Authors:
Daria Loi, Thomas Lodato
Stereotypes are problematic in how they essentialize individuals, yet they are hard to avoid. Arising from ordinary cognitive processes of how individuals perceive themselves relative to others, stereotypes emphasize dimensions of meaningful differences between groups [1] that are defined by one's specific social and cultural environment rather than unfiltered cognition or objective perspective. "Stereotypes are cognitive schemas used…to process information about others" [2] and arise in part from the mundane ways in which humans encode information and the social processes of maintaining group characteristics.
Stereotypes are difficult to avoid even at the most granular level of cognition. In the context of product design and HCI, they may arise in explicit ways (e.g., outright claiming that older adults are not tech savvy) and, frequently, in implicit, insidious ways: unspoken assumptions (e.g., hip users as coded language for young users), backhanded "jokes" (The rebrand of SOCIAL MEDIA PLATFORM makes it easier to read for its user base *wink*), dismissal of data (Even though our data skews older than we expected, we know who are users *really* are), the absence of substantive evidence behind decisions (I can't see my grandmother using this!), and the use of methods that fundamentally promote and support stereotyping formulations (e.g., personas, focus on user groups, and segmentations).
In all these ways, stereotypes foreclose curiosity, empathy, and understanding about the lives of people by assuming we already know who they are and what they want. Stereotypes, then, are antithetical to human-centered design because they center the observer's lifeworld rather than the lifeworlds of people using (and not using) technologies, products, services, and systems. Rather than being lenses onto the people they purport to explain, stereotypes are mirrors of the cultures and groups that produce them.
Within the design of digital and computational technologies, age is commonly stereotyped relative to the desire for and use of technologies. Broadly, this stereotype asserts that aging hampers technological fluency, literacy, and interest. Older adults, as the terminus of this trajectory, are both resistant to and incompetant with novel technologies. Simply put, older adults are framed as lacking technological savvy. This stereotype pervades technology companies in many ways, from research and design activities to hiring and firing practices. Do you recall the iPod advertisements featuring dancing silhouettes and the "I'm a Mac" ad? Both campaigns sought to associate youthfulness with Apple, and, by extension, agedness with other brands. The reinforcement of stereotypes about older adults stems from a variety of motivations and assumptions, all of which exclude and shame older adults for the failures of those who make technology.
Older adults is a broad and diverse demographic category of individuals age 65 or older. We all age, yet do so differently. Being 65+ does not denote a coherent and uniform group of people; for instance, social scientists subdivide older adults into smaller age groups to better attend to age-related variations (e.g., predict ER-visit outcomes): the youngest old (65–74), the middle old (75–84), and the oldest old (85+). Additionally, the global older-adults population is not evenly distributed, with the highest percentages in the northern hemisphere. With populations growing in the southern hemisphere and life expectancy increasing in many countries alongside decreases in birth rates, many countries are experiencing increasing dependency ratios between those who need elder care and those able to provide it. The impact is that older adults will be woefully underserved in the near future.
In a recent interview, eldercare expert Linda Jacobson explained how commonalities among older adults are the sum total of a life of experiences, health states, and various decisions. The stereotype of older adults as not savvy, in her experience, stems from "vast generalizations" that do not attend to the subtlety of older adults' lived realities nor to the histories of these technologies: "People in their 60s and 70s created this technology," she reminds us. What can be generalized is that older adults are more dependent on others for their care as they age. This dependence feeds technology stereotypes, as Jacobson explains, because in many Western contexts the "model for dependence is children." As such, the dependence on others results in the infantilization of older adults and the projection that they lack knowledge, capability, and/or comprehension. One concrete example is elderspeak, a "specialized speech style" that patronizes older adults while negatively impacting health outcomes for those with dementia [3].
