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Author: Jeffrey A. Kaye
In 1881 Chancellor Otto Von Bismarck of Germany proposed the first social insurance program of government pensions for nonworking older citizens. The age chosen for eligibility was 70 (later lowered to age 65, which subsequently became popularized as a milepost for when a person is “old”). Although historians and gerontologists suggest that this was a cynical political move since at the time life expectancy from birth was less than age 50 and thus the number of pensions to pay out would be relatively small, the concept of support for aging well remains a valued goal. Now, however, it poses very different kinds of demographic challenges.
For a number of reasons, life expectancy trends in the United States have increased steadily during the past 40 years (Arias and Xu 2018). Accordingly, the number of older persons over age 65 has grown -rapidly, from 29 million in 2000 to 49.2 million in 2016, and the number is projected to climb to 78 million by 2035, when for the first time in America the “elderly” (those over age 65) will exceed the number of children (those under 18).
At the same time, the top concerns of aging—-physical health and personal finances—and the intersecting value proposition of surmounting these two concerns—remaining independent—remain a challenge. This results at multiple levels in stress to not only aging individuals but also their families and the institutions that support them.
The irony of living longer is illustrated by the ancient Greek myth of Tithonus whose lover Eos asked Zeus to grant Tithonus immortality. She should have asked for eternal youth. Instead the prince was doomed to an increasingly debilitating, dependent existence.
The age-associated risk of progressive disablement is why concerns about aging center around sustained health and in particular mental or cognitive function. Nearly half of those over age 65 have difficulty or need help with activities of daily living (Freedman and -Spillman 2014), and over a third of adults in the United States will develop cognitive impairment or -dementia after age 65 (Alzheimer’s Association 2018). This -latter statistic is of special concern because, of the top ten leading causes of death and disability, -Alzheimer’s disease and related dementias are the only ones with no prevention or cure. Without change, such as the development of effective management techniques, this age-driven disability alone will become a trillion-dollar expense in just the next 30 years.
With this context in mind, many policy and social changes have been proposed to ease the potential nexus of personal and societal strain posed by an aging society, often with an eye toward finding or shifting money to support the needs of a growing older population. For example, extended employment for older workers with part-time positions (thus generating additional tax revenue) or policies promoting and rewarding volunteering, care, and artistic work have been proposed. But many of these proposals suffer from the criticism that they “just throw money at the problem,” or will fail by trying to change deeply rooted cultural norms. They do not deal with the individual challenges of maintaining independence in daily life.
A major opportunity to transform and improve the aging experience resides in the rapidly advancing field of digital technologies and related sciences. Of course, the word “technology” conjures up a range of concepts that differ depending on one’s point of view and age. Alan Kay famously observed in the 1980s that “technology is anything that wasn’t around when you were born.”
Today, technologies such as wearable devices, robots, smartphones and apps, and artificial intelligence (AI) pervade everyday activities and discourse, and they exist in a larger universe of technologies such as pervasive and ubiquitous sensing and computing, the Internet of (connected) Things (IoT), and high-dimensional data analytics. The articles in this issue of The Bridge explore the intersection of these technologies, engineering science, and aging to provide state-of-the-art reviews and perspectives of key topics in this area. The authors explain the promise of emerging technologies and solutions, as well as how to address challenges so as to fully realize their potential.
In the opening article Charles Consel and I explore the possibilities of the IoT to address age-related -changes and help maintain independence, using a hypothetical scenario of an older individual taking advantage of the connected world of sensors and devices with AI and services. One of the barriers to adoption of this vision is technology acceptance, an important subtext for many of the subsequent articles. A larger, more coordinated research ecosystem is needed to design, develop, deploy, and evaluate these technologies and generate needed evidence to move users, as well as governments, toward adoption.
