By:

Anil D. Salve

21 March 2026 at 8:11:09 pm

A Drought of Wisdom in an Ocean of Information

We live in an age where information is everywhere. With a single click, we can access news from across the world, thousands of opinions, countless videos and endless claims. Knowledge has never been so accessible. Yet, in this overwhelming flow of information, something increasingly scarce is discernment-the ability to distinguish what deserves our belief from what deserves our doubt. Information and knowledge are not the same. Reading, watching or hearing something does not automatically...

min read

A Drought of Wisdom in an Ocean of Information

We live in an age where information is everywhere. With a single click, we can access news from across the world, thousands of opinions, countless videos and endless claims. Knowledge has never been so accessible. Yet, in this overwhelming flow of information, something increasingly scarce is discernment-the ability to distinguish what deserves our belief from what deserves our doubt. Information and knowledge are not the same. Reading, watching or hearing something does not automatically make it true. We need the ability to verify information, understand its context, recognise its purpose and only then form an opinion. In the digital age, this ability has become one of the most important forms of wisdom. Social media has transformed the way information travels. WhatsApp, Instagram, Facebook and other platforms have made communication faster, wider and more accessible. But the same speed that connects society can also overwhelm it. Information often reaches us before facts do. A headline is read before the full story. A short video is watched without knowing what happened before or after it. A photograph is circulated without its original context. A message arrives with the familiar words, “Forwarded as received,” and within minutes it may reach thousands of people. By the time the truth catches up, the rumour may already have done its work. The problem becomes even more serious when misinformation is deliberately created and circulated. Rumours may be planted not merely to mislead individuals but to divert public attention from an important issue, create suspicion, damage someone's reputation or push society towards a particular narrative. A distraction does not always need to be completely false. Sometimes a small piece of truth is mixed with exaggeration, selective facts or emotional language. The result can be more powerful than an outright lie because it appears believable. This is how narratives are manufactured. Social media platforms can become powerful tools in this process. A repeated claim begins to look familiar, and familiarity is often mistaken for truth. A provocative post attracts attention. Thousands of reactions create the impression that “everyone” believes it. One emotional video triggers another, comments intensify the mood, and before facts have an opportunity to speak, public sentiment may have already shifted. This is where mob psychology enters the picture. A society can move from calm to anger, suspicion to trust, or optimism to fear with surprising speed. People who would ordinarily think carefully may react differently when they see thousands of others expressing outrage, fear or hostility. The individual begins to follow the crowd, and the crowd begins to reinforce the individual. The danger is not limited to negative emotions. The same mechanism can also be used positively-to mobilise people for social causes, humanitarian assistance, disaster relief, public awareness and community action. Technology itself is neither wise nor foolish. Its impact depends on how information is created, amplified and consumed. The greatest danger, therefore, is not that we have too much information. It is that we may lose the habit of thinking while consuming it. We are increasingly becoming consumers of information rather than creators of thought. Everyone has access to information today, but access does not necessarily mean understanding. The boundaries between a rumour and a report, an opinion and a fact, popularity and truth are becoming increasingly blurred. A post does not become true because thousands of people have liked it. A video does not become evidence merely because it has gone viral. An opinion does not become a fact because it is expressed confidently. An idea does not become correct simply because it confirms what we already believe. This last point deserves particular attention. We often accept information not because it is accurate, but because it is comfortable. We are naturally attracted to information that confirms our existing beliefs and suspicious of information that challenges them. In the digital world, this tendency can be amplified by algorithms that repeatedly expose us to content similar to what we have already watched, liked or shared. Gradually, we may find ourselves living inside an information bubble where we hear many voices-but mostly voices that agree with us. That is not diversity of information. It is an illusion of certainty. Discernment does not mean doubting everything. It means thinking before believing. It means asking simple but powerful questions: Who is saying this? What is the evidence? What is the context? What may be missing? Who benefits if I believe it? And have I heard the other side? These questions may take only a few seconds, but they can prevent hours, days or even years of misunderstanding. This responsibility is particularly important for the younger generation. Children today are growing up in an environment of unprecedented information exposure. They can encounter more information in a few hours than earlier generations might have encountered in weeks. Therefore, education cannot merely teach students how to collect, remember and reproduce information. It must teach them how to question, verify, analyse and interpret it. A student who can write the correct answer in an examination may be academically successful. But a student who knows how to ask the right question is better prepared for life. The classroom of the future must therefore produce not merely informed students, but thinking citizens. They must learn that forwarding a message is also a form of responsibility. Sharing a post is not an innocent act when it can affect someone's reputation, create public fear or influence social behaviour. The challenge becomes even greater in the age of Artificial Intelligence. AI can generate information, images, audio and video with extraordinary speed and sophistication. The distinction between what is real and what merely appears real may become increasingly difficult. In such a world, human judgment becomes more valuable, not less. Technology can produce an answer in seconds. It cannot automatically tell us whether that answer deserves our trust. Some answers require experience. Some require context. Many require the ability to think independently. We have more information, more technology and more connectivity than any previous generation. Yet our real challenge is to preserve something technology cannot manufacture for us: the capacity to think for ourselves. The ocean of information will only become larger. The question will no longer be, “How much information do we have?” The more important questions will be: What should we accept? What should we question? What should we verify? And what should we reject? No technology can completely answer these questions for us. No number of likes can substitute for evidence. No viral trend can replace judgment. No majority can turn misinformation into truth. That responsibility belongs to human beings. Information can tell us what happened. Discernment helps us understand what it means, why it happened, what may be missing from the story and how we should respond. Perhaps, therefore, the greatest educational challenge of our time is not to teach people how to find more information. They already know how to do that. The greater challenge is to teach them how to pause-to pause before believing, to pause before reacting, to pause before forwarding and to pause before joining the crowd. Because sometimes the most intelligent response to information is not an immediate reaction, but a moment of reflection. The ocean is already around us. It is growing deeper every day. What we need now is not more information to swim through it-but the wisdom to know which direction to take. (The writer is the Principal of Podar International School, Ausa, Latur. Views personal.)

