notified by the Appropriate Government or its agency under clause (b) of sub-section (3) of section 79 of the Act, shall not ‍, which is prohibited under any law for the time being in force in relation to the interest of the sovereignty and integrity of India; security of the State; friendly relations with foreign States; public order; decency or morality; in relation to contempt of court; defamation; incitement to an offence relating to the above, or any information which is prohibited under any law for the time being in force”

‍

Law grows by confronting its absences, it heals itself through its own gaps. The most recent notification from MeitY, G.S.R. 775(E) dated October 22, 2025, is an illustration of that self-correction. On November 15, 2025, the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules, 2025, will come into effect. They accomplish two crucial things: they restrict who can use "actual knowledge” to initiate takedown and require senior-level scrutiny of those directives. By doing this, they maintain genuine security requirements while guiding India’s content governance system towards more transparent due process. 

‍

When Regulation Learns Restraint

‍

To better understand the jurisprudence of revision, one must need to understand that Regulation, in its truest form, must know when to pause. The 2025 amendment marks that rare moment when the government chooses precision over power, when regulation learns restraint. The amendment revises Rule 3(1)(d) of the 2021 Rules. Social media sites, hosting companies, and other digital intermediaries are still required to take action within 36 hours of receiving “actual knowledge” that a piece of content is illegal (e.g. poses a threat to public order, sovereignty, decency, or morality). However, “actual knowledge” now only occurs in the following situations: 

(i) a court order from a court of competent jurisdiction, or

(ii) a reasoned written intimation from a duly authorised government officer not below Joint Secretary rank (or equivalent)

‍

The authorised authority in matters involving the police “must not be below the rank of Deputy Inspector General of Police (DIG)”. This creates a well defined, senior-accountable channel in place of a diffuse trigger. 

There are two more new structural guardrails. The Rules first establish a monthly assessment of all takedown notifications by a Secretary-level officer of the relevant government to test necessity, proportionality, and compliance with India’s safe harbour provision under Section 79(3) of the IT Act. Second, in order for platforms to act precisely rather than in an expansive manner, takedown requests must be accompanied by legal justification, a description of the illegal act, and precise URLs or identifiers. The cumulative result of these guardrails is that each removal has a proportionality check and a paper trail. 

‍

Due Process as the Law’s Conscience 

‍

Indian jurisprudence has been debating what constitutes “actual knowledge” for over a decade. The Supreme Court in Shreya Singhal (2015) connected an intermediary’s removal obligation to notifications from official channels or court orders rather than vague notice. But over time, that line became hazy due to enforcement practices and some court rulings, raising concerns about over-removal and safe-harbour loss under Section 79(3). Even while more recent decisions questioned the “reasonable efforts” of intermediaries, the 2025 amendment institutionally pays homage to Shreya Singhal’s ethos by refocusing “actual knowledge” on formal reviewable communications from senior state actors or judges. 

The amendment also introduces an internal constitutionalism to executive orders by mandating monthly audits at the Secretary level. The state is required to re-justify its own orders on a rolling basis, evaluating them against proportionality and necessity, which are criteria that Indian courts are increasingly requesting for speech restrictions. Clearer triggers, better logs, and less vague “please remove” communications that previously left compliance teams in legal limbo are the results for intermediaries.

‍

The Court’s Echo in the Amendment

‍

The essence of this amendment is echoed in Karnataka High Court’s Ruling on Sahyog Portal, a government portal used to coordinate takedown orders under Section 79(3)(b), was constitutional. The HC rejected X’s (formerly Twitter’s) appeal contesting the legitimacy of the portal in September. The business had claimed that by giving nodal officers the authority to issue takedown orders without court review, the portal permitted arbitrary content removals. The court disagreed, holding that the officers’ acts were in accordance with Section 79 (3)(b) and that they were “not dropping from the air but emanating from statutes.” The amendment turns compliance into conscience by conforming to the Sahyog Portal verdict, reiterating that due process is the moral grammar of governance rather than just a formality. 

‍

Conclusion: The Necessary Restlessness of Law 

‍

Law cannot afford stillness; it survives through self doubt and reinvention. The 2025 amendment, too, is not a destination, it’s a pause before the next question, a reminder that justice breathes through revision. As befits a constitutional democracy, India’s path to content governance has been combative and iterative. The next rule making cycle has been sharpened by the stays split judgments, and strikes down that have resulted from strategic litigation centred on the IT Rules, safe harbour, government fact-checking, and blocking orders. Lessons learnt are reflected in the 2025 amendment: review triumphs over opacity; specificity triumphs over vagueness; and due process triumphs over discretion. A digital republic balances freedom and force in this way. 

‍

Sources

• https://pressnews.in/law-and-justice/government-notifies-amendments-to-it-rules-2025-strengthening-intermediary-obligations/ 
• https://www.meity.gov.in/static/uploads/2025/10/90dedea70a3fdfe6d58efb55b95b4109.pdf 
• https://www.pib.gov.in/PressReleasePage.aspx?PRID=2181719 
• https://www.scobserver.in/journal/x-relies-on-shreya-singhal-in-arbitrary-content-blocking-case-in-karnataka-hc/ 
• https://www.medianama.com/2025/10/223-content-takedown-rules-online-platforms-36-hr-deadline-officer-rank/#:~:text=It%20specifies%20that%20government%20officers,Deputy%20Inspector%20General%20of%20Police%E2%80%9D.

