In a rapidly evolving post-pandemic world, what it means to work has permanently shifted.
We’re living in the midst of a fourth industrial revolution — one of technological growth — and the COVID-19 pandemic has sent the workforce into a crisis. There are unprecedented job vacancies and displacements, both in skilled and unskilled labor.
Filling these vacancies could raise Canada’s GDP by over $100 billion.13
The key to mitigating our employment problem may lie in the hands of older workers. Our policies and norms communicate that the workplace is not for older workers — but rising flexibility means now is the time to change the narrative and help address our job vacancy crisis.
Behavioral Science, Democratized
We make 35,000 decisions each day, often in environments that aren’t conducive to making sound choices.
At TDL, we work with organizations in the public and private sectors—from new startups, to governments, to established players like the Gates Foundation—to debias decision-making and create better outcomes for everyone.
The challenge: a graying population and a shortage of workers
Our population is graying. As many countries enter the final stage of demographic transition, a predicted 21% of our population to be over 60 years of age by 2050.14 If the demographic composition of our current workforce is maintained, the ratio of retirees to workers will be drastically increased.
A greying workforce and a worker shortage hold one common solution: to expand the age demographics of our workforce to include older adults (i.e. those over 60-65). Encouraging older adults to remain in the workforce will become necessary for a thriving economy, but our industries aren’t yet conducive to an older workforce.
Accommodating older workers will require structural and cultural shifts, including:
- Improving working conditions
- Normalizing lifelong learning
- Creating age-inclusive workplaces
The key to older worker inclusion is an understanding of the behavioral science behind how younger and older people think differently.
Older workers face situational disadvantages based on circumstance
Older workers are inherently disadvantaged in two ways: educationally and technologically.
Over the past century, post-secondary education has become more accessible and expected — so those born in the 60s’ are likely to have lower education levels than those born in the 90s’.20 This gap varies by country and disproportionately affects women and people of color.
And due to the lack of vocational training and reskilling at work, our increasing reliance on technology is leaving older people behind. Many essential softwares are hard to navigate and lack options for customized accessibility, which creates a barrier for older workers.
Ageism, though prevalent, lacks mitigation
Ageism (age-based prejudice and discrimination) is just as institutionalized as racism and sexism, but rarely at the forefront of public discourse. Whether it’s joking about being too old or the rise of plastic surgery, society tends to antagonize aging and assign older adults stereotypes of cognitive decline.
Implicit negative attitudes towards older people in the workplace are psychologically ingrained:
- We subconsciously associate being old with negative traits.19
- 61% of people have witnessed or experienced age-based discrimination in the workplace. (and only 3% report it)5
- Working people perceive people 45 years and older to be the least employable, most unskilled, and most untrainable age range.17
This ageism can manifest in several ways:
- Stereotyping of older workers as incompetent
- Lower wages
- Lack of reskilling and networking opportunities
- General preference for youth, often based on appearance
- Disproportionate effects on women (especially in male-dominated industries) and people of color5
This understandably makes older workers feel unwelcome in the workplace, deterring their participation as workers - even if they want to continue working.
In-group bias perpetuates ageist attitudes
We subconsciously favor younger workers over older workers due to in-group bias. We’re wired to perceive people in the same demographics as us as more socially favorable, including our age brackets.9
How behavioral science can change workforce demographics
The distinction between fluid and crystallized intelligence
Psychologists acknowledge two types of intelligence:
- Fluid intelligence, defined by:
- Crystallized intelligence, defined by:
Fluid intelligence peaks in early/middle adulthood and declines after a person’s mid-sixties, whereas crystallized intelligence doesn’t peak until middle age and doesn’t decline until the mid-seventies.21
The majority of education is designed for children and young adults. But older adults are not a blank slate — they already possess a wealth of knowledge and have existing attitudes.
Because their crystallized intelligence tends to be stronger than their fluid intelligence, they will thrive most with ‘crystallized intelligence’ tasks, including verbal and reading comprehension,1 and are generally less strong with fluid intelligence-related skills like math.18 However, overgeneralizing these trends can also be counterintuitive — it’s important to consider individual differences!
1. Design reskilling workshops & encourage lifelong learning attitudes
Older workers can thrive in the workforce with the help of reskilling workshops. Making opportunities abundant and accessible asserts that lifelong learning is valued.
A good example is Singapore’s #GetReadySG initiative, launched with Microsoft. #GetReadySG organized boot camps and training programs for mid-career workers, providing them with the necessary skills for entry-level jobs in the tech sector.
