For thirty years technology was the thing young people were good at. It made them feel capable and connected. Some researchers now think that has flipped — that for the first time the same technology is a source of stress for the young and barely touches the old. That flip is what this page is about.
Students often treat HDI as a vague “quality of life” score. It is more specific than that, and knowing the three parts lets you write a much sharper answer.
Why would the same technology affect two age groups so differently? The source suggests two threads.
Someone aged 18–30 is trying to enter a career. If AI is spreading across the professions they were training for, the ladder they were climbing looks shorter. Someone aged 50+ is usually already established or approaching retirement, so the same change threatens far less.
Young people also use AI across more tasks — writing a CV, gathering research, drafting an essay. It saves time, but a task finished by a machine gives no sense of having overcome anything. Over time that can produce a feeling of being de-skilled: capable of producing work, but not of doing it.
This links directly to self-efficacy — your belief that your own effort produces results. Self-efficacy is built by mastering hard things. If the hard part is automated away, the mastery experience never happens, and confidence and motivation can fall with it.
This source is unusually thin, and that is deliberate: it tests whether you notice. Run the checklist.
| What is missing | What that stops you concluding |
|---|---|
| No raw scores or statistics | You cannot say how big the predicted fall is, or whether it is meaningful |
| No sample details | You do not know which countries or groups were studied, so generalisation is unsafe |
| No measure of spread | An age band contains huge variation, and an average hides it |
| A prediction, not a measurement | The fall has not happened yet, so this is a forecast that could be wrong |
| No test of causation | AI is described as associated with the disparity; nothing demonstrates it produced it |
Analyse the findings in this source and state a conclusion based on them. [6 marks]
The source reports that HDI — a measure combining health, knowledge and standard of living — is expected to fall for 18 to 30 year olds while remaining stable for people over 50, and links this disparity to the growing presence of AI. The group performing worse is clearly the younger one.
A psychological explanationA plausible reason is opportunity. Younger adults are still trying to enter careers that AI is now doing parts of, whereas older adults are established or retired and so are less exposed. Young people also rely on AI across more everyday tasks, from writing applications to producing coursework. Because a task completed by a machine provides no experience of mastering something difficult, self-efficacy and motivation may fall, and with them the sense of control over one’s own future.
Conclusion, with limitsThe findings suggest that technology, which has been a source of confidence for young people for three decades, may be becoming a source of stress instead. However, no raw data, statistics or sample details are given, and the disparity could equally be explained by housing costs, wages or job insecurity. The conclusion should therefore be that the pattern is worth investigating, not that AI is causing a fall in young people’s development.
Explain one limitation of the data presented in this source. [3 marks]
The source reports a finding without giving any numbers or details of the sample.
ExplainWithout a sample size, the countries involved, or the size of the predicted change, there is no way to judge whether the difference between age groups is large or trivial, or whether the people studied resemble any wider population.
LinkThis makes the finding impossible to evaluate properly, so any conclusion about AI and human development from this source alone lacks support.
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