ARCH Seminar: Bridging the Digital Divide: Stakeholder Engagement for AI/ML Practitioners, AIM AHEAD DICB Program, Laboratory of Experimental Medicine, University of Hawaii, John A. Burns School of Medicine
Created by AI Navigator
Tue Apr 29, 2025
Register now to attend the virtual ARCH Workshop, "Bridging the Digital Divide: Stakeholder Engagement for AI/ML Practitioners" hosted by Dr. Helen Turner.
Seminar Date: May 13, 2025
Time: 10:00 AM Hawaii Time (1:00PM PT/3:00 PM CT/4:00 PM ET)
Brief Description
Technical experts in areas such as data science and AI/ML often confront digital divides when working with stakeholders and clients. This workshop provides professional development in stakeholder engagement for AI/ML practitioners. We review structural barriers and hegemonies that limit stakeholder engagement with AI/ML, and identify practical approaches to overcoming them through project design and implementation. The workshop prepares AI/ML practitioners for productive and transparent research collaboration with partners across the community, social sector, and academic settings.
Prerequisites
This workshop is intended for AI/ML practitioners, data scientists, and technical professionals interested in improving stakeholder collaboration. No prior experience with community-engaged research is required, though familiarity with AI/ML workflows and project development is recommended.
This workshop is intended for AI/ML practitioners, data scientists, and technical professionals interested in improving stakeholder collaboration. No prior experience with community-engaged research is required, though familiarity with AI/ML workflows and project development is recommended.
Datasets and tools
This is a discussion- and reflection-based workshop; no computational tools or datasets are required. Case examples, frameworks, and scenario-based exercises will be used to guide participants through real-world applications of collaborative project design and stakeholder engagement.
This is a discussion- and reflection-based workshop; no computational tools or datasets are required. Case examples, frameworks, and scenario-based exercises will be used to guide participants through real-world applications of collaborative project design and stakeholder engagement.
Expected Outcomes
(1) Identify structural barriers and digital divides that limit stakeholder engagement in AI/ML projects.
(1) Identify structural barriers and digital divides that limit stakeholder engagement in AI/ML projects.
(2)Explain how hegemonic systems and power dynamics impact collaboration with the community, social sector, and academic partners.
(3) Demonstrate strategies for designing AI/ML projects that effectively involve stakeholders throughout the project lifecycle.
(4) Tailor communication of technical concepts effectively to non-technical audiences to foster trust and mutual understanding.
About ARCH:
The National Institutes of Health AIM-AHEAD program supports the AI Resource Concierge for Health (ARCH).
ARCH Mission:
Support academic and community stakeholders in the adoption of AI/ML tools to advance their health and disease research goals.
ARCH Vision:
ARCH provides expert technical assistance, guidance, and collaboration to facilitate the adoption of AI/ML tools, supporting the AIM-AHEAD and wider research communities in leveraging these technologies to improve the health of the Nation.
Need Support?
Contact the AI Navigators HelpDesk to request support here: https://helpdesk.aim-ahead.net/ticket/create/35bD542BF0
Interested in learning more?
See a schedule of all upcoming ARCH Workshop details here: https://www.arch.health/stakeholder-engagement-workshops
