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Artificial intelligence (AI)—encompassing machine learning, neural networks, generative models, and advanced algorithms—is a defining technology of the 21st century, reshaping economies, societies, and global systems. Its capacity to address pressing challenges is unparalleled: AI-driven climate models enhance disaster preparedness, medical diagnostics accelerate drug discovery, and predictive tools boost economic efficiency. Yet, these advancements carry significant risks, including deepening wealth inequalities through corporate monopolies, enabling digital authoritarianism via surveillance systems, and threatening individual freedoms through unchecked data exploitation. The dual nature of AI—its potential for progress and peril—raises a critical question: How can society harness its benefits while mitigating its dangers?

This article does not address the Nepal-specific context, as that could be a comprehensive topic for a separate write-up. Instead, it examines the trajectory of state-of-the-art AI through a multifaceted lens: historical lessons, information networks, practical applications, health and media innovations, corporate accountability, global competition, and ethical realities. We argue that deliberate, equitable governance, ethical system design, and robust global cooperation can maximize AI’s societal benefits while preventing division, surveillance states, or corporate-driven harm. Without proactive measures, AI risks eroding democratic liberties and exacerbating global inequities. With foresight and collective action, however, it can foster an inclusive future prioritizing shared prosperity, human dignity, and sustainable progress.

Historical lessons and corporate power: governing technology for equity

History shows that transformative technologies drive progress but often concentrate wealth and power unless governed equitably. For centuries, global productivity growth stagnated, with innovations like the iron plow benefiting feudal elites while most lived in subsistence. The Industrial Revolution marked a shift, with steam engines and mechanized production boosting annual growth from 0.1 percent to 1.9 percent by the late 19th century, and averaging 2.8 percent through the 20th century. Yet, mechanization displaced workers, sparking unrest until labor movements and policies like the Factory Acts secured protections such as fair wages and working hours. This pattern underscores a key lesson: technological advancements require governance to ensure broad societal benefits.

AI’s evolution mirrors this dynamic. From IBM’s Deep Blue defeating chess champion Garry Kasparov in 1997 to transformer-based models enabling nuanced language processing, AI has advanced from narrow applications to systems with widespread impact. However, a “productivity paradox” persists: global labor productivity growth slowed to 1.8 percent annually between 2005 and 2015, down from 2.5 percent in the 1990s, due to uneven adoption, skill gaps, and corporate prioritization of shareholder value over societal good.

AI offers a path to reverse this trend, streamlining manufacturing and increasing agricultural yields through precision farming tools, such as AI-powered irrigation systems in sub-Saharan Africa that enhance food security. Yet, without equitable deployment, AI risks replicating historical inequities. Tech giants and state-backed firms could monopolize benefits, marginalizing workers and smaller economies. Corporate monopolies control vast data and computational resources, stifling competition and limiting access, particularly in developing economies. Corporate negligence, such as failing to moderate harmful content, has fueled social unrest and public health crises, while partnerships with authoritarian regimes for surveillance tools highlight complicity in undermining freedoms. To counter these risks, antitrust enforcement, public investment in research, and upskilling programs are essential. Policies like universal basic income, piloted in Scandinavia, support workers displaced by automation, enabling retraining for an AI-driven economy. Transparent accountability mechanisms and global standards, despite resistance from corporate lobbying, are critical to ensure AI fosters inclusive growth rather than concentrated power.

AI as an information network: Connectivity and risks

AI extends humanity’s information networks, building on the legacy of the printing press, telegraph, and internet, which enabled unprecedented cooperation but also amplified risks like misinformation and propaganda. AI embodies this duality. It enhances global connectivity and efficiency, with climate models improving flood predictions in vulnerable regions and predictive algorithms optimizing retail supply chains to reduce waste and costs. These advancements demonstrate AI’s potential to strengthen global systems and foster collaboration.

However, AI networks pose significant dangers. Fabricated content, such as deepfake videos, erodes trust in democratic processes, as seen in election-related misinformation campaigns. Authoritarian regimes leverage AI for behavioral surveillance, tracking citizens through data-driven systems. Corporate negligence exacerbates these risks, with social media platforms often failing to curb harmful content due to profit-driven priorities. Solutions include algorithmic transparency, strict content moderation, and decentralized data governance. Some democracies mandate audits of AI systems to prevent bias and misinformation, but global enforcement remains fragmented due to corporate resistance and varying legal standards. Robust accountability mechanisms are essential to ensure AI serves as a tool for cooperation rather than division.

