Artificial Intelligence (AI) Is Not the Culprit but Human Beings Are (02) by Ajith Rohan J.T.F.

• Gist of the article - I consider AI as neutral, humanity as the dynamic force of creation and destruction. I kept a reflective tone yet urgent, aiming to provoke thought without advocating or preaching. I omit the abstract and reported with tangible stakes to show humanity’s dual nature. I call to action focusing inward, framing self-mastery as the true frontier, with AI as a means, not and end.

Prologue

Artificial intelligence (AI) appears large in human collective imagination, often cast as a shadowy Specter— a rival, a usurper, a harbinger of doom. But they have to understand the fact that AI isn’t the challenge they face. AI is not a problem to solve or a foe to vanquish. But, AI is a mirror, a tool, an amplifier—nothing more, nothing less. The real problem lies not in circuits or code, but in the restless, contradictory heart of humanity itself. Human beings are their own greatest obstacle, the architects of their triumphs and their chaos, and the world bears the scars of their struggle.

AI is A Neutral Canvas

AI doesn’t program or dream. It doesn’t hunger for power or struggle with guilt. It processes, predicts, and performs—precisely according to the data human beings feed it and the goals they set. When it accelerates drug discovery or maps the cosmos, it’s not chasing glory; it’s executing their commands. When it falters—misidentifying faces or amplifying biases—it’s not sabotaging them; it’s reflecting their own skewed inputs. AI is a blank slate, a hammer in human’s hands. Whether it builds or breaks depends entirely on human beings.

Compare that with humanity. Human beings are a tangle of brilliance and folly—capable of splitting atoms and curing diseases, yet equally prone to hoarding wealth, waging wars, and torching the planet they live on. AI doesn’t grapple with pride or greed, human do. It doesn’t cling to outdated beliefs or sabotage itself out of fear; those are human signatures. The machine hums along, indifferent, while man struggle with the mess of being human (civil-cultural).

The Human Paradox: Creators and Destroyers

Nature is neither good nor bad. It has no culture or civilization founded on human consciousness. So, human beings are always prone to this natural destructive process. Human history is a testament to this self-imposed challenge. They’ve built wonders—the Pyramids, the internet, vaccines—driven by curiosity and grit. Yet they’ve also unleashed horrors: slavery, genocide, ecological collapse. Each breakthrough carries a shadow, not because tools like AI force it, but because human beings wield them with hands stained by ambition and short-sightedness. The Industrial Revolution birthed modernity—and choked the skies with smog. Nuclear power lit cities—and levelled them. AI could solve hunger or sharpen inequality, the outcome hinges not on its circuits, but on their choices.

Take climate change, a crisis of their own making. AI can model carbon sinks or optimize renewable grids, but it’s humans who delay, deny, or profit from the status quo. The tech isn’t the bottleneck—their will is. Or consider war: drones and algorithms might refine the battlefield, but they don’t ignite the conflicts. Human beings do, fuelled by tribalism and ego. AI doesn’t dream of domination; human beings dream through it.

The World as Witness

The planet itself testifies to this truth. Forests don’t burn because AI wills it—they burn because human beings prioritize convenience over consequence. Oceans don’t block on plastic because machines demand it—they choke because human discard without care. The world isn’t a victim of AI’s rise; it’s a canvas for their recklessness. And yet, it’s also a stage for their recovery. Every act of restoration—reforestation, clean energy, global cooperation—springs from the same human spirit that falters. Thus, it is clear that human beings are the problem and the promise.

The Real Challenge: Mastering human beings themselves

If AI isn’t the hurdle, what is? It’s human—their capacity to harness their gifts without succumbing to their defects. To employ tools like AI with foresight, not just appetite. To confront their biases, not encode them. To choose collaboration over conquest. The machine won’t save them from themselves, nor will it doom them—it simply waits for their lead. The question isn’t whether AI will evolve; it’s whether human beings will.

Imagine a future where human beings rise to this challenge. Where human use AI not to amplify their worst impulses, but to temper them—pairing its precision with their empathy, its speed with their wisdom. That’s not a battle against technology; it’s a reckoning with who human beings are. The world doesn’t need them to tame AI—it needs them to tame themselves according to their cultural-civil dynamics.