To account for a life of accumulated experiences and variation, we can borrow from analytical distinctions used by social scientists referred to as age effects, period effects, and cohort effects [4]. Age effects (related to the durational time since birth) include the physical, cognitive, and emotional processes of aging (e.g., maturation, cognition, emotional regulation) as well as the sociocultural processes of aging (e.g., employment state, wealth accrual, seniority in organizations). Period effects (historical time in which someone lives) include local and global conditions that impact all peoples within a given geography and time period. For example, the Covid-19 pandemic has changed the lives of individuals within this particular historical moment and is different from other pandemics (e.g., Spanish Flu) or other global events (e.g., WWII). Cohort effects refer to the relational time or shared experiences of specific groups. For instance, while those migrating to the U.S. in the 1900s experienced similar policies, patterns, and conditions [4], many subcohorts (e.g., those migrating from Europe or Asia) experienced differences in factors such as working contexts and conditions, cultural discrimination, and geographic settlement patterns. As experienced, age, period, and cohort effects overlap and intersect themselves and other factors. Applied to older adults, these analytical distinctions help locate the source of perceptions and needs.
During a workshop that we conducted in April 2020, older-adult tech-education experts explained that their students tend to strive for skill mastery, acquired through teaching and repetition. These expectations stem from U.S. educational models that emphasize particular types of authority and pedagogical practices. In contrast, contemporary STEM education emphasizes experimentation, exploration, and productive failures. These differences mean that teaching technological literacy requires a different approach from that assumed by many technologies or teachers. For technology that tends toward feature discoverability, the difference in learning styles makes a difference in relation to the frustration one is willing to endure and what learning a new technology entails. One of the impacts of such diverse expectations is that older adults report less confidence with new technology, expressing feelings of embarrassment, frustration, fear, insecurity, and resignation relative to learning, asking questions, purchasing, and using such technologies. Internalizing the stereotype of lacking savvy, many older adults express sentiments that this technology is not for them, which is not inaccurate given the lack of work done by many companies to understand the unique and intersecting needs of older adults.
Bodies change as they age, yet most technology does not account for this everyday reality. Capacitive touch, for instance, has decreased responsiveness when one has reduced circulatory function, which is frequent in older adults. While changes in visual or auditory acuity are common, attending to such changes is not simply a matter of increasing text size or amplifying volume. Since cognitive changes, particularly issues related to memory, increase in likelihood with age, technology that requires a relatively high degree of information recall may become frustrating.
Age effects are, however, not only related to declining health or accessibility challenges. Healthy aging means staying active [5], and marking aging with decline overlooks the opportunities that aging presents to individuals. For technology companies that often dwell on novelty and change, older adults show us the relationship among adoption, adaptation, and reprioritization as lives change.
Research shows that on average, older adults—at least within the U.S.—adopt computational and digital technology later than younger populations. This lagging adoption, according to IFTF fellow Richard Adler, stems from a variety of factors, some of which are attributable to period and cohort effects, such as perceptions of security and privacy. In our research about individuals using videochat technologies, many participants pointed out that their exposure to technology comes from the workplace or their peers and families. Workplace technologies are often adopted for personal uses—take, for example, the increasing number of family calls via Zoom and the explosion of "how to use" posts during the current pandemic. Retirement often makes workplace exposure less possible and, as a result, older adults report relying on particular social situations to force adoption. One study participant shared her usage of Zoom for some calls, FaceTime for others, and an Alexa Show for her mother (easier to set up). While this example illustrates how social bonds foster adoption, use, and trouble-shooting, experts we interviewed report that many technologies for older adults frequently remove important social dynamics around support and use. These technologies make use easy without considering who technology is used with, who assists when technology does not work, and the beneficial social wellness that such endeavors may enable. Barring the obvious period effect of Covid-19—a forcing function for everyone, including older adults, to rely on digital communication—many older adults have longstanding social bonds that are formed around conventions of communication and socialization that may not use computational and digital technology at all. These might include calling a friend on the phone or going for an early-morning bike ride.
Stereotypes are mirrors of the cultures and groups that produce them.
How should we account for the reality of aging? One frequent approach is to identify older adults' frictions and frustrations with technology to then design to reduce pain points on their behalf. Another approach is to understand how technology can meet the goals of older adults.
