The Future of Work: Will AI Make Work Fairer...or More Oppressive?

The Future of Work: Will AI Make Work Fairer — or More Oppressive?

I think it all has good intentions.  We want to make it easier, faster, and more profitable.  We want to produce more.  We want success.

But there are stories.

Like when I heard about a large retail company introducing a new artificial intelligence system to oversee hiring and performance evaluations. Algorithms, the leadership explained, could read resumes with neutrality.  Productivity would be analyzed by facts, and personalized growth paths would be based on data. 

Finally, fairness.

At the beginning, it was really exciting.  Resumes that might have been discarded by human recruiters received a second look. Patterns of overlooked talent began to emerge. Current employees who had long felt invisible were suddenly flagged as “high potential.”

But soon the cracks appeared. The same technology that promised impartiality began measuring every aspect of an employee’s day. Every keystroke was logged. Every break was timed. Even a brief pause to gather one’s thoughts registered as “lost productivity.” The system didn’t know how to measure creativity, empathy, or collaboration, which are the intangible skills that drive innovation and make work worth doing. It only knew how to count.

The problem with this is that employees began to feel less like people and more like data points. Work isn’t being seen, it’s being scored.  What was intended as a tool to make work more just had begun to suffocate the very humanity it sought to protect.

This is just one of the paradoxes of artificial intelligence in the workplace: the same technology that can make work fairer has the power to make it far more oppressive. And the direction it takes will depend less on the sophistication of the software than on the values of the organizations deploying it.

Artificial intelligence is not a villain waiting to destroy jobs, nor is it a benevolent savior sent to solve all of our human failings. It is a tool that amplifies the priorities of those who wield it. The difference between fairness and oppression lies not in the code, but in the choices leaders make.

When AI is designed and implemented with integrity, it can reduce bias in hiring and give overlooked candidates a fair chance. Algorithms can analyze vast pools of applicants without being swayed by unconscious prejudices about gender, race, or age. Data can reveal hidden patterns of talent and help match people to opportunities they might never have known existed. For employees already inside an organization, AI can highlight personalized pathways for growth, flag risks of burnout, and even create safer working environments by monitoring hazards.

But technology is never neutral. When efficiency and profit take precedence over human well-being, AI quickly becomes oppressive. In some organizations, algorithms track not only whether employees are meeting goals but whether they are typing fast enough, taking too many restroom breaks, or spending too much time in conversations with colleagues. Productivity is reduced to numbers, while meaningful human qualities like creativity, problem-solving, or empathy end up being irrelevant because they cannot be easily quantified.

In such environments, the balance of power tips even further toward employers. An employee’s ability to challenge a decision made by an algorithm is often nonexistent. Even when mistakes are made, the phrase “the system decided” can become an unassailable shield for unfair practices. Under the banner of fairness, AI risks institutionalizing a new kind of digital oppression.

This tension forces us to confront an uncomfortable truth: organizations are not machines, and people cannot be managed like software code. The impulse to use AI purely for optimization misunderstands the very nature of work. A company is not a collection of inputs and outputs. It is a living ecosystem of human beings, each with emotions, needs, and capacities that extend far beyond what a data model can capture.

Wellness, trust, and belonging are not peripheral concerns. They are the soil in which performance and innovation grow. When employees feel respected, supported, and psychologically safe, they bring their full selves to work. They take risks, offer creative solutions, and invest their energy not just in tasks but in the larger mission of the organization. Countless studies have shown that healthy, engaged employees drive better results. Burnout and fear may deliver short bursts of output, but they erode resilience, loyalty, and innovation in the long run.

AI may be able to make decisions more quickly than humans, but it cannot replicate the nuance of empathy or the moral weight of fairness. Fairness without humanity is hollow. Imagine a perfectly “fair” system where every decision is technically unbiased but where employees feel like cogs in a digital machine. That is not fairness, it’s sterile uniformity. Real fairness is relational. It requires leaders to understand people as more than datasets, to recognize that dignity matters as much as efficiency.

Without this grounding, technology inevitably drifts toward oppression. Efficiency is a seductive metric because it is easy to measure. Dignity, respect, and creativity are harder to quantify, but they are the foundation of thriving workplaces. If leaders fail to ask, “Does this system protect the humanity of the people it governs?” then AI will default to cold calculation. And cold calculation, unchecked, erodes the very thing organizations rely on most: the well-being of their people.

The organizations that will succeed in the future are not the ones that deploy AI the fastest, but the ones that integrate it thoughtfully. They will ask how technology can support human beings rather than replace their judgment, how it can relieve administrative burdens rather than increase pressure, and how it can extend opportunities rather than narrow them.

The urgency of this conversation cannot be overstated. Artificial intelligence is no longer confined to Silicon Valley experiments. It is already in hospitals, banks, factories, classrooms, and office cubicles. Decisions about how it will be used are being made today, often quietly and without broad input. By the time many employees realize how much their work lives have changed, the systems may already be deeply embedded.

This moment represents a profound inflection point. Leaders who treat AI as just another tool to squeeze more productivity from workers may see short-term gains, but they will also create environments of mistrust, stress, and eventual disengagement. Leaders who anchor their use of AI in wellness, equity, and dignity will build workplaces that not only endure but thrive.

The difference is not the sophistication of the technology. It is the vision and values of those who deploy it.

AI in the workplace is not simply a technological issue; it is a human one. It forces us to wrestle with questions that have existed for centuries but now appear in sharper relief. What does fairness really mean in a world where decisions are delegated to machines? How do we measure value when the qualities most essential to humanity like creativity, empathy, or integrity, are also the hardest to quantify? Are we willing to sacrifice long-term well-being in pursuit of short-term efficiency? And perhaps most importantly, what kind of culture do we want to leave for future generations?

These are not technical dilemmas that can be solved with more data or better code. They are ethical, social, and philosophical challenges. That is precisely why they cannot be left only to software engineers or procurement officers. They require broad, thoughtful leadership and a willingness to prioritize human wellness even when it is less measurable than output metrics.

As artificial intelligence pushes further beyond the boundaries of the tech industry, the stakes could not be higher. AI has the potential to dismantle bias, expand access to opportunities, and create safer and more equitable workplaces. But it also has the potential to entrench surveillance, strip away dignity, and reduce human beings to numbers in a system that was never designed to see them fully.

The deciding factor will not be the code itself. It will be the courage and vision of leaders who recognize that the future of work must remain rooted in human wellness. Technology can enhance fairness, but only if fairness is defined as more than neutrality. It must include dignity, belonging, and respect for the whole human being.

The most advanced algorithm in the world will fail if it forgets this truth: a workplace that does not nurture its people will never be truly intelligent.