War at Machine Speed

Akhilesh Sinha

Mar 14

8 min read

The US–Israel strikes on Iran have shown how artificial intelligence will dictate the future of warfare.

Military history is punctuated by moments when technology abruptly shifts the balance of power. The machine gun, radar and nuclear weapons each transformed warfare in their time. Artificial intelligence now appears poised to join that list. Recent clashes involving Israel, the United States and Iran suggest that algorithms are beginning to shape the outcome of conflicts as decisively as tanks or aircraft once did.

In modern war, victory increasingly belongs not only to the side with superior firepower but to the one that can process information fastest. AI systems can sift through torrents of intelligence, from satellites, drones, intercepted communications and social-media signals, and convert them into precise targeting decisions within minutes. This compression of time has altered what strategists call the ‘kill chain’, or the sequence that turns raw data into military action.

During recent hostilities in the Middle East, American and Israeli forces reportedly deployed sophisticated machine-learning systems to integrate streams of intelligence and guide precision strikes against Iranian assets. Before launching attacks, cyber teams infiltrated digital networks, intercepting surveillance feeds and communications that were then analysed by AI tools to verify targets. Iranian air-defence systems were swiftly neutralised, allowing waves of coordinated strikes. Tehran’s response relied largely on missile launches, highlighting the asymmetry between traditional firepower and data-driven warfare.

Algorithmic Kill Chain

At the centre of this transformation lies Project Maven, a Pentagon programme first launched in 2017 to harness artificial intelligence for battlefield intelligence. Developed with the help of firms such as Palantir Technologies, the system analyses vast volumes of surveillance imagery and communications data to identify potential targets.

Traditionally, military analysts required hours or even days to evaluate intelligence streams and decide where to strike. The United States once acknowledged that assembling reliable targeting options could take as long as 72 hours. AI systems such as Maven can compress that process into minutes, producing hundreds of potential strike options almost instantly. During the opening hours of recent hostilities, American and Israeli forces reportedly launched hundreds of AI-coordinated strikes, overwhelming Iranian defences before commanders could react.

The implications are profound. Modern battlefields generate enormous volumes of data: satellite imagery, drone feeds, intercepted phone calls, emails and encrypted messages from platforms such as WhatsApp and Telegram. Some of it is genuine intelligence; much of it is deliberate disinformation designed to confuse analysts. AI systems excel at detecting patterns within this chaos, filtering out false signals and highlighting credible threats.

In effect, machines are beginning to assist, if not entirely replace, human judgement in selecting targets, estimating damage and recommending the most effective course of action.

Major Shift

The shift from human analysis to algorithmic decision-making is stirring unease. Critics warn that delegating lethal decisions to machines risks lowering the threshold for war or amplifying errors at unprecedented speed. American policymakers have wrestled with the ethical implications of such systems, particularly as private technology firms become involved in military programmes.

One such debate has centred on Anthropic, the developer of the large language model Claude. American defence officials have explored whether similar AI systems could assist in military planning and logistics. The discussion highlights a deeper tension: advanced AI is becoming indispensable to national security, yet its autonomous capabilities raise difficult moral and strategic questions.

