Events

Upcoming Webinar – TRIALCHAT: Developing Agentic AI Chatbot Tools with Older Adults and Caregivers to Encourage Participation in ADRD Clinical Trials

Zoom Registration: https://umass-amherst.zoom.us/meeting/register/_c8H4BLBRROxD7FH1g3KSg Abstract: Hype around the potential of generative AI tools to transform healthcare is at an all time high, but their design and utility is often not user or patient-centered. This is particularly true for generalized large language models that have limited UI/UX features, may hallucinate or give incorrect medical/healthcare advice, or may lack conversational clarity and specificity. In fact, these tools are rarely designed in partnership with the end-user or patients they intend to serve. As part of a2 Collective Pilot award in partnership with MassAITC, S-3 Research and California State Fullerton have been developing “TRIALCHAT", a multiagentic AI tool with the goal of navigating older adults and their caregivers to resources related to Alzheimer’s Disease and clinical research participation opportunities. Lessons learned from a technology design and development process that involved…

Continue ReadingUpcoming Webinar – TRIALCHAT: Developing Agentic AI Chatbot Tools with Older Adults and Caregivers to Encourage Participation in ADRD Clinical Trials

Upcoming Webinar – From AI Validation to Evidence: Proving Readiness for Real-World Aging Care Systems

Zoom Registration: https://umass-amherst.zoom.us/meeting/register/TQr7brHuS_SYf1O3AXYJQA Abstract: Artificial intelligence is increasingly being deployed to support aging populations through applications such as remote monitoring, fall detection, cognitive assessment, and caregiver support. While many AI systems demonstrate strong performance in pilot studies, only a small fraction successfully translate into safe, reliable, and scalable real-world deployments. A key challenge lies in the gap between validation and real-world evidence. Traditional evaluation approaches emphasize model performance, but aging care environments introduce additional complexities—including multimorbidity, heterogeneous living conditions, and safety-critical decision contexts—that are often not adequately captured during pilot validation. This webinar presents a structured approach to moving from AI validation to evidence-driven deployment readiness for aging care systems. The session will explore lifecycle-based evaluation methods spanning data, model development, pilot testing, real-world deployment, and continuous monitoring. It will highlight approaches for assessing fairness…

Continue ReadingUpcoming Webinar – From AI Validation to Evidence: Proving Readiness for Real-World Aging Care Systems

Past Webinar – Old School Meets New School: Voice-Based, AI-Enabled Cognitive Rehabilitation for Dementia Care

https://youtu.be/tY05wZMGYg8 Abstract: Cognitive rehabilitation therapy supports individuals living with mild cognitive impairment and early-stage dementia in maintaining and improving function in daily life. However, access remains limited due to constraints in the availability and scalability of trained therapists. Recent advances in artificial intelligence, combined with evolving reimbursement pathways for remote care in the United States, now make virtual delivery models increasingly viable, creating new opportunities to expand access to high-quality cognitive care. Moneta Health has developed a telephone-based cognitive rehabilitation platform that enables structured, personalized therapy sessions delivered remotely and overseen by licensed speech-language pathologists. The platform leverages AI-driven speech analysis and automated session orchestration to support consistent therapy delivery while preserving clinician oversight, enabling older adults to engage in care from their homes through a familiar and intuitive interface. This approach is designed to…

Continue ReadingPast Webinar – Old School Meets New School: Voice-Based, AI-Enabled Cognitive Rehabilitation for Dementia Care

Past Webinar – How to Develop and Test Mechanism-Driven, Technology-Enabled Interventions in Response to the Scientific Foci of ASU Roybal Center for Older Living Alone with Cognitive Decline

http://youtube.com/watch?v=6n6meYGI_Ug Abstract: Purpose: 1) Explain the scientific foci of ASU Roybal Center for Older Adults Living Alone with Cognitive Decline to delay the onset and progression of Alzheimer’s disease and related dementia (AD/ADRD), and 2) Guide investigators to develop strong research proposals, focusing on the significance of a proposed solution, mechanism-driven and technology-enabled interventions, and health disparity factors.  Rationale: Poor lifestyle behaviors such as physical inactivity, unhealthy diet, and stress contribute to up to 40-50% of AD/ADRD cases; however, few intervention successes have been translated into real-world impacts. Most interventions are not mechanism-driven, precise, accessible, cost-effective, and/or scalable, which could potentially be addressed by technology through integrating Artificial Intelligence, real-time analytics and feedback, enhancing user autonomy and person-centeredness, and personalizing intervention prescription and delivery. In addition, the population of older adults living alone with cognitive…

Continue ReadingPast Webinar – How to Develop and Test Mechanism-Driven, Technology-Enabled Interventions in Response to the Scientific Foci of ASU Roybal Center for Older Living Alone with Cognitive Decline

Past Webinar – Advancing Fair & Effective AI for Older Adults

https://www.youtube.com/watch?v=67St-zDEzjk Abstract: Artificial intelligence holds promise to transform care for older adults, yet today’s AI systems routinely underperform for this population due to poor data representation, limited validation, and weak alignment with lived experience. Drawing on a six-month collaboration between the SCAN Foundation, CHAI will be synthesizing evidence from literature review, expert interviews, and multi-stakeholder roundtables to surface why AI fails older adults—and what must change. They will outline practical pathways for building equitable AI, including multimodal data integration, standardized validation, local testing, and patient-centered deployment. The talk concludes with a roadmap for developing trustworthy AI that meaningfully improves outcomes for aging populations. Biography: Lucy Orr-Ewing, Head of Policy & Strategy, Coalition for Health AI (CHAI) Lucy Orr-Ewing leads Policy and Research for CHAI, where she leads policy engagement at both the state and federal…

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Workshop Registration Now Open – Join us on January 23, 2026 in Newton, MA!

  • Post category:EventsNews

When:  Friday, January 23rd, 2026Where: Mount Ida Campus of UMass Amherst in Newton, MA (In-person) | Zoom Webinar (Virtual option)Registration: Free Registration Link here MassAITC is hosting the Digital Frontiers in Frailty: Opportunities for Early Detection and Clinical Action Workshop. The free workshop will be held on January 23rd, 2026 at the Mount Ida Campus of UMass Amherst in Newton, MA and aims to bring together technologists (engineers, computer scientists, academic researchers, start-up founders) and clinicians (geriatricians, neurologists primary care providers) to redefine how we measure, assess, and provide time appropriate care for frailty. The workshop will include plenary speaker sessions from frailty and technology research experts, contributed poster and technology demo presentations, and a moderated discussion. By 2060, it is estimated that nearly a quarter of the US population (over 95 million people) will…

Continue ReadingWorkshop Registration Now Open – Join us on January 23, 2026 in Newton, MA!

Past Webinar – Can You Walk Me Through It? Explainable SMS Phishing Detection using LLM-based Agents

https://www.youtube.com/watch?v=XST7eqXmFQQ Abstract: Phishing attacks pose a significant threat to users, especially older adults. Existing defenses mainly focus on phishing detection but often cannot explain to lay users why a message is malicious. In this talk, I will discuss how we use Large Language Models (LLMs) to detect SMS phishing while generating evidence-based explanations. The key challenge is that SMS is short, lacking the necessary context for security reasoning. We develop a prototype called SmishX that gathers external contexts to augment the chain-of-thought (CoT) reasoning of LLMs and facilitate the explanation process. I will further discuss our user studies to evaluate the effectiveness and usability of SmishX. Finally, I will discuss the open challenges and opportunities of using AI to help older adults better protect themselves from cybersecurity threats in general. Biography: Gang Wang, PhD, Associate…

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