Look to existing programs for best practices, but when developing your training programs, be sure that older adults have input every step of the way. This ensures the program can be customized to meet each person’s individual needs,16 like accessibility, formatting, and activity preferences.
Program design should:
- Allow customizability: Ensure that users can customize the program and its delivery platform
- Focus on real-world, pragmatic applications of theory: Older adults are rich in experience, so relate it to real-world operations.
- Give users the option to reduce task size
- Incorporate team projects and group discussions16
- Provide networking opportunities: These are crucial to professional development, but older adults are often not given access to as many of these opportunities as young professionals.
- Avoid paternalistic design/language: Giving older adults autonomy within the learning process drives up engagement.
You can even try taking input from outside parties to create a more comprehensive reskilling process. Some suggestions include:
- Product manufacturers: Manufacturers know their product best, and their business depends on successful product experiences. Ask them about accessibility options.
- Universities: Schools can provide existing educational components like curricula, class structures, and learning materials - as well as give advice on designing the learning process.
- User input: Program participants have the most valuable input. Be sure to put their needs first and give them a voice throughout the whole process.
2. Combatting ageism within the workplace
Older workers must feel welcome to ask questions, learn, and engage with others. Here are some ways to reduce the prevalence of workplace ageism:
- Humanize the jobs of older workers: Recognize the contributions of older workers and ensure they feel supported and valued. Whether it’s a pat on the back or inviting them over for dinner, building community humanizes all workers and reduces ageism.
- Advocate for older workers within the workplace: Older, experienced workers may stand up for young workers who are stereotyped to lack experience - young workers must be vigilant to return the favor when they see hints of ageism.
- Encourage personal advocacy: Encourage older adults to advocate for themselves in situations of age-based discrimination, and support them when they do so. This helps build a culture where everyone can set boundaries and be assertive when needed.5
- Look to other discrimination mitigation techniques: How else do you combat discrimination, like sexism and racism,in the workplace? Apply it to age-based discrimination.
The fight against ageism is a self-perpetuating cycle: Inclusive workplace practices can help older adults find employment, which further integrates older adults into the workforce and demonstrates the false nature of ageist prejudice.
3. Turning technological growth from a hindrance into an effective tool
Technological growth offers employees an unprecedented amount of accessibility, dismantling physical obstacles like distance and physical strength.20
We can maximize these advantages through customization, giving older adults the power to choose what works best for them. For example, someone with severe short-sightedness will opt for a different user interface than someone with hearing problems.
Modern software interfaces are capable of detailed customization, which in turn helps them optimize their job performance, but not all are suited for older adults. When selecting tools for your workspace, try to pick software that:
- Has a clutterless user interface
- Clearly presents where and how to set accessibility preferences, such as font size and text-to-speech10, 20
- Provides intuitive navigational support (eg. include search bars and help guides)6
- Simplifies operational procedures6
- Removes time constraints6
- Ensures consistency between other software6
Making workspaces inclusive is mutually beneficial
Ameliorating the disadvantages faced by older workers is a win-win. Not only are we facing a shortage of workers, but older people within the workplace are also able to pass down experience within fields that younger colleagues may lack.
Unlocking the full potential of our workforce, especially in the coming decades, not only means designing tools and workspaces to include older workers, but to design it for them.