Nevertheless, the logic of competition is relentless. As great powers integrate AI into their armed forces, others feel compelled to follow.

For India, the rise of AI-driven warfare carries particular urgency. The country faces persistent security challenges along its borders and through proxy conflicts, including militant activity linked to neighbouring Pakistan. In such an environment, technological superiority can offer a decisive advantage.

Globally, India currently ranks around tenth in overall AI capability. The leaders remain the United States and China, followed by technologically advanced states such as Singapore and the United Kingdom. Yet India possesses notable strengths: a vast pool of technical talent and a rapidly expanding digital ecosystem.

The weaknesses are equally clear. The country’s digital infrastructure still trails that of leading AI powers, and it accounts for only a small share of global high-performance computing capacity. Venture capital investment in AI remains heavily concentrated in America and China.

Recognising the stakes, New Delhi has begun pushing forward. Institutions such as NITI Aayog have crafted a national AI strategy emphasising education, data infrastructure and collaboration between universities and industry. Premier institutions, from the Indian Institutes of Technology to the Indian Institute of Science, are expanding programmes in machine learning and data science. The goal is not merely to use foreign technology but to develop indigenous AI systems suited to India’s needs, including tools for healthcare, agriculture and Indian-language computing.

India also sees AI through a broader geopolitical lens. As the world’s largest democracy and a leading voice of the Global South, it hopes to shape the governance of emerging technologies rather than simply adapt to them. At gatherings such as the G20 Delhi Summit and the India AI Impact Summit, officials have emphasised the need for inclusive innovation and ethical safeguards.

Yet the strategic message remains unmistakable. Just as nuclear capability once conferred geopolitical weight, mastery of artificial intelligence may soon define the hierarchy of power in the twenty-first century.

In war as in commerce, the countries that command algorithms and the data that feeds them are likely to command the future.

Digital Shields in Proxy War

Terrorism, like most other forms of conflict, has migrated online. The modern extremist organisation no longer relies solely on clandestine camps in remote mountains; it recruits, radicalises and coordinates through the glow of smartphone screens. For countries such as India, facing persistent proxy warfare in its neighbourhood, artificial intelligence is becoming an increasingly vital defensive tool.

The digital battlefield is vast. Extremist groups have learned to exploit social-media ecosystems to spread propaganda, identify vulnerable recruits and orchestrate attacks with alarming sophistication. These networks blend online persuasion with operational planning. Encrypted messaging, algorithm-driven propaganda and psychological manipulation form part of a digital playbook designed to convert alienated individuals into instruments of violence.

Recent incidents illustrate the pattern. A terrorist attack near Red Fort on November 10, 2025, and another assault weeks later at Bondi Beach revealed how seemingly isolated ‘lone wolf attacks can in fact be carefully orchestrated through online networks. The perpetrators may appear to act alone, but their radicalisation often occurs in the hidden corners of the internet, where extremist narratives circulate unchecked.

The shift to digital radicalisation reflects a broader geopolitical reality. Even as territorial strongholds in Iraq and Syria were dismantled, groups such as Islamic State adapted by strengthening their online operations. Secure messaging platforms and anonymous forums now serve as substitutes for physical training camps, allowing extremist networks to operate across borders with relative ease.

For India, the problem is compounded by the long shadow of cross-border militancy. Security officials frequently accuse Pakistan of sustaining a strategy of proxy warfare through militant intermediaries. Groups such as The Resistance Front and People’s Anti-Fascist Front have been linked to online propaganda campaigns designed to recruit and radicalise youth in the sensitive region of Jammu and Kashmir.

Investigations into attacks such as the Red Fort bombing revealed a striking detail: some of those drawn into extremist plots were highly educated professionals, including doctors. The term “white-collar terrorism” has begun to circulate among investigators, reflecting the uncomfortable reality that digital radicalisation can reach far beyond marginalised communities. Encrypted platforms such as Threema complicate forensic investigations, allowing recruiters to communicate with potential operatives while evading surveillance.

To counter this evolving threat, governments are increasingly turning to artificial intelligence. AI systems can analyse vast streams of digital information to detect early signs of radicalisation or coordinated activity. For intelligence agencies overwhelmed by the sheer volume of online data, such tools offer a crucial advantage.

India has begun integrating these technologies into its security apparatus. At the country’s AI Impact Summit, police personnel demonstrated smart glasses equipped with AI-powered facial-recognition capabilities, designed to identify suspects in crowded public spaces. The government has also moved aggressively to curb online propaganda: in 2025 alone, authorities blocked nearly 9,845 internet addresses linked to extremist or terrorist content.