‍

‍

Introduction

‍

We live in a time where technological change is no longer slow or subtle. Robotics, automation, artificial intelligence, and digital systems are transforming the way we work, think, and even imagine the future. This is often celebrated as great progress. But a deeper question quietly waits behind the noise. Is every advancement truly an uplift when seen through the lens of scriptures, culture, and Indian philosophical thought? Are we creating for the good of humanity, or are we only chasing convenience and speed? And what kind of future are we actually preparing, not just for ourselves, but for those who will be born into this world shaped by these tools from the very beginning?

India has long been seen as a land that values balance, purity, and harmony with nature. Its rivers, mountains, forests, and traditions are not just geography or history, they are part of a civilizational way of thinking that connects life, duty, and responsibility. In this context, it becomes important to ask what the long-term cost of our technological appetite might be. Every invention has a footprint. Industries change landscapes. Energy demands reshape ecosystems. Convenience today often hides consequences that only appear years later. Progress, when measured only in speed and output, forgets to ask what it takes away in silence.

There is also a quieter change happening inside the human mind. As tools become smarter, humans begin to feel more powerful. The thought slowly shifts from “I can use this” to “I control this.” With artificial intelligence, the language becomes even bolder. We start hearing phrases like “we can create worlds, faces, voices, even minds.” But history have always warned us about ‘overreach’. Not because power is evil, but because pride blinds judgment. When ability grows faster than wisdom, imbalance follows. We can already see early signs of this in concerns about shrinking attention spans, weakening cognitive habits, and a growing dependence on systems that think for us before we learn to think for ourselves deeply.

None of this is an argument to reject innovation. The idea is not to blacklist technology or romanticise the past. The real question is about direction and responsibility. Advancements are not only for the comfort of the present generation. They shape the mental, moral, and emotional world of future generations who will grow up surrounded by these systems as something normal and unavoidable. What values will guide that world? What habits will it encourage? What will it quietly take away?

This is where the richness of Indian thought becomes relevant, not as nostalgia, but as guidance. Ideas of dharma, restraint, balance, and ethical action were never anti-progress. They were reminders that power without responsibility becomes dangerous, and that ability without humility leads to decline. In modern terms, we talk about safety by design, ethical innovation, and human-centred technology. In older language, we talked about duty, limits, and the consequences of unchecked desire. The words have changed, but the concern is the same.

Perhaps the real question is not whether we are becoming creators, but whether we remember that we are also caretakers. We do not bring existence out of nothing. We reshape what already exists. And in that reshaping, the line between wisdom and arrogance, between progress and pride, becomes the most important line of all. 

‍

The futuristic impact of AI, robotics, and technologies

‍

In every yuga, humans have extended the limits of what they can do. What changes is not the desire, but the form it takes. Our ancient history speak of extraordinary abilities, not as fantasies, but as reminders of how power tests character. Figures like Naradmuni (a prominent divine sage (Rishiraja) in Hinduism) are described as moving from one place to another in moments. Others gained immense strength, knowledge, or influence through years of discipline and tapasya. Ravana (Figure from Ramayana) himself was learned and powerful, far beyond ordinary human measure. Sanjaya (the charioteer and advisor of King Dhritarashtra in the Mahabharata) receives the gift of divya drishti and narrates the events of the battlefield without being physically present there, seeing and speaking across distance in a way that still feels remarkable even today.

In this yuga, that ancient search for power and reach has not disappeared, it has only changed its language, and today it speaks through robotics, artificial intelligence, and advanced technologies, making us ask whether we are truly creators or only very advanced arrangers of what already exists.

In this age, science and technology are attempting something similar in a different language. We may not travel like Naradmuni, but we send our voices, images, and thoughts across the world in seconds. We build machines that can see, listen, respond, and even imitate human thinking. Artificial intelligence and robotics promise comfort, speed, and efficiency, and in many ways, they truly improve human life. Yet the old question remains. Not just what can we do, but how far should we go, and at what cost.

When we primarily build for human convenience, we often fail to thoroughly examine the long-term consequences. The environmental impact of large-scale technology is already visible in the pressure on resources, the growth of waste, and the slow damage to air, water, and soil. Nature does not recover at the pace of human ambition. What feels like small compromises today can become heavy burdens for tomorrow.

There is also the impact on the human mind. As systems become more capable, humans risk becoming more dependent. When answers arrive instantly, patience weakens. When machines start deciding for us, the habit of deep thinking slowly fades. Over time, this can affect attention, memory, and judgment. Knowledge becomes easier to reach, but wisdom becomes harder to build. Just as in old stories, the danger is not in having power, but in losing clarity while using it.

Future generations will not encounter these technologies as new inventions. They will be born into them. What we treat today as tools, they will experience as the normal environment of life. This makes responsibility unavoidable. The real question is not only whether these systems work, but what kind of humans they will shape.

