The goal of the Johns Hopkins University Technology Identification and Training Core is to develop a Science of Translation of Artificial Intelligence (Al) for Older Adults by developing processes that identify and articulate the needs of older adults and their family caregivers, connect those needs to promising areas of Al technology, and accelerate the refinement of these opportunities into tangible products.

The strategy of the JHU TITC will be to develop and deploy two key elements: 1) A  Human Factors Engineering (HFE-AI) informed participatory framework for user needs assessment and technology evaluation: and 2) a structured process, the Al-Readiness Framework (AIRF), to benchmark the technological suitability of Al-driven solutions.

Core Leadership:

Alicia I. Arbaje, MD, MPH, PhD

Alicia I. Arbaje, MD, MPH, PhD

Co-Director of Technology Identification and Training Core
Technology Identification and Training Core Core Leaders
Mathias Unberath, PhD

Mathias Unberath, PhD

Co-Director of Technology Identification and Training Core
Technology Identification and Training Core Core Leaders
An AI-generated drawing of a robot following a female doctor pushing an elderly woman in a wheelchair. This image was created using a free version of Bing Image Creator (https://www.bing.com/create) that runs on a text-to-image conditional diffusion model named DALL-E 3.
This image was created using a free version of Bing Image Creator that runs on a text-to-image conditional diffusion model named DALL-E 3.

Core Activities:

  • To convene experts in Al and in Aging Research to develop and apply a stakeholder­informed Al Readiness Framework (AIRF) to identify promising technology directions to support older adults’ and caregivers’ needs. In collaboration with the Stakeholder Engagement Core, and guided by a participatory ergonomics approach, we will:
    • 1a. Convene stakeholders and to develop stakeholder-informed conceptual frameworks outlining key domains of older adults’ and caregivers’ technology needs to support optimal well-being and resilience.
    • 1b. Conduct structured identification and assessments of Al suitability and maturity to meet the needs  identified in 1a.
  • To create in-person and online training tools that both exploit and expand our knowledge of the Science of Translation of Artificial Intelligence for Older Adults.
  • To develop and deploy instructional tools that describe Science of Translation of Artifi­ cial Intelligence for Older Adults and related best practices for wider use and dissemination.