During our research, older adults emphasized three key opportunity areas for the HCI community to consider:
Privacy and security are priorities. In current and past [6] work and in the work of others, privacy and security arise as primary concerns of and barriers for using digital and computational technologies among older adults. Additionally, privacy and security frame the relationship between adoption and non-adoption as responses to the same, rather than different, conditions, thereby framing the digital divide as more than a problem of access. The opportunity is to diversify one's approach to non-adoption by understanding rational behaviors alongside issues of low access.
The need for continuous onboarding. As previously documented [6] and found in our recent studies, key barriers to adoption among older adults are the effort and anxiety associated with starting. Designing technology for initial and ongoing learning reframes the challenge of usability from reducing errors to supporting knowledge creation. As such, continuous onboarding as a strategy and metaphor focuses on the ways in which technology ages and grows alongside individuals, addressing new needs and adapting to new conditions.
Tech as a means and not an end. Many older adults expressed that technology was a means of reaching family, learning about their community, or staying healthy—in other words, technology that enables specific, personal, meaningful goals. As a means, technology becomes subsumed in its task, meaning that makers of technology need to continually find ways to enable the tasks and goals of people's lives. The opportunity is then to find ways to engage older adults in an ongoing dialogue about their lives, goals, and contexts. Moreover, a continual inquiry into and dialogue with people holds us accountable to our mission by being present as listeners and responding to new circumstances as they arise.
A Closing Exercise
Stereotypes are like mirrors: They reveal what one fears or worries about through attribution to others. Let's conclude with an exercise to consider age-related assumptions and stereotypes.
Look in the mirror and state your age. What did you think about your current age 10 years ago? How, if at all, are those beliefs accurate or inaccurate? What does your age as a number (age effects), set of historical experiences (period effects), and group of people you aged with (cohort effects) say about you? Now think about yourself 10 years from now. What assumptions and beliefs do you have about that person? How right or wrong do you think they will be?
Keep these three people in your mind (You 10 years ago, you now, you in 10 years). When you come to a decision, assumption, and direction, consider the ways these three people may not agree on what to do.
Take this brief exercise as a starting point where exploring stereotypes means turning the mirror inward to find ways to listen and learn better as we age. Next steps could include investing in reflective and open ethnographic methods that invite participants into the discussion and shaping of frameworks, focusing on stereotypes as subject and material for HCI design, and integrating experts in intersectional scholarship into design as collaborators and partners rather than simply citable sources.
References
1. Bodenhausen, G.V. and Richeson, J.A. Prejudice, stereotyping, and discrimination. In Advanced Social Psychology: The State of the Science. R.F. Baumeister and E.J. Finkel, eds. Oxford Univ. Press, 2010, 341–383.
2. Dovidio, J. et al. Prejudice, stereotyping and discrimination: Theoretical and empirical overview. In The SAGE Handbook of Prejudice, Stereotyping and Discrimination. J.F. Dovidio et al., eds. SAGE, London, 2010, 3–28.
3. Williams K.N. et al. Elderspeak communication: Impact on dementia care. American Journal of Alzheimer's Disease & Other Dementias 24, 1 (2009), 11–20.
4. Altman C.E. Age, period, and cohort effects. In Encyclopedia of Migration. F. Bean and S. Brown, eds. Springer, 2015.
5. Hollwich, M. New Aging: Live Smarter Now to Live Better Forever. Penguin, 2016.
6. Loi, D. @HOME: Exploring the role of ambient computing for older adults. In Universal Access in Human-Computer Interaction. Multimodality and Assistive Environments. HCII 2019. Lecture Notes in Computer Science, vol 11573. M. Antona and C. Stephanidis, eds. Springer, 2019.
Authors
Daria Loi is senior director and head of product design at Mozilla. Her work revolves around mixing design strategy with UX research to enrich people's everyday lives. In 2018 she was recognized as one of Italy's 50 most inspiring women in tech. [email protected]
Thomas Lodato is a designer and researcher at Mozilla. As a recovering academic, he brings design and media studies—as well as sociological and anthropological theory and methodologies—to his professional work through participatory and human-centered design methods and approaches. His goal is to foster participation, equity, and justice in the design process and in organizations that engage in design. [email protected]
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The Digital Library is published by the Association for Computing Machinery. Copyright © 2021 ACM, Inc.
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