Practical applications and health innovations: Promise and pitfalls

AI’s practical applications span diverse sectors, driving productivity when designed collaboratively and ethically. In education, AI-powered tutoring systems address teacher shortages, improving outcomes in underserved areas. In energy, AI-optimized grids enhance reliability, reducing outages in unstable infrastructures. In logistics, predictive models streamline delivery networks, cutting costs and emissions, as seen in AI-driven route optimization in shipping that reduces fuel consumption. Long-term, AI holds promise for climate solutions like advanced carbon capture and renewable energy forecasting, critical for global net-zero targets.

In healthcare, AI is revolutionizing synthetic biology and diagnostics. AI-driven protein modeling accelerates drug discovery for diseases like cancer, while diagnostic tools enhance accuracy in resource-constrained settings, improving tuberculosis detection in low-income regions. AI-engineered microbes show promise in reducing environmental waste, aligning health innovation with sustainability.

However, pitfalls persist. Biased algorithms, trained on skewed datasets, perpetuate inequities, as seen in early AI hiring tools that favored certain demographics. Flawed datasets in healthcare can lead to misdiagnoses, while underrepresentation of diverse populations reduces efficacy and exacerbates health inequities. Biosecurity risks, such as AI designing harmful pathogens, demand urgent attention. Misinformation on AI-driven platforms has eroded public trust, fueling vaccine hesitancy during health crises.

To address these challenges, bias audits, mandatory kill switches, and human-in-the-loop frameworks ensure oversight. Transparent, inclusive datasets and international oversight through global health AI guidelines are vital, as are robust bioethics protocols. Regulatory delays hinder progress, with some regions struggling to implement biosecurity measures. Collaborative innovation—pairing public, private, and academic efforts with ethical scrutiny—will ensure AI drives progress without deepening divides or enabling unchecked power.

AI, media, and democratic governance: Strengthening civic engagement

AI is reshaping political discourse, amplifying populist narratives while offering tools to strengthen democratic engagement. Social media algorithms fuel sensationalism, polarizing societies and undermining trust in institutions. Micro-targeting exploits psychological data to sway voters, and privacy-invasive systems threaten autonomy, with large-scale voter data systems raising concerns about surveillance and democratic erosion. Yet, AI also empowers civic participation. Digital platforms facilitate transparent budget audits, uncovering fraud and enhancing governance, while AI-driven apps boost voter turnout by simplifying access to information and fostering community engagement.

To counter manipulation, algorithmic transparency and independent content moderation are critical. Some governments require platforms to disclose content prioritization methods, reducing harmful narratives. Balancing free speech with global standards remains challenging, particularly on platforms where echo chambers entrench division. Public literacy programs, teaching citizens to evaluate AI-driven content critically, are vital. Inclusive governance, such as participatory platforms engaging diverse voices, can protect democracy. By leveraging AI’s potential for transparency and engagement while addressing its risks, societies can strengthen democratic institutions in an era of rapid technological change.

Global competition and ethical realities: Navigating geopolitics and technical limits

The US-China AI race is reshaping global geopolitics, with both nations vying for technological supremacy. The US leverages advanced chip production and private-sector innovation, while China counters with state investment and domestically developed models. Developing nations, caught in this rivalry, face risks of surveillance and economic dependency, as seen in the adoption of certain 5G infrastructures. Sanctions and competing economic systems deepen divides, with hardware access restrictions prompting alternative supply chains and technological fragmentation.

AI excels in specific tasks but falls short of general intelligence, revealing technical and ethical limitations. Adversarial attacks, where systems misinterpret inputs, and biased outputs from skewed datasets highlight the alignment problem: AI often fails to reflect human values. Errors in welfare systems have excluded vulnerable populations, while biased algorithms perpetuate inequities in justice and hiring. Regulatory frameworks, like risk assessments and transparency mandates, aim to address these issues, but rapid advances outpace governance. Interdisciplinary research, including AI ethics boards, reduces bias through iterative testing, though encoding diverse values, particularly from underrepresented regions, remains challenging.

Cooperative frameworks, such as international AI safety protocols, aim to curb escalation, but geopolitical tensions and corporate interests undermine progress. Developing nations are building local AI capacity through public-private partnerships and research hubs tailored to local needs. AI-driven military systems and surveillance programs threaten privacy and freedom, with global powers deploying data collection at unprecedented scales. Global ethical standards, transparent governance, and international treaties can balance security and liberty, but superpower rivalries complicate cooperation. Balancing competition with collaboration is essential to ensure AI drives global progress rather than conflict or exclusion.

Conclusion: A human-centric vision for AI’s future

AI’s potential to tackle humanity’s greatest challenges—healthcare, productivity, climate change—is matched by its risks to equity, freedom, and trust. Historical lessons, from the Industrial Revolution to modern generative models, underscore the need for deliberate, inclusive policies. Collaborative innovation, corporate accountability, and global cooperation provide a roadmap for a sustainable AI future. Antitrust measures, workforce upskilling, and public investment counter wealth concentration, while transparent information networks and ethical frameworks mitigate misinformation and biases. Global treaties prevent technological fragmentation, and public literacy empowers democratic oversight.

