Center Sponsored and Related Conferences

Stony Brook University Hospital’s Institutional Ethics Committee is pleased to announce our Call for Abstracts for our 9th Annual Medical Ethics Symposium, Trust but Verify: Ethical Challenges of AI in Healthcare. 

Artificial intelligence (AI) is transforming healthcare by improving diagnosis, streamlining administrative tasks, supporting personalized treatment plans and in medical research. However, the growing use of AI in medicine also raises important ethical concerns. While AI has the potential to enhance patient care and efficiency, healthcare providers and patients must approach these technologies with caution and critical oversight.

Professionals and students from all healthcare, legal and other associated disciplines are invited to submit poster proposals associated with this theme. Chosen topics should consider evidenced based evaluation, ethical principles to be considered, effective strategies for implementation, risk assessment and /or guidance for improved practice and conflict resolution.

According to the National Academy of Medicine’s An Artificial Intelligence Code of Conduct for Health and Medicine, Essential Guidance for Aligned Action, “Over the last decade, advances in artificial intelligence (AI) technologies have created transformational opportunities for health, health care, and biomedical science. While new tools are available to improve effectiveness and efficiency in myriad applications in health and health care, challenges persist, including those related to increasing costs of care, staff burnout and shortages, and the growing disease burden of an aging population. The need for new approaches to address these long-standing challenges is evident, and AI offers both new hope and new concerns. This publication presents an AI Code of Conduct (AICC) framework developed to align the field around responsible development and application of AI, and to catalyze collective action to ensure that the transformative potential of AI in health and medicine is realized.”

Suggested Topics (some listed in the NAM Code of Conduct Framework):

• Embedding a “Moral Conscience " or Ethical Framework into AI applications
• Developing approaches and considerations for inclusion and alignment when providing internal guidance for the development, purchase, or use of AI in their specific context, thereby advancing trust and minimizing the likelihood of actors across the field contending with approach inconsistencies.
• Reskilling and training programs for workforce AI competency
• Positive work and learning environments and culture
• Measurement, assessment, strategies, and research
• Disruptive technologies with change management strategies that promote worker well-being
• Development of standards and other governance structures to assess alignment by developers and users of health AI with societal and cultural goals for health AI
• Development and implementation of processes for independent evaluation, guidelines, standards and evidenced based oversight of these programs to monitor for accuracy, acceptable standards of practice, conflicts of interest etc.
• Incentives and structures for independent evaluation, certification to the AI Code Commitments, and public and transparent reporting on certification status
• Standardized metrics to assess and report bias in data, AI output, and AI use, in the interest of equitable distribution of benefit and risk Incentives and supports
• Informed consent and ethical communication regarding the use of AI
• Standardized quality and safety metrics to be used to assess the impact of the use of health AI on health outcomes
• Aligned frameworks for safety, equity, and quality in AI performance
• A well supported national health AI research agenda
• Participation in shared learning across all stakeholders
• Innovation as a core investment
• Data Security, Patient Privacy and Accountability
• Bias in AI, from data collection to biased algorithms
• Transparency in the use of AI, such as use in radiology, informed consent
• Harm to patients from the use of AI – who is responsible
• Transparency in research generated with AI
• Risk of exacerbating health disparities and AI

Abstracts must be uploaded in PDF format by the deadline of June 30th, 2026, to jean.mueller@stonybrookmedicine.edu; late entries will not be accepted. Notification of abstract acceptance for poster presentations will occur by July 9th, 2026.

Abstracts must include:Title of Project/Presentation, authors name including earned degree(s) and professional title, and a short bio including description of your work and research or quality improvement initiatives in medical bioethics, in fewer than 500 words including:

• Statement of Purpose and/or aims of the research or quality improvement initiative,
• Ethical Principle(s) Involved,
• Approach/Methodology/Strategy, Importance,
• Significance and Implications.

Accepted Posters must be mounted (36” x 44”) and will be displayed during the conference on August 7, 2026. All Poster presenters will be expected to be available for questions and answers during lunch and break times to share their projects. First, Second and Third Place Winners will be notified prior to the conference and given the opportunity to present their Poster in a 10-minute Rapid Fire Session during the Symposium.

Presented by the Stony Brook University Hospital Institutional Ethics Committee and cosponsored by the Center for Medical Humanities, Compassionate Care and Bioethics, Stony Brook University

8am Registration/Light Breakfast
Provided by The Center for Medical Humanities, Compassionate Care and Bioethics

8:30am Welcome
Jean Mueller, MPS, BS, RN, CPHQ Ethics Symposium Coordinator

Opening Remarks
Carolyn Santora, MS, RN, NEA-BC, CPHQ, Chief Nursing Officer; Chief Nursing Officer; Chief of Regulatory Affairs, Patient Safety and Ethics, Stony Brook University Hospital; Chair/Institutional Ethics Committee, Stony Brook Medicine

KEYNOTE
9- 10:30am "Trust, Communication, and Consent in AI-Mediated Healthcare"
Kellie Owens, PhD
Assistant Professor, Medical Ethics, Department of Population Health, NYU Grossman School of Medicine

KEYNOTE
10:45- 12:15pm "AI That Measures, AI that Speaks: A Decade of Surgical AI and the Problem of Verification"
Alexander Winkler- Schwartz, MDCM, PhD, FