AI is not the enemy, but it is here to stay - so get used to it

I was recently made aware of survey results showing a growing fear among people under 30 that AI will replace them in the workforce.

In some respects, I think that fear is justified.

It may be younger workers who have the most to worry about. They are only at the beginning of their professional learning journey and, as a result, have had less opportunity to build the accumulated knowledge and experience that comes from years of working in a particular field.

They have not yet spent years doing the basics, making mistakes, solving problems and learning through trial and error.

Yet these are precisely the kinds of jobs AI is most likely to disrupt first.

AI will almost certainly take over some of the work that requires less sophisticated knowledge, less experience and less responsibility: repetitive or relatively straightforward tasks that have traditionally been given to junior employees.

That means the fears of younger workers are grounded in a genuine uncertainty. Employers may increasingly decide that a more experienced employee equipped with AI can perform both senior-level work and many of the routine tasks that would once have been assigned to someone entering the profession.

If that happens, it creates a serious problem.

How does a young person gain the experience required for senior positions if they can no longer get the junior positions through which that experience was traditionally acquired?

The software industry provides a useful example, because it is one of the areas where the impact of AI is already particularly visible.

Junior developers naturally lack the experience of senior developers who built their knowledge before AI coding tools became widely available. Senior developers tend to have a more sophisticated understanding not simply of how to write code, but of the consequences of the code they write.

When building software with AI, that experience becomes extremely important.

AI can generate code very quickly, but a developer still needs enough knowledge to recognise when the code is wrong, insecure, inefficient or likely to create problems elsewhere in the system. The developer needs to understand the potential consequences of what the AI has produced.

This creates a conundrum for junior developers:

How do I gain the experience necessary to identify those problems if I cannot get an entry-level job because companies prefer experienced developers using AI, who can now cover a much wider range of tasks?

In effect, AI could create a barrier that locks younger and less experienced developers out of the industry.

But there may be another way of looking at the problem.

What if we begin with the assumption that AI is here to stay and that it will almost always be available in the workplace?

Computers did not disappear. Smartphones did not disappear. AI is unlikely to disappear either.

If that is true, perhaps our education system should adapt accordingly.

What if, instead of discouraging students from using AI or threatening punitive action when its use is detected in assignments, we trained students to use AI as an ordinary tool throughout their education?

Yes, the words on the page may sometimes have been generated by AI and may not technically have been written by the student. But is that necessarily the most important question if the ideas are theirs and the final work is accurate?

After all, when a student submits a printed assignment, the handwriting produced by the printer is not theirs either.

What matters is the thinking.

To use AI effectively, a student still has to decide what they want to know, formulate the question, provide the appropriate context, evaluate the response and determine whether the answer is correct.

That is itself a form of thinking.

Students still need a foundational understanding of how things work. But AI can also be an extraordinarily powerful tool for acquiring that foundational knowledge.

The greater danger lies in the gaps: the subtle errors, missing context, incorrect assumptions and plausible-sounding answers that AI can produce. Recognising those weaknesses is where deeper knowledge and expertise become essential.

Perhaps, then, education should increasingly focus on teaching students how to use AI while also teaching them how to challenge it.

Students could learn how to verify its answers, identify its limitations, recognise when something does not look right and understand the consequences of relying on a flawed output.

If we concentrated more of our educational effort on developing those abilities, young people entering the workforce might arrive with capabilities that were once associated with much more experienced workers.

The traditional path was to spend years performing relatively simple tasks before progressing towards more complex ones.

But if AI increasingly performs those simple tasks, perhaps education needs to find another way of giving young people the judgement and experience they would previously have acquired through them.

If we embrace AI as part of both the learning process and the way work is now performed, we may be able to address some of the fears highlighted by these surveys.

The answer may not be to protect younger generations from AI.

It may be to prepare them to use it better.

Perhaps solving the problem requires those of us from older generations to adapt the education system to the technologies young people will actually encounter, rather than expecting an education system designed for the world we entered to continue working unchanged in a world being transformed by AI.

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The Anti-AI Movement Grows Stronger - BlueMail