AI raises profound questions about truth, agency, and global power, challenging traditional notions of knowledge and autonomy. By prioritizing human dignity, fairness, and freedom through ethical design and governance, we can ensure AI’s benefits outweigh its harms. Interdisciplinary collaboration—spanning governments, academia, and civil society—can overcome corporate lobbying and technical complexity, steering AI toward collective human progress. This human-centric vision fosters an inclusive future where technology amplifies shared potential, driving equitable, sustainable progress for all.

Note: The author acknowledges using large language models, such as Grok and ChatGPT, to edit this article

Alright, buckle up because out of all the wild science headlines this decade, nothing’s got people buzzing like this. Scientists are genuinely trying to bring back the woolly mammoth. Not in a “run for your life, T. rex on the loose” kind of way, but as a legit plan to tackle climate change. Sounds like science fiction, right? But gene-editing nerds are already in the lab, mixing DNA like it’s a high-stakes cocktail party. Which begs the question: Just because we can play Dr Frankenstein with extinct creatures, does that mean we actually should?

How are they pulling this off? Here’s the deal. Nobody’s pulling a frozen mammoth out of the ice and zapping it back to life. Instead, the plan is to grab some DNA from those long-dead shaggy beasts and mash it together with Asian elephant DNA, the mammoth’s closest living cousin. What do you get? Basically a cold-resistant elephant-mammoth mix that’s supposed to be right at home in Siberia’s freezing tundra.

A startup with the Hollywood-ready name Colossal Biosciences is leading the charge, and Harvard’s George Church is the ringmaster. Their pitch is simple. Let these mammoth-like creatures loose in the tundra, and they’ll stomp around, restore grasslands, trap carbon, and maybe slow down global warming. It’s not just a nostalgia trip for Ice Age fans. It’s eco-engineering on steroids.

Sounds epic, but let’s pump the brakes. Playing God with extinct animals comes with a truckload of headaches. What if the mammoth-elephant hybrids end up suffering in ways we can’t predict? Or what if they break out of their “controlled” parks and start trashing today’s ecosystems? And here’s a big question. Should we really be tossing millions at resurrecting the dead when actual endangered animals like rhinos and tigers are disappearing right now?

Some folks say we’re just making pricey sideshows for rich people’s zoos. Others believe science could help us save animals teetering on the edge today. Depends on who you ask.

Alright, so Nepal’s not exactly in the running for best habitat for mammoths. But don’t tune out yet. This gene-editing tech could totally shake up conservation in the Himalayas too. Imagine using it to bring back lost mountain plants or even strengthen snow leopards so they don’t get wiped out by new diseases.

Dr Neelam Thakur at Bir Hospital says Nepal should keep a close eye on all this. “We might not be leading the charge in de-extinction, but these techniques could help our own species hang on,” she says. The catch is Nepal has almost no rules for this stuff. If we just jump in, it’s basically an ethical free-for-all.

De-extinction shouldn’t be a free-for-all where anyone with a gene gun can play mad scientist. If we’re going to do this, we need real rules, ecological studies, and public debate, not just billionaires chasing headlines and viral videos.

For Nepal, the takeaway is simple. Put money into genetic research that helps the wildlife we have now. Let’s not get ahead of ourselves dreaming about reviving the ghosts of the past.

Woolly mammoth comebacks aren’t science fiction anymore. They’re in the works. The big question isn’t “Can we pull it off?” It’s “Will this actually make the world better, or is it just a weird flex?” If we play it smart, de-extinction could be one more tool to heal broken ecosystems. But saving what’s still alive should be the priority, for Nepal and everywhere else. Because once species are gone, bringing them back is a lot harder than protecting them in the first place.

Prakash Khadka

Kathmandu Model College, Bagbazar

When Covid-19 reached Nepal in early 2020, everything came to a halt. The once-bustling streets of Kathmandu fell silent. In the villages, an even deeper stillness took hold. Families stopped hearing from loved ones working abroad. Schools closed. Health centers ran out of medicine. People felt completely alone.

For many, the hardship went far beyond staying indoors. The virus made it hard to breathe, but so did poverty and fear. Countless families lost their sole breadwinner. That meant no food, no school, and no hope. Nepal didn’t just get sick. It broke. And the weight of that breaking felt insurmountable.

But what if the crisis that brought Nepal to its knees wasn’t the final chapter, but the necessary prologue to a national reinvention?

Forget “recovery.” Recovery suggests a return to the same fragile system that collapsed at the first tremor. The pandemic wasn’t just a tragedy to repair; it was a revelation. A siren call to abandon broken blueprints and design an economy that actually works. What if the architecture of our collapse could become the model for our rebirth?