The purpose of this reflection is not to reject progress. It is to ask for balance. Building for human comfort is important, but building without studying long-term impact is risky. If this age has the power to create intelligent systems, it must also have the wisdom to protect the environment, care for future generations, and preserve the depth of the human mind. Otherwise, advancement becomes speed without direction, and power without responsibility.

‍

The Acceleration of the Technological Age

‍

The current era has reached a state where technological progress now occurs through instantaneous changes which transform our methods of working and decision-making and future planning. People often view robotics and automation and artificial intelligence as signs of progress yet a less audible inquiry persists through time which asks whether every technological advancement enhances human existence or whether we merely pursue efficient and easy solutions without thinking about their implications. Indian philosophical thought offers a useful lens here, one that does not reject progress but asks whether it aligns with balance, responsibility, and long-term harmony. The definition of intelligence according to this perspective extends beyond computational skills and pattern imitation because it requires people to achieve awareness and intent and their complete understanding. Current machines possess the ability to mimic human reasoning and produce language while they can replicate decision-making processes, but they lack both consciousness and personal experience. 

‍

Power, Responsibility, and Ethical Imbalance

‍

The development of new technological capabilities brings with it ethical responsibilities which every society must handle. Human beings must take on new ethical duties which match their increasing capabilities according to historical evidence. The current situation shows that people create new things at a speed which exceeds their ability to think about those innovations. Systems exist to enhance operational performance while they determine human actions and extend their power but they do not always evaluate their complete impact. Indian traditions emphasize dharma, the principle of balance and rightful action, which shows that power without ethical grounding creates destructive human force. The state of imbalance exists without showing its presence at all times. The process of imbalance development takes place through three channels: environmental degradation, social inequalities, and the gradual decline of human control.

The current society demonstrates this transformation through its existing results. The algorithms now determine our consumption choices and our methods of understanding everything around us. The system provides users with personalized comfort, but it also creates hidden patterns that determine their preferences. The process starts with decision assistance before it progresses to decision influence which eventually leads to decision conditioning. The concept of swatantrata as inner freedom becomes more complicated within such an environment. People stop making freedom choices when they find it easier to select between things that exist in their surroundings because they lose their ability to choose. People start to measure their work activities and personal identity through systems that use optimization techniques and digital validation systems, which leads to a decrease of space that exists for individuals to think and consider matters independently.

‍

Technology, Ecology, and Civilizational Values

‍

The environmental impact of technological demand exists together with social transformations. All systems need power while all infrastructure creates environmental effects and all products, we use contain unknown expenses which become apparent after many years. India's civilizational values maintain their dedication to nature because people see rivers and forests and ecosystems as essential parts of existence. Success in modern society measures output as the main achievement while actual value disappears through the evaluation process. The future requires us to create new things but we must also decide which things to keep intact.

The current situation requires progress to be defined differently because it needs to be measured through precise management instead of continuous rapid development. The question now extends beyond technological advancement to include the need for technologies to be operated through intelligent guidance. The increasing abilities of machines create a greater need for people to maintain their essential human characteristics. Human beings must actively maintain their capacity to make ethical decisions and understand their life's meaning and purpose. The future depends on two factors: the “innovations that will emerge and the values that will guide their development.”

‍

Conclusion

‍

It is high time we pause and honestly examine the path we are taking. The question is not whether technology should grow, but whether its overreach should be allowed to shape the future without restraint. We are building faster than ever, developing systems that touch every part of life. That makes it even more important to study their long-term impact, not only on markets or productivity, but on nature, on the human mind, and on the generations who will inherit this tech-driven world.

Progress should benefit those who come after us, not quietly weaken them. A future where people are born into pure convenience, surrounded by tools that think, decide, and act for them, may look comfortable, but comfort alone does not build strong, aware, or responsible human beings. Growth without effort and ease without discipline slowly takes away depth, resilience, and clarity. Technology should support human potential, not replace it.

This is why morality, ethics, and balance cannot be treated as optional ideas. They must guide innovation, not follow it. We do not need to overcreate. We need to create ‘wisely’. We need to build systems that remain under human control, not systems that slowly train humans to surrender their judgment, attention, and responsibility. Tools should remain tools. They should serve life, not define it.

Indian thought has always placed intention at the centre of action. Karma is not judged only by outcome, but by the spirit in which an act is performed. A tool in itself is neither pure nor impure. It becomes one or the other through the hand that uses it. This is a lens through which modern technology can also be examined. Artificial intelligence can help doctors read scans faster, help farmers predict weather patterns, and help students in remote areas access knowledge. At the same time, it can be used to watch, to sort, to exclude, and to reduce human beings to data points that fit neatly into a system. The difference lies not in the machine, but in the values of those who design and deploy it.

The purpose of this reflection is simple. We should build, but we should build with responsibility. We should innovate, but with awareness of consequences. True progress is not just about what is possible today. It is about what remains healthy, meaningful, and sustainable tomorrow. If this age can combine intelligence with humility, and power with restraint, then technology will not become a symbol of overreach. It will become a sign of maturity.

‍