The effort is hardly confined to India. Countries across Asia including Australia, Malaysia, Singapore and Indonesia have strengthened legislation and surveillance tools to combat online radicalisation. Regional cooperation has also deepened, reflecting the recognition that digital extremism respects no borders.

Artificial intelligence, of course, is no panacea. Terrorist groups adapt quickly, exploiting new platforms as soon as old ones are closed. Yet the technology offers governments a powerful means of shifting the balance by detecting patterns invisible to the human eye and enabling earlier interventions.

Revolutionizing Professions, Boosting Incomes

Artificial intelligence is often portrayed as a technological juggernaut poised to devour jobs. Yet the reality emerging across industries is subtler and more optimistic.

Like earlier general-purpose technologies such as electricity or the internet, AI is proving less a destroyer of professions than a multiplier of human productivity. By automating drudgery and refining decision-making, it is quietly raising incomes and creating niches that did not exist a decade ago.

Consider an unlikely beneficiary: the humble florist. Algorithms that analyse footfall, seasonal demand and social-media trends now guide flower retailers in managing their most perishable asset fresh blooms. Smart inventory systems help sellers maintain just enough stock to keep bouquets fresh while avoiding spoilage. Machine-learning tools sift through sales data to forecast seasonal hits, allowing shopkeepers to place their displays strategically. Staff spend less time on guesswork and manual records, and more on customer service. A small shop becomes, in effect, a data-driven enterprise.

Such transformations echo a broader historical pattern. The mechanisation of textile mills in the 19th century did not eliminate textile workers; it changed their roles and multiplied output. AI is performing a similar function across today’s knowledge economy.

Education illustrates the point well. Adaptive learning platforms such as Duolingo adjust lessons to a student’s pace, improving retention rates dramatically. Teachers increasingly rely on AI-assisted grading tools and virtual tutors, saving hours each week that can be redirected toward mentoring and classroom engagement. Algorithms also flag students at risk of falling behind, enabling earlier interventions that can improve graduation rates.

Agriculture, the world’s oldest industry, is undergoing a comparable technological revival. AI-driven drones and sensors enable precision farming: crops are monitored in real time, irrigation is tailored to soil conditions, and yields are optimised while water use falls. Smartphone-based image recognition allows farmers to identify pests instantly and deploy targeted pesticides instead of blanket spraying. In regions where weather shocks can devastate livelihoods, from India’s monsoon belt to America’s Midwest, predictive models offer a valuable early warning. The result is not only greater efficiency but also a measurable rise in farm incomes.

Finance, long an early adopter of computing, has embraced AI with particular enthusiasm. Algorithms now scan thousands of transactions per second to detect fraud in real time, a task once handled by armies of analysts. Retail investors increasingly turn to automated advisory platforms that build portfolios and rebalance them with mathematical discipline. Natural-language tools sift through regulatory documents and compliance reports in hours rather than weeks, sparing banks costly errors.

Healthcare offers perhaps the most striking examples. AI-assisted imaging can analyse scans and flag potential cancers with remarkable accuracy within seconds, helping doctors make faster diagnoses. Predictive analytics forecast complications before they occur, allowing hospitals to shorten patient stays and allocate resources more efficiently. Robotic-assisted surgery systems such as da Vinci Surgical System reduce the likelihood of human error while enabling surgeons to perform delicate procedures with unprecedented precision. Even mundane tasks are shifting: chatbots handle routine patient queries, freeing nurses to focus on bedside care.

Factories, too, are becoming laboratories of algorithmic efficiency. Predictive-maintenance systems analyse vibrations, temperatures and machine performance to anticipate breakdowns before they occur. Collaborative robots (‘cobots’) work alongside humans, boosting output while maintaining safety. Vision systems inspect products on assembly lines, identifying defects far more reliably than the human eye.

The legal profession, once thought resistant to automation, is also adapting. AI systems now scan lengthy contracts for hidden risks and precedents in seconds, enabling lawyers to focus on strategy rather than paperwork. Similar tools analyse past rulings to estimate the likelihood of success in litigation. In creative industries, generative systems from Midjourney to GitHub Copilot are accelerating content creation and software development, giving rise to new roles such as ‘prompt engineers.’

The cumulative effect is striking. Across manufacturing, predictive maintenance alone can halve equipment downtime; automated quality control dramatically reduces defects; and algorithmic supply-chain management trims inventory costs.

History suggests that such technological leaps rarely shrink the total number of jobs. The steam engine, electrification and the computer all displaced certain roles while creating new industries and professions. AI appears set to follow the same path.

A Drought of Wisdom in an Ocean of Information

War at Machine Speed

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