Before Covid-19, Nepal was celebrated for its “remittance economy.” We sent our youth abroad, and their earnings helped sustain the nation. But we ignored the true cost. Villages emptied out. Land was abandoned. Families were split across continents. A national identity was built on the loneliness of video calls.

Then the borders closed, remittances collapsed, and the illusion vanished. What we thought was a safety net turned out to be a tightrope—and Covid-19 cut the line.

Tourism, once touted as a cornerstone of our GDP, proved just as fragile. When it collapsed, it left behind shuttered hotels, unemployed guides, and debt-ridden businesses. We had relied too heavily and planned too little.

And what about the informal sector, the backbone for over 70 percent of our workforce? It was always a blind spot we chose to ignore. When lockdowns hit, 1.6 million jobs vanished overnight. No contracts. No insurance. No savings. Just millions rendered invisible by a system that never acknowledged them.

Education failed, too. Many schools turned to online learning—but what about children in villages without internet, electricity, or smartphones? Around 95,000 children, mostly girls, dropped out and never returned. Some were forced into child labor or early marriage. This wasn’t an unforeseen consequence. It exposed a long-standing failure to support the most marginalized.

None of these problems were new. The pandemic simply made them impossible to ignore. It held up a mirror to a system already cracked. And even amid the pain, it gave us something else—a rare chance to build something better.

So what if we stopped exporting our youth and started investing in them at home? What if empty villages became hubs of tea, coffee, and herb production? What if young people were trained to use digital tools to sell their own products?

Imagine if every village had a solar-powered tech center, where children could access online learning, patients could consult doctors remotely, and local businesses could connect with global markets. This is not a fantasy. Nepal has smart, capable young people. Instead of waiting for foreign help, let’s back their ideas.

The government can create youth innovation funds to support small-scale projects in farming, green energy, recycling, and technology. Trust the youth. They understand the problems because they live them. Their solutions are rooted in reality, not written in distant reports.

This isn’t utopian thinking. It’s a survival strategy. Look at our neighbors. Sri Lanka’s economic collapse was built on the same foundations of debt and import dependency. Bangladesh is now facing a foreign reserve crisis. These are not distant warnings; they are potential previews of Nepal’s own future if we try to return to “normal.”

After Covid-19, poverty in Nepal surged again, with rural areas hit hardest. In some regions, one doctor serves thousands. That’s not just unfair, it’s unsustainable. An economy built on foreign labor, foreign remittances, and foreign tourists is neither strong nor safe.

If we go back to the old system, we’re not recovering—we’re refusing to learn. We’re choosing to leave millions behind.

Covid-19 taught us the unimaginable can happen overnight. In just a week, the global systems we depended on were unplugged. That’s terrifying, but also liberating. It showed us that the structures we thought were permanent are, in fact, fragile.

So why rebuild the same system that failed us? The wreckage is all around us. It’s time to stop mourning what we lost and start building what we need. It’s time to turn the memory of our greatest crisis into the blueprint for our greatest awakening.

Let’s not waste this chance. Let’s turn this crisis into a new beginning. We have seen the problems. Now we must build the solutions. Nepal deserves an economy that works for everyone. It’s time to stop waiting, and start building.

Himal Subedi 

Narayani English Public Secondary School, Bharatpur, Chitwan

Recently, we, the students of grade 10, were shown a movie in our school to help us learn how to write a movie review in English. The review about the same movie has been included in our textbook. The movie made me marvel over something which I had always taken for granted. Yes, it’s the sense of loyalty in a dog towards its master. This article is my general reflection as a result of watching the movie. It is not a review of the movie. 

Even if dogs bring out their fierce self at times, there always lies an unassuming being underneath. The haters and non-sympathisers of dogs squarely blame the latter’s instinctive nature. But there are methods to their madness. It’s the government’s responsibility to check their menace. If we somehow had some unpleasant experiences with dogs, it would be more because of stray dogs. Developed countries with proven track records of humane treatment of animals never have stray dogs in their streets. Respect to dogs shouldn’t limit to worshipping them on Kukur Tihar and forgetting them the rest of the year. 

We can say that dogs are the only animal who defines loyalty, even better than the supremely sentient human. They stay with us through thick and thin even though people leave us like rats deserting a sinking ship. 

I have heard of a true story of a dog named Charlie in the USA. In an emergency situation, his mental reflex worked to our bewilderment and sacrificed his life to save his master’s life in a house fire. The dog rushed into the burning house and woke up the master but the dog got trapped inside. 

It is often said that God has created dogs as an apology for creating humans. God has sent dogs to heal something inside us that dogs didn’t break. We humans can learn unwavering loyalty and love at its purest form from dogs.

Mohishu GC

Grade: X

Sanskar Pathshala, Dang