The ethical considerations of replacing human tasks with AI

The debate around AI and the future of work often boils down to one fundamental question: what should be automated and what should stay in human hands?

Is it ok to displace certain workers? For example, what if an AI could analyse thousands of data points and assess someone’s suitability for a loan or insurance policy far better than a human underwriter? What do we owe people?

These aren’t just practical questions — they’re ethical ones that challenge us to consider the value of human work in a world increasingly dominated by AI.

Inhuman repetitiveness vs. human creativity

There are tasks that humans do every day that are repetitive, monotonous and, frankly, not the best use of our potential. This is where AI excels: processing data, sorting information, performing routine transactions. AI can handle these jobs with unmatched efficiency and precision, giving humans more time to focus on higher value tasks that require creativity, judgement and emotional intelligence.

But not all tasks can or should be handed over to AI.

High value human tasks involve more than just following a script or processing data — they require nuanced understanding, empathy and real world thinking. In other words, an ability to consider the grey areas. In its current state, AI can’t navigate complex social dynamics and human emotions, it isn’t truly empathetic.

This is where human creativity and decision making come into play, and where AI, for all its strengths, still falls short.

Things like meaningful marketing strategies that require an understanding of causal relationships and human intelligence, or management that makes people feel understood and cared for because it comes from a place of empathy, still need humans.

Ethical considerations

The ethical implications of replacing human tasks with AI are complex. On the one hand, automating routine, process-driven tasks can lead to greater efficiency and productivity. In this scenario, humans and AI can often work together, each contributing their expertise to make the overall output better.

Education, for example, could be greatly enhanced by AI, with tasks like planning and grading automated by micro roles, while human teachers focus on personalised interaction with students, developing core skills and offering guidance.

On the other hand, it can also lead to job displacement and a loss of purpose for those whose tasks are being completely automated. White collar jobs like bookkeeping, routine analysis and data entry are likely to fall into this category.

Value is relative — it depends on the person, their role and their perspective. For some, the automation of a task might seem like progress. For others, it might feel like a threat to their livelihood and sense of self.

The key is finding a balance between efficiency and humanity, between progress and preservation.

Lessons from history

History offers us some valuable lessons. Consider the introduction of ATMs, which replaced bank tellers for routine transactions, or the arrival of online booking systems that made travel agents less in demand. These shifts brought convenience and efficiency, but they also fundamentally changed the nature of work for millions of people.

What was gained? Speed, accessibility and a new level of convenience for most people. Everyday consumers also learned some important skills. But we also lost personal interaction, expertise in some cases and the unique value that human workers bring to the table.

As we continue to integrate AI into the workplace, we need to learn from these past transitions. The goal shouldn’t be to eliminate human work, but to enhance it, enabling people to focus on tasks that truly matter, while AI handles the rest.

The ethical questions surrounding AI are complex and multifaceted

What does AI mean for the future of jobs? It's not something that can be answered here and now, especially given the rate at which AI is moving, but we know one thing for sure: AI has the potential to enhance efficiency, convenience and precision in ways we’ve never seen before.

The challenge lies in ensuring that this progress benefits everyone, empowering humans — not just the lucky or super skilled ones — to focus on higher value outputs while AI takes care of the rest.