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The Challenge
Gendered Innovation 1. Assessing Women's and Men's Needs for Assistive Technologies
Method: Analyzing how Sex and Gender Interact
Gendered Innovation 2. Developing Assistive Technologies Considering Women’s and Men’s Needs
Method: Co-Creation and Participatory Research
Gendered Innovation 3. Using Participatory Design to Create the Next Generation of Assistive Technology
Conclusions
Gendered Innovation 1. Assessing Women's and Men's Needs for Assistive Technologies
Method: Analyzing how Sex and Gender Interact
Gendered Innovation 2. Developing Assistive Technologies Considering Women’s and Men’s Needs
Method: Co-Creation and Participatory Research
Gendered Innovation 3. Using Participatory Design to Create the Next Generation of Assistive Technology
Conclusions
The Challenge
The proportion of the world population over age 60 is projected to increase from 11 percent today to 22 percent by 2050—see charts below (data from United Nations, 2012). Population pyramids, especially in Europe, the U.S. and Canada, reveal that the proportion of the elderly is increasing while that of young people is shrinking. As the population ages, more people will need care. At the same time, fewer people will be available to provide and pay for the patient-centered care characteristic of Western societies today. With fewer people available to provide care, new solutions will be needed. In recent years, researchers have developed technologies to assist in elder care (Peterson et al., 2012; Broekens et al., 2009).
Gendered Innovation 1: Assessing Women's and Men's Needs for Assistive Technologies
Understanding the characteristics of elderly populations is key to designing successful assistive technologies. While elderly women and men often have similar needs, understanding how sex and gender interact to impact aging can assist engineers in developing technologies that best fit user needs. Studies show that sex and gender interact to impact health in old age.
- • Dementia strikes women and men in equal numbers as they age, but because women live longer in most developed countries, they suffer more dementia (Plassman et al., 2007; Nowrangi et al., 2011).
- • Arthritis is more common in women than in age-matched men, and rheumatoid arthritis occurs 2-3 times more often in women than in age-matched men (Alamanos et al., 2005; Linos et al., 1980).
- • Dexterity impairment impacts men more than age-matched women (Desrosiers et al., 1995).
- • Hearing impairment is more common among men than in age-matched women (Cruickshanks et al., 2010)—see chart. These differences may depend on sex-specific biology, but gendered divisions of labor also mean that men are more likely than women to be exposed to occupational noise (Engdahl et al., 2012).
Analyzing sex and gender is important for engineering successful assistive technologies, and this will become even more important as the population continues to age. Data from the U.S. reveal that the majority of the elderly are women, and women make up an increasingly large proportion of older people at more advanced ages. About 53 percent of the U.S. population aged 65-69 are women; this increases to 65-80 percent among the "oldest old," aged 85 and over—see chart below. These data require special attention: When research for assistive technologies is sex- and gender-blind, the marketability, usefulness, and acceptability of such technologies can be limited.
Method: Analyzing how Sex and Gender Interact
Analyzing sex (physical needs) and analyzing gender (social needs) of the elderly, and analyzing how these physical and socio-cultural needs combine in individual women and men helps researchers design the most effective and marketable assistive technologies. Overall, designers should be aware that the majority of the elderly are women. Analyzing sex differences reveals that women and men often have distinctive needs for physical mobility, cognitive dexterity, etc. Gender differences in marriage age, partnering patterns, experience in household management, and receptivity to technology may be important to consider for effective design. When addressing the market for assistive technologies, researchers will want to take into account women's and men's specific needs as elderly and as elder caregivers.
Gendered Innovation 2: Developing Assistive Technologies Considering Women's and Men's Needs
This section presents examples of assistive technologies designed to respond to women’s and men’s needs as discussed above—with special attention to gendered innovations in design.
1. Visual assistance:
The European Union's Framework Programme 7 (FP7) project, "Assisting Personal Guidance System for People with Visual Impairment" (ARGUS), is developing a system to promote safe, autonomous movement for visually-impaired people (Dubielzig et al., 2012). ARGUS is envisioned as a handheld device containing a global positioning system (GPS) receiver and wireless modem that will determine the location of the user and provide audio and haptic guidance allowing the user to follow pre-determined paths in both built and natural settings (Otaegui et al., 2012—see diagram.)
