Someone may be XX years old but ‘age’ is in actuality a combination of chronological, biological, and psycho-social factors that are ever in flow.

Psychological stages of development

  • continuous from infancy through old age.

  • sequential with each stage building upon the previous.

  • each stage characterized by a core conflict.

  • successful resolution of a stage-specific conflict leads to a virtue.

  • un-successul resolution of a stage-specific conflict can negatively affect future stages and wellbeing.

Values throughout the lifespan

Values are ideals of living, standards, goals that people pursue in life (Schwartz, 2012).

  • they develop at an early age through learning from the social environment and personal experience.
  • at adulthood value development slows down but the development processes continues throughout the lifespan.

There is a greater priority given to values of conservation at older age, and there is a generally greater preference for values of growth at younger age (Smallenbroek et al., 2023).

Data from Germany. Average age in 1990 was 21. Smallenbroek et al. (2023).

Data from Germany. Average age in 1990 was 21. Smallenbroek et al. (2023).

Losses and gains with age

Growing old involves processes of internal and external resource re-allocation to meaningfully manage losses and gains throughout the lifespan (Ebner et al., 2006).

Growth = development, delineation, and commitment to new goals aimed at achieving higher levels of functioning as well as the pursuit of these goals through acquisition, practice, and refinement of goal-relevant skills and resources.

Loss = adjusting one’s goals in response to losses in goal-relevant resources as well as counteracting impeding or actual losses by investing remaining resources into maintaining or regaining functioning.

18-26 vs. 40-59 vs. 65-84. Ebner et al. (2006).

18-26 vs. 40-59 vs. 65-84. Ebner et al. (2006).

Conclusion 1

Age is on a continuum.

Growth has a greater priority than prevention of loss at younger ages,

whereas prevention of loss has a greater priority than growth at older ages.

Chronologic age

Age is a state counting the passed time from birth (0) to end of life cycle (death).

Highly regulated. For example, retirement age.

A standardized approach that insufficiently captures inter-individual differences.

Biologic age

Epigenetic biomarkers of age and aging can be thought of as individual-level measures of aging that capture inter-individual differences in the timing of disease onset, functional decline, and death over the life course (Levine et al., 2018).

One is as young or old as their biological markers are fitting pre-determined criteria of ‘young vs. old body’.

Age is then defined in terms of bodily indicators. For instance, white blood cell count.

An approach that does not consider what a person thinks about their own age.

Subjective age

Age is defined by how young or old a person feels (Kotter-Gruehn et al., 2015).

  • self-perceptions of aging (how people experience their aging)
  • old-age stereotypes (beliefs about typical characteristics of older people)
  • age identity (identification with an age group)
  • awareness of age-related change (experiences of changes that increase awareness of having grown older)
  • felt age (how old a person perceives him-/ herself)

Famous optical illusion depicting both a young and old woman. The perceiver can see either or both.

Famous optical illusion depicting both a young and old woman. The perceiver can see either or both.

Conclusion 2

Age is on a continuum.

Growth has a greater priority than prevention of loss at at younger ages,

whereas prevention of loss has a greater priority than growth at older ages.

Age of a person is defined at once by time, biology, and social and psychological factors.

Individual traits

Ageing well is a term describing processes of developing and maintaining high levels of health throughout the lifespan including in old age.

Chronological age may be 65, but a person may ‘feel and have the body of a 50 years old’.

Mental and physiological health indicators are generally associated with a felt younger age.

Resilience, agency, capacity to re-define losses into gains are a few examples.

People can differ because of distinct opportunities in their environments.

Social ties

People become more selective in their social contacts as they grow older.

Surrounding oneself with ‘like-minded’ others creates a sense of community to which people belong to. This also is important for social support in times of need.

Belonging to a community where the chronological old age is ‘but a number’ has a different impact on the individual than belonging to a community where old age equates with ‘frailty and incompetence’.

People and communities live and operate within society which has specific, normative and prescriptive views on ageing and old age.

Societal culture

We are not born with a definition of age and old age. We internalize during early life stages the societal beliefs existent in our social environments.

Although these initial beliefs may modify over our lifecycle, they have a fundamental impact on how ‘old’ a person is and feels.

Data from the European Social Survey showing when people across acountries think old age begins. Abrams et al. (2011).

Data from the European Social Survey showing when people across acountries think old age begins. Abrams et al. (2011).

Conclusion 3

Age is on a continuum.