- Ackerman, P. L., Beier, M. E., & Bowen, K. R. (2000). Explorations of crystallized intelligence. Learning and Individual Differences, 12(1), 105–121. https://doi.org/10.1016/s1041-6080(00)00034-0
- Akinola, S. (2021, May 20). How can we best engage older workers in reskilling efforts? World Economic Forum. https://www.weforum.org/agenda/2021/05/how-can-we-engage-older-workers-in-reskilling-efforts-jobs-reset-summit-ageing-workforce-longevity-upskilling/
- Burtless, G. (2013, June 10). Is an Aging Workforce Less Productive? Brookings; Brookings. https://www.brookings.edu/blog/up-front/2013/06/10/is-an-aging-workforce-less-productive/
- Cherry, K. (2021, August 23). Fluid vs. Crystallized Intelligence? Verywell Mind. https://www.verywellmind.com/fluid-intelligence-vs-crystallized-intelligence-2795004
- Cole, E., & Hollis-Sawyer, L. (2021). Older Women Who Work: Resilience, Choice, and Change. In JSTOR. American Psychological Association. https://www.jstor.org/stable/pdf/j.ctv1chs38v.18.pdf?refreqid=excelsior%3Acddbd39d4c144bdbdb49946a0a329954&ab_segments=&origin=&acceptTC=1
- Czaja, S. J., & Lee, C. C. (2006). The impact of aging on access to technology. Universal Access in the Information Society, 5(4), 341–349. https://doi.org/10.1007/s10209-006-0060-x
- Data and Statistics - Productive Aging and Work. (2014). Centers for Disease Control and Prevention. https://www.cdc.gov/niosh/topics/productiveaging/dataandstatistics.html
- Hamburg, I. (2021). COVID-19 as a Catalyst for Digital Lifelong Learning and Reskilling. Advances in Research, 21–27. https://doi.org/10.9734/air/2021/v22i130282
- Hanley, C. J., Burns, N., Thomas, H. R., Marstaller, L., & Burianová, H. (2022). The effects of age-bias on neural correlates of successful and unsuccessful response inhibition. Behavioural Brain Research, 428, 113877. https://doi.org/10.1016/j.bbr.2022.113877
- Hanson, V. L., & Crayne, S. (2005). Personalization of Web browsing: adaptations to meet the needs of older adults. Universal Access in the Information Society, 4(1), 46–58. https://doi.org/10.1007/s10209-005-0110-9
- Ihle, A., Borella, E., Rahnfeld, M., Müller, S., Enge, S., Hacker, W., Wegge, J., Oris, M., & Kliegel, M. (2015). The role of cognitive resources for subjective work ability and health in nursing. European Journal of Ageing, 12(2), 131–140. https://doi.org/10.1007/s10433-014-0331-y
- Kaufman, A. S., Kaufman, J. C., Liu, X., & Johnson, C. K. (2009). How do Educational Attainment and Gender Relate to Fluid Intelligence, Crystallized Intelligence, and Academic Skills at Ages 22-90 Years? Archives of Clinical Neuropsychology, 24(2), 153–163. https://doi.org/10.1093/arclin/acp015
- Langton, J. (2022, June 15). Children may be the future, but older workers are needed now | Investment Executive. Investment Executive. https://www.investmentexecutive.com/news/research-and-markets/children-may-be-the-future-but-older-workers-are-needed-now/
- Population of Older Adults Increasing Globally Partly Because of Declining Fertility Rates. (2021). PRB. https://www.prb.org/news/population-of-older-adults-increasing-globally/
- Price, J., & Murray, R. G. (2012). The region of proximal learning heuristic and adult age differences in self-regulated learning. Psychology and Aging, 27(4), 1120–1129. https://doi.org/10.1037/a0029860
- Rangraz, M., & Pareto, L. (2020). Workplace work-integrated learning: supporting industry 4.0 transformation for small manufacturing plants by reskilling staff. International Journal of Lifelong Education, 1–18. https://doi.org/10.1080/02601370.2020.1867249
- Reskilling older workers for new careers in tech. (2022, June 10). McKinsey & Company. https://www.mckinsey.com/about-us/new-at-mckinsey-blog/reskilling-older-workers-for-new-careers-in-tech
- Thorsen, Gustafsson, J.-E., & Cliffordson, C. (2014). The influence of fluid and crystallized intelligence on the development of knowledge and skills. British Journal of Educational Psychology, 84(4), 556–570. https://doi.org/10.1111/bjep.12041
- Wiener, R. L. & Willborn, S. L. (2011). Disability and Aging Discrimination Perspectives in Law and Psychology / edited by Richard L. Wiener, Steven L. Willborn. (Wiener & S. L. Willborn, Eds.; 1st ed. 2011.). Springer New York. https://doi.org/10.1007/978-1-4419-6293-5
- Willis, S. L., & Margrett, J. A. (2001). Aging and Education. International Encyclopedia of the Social & Behavioral Sciences, 299–304. https://doi.org/10.1016/b0-08-043076-7/02460-8
- Zaval, L., Li, Y., Johnson, E. J., & Weber, E. U. (2015). Complementary Contributions of Fluid and Crystallized Intelligence to Decision Making Across the Life Span. Aging and Decision Making, 149–168. https://doi.org/10.1016/b978-0-12-417148-0.00008-x
About the Authors
Janessa is a rising junior at the University of California, Los Angeles pursuing a BS in Cognitive Science with a Specialization in Computing, and minoring in Bioinformatics. She believes that psychology holds the power to ameliorate many of the world’s biggest problems, with climate change being one that she holds closest to her heart. It ultimately serves as a roadmap to why humans do what they do. Understanding this roadmap — our predispositions, biases, and instincts — are crucial to guiding people to make better choices for themselves, others, and our planet.
Dan is a Co-Founder and Managing Director at The Decision Lab. He has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.