THE MIRROR CALLED AI REFLECTS OUR OWN ETHICS NIRANJAN GIDWANI

 

Artificial Intelligence is often described as humanity’s most transformative creation. It may well turn out to be so.

A tool that can think, decide, and even predict better than most humans. But amidst the fascination and fear surrounding AI, one truth is often ignored, and most of the time, intentionally. AI is not ethical or unethical by itself. It simply mirrors the values, intent, and blind spots of those who build, deploy, and control it. The real question, therefore, is not whether AI can be ethical. The real question is whether we, as a race, still wish to operate at the highest level of ethics.

 

The uncomfortable truth about ethical lapses

Across boardrooms, political circles, and even personal lives, we are all able to see a common pattern. Ethical compromises justified in the name of survival, ambition, or what we call as “greater good.” Sometimes even referred to as “Collateral Damage”. Whether it is corporate greenwashing, data manipulation, biased hiring, or the silent acceptance of workplace injustice, ethics is often treated as an optional extra, not a fundamental baseline.

When leaders make decisions that prioritize profit, speed, or social dominance over fairness, transparency, and empathy, then technology becomes a helpless accomplice. This is precisely what we witness in AI today. Bias in algorithms, opaque decision systems, and large-scale automation without accountability. These are not AI’s failures. Aren’t they reflections of human systems that built them, and continue to do so, without moral guardrails?

 

 

Leaders define the soul of AI, not coders

A machine learning engineer can design an algorithm, but it is the leaders, policymakers, and investors who decide how it will be used. Whether AI results in job creation or mass layoffs, empowerment or exploitation, inclusion or discrimination, all of it finally depends on one aspect - Human Intent.

Consider an example: when a large corporation decides to replace customer service staff with AI chatbots, the decision isn’t made by the AI itself. It is made by a leadership team trying to reduce costs. Or to better the profits or bonuses they are already making. The machine becomes the messenger, not the executor of morality. Similarly, when governments use facial-recognition systems for surveillance rather than safety, the ethical compromise lies in governance, not in the code.

Contrast that with healthcare innovations using AI to detect cancer early or forecast epidemics. These reflect human compassion which is wonderfully channeled through technology. The difference lies, not in the algorithm. The difference clearly lies in purpose.

Why ethics has taken a backseat

There are deeper reasons why ethics keeps losing ground.

First, ethics is rarely rewarded. Markets reward productivity, shareholders reward profits, and voters reward populism. Ethical reflection takes time, humility, and often personal risk. Ethical reflections seem to be a luxury in an age of instant performance comparisons.

Second, society has fallen into a collective illusion: that technology itself will fix our moral shortcomings. Many believe AI can be taught fairness, that code can learn empathy, or that governance frameworks can “automate” ethical restraints. Sadly, empathy isn’t an algorithmic skill. It is a moral discipline cultivated through awareness and human example.

Finally, most leaders and professionals face simple temptations. Cut corners, chase recognition, avoid accountability. All of which erode ethical culture over time. AI, when introduced into such environments, magnifies only what already exists.

 

Lessons from around the world

• The negative: In 2020, an AI recruitment tool used by a leading global firm was found to favor male candidates over female ones. The algorithm had learnt from years of biased human hiring data. Instead of correcting discrimination, AI inherited it.
• The positive: Meanwhile, in India and Singapore, government-backed AI systems have been developed to monitor water usage and optimize resource distribution. This blends technology with social responsibility. While results in Singapore are visible, India still has some way to go.
• The cautionary: Some predictive policing tools used in the United States began profiling minority communities disproportionately. Left unchecked, they risk turning old prejudices into digital certainties.

Each of these examples carries one clear message: ethics must be designed into the process. Ethics cannot be patched on after a scandal.

 

Corrective steps before it’s too late

1.  Embed ethics into leadership education. Leaders must treat ethical reasoning as a professional skill, not personal virtue. It should sit alongside data literacy, strategy, and financial acumen.

2.  Set human oversight as a rule, not an option. Wherever AI impacts people’s lives, whether in jobs, justice, or healthcare, there must be a transparent and clearly recorded human decision chain.

3.  Reward ethical choices publicly. Boards, investors, and regulators should acknowledge and incentivize leaders and organizations that prioritize human-centric AI deployment.

4.  Foster a culture of questioning. Ethical conversations must be encouraged across all organizational levels, not limited to risk committees or compliance teams.

5.  Create shared accountability. The responsibility for making AI ethical cannot rest solely on developers. It is a shared responsibility across leadership, policy, and society.

The moral mirror ahead

We keep hearing that AI is learning super-fast. But who is it learning from?  It’s learning from us. It’s learning from the data, the data biases and our biases that we are okaying. The real danger is not that machines will become more intelligent. Chances are high that we may become less reflective.

If humans surrender decision-making, not because AI is better, but because we want to avoid responsibility, we risk losing the moral compass that defines leadership.

Ethics cannot be outsourced, automated, or delegated. It begins with every individual who chooses integrity over convenience. Leaders, especially, carry the torch. Not only to guide AI’s direction but to ensure it reflects the best version of what humanity stands for. If the current version of what humanity stands for needs to be improved, then that is the area to first focus on.

In the end, AI will not replace people. People will replace people. Based on decisions some other people make. If those other people’s decisions lack empathy and fairness, then let us not believe that some algorithm, however advanced, will end up making the world more just.

A concluding reflection

AI will become mankind’s most powerful mirror. Whether it reflects brilliance or blindness will depend on our moral clarity. The urgency is not to fear AI but to reawaken the conscience that must guide it. Return on Ethics Investment may need to get healthier than Return on Investment. For the sake of our future generations.