Caring Machines: AI in Eldercare
Much has been published on the looming demographic crisis in the U.S., with the number of older adults skyrocketing while the number of human caretakers dwindle. Combined with a strong desire by aging individuals to remain independent in their homes as long as possible, these conditions motivate technological solutions to human care-giving.
While this situation has inspired many research projects in AI, HCI and robotics over the last decade, most of these solutions have addressed only very narrow aspects of the total care-giving needs of older individuals. Social psychologists have identified a number of types of social support that people provide for each other, and this taxonomy may be useful in grasping the entire range of needs that an individual may have. Instrumental support provides material aid for individuals, such as help with shopping or household chores, and may require robotic assistance to effect. Informational and cognitive support provides advice, suggestions, and information that a person can use to address problems, and may require proactive reminding and intervention for individuals with cognitive impairments. Emotional and appraisal support involves the provision of empathy to help individuals manage their adverse emotional states and provide feedback that is useful for self-evaluation, and may help address loneliness and depression. Social network support helps an individual maintain an active social network, and can be provided by systems that introduce elders to others with similar interests or proactively take steps to maintain existing friendships.
The goal of this symposium is to bring together researchers in AI?including computational linguistics, planning, user modeling, social agents, robotics, intelligent sensing and machine learning?with researchers in gerontology, geriatrics health communication, public health and other medical sciences. The overall focus will be the design, implementation and evaluation of integrated intelligent support systems for older adults, and cover topics such as the following:
- Frameworks for integrating assistive and supportive technologies for older adults.
- Approaches to maintaining trust and engagement between support systems and elders over years of use, while avoiding user complacency and over-reliance.
- User modeling and system adaptation over time.
- Recognition, display, or management of affect to support system goals.
- Uses and comparisons of different HCI modalities for older adults, including text, audio, embodied agents or robots, and other human factors issues.
- Ethical and privacy issues.
- Approaches to evaluation of these systems and results from studies and clinical trials.
Submissions
Potential participants may submit a technical paper (up 8 pages), or a short paper (up to 4 pages) in the form of an extended abstract or a description of a proposed demo. Potential participants who are unable to submit a paper are encouraged to submit a one-page statement of interest. PDF-submissions in AAAI format should be sent to bickmore@bu.edu.
Organizing Committee
Timothy Bickmore (chair), Boston University School of Medicine; Karen Haigh, Honeywell Laboratories; Stephen Intille, House_n, Massachusetts Institute of Technology; Henry Kautz, Department of Computer Science and Engineering, University of Washington; Richard Simpson, School of Health and Rehabilitation Sciences, University of Pittsburgh.
Additional Information
For additional information, please see www.misu.bmc.org/~bickmore/eldertech
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