2. Mobility assistance
Wheelchairs are important mobility aids, and powered wheelchairs can allow mobility for people who lack the strength and/or dexterity to operate manual wheelchairs. However, some people cannot operate powered wheelchairs (Fehr et al., 2000). In recognition of this, researchers are developing a robotic wheelchair, "Wheeley," designed to perform semi-automatic navigation. Rather than controlling the wheelchair's fine movements manually, users are to be able to issue general voice commands ("turn left," "move forward," etc.). Computer vision systems then determine the exact path to be taken (Bailey et al., 2007).3. Cognitive assistance: Mental exercises may slow cognitive decline (Wilson et al., 2010). A number of technologies have been developed to keep minds sharp. These include:
- -The BrightArm Rehabilitation System, developed with support of the U.S. National Institutes of Health (NIH), monitors and trains arm and hand movements in users with stroke-related dementia (Rabin et al., 2012; Rabin et al., 2011). The NIH is also supporting development of a robotic exoskeleton for stroke patients. The exoskeleton is intended for both diagnostic and rehabilitative use, and will incorporate a brain-machine interface (NIH, 2012).
- -A 3-D game where users search for objects in a simulated apartment, developed at the Technische Universität Chemnitz (Lange et al., 2010; Sitzer et al., 2006).
- -A memory training game in which users are asked to memorize a shopping list and pick out items at a virtual convenience store, developed and tested in Hong Kong (Man et al., 2011).
-The EU's “Development of High Therapeutic Value Information Systems and Technology [IST]-Based Games for Monitoring and Improving the Quality of Life of Elderly People” (ELDERGAMES) uses virtual reality and specialized hardware to train a range of skills, such as memory, reasoning, and selective attention (Gamberini et al., 2009).
In addition to projects aimed at slowing the onset of dementia, the European Union’s Framework Programme 6 (FP6) project, “Helping People with Mild Dementia Navigate their Day” (COGKNOW), has developed prototype technologies to assist people with dementia in their daily activities. COGNOW can remind users of medical appointments and mealtimes, help users locate items such as keys, and support contact between the user, carers, and health professionals (Bresciani et al., 2008).
Method: Co-Creation and Participatory Research
Research and design of assistive technologies also gain by including health professionals and caregivers. EU women are about twice as likely as EU men to provide informal care for ill or elderly adults (Daly et al., 2003). Researchers in the U.S. report similar findings—about 70 percent of informal care is provided by women (Lahaie et al., 2012; Kramer et al., 1995). Over the years, these care givers develop hands-on knowledge that technology designers can access have through participatory design (Landau et al., 2010). COGKNOW designers, for example, tapped into this knowledge by consulting women and men caregivers and with different relationships to dementia patients (sons, daughters, spouses, cousins, etc.) (Andersson et al., 2007). In Finland, researchers have studied both care recipients' and caregivers' responses to over 60 assistive technologies in four pilot "smart homes" (Melkas, 2012)—see also Rethinking Engineering Processes.
Gendered Innovation 3. Using Co-Creation and Participatory Research to Create the Next Generation of Assistive Technology
Studies show that assistive technologies developed with the participation of the intended users are accepted at a higher rate. Involving the users-to-be already in the early stages of development ensures that the technology fits their needs (Ghorbel et al. 2008; Kanis, 2011). McCreadie et al. found that when the assistive technologies are smart, simple, reliable, and meet a specific need, they are likely to be integrated into everyday life (McCreadie et al., 2005).
Many assistive technologies will be delivered as handheld, room-installed devices, etc. that simply work in the background. Some, however, may be robotic, working collaboratively with a smart home environment to address psychosocial conditions, such as isolation and depression. Robots may interact directly with users to monitor mental status, provide cognitive stimulation, companionship, and assist with navigating complex environments (Pollack, 2005). Tapus et al. defined some criteria for assistive technology used in physical interaction, which increase the acceptance of the user. These criteria are embodiment, personality, empathy, engagement, adaption and transfer (Tapus et al., 2007). Machines that interact with humans provide further design challenges:
1. Emotion: Definitions of artificial intelligence (AI) are changing as engineers recognize emotion not as a byproduct of intelligence but rather as a driving force behind cognition, attention, and learning (Minsky, 2007; Arbib et al., 2004). In developing emotional intelligence in robots, gendered differences in expression may become important (Brody et al., 2008). The CompanionAble robot expresses emotion via digitally-rendered “eyes” that appear on a screen (CompanionAble, 2010).