Joseph Coughlin and Samantha Brady focus on a critical area for maintaining independence outside the home, the ability to navigate in one’s community. After describing mobility challenges and the characteristics of the aging population that bear on the choice and design of transportation modes and systems, they outline a useful framework of micro- and macro-mobility, differentiating between travel in the community and farther afield. Using this framework, the authors consider mobility-related scenarios—e.g., public transport, conventional personal vehicles, autonomous vehicles—that are a major focus of transportation research for the aging population. As in other articles, they make the point that transportation solutions can connect with other technologies and must be designed with the user in mind.
Cynthia Breazeal and her coauthors report advances and possibilities with social robotics, which can reduce older adults’ isolation, provide support and coaching, and increase social engagement. The authors discuss advances in the field and their own work showing how social robots and the services they can provide require an understanding of user interfaces to successfully develop technologies that support the essential human need for interpersonal interaction. They call for integration across development teams with multidisciplinary specialization.
In the next article, William Rouse and Dennis McBride review technologies that can provide func-tional cognitive support for the daily tasks of work or life. Many of the considerations here align with the previous article, illustrating the use of smart technologies for social interaction assistance, coaching, and cognitive assistance. Rouse and McBride take a systems approach, outlining the levels of interaction that a successful cognitive assistant application must traverse. They briefly describe a Wearable Coach system for developmentally disabled persons that could be adapted for aging adults. In their systems approach they point out that cognitive assistants will achieve their potential only if they are fully integrated into the care and support eco-system, which is currently unintegrated and uncoordinated across agencies and regulatory policies at the state and national levels.
Weaving through the technology development and solutions presented in the previous articles are the data generated with these new technologies. These data—diverse, multidimensional, often unsupervised, and continuous—require special consideration for both their information content and the analyses that can be conducted. Hiroko Dodge and Deborah Estrin consider some fundamental issues regarding the data and in particular implications of digital data streams. They explain the distinction between big data, which applies to populations, and “small data,” which they define as “the big data of the individual,” and explain how pervasive computing and the digital biomarkers that result from small data are particularly suited to providing unique insights at the person-level for aging and disease management.
In the final article Eric Dishman presents a grand synthesis encompassing much of the information in the foregoing articles into the concept of precision aging, the use of an individual’s real-life data-based “lifeprint,” incorporating both personal data generated over the life course from diverse sources (e.g., omics, digital health, activity readouts, environmental conditions) and the big data of the populations and systems in which they live. He echoes the other authors in noting challenges, from basic usability issues to the need for integrated policy-level planning.
I thank the authors for their insightful and forward-thinking contributions. Collectively, the articles describe many promising technologies and systems in development that can improve the aging experience at the personal as well as the societal level. Some solutions have begun to be adopted, but clearly there is considerable technology and engineering research and development yet to be done.
As everyone ages, let us hope the scientific community and all its stakeholders are successful as they build out and unlock the potential at the intersection of the world’s aging society and technology.
The following experts helped improve this collection of papers by offering thoughtful comments on them: Mohan Karunanithi (Commonwealth Scientific and Industrial Research Organisation, Canberra), -Chaiwoo Lee (MIT AgeLab), Guru Madhavan (National -Academy of -Medicine), Indira Nair (Carnegie Mellon University), and Lesley Ross and Sara Freed (-Pennsylvania State University). Cameron Fletcher must also be prominently acknowledged and thanked for her terrific editing and guidance, which truly enhanced not only the quality and clarity of the articles but the experience of the authors while writing them.
Alzheimer’s Association. 2018. Alzheimer’s disease facts and figures. Alzheimers & Dementia 14(3):367–429.
Arias E, Xu JQ. 2018. United States life tables, 2015. -National Vital Statistics Reports 67(7). Hyattsville MD: National Center for Health Statistics.
Freedman VA, Spillman BC. 2014. Disability and care needs among older Americans. Milbank Quarterly 92(3):509–541.
 US Census Bureau, “An Aging Nation: Projected Number of Children and Older Adults” (https://www.census.gov/library/visualizations/2018/comm/ historic-first.html).