top of page
Research Projects
Past Projects
Explainable AI for Older Adults
Design of explanations in assistive AI systems, focusing on how people ask for and perceive explanations in AI technologies.
Conversational Assistants (CAs) to Empower Older Adults
In this project, we deployed Google Home Hubs to dyads of older adults with MCI and their care partners. People with MCI experience more difficulties with memory and decision making compared to others their age. About 20% of adults over 65 will get MCI and of those, 80% will progress to Alzheimer's disease or dementia. Many people with MCI are aging in place and rely on their spouses or adult children to act as care partners for them. We logged the CA interactions of the people with MCI and their care partners over 10 weeks and then analyzed the resulting corpus of nearly 4000 interactions. Care partners logged roughly double the number of interactions as people with MCI, and had more varied usage, but people with MCI also used the CA fairly regularly. We interviewed the dyads and surveyed individual participants about their preferences in receiving automated assistance. After our initial deployment, we are now preparing to start the second cohort of 10 dyads, to see if we can recreate the encouraging results we found in the first group, and to see if we can further improve the participants' experience using the CA. In this work, we have found that empowerment means different things to the different stakeholders involved, and we have seen how the CA specifically supports these individual paths towards empowerment. For people with MCI, the CA can provide comfort, entertainment, social presence, and useful information. Care partners are empowered by CAs because they are able to scaffold interactions in advance that support more independence for the person with MCI. For example, a care partner may add information into the CA calendar that the person with MCI can ask about later, without needing to nag the care partner. There are of course challenges in this work, as some of our participants with MCI could not remember the CA was there, while others had trouble finding the words to initiate conversations. While we provided various training materials to support successful usage, more work will be required to provide support for the more complicated interactions. This research is situated within a larger research program called the Cognitive Empowerment Program (CEP), which strives to empower people going through mild cognitive impairment and their families through structured programming, social interaction, therapy and more.
Cognitive Empowerment Program (CEP)
Mild cognitive impairment (MCI) is an intermediate stage in cognitive decline, between the normal cognitive decline associated with aging, and the more abrupt decline of dementia. Nearly 20% of adults over 65 years old are at risk of getting MCI, and of those who do get it, 80% will progress to develop dementia or Alzheimer’s disease. Furthermore, this population of adults over 65 is expected to double by 2050. An MCI diagnosis affects the whole family, not just the family member who is diagnosed. Our lab works on many different projects in this space including measuring the impact of soundscapes and lighting on cognition or sleep, developing and evaluating novel medication management techniques, using passive sensing techniques to understand patterns of daily activity for this population, and empowering older adults with MCI and their care partners using conversational agents, such as the Google Home.
Data Ethics
In addition to the lab research focused on the use of social media and social technologies in relation to an individual's everyday health is the ethics involved in this type of research. Technology ethics include topics such as privacy, literacy, and research design.
This research is also in collaboration with the PERVADE Team - an NSF-supported collaborative focused on answering pervasive questions such as how do we quantify the risks to individuals and groups in the use of pervasive data, how do people experience the reuse of their personal data and how should existing ethical codes be adapted and adopted for computational research? Jessica serves as a research collaborator to the PERVADE team.
Because of her contributions to the HCI community in this space, Jessica has been selected to serve on the ACM SIGCHI Ethics committee starting this summer.
This research is also in collaboration with the PERVADE Team - an NSF-supported collaborative focused on answering pervasive questions such as how do we quantify the risks to individuals and groups in the use of pervasive data, how do people experience the reuse of their personal data and how should existing ethical codes be adapted and adopted for computational research? Jessica serves as a research collaborator to the PERVADE team.
Because of her contributions to the HCI community in this space, Jessica has been selected to serve on the ACM SIGCHI Ethics committee starting this summer.
Interactive Models of Healthcare Journeys
In this work we examine how support may be improved for those managing chronic illness. Health information management for individual's with a chronic illness is a challenging and personal process that changes over time based on one’s needs, goals, and health status. While technologies supporting health information management appear promising, we do not fully understand how health information tools fit into patients’ daily lives. To better understand the opportunities and usage barriers of these tools, we have partnered with healthcare professionals in Rome, GA to develop, deploy, and assess novel technologies that offer support to breast cancer patients throughout the entire cancer journey.
Digital Self Harm
Self-harm is the infliction of pain or injury onto oneself. Historically these behaviors have been relegated to the fringes of communities. Technology now enables new ways to foster and encourage these dangerous activities. The HCI field possesses few examples of scholarship focused on self- harm. This research focuses on characterizing the presentations of non-suicidal self-harm behaviors within social computing platforms. Building on these characterizations, we can begin to look at diagnostic screeners and tools to better understand how we can start connecting online activities related to one's mental illness to the physical presentation, detection, and treatment related to their disease.
Health
RADx-UP: COVID Testing in GA
Cyber Citizenship and Emotional Wellness
Supporting Epileptic Patient Self-Management
Collaboration
Aging in Place
Social Search
Online Communities
bottom of page