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2. Ethnicity and Skin Color: Existing facial recognition algorithms—used to uniquely identify individuals, detect emotional cues, etc.—often show better performance for subjects of one skin color than another. For example, in an international competition, facial recognition algorithms developed by researchers in East Asian countries were more accurate for Asian faces than Caucasian faces, while algorithms developed in Western countries were more accurate for Caucasian faces than Asian faces (Phillips et al., 2011). Considering these variables may be important in developing robotic facial recognition systems for global markets.
3. Culturally-Determined Sense of Personal Space: Cross-cultural differences in perceptions of personal space are well documented; a distance that is considered "standoffish" in one culture might be considered "pushy" in another (Fries, 2005). Research on cross-cultural standards of personal space may help the assistive robots interact with users in a socially-acceptable way.
Conclusions
Women and men differ in their needs for and experience with technology. Women may have less technical experience and less positive attitudes toward technology (Gaul et al., 2010). They may also be more apprehensive about using assistive technologies, such as robots, in domestic environments (Cortellessa et al., 2008). Thus it is important to include both women and men in technology design. Analyzing sex and gender as well as including both women and men users in technology development is a positive action that can lead to better designs and improve marketability of products.
Researchers are developing new assistive technologies to support independent living for the elderly and to lighten the burdens of caregivers. Through participatory research and design with both the elderly and their caregivers, designers have gained key insights for developing assistive products that are useful to a broad user base. Involving users and stakeholders in the design process enhances outcomes. Building machines that based on sex and gender analysis of demographic data will be important for the development of the next generation of assistive technology.
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The world population will age dramatically by 2050—a problem especially for Japan, Europe and the U.S. Large elderly populations will place a growing strain on human caregivers as well as health and social systems. This case study explores the value added of considering both sex and gender when designing Assistive Technologies for the Elderly.
Method: Analyzing How Sex and Gender Interact
Assistive technologies support independent living for the elderly. When developing these technologies, it's important to look at sex differences. Women for example live longer, but may have more debilitating disease; men, for example, lose their hearing earlier. In addition, it is important to look at gender differences: as they age, women and men have different partnering patterns (elderly women, for example, more often live alone), men and women have different experience in household management, and elderly men and women have different receptivity to technology. We encourage researchers to analyze how sex and gender interact in individual women and men so that researchers can design the most effective and marketable assistive technologies—designers want their products to be useful and appealing to both women and men.
Gender issues become especially important as assistive technologies become more personalized. Engineers in the U.S., Europe, and Japan are developing robots to help elderly people. Georgia Tech, for example, has created a robotic nurse, named "Cody," that can bathe elderly people. Bathing is an intimate activity that requires careful thought—for women and for men. Carnegie Mellon is developing HERB (Home Exploring Robot Butler) that can fetch household items for you, remind you to take your medicine, or even clean up the kitchen. If there is a robot to clean up the kitchen, I'm ordering it immediately!
As these robots enter our lives, we humans will gender them. Studies of synthetic voices (machine-generated voice) show that human listeners assign gender to machine voices; that is to say, we interpret these machine voices as the voice of a woman or a man, even when the designers may have tried to create a gender-neutral voice (see Making Machines Talk). Apple's Siri (the original iPhone voice) is interesting in this regard. Ask Siri why she is a woman, one of her responses is, "I was not assigned a gender," implying that it's not Apple's fault that you, the listener, ascribe gender to her. As soon as humans interpret a voice as masculine or feminine, we tend to apply all of our cultural stereotypes to the machine.
Gendered Innovations:
Considering sex and gender when designing new assistive technologies will be ONE important factor to ensure that the products are successful with all users.
- 1. Assessing women's and men's needs for assistive technologies.
- 2. Developing assistive technologies considering women's and men's needs.
- 3. Using participatory design to create the next generation of assistive technology.