Growth has a greater priority than prevention of loss at younger ages,

whereas prevention of loss has a greater priority than growth at older ages.

Age of a person is defined at once by time, biology, and social and psychological factors.

Resources and lack thereof in view of traits, social ties, and societal culture informs how ‘old’ a person is and feels.

On AI

  • a form of advanced technology yet fully understood by developers and the scientific community, and especially the general public.
  • primarily useful in simplification of redundant tasks and detection of systematic patterns in large data.
  • direct applications in administration, health and healthcare sectors, as well as in some types of work.

Increased fears and anxieties in people tend to associate with uncontrollable events and insufficient information.

AI is human made

AI technologies are developed by humans who have their own beliefs, expectations, and world views.

AI algorithms are trained on human data or human-generated data.

The implementation of AI will exacerbate existent inequalities while also creating novel ones if the specific risk factors, limitations, and needs in people of all ages are insufficiently addressed.

Societal and technological discourses currently shape the direction of AI implementation leaving people with vulnerabilities at the fringe (Winkel, 2025).

Indicators of problematic mental and physiological health (thus of reduced productivity) tend to be associated with limited agency in decision making processes.

Younger and older workers and AI

Younger people may generally be more AI receptive because of them being at a life stage characterized mainly by growth.

Instability and ambiguity associated with AI can interfere in their developmental processes leading to un-transferable skill development and career gaps.

With limited available resources, growth and stability is partly fulfilled causing increased distress.

Older people may generally be less AI receptive because of them being at a life stage characterized mainly by prevention of loss.

Excluding them from societal and technological advancement can aggravate existent inter-generational divides in addition to adding the burden of responability in updating the skill set.

With limited available resources, an additional responsibility is distressing.

Regulatory frameworks can facilitate and promote an equitable representation of the specific risk factors, limitations, and needs in people at all ages.

Conclusion

Age is both state and process.

A focus on chronological age in regulatory frameworks may be too restrictive because people’s age is defined and informed at once by time, biology, and social and psychological factors.

Younger and older people benefit at work and in general from the AI transformation contingent on having the right resources.

  • skills can be learned at all ages, but age inclusive education must be employed.
  • fears and anxieties can be addressed in policy that is individual age sensitive.
  • hardware that are available across life domains integrates rather than fragments developmental processes in people.

How do you see the impact of AI on ageing at work?

adrian.stanciu@uni.lu

Reference list

Abrams, D., Russel, P. S., Vauclair, M., & Smith, H. J. (2011). Ageism in europe: Findings from the european social survey. AgeUK. https://kar.kent.ac.uk/29733/1/ID10704%20AgeUKAgeism%20Across%20Europe2011%20prepubReport%5B1%5D.pdf
Ebner, N. C., Freund, A. M., & Baltes, P. B. (2006). Developmental changes in personal goal orientation from young to late adulthood: From striving for gains to maintenance and prevention of losses. Psychology and Aging, 21(4), 664–678. https://doi.org/10.1037/0882-7974.21.4.664
Erikson, E. H. (1959/ 1994). Identity and the life cycle. W. W. Norton & Company.
Kotter-Gruehn, D., Kornadt, A. E., & Stephan, Y. (2015). Looking beyond chronological age: Current knowledge and future directions in the study of subjective age. Gerontology, 6(62), 86–93. https://doi.org/10.1159/000438671
Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., Bandinelli, S., Hou, L., Baccarelli, A. A., Stewart, J. D., Li, Y., Whitsel, E. A., Wilson, J. G., Reiner, A. P., Aviv, A., Lohman, K., Liu, Y., Ferrucci, L., & Horvath, S. (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging, 10(4), 573–591. https://doi.org/10.18632/aging.101414
Schwartz, S. H. (2012). An overview of the schwartz theory of basic values. Online Readings in Culture and Psychology, 2, 1. https://doi.org/10.9707/2307-0919.1116
Smallenbroek, O., Stanciu, A., Arant, R., & Boehnke, K. (2023). Are values stable throughout adulthood? Evidence from two german long-term panel studies. PLoS ONE, 18(11), e0289487. https://doi.org/10.1371/journal.pone.0289487
Winkel, M. (2025). Controlling the uncontrollable: The public discourse on artificial intelligence between the positions of social and technological determinism. AI & Society, 40, 1947–1959. https://doi.org/10.1007/s00146-024-01979-z

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