Conclusion

So, let’s drop the narrative of AI as humanity’s great adversary. It’s not the anti-hero in this story—human beings are, and they always have been. But, clearly they’re also the heroes, the dreamers, the builders. The challenge isn’t to outsmart the machine; it’s to outgrow their own limitations. AI stands ready, a silent partner in their saga. The next chapter—whether it’s one of ruin or renewal—rests exactly on human being’s shoulders.

Artificial Intelligence (AI) and Objective Research Development (part 01) - Ajith Rohan J.T.F.

 

Introduction - Between Precision and Perspective

In the sprawling landscape of human inquiry, artificial intelligence (AI) has emerged as both a tool and a provocateur, reshaping how we chase the elusive ideal of "objective" research. As of March 10, 2025, AI’s fingerprints are all over scientific discovery, data analysis, and even the philosophical underpinnings of what we call truth. But what does it mean for research to be objective when the hands guiding it—human or silicon—are steeped in their own biases, limits, and dreams? This is a story of promise, tension, and a little existential musing, perfect for anyone peering into the mirror of progress.

The Promise of AI in Research

AI’s strength lies in its ability to chew through mountains of data with an elevate speed and precision no human could match. Take drug development: algorithms now sift through molecular libraries, predicting interactions that once took years of lab grunt work. A 2024 study from MIT showed AI cutting discovery timelines for antibiotics by 40%, a feat that could save lives faster than ever. In physics, AI models crunch cosmic datasets, spotting patterns in galaxy clusters that hint at dark matter’s secrets—work that’s less about intuition and more about raw computational muscle. This feels objective, doesn’t it? Numbers don’t lie, and machines don’t care about prestige or tenure. AI can strip away the human tendency to see what we want to see, offering a cold, clear lens on reality.

The Bias Beneath the Code

AI isn’t a blank slate. It’s built by humans, trained on human data, and reflects human choices. If the dataset feeding an AI is skewed—say, medical trials favouring one demographic—the output inherits that tilt. A 2023 report on facial recognition showed error rates spiking for non-white faces, not because the AI “chose” to fail, but because its training mirrored historical neglect. Objectivity falters when the starting point is already a story of who mattered enough to be counted.

Then there’s the question of intent. Researchers wield AI like a scalpel, but they decide where to cut. An AI analysing climate models might prioritize economic impacts over ecological ones if that’s what the grant demands. The machine doesn’t care, but its masters do. This isn’t a flaw to fix—it’s a feature of any tool shaped by purpose. The dream of pure, detached research bumps up against the messy truth: even AI serves someone’s why.

Accelerating the Objective Chase

Still, AI pushes us closer to objectivity by outpacing our limits. It can run thousands of simulations, test hypotheses we’d never dream up, and spot correlations buried in noise. In 2025, a famous AI company’s own work has leaned into this, using AI to model complex systems—think planetary atmospheres or neural networks—with fewer assumptions baked in with the method of letting the machine question itself, tweaking variables to challenge its own conclusions. It’s not perfect, but it’s a step beyond the human ego’s blind spots (emotions and other subjective reactions).

The Human-AI Relation 

Here’s where it gets personal. Objective research isn’t just about data—it’s about what we do with it. AI can churn out facts, but humans still weave the narrative. Objectivity lives in the cracks between calculation and interpretation.

For researchers, AI is a partner, not a replacement. It’s the silent collaborator that says, “Check this,” while we decide, “Tell me more.” That dance keeps development honest—AI’s rigor tempers our leaps, and our curiosity nudges its focus. Together, they’ve pushed boundaries: cancer diagnostics, quantum computing, even art analysis.

Conclusion - objectivity is a horizon, and the subjectivity depends on “Art of Seeing”

So, is AI the key to objective research? Not quite. It’s a booster rocket, not the destination. It amplifies our ability to chase facts but can’t escape the shadow of who we are (human)—flawed, hopeful, and “endlessly subjective”. Maybe that’s the real lesson: objectivity isn’t a finish line; it’s a horizon. AI gets us closer, but the last step is ours to stumble through.

WATER - MAN THE NARRATOR (10) Autobiographical-Philosophical story - by Ajith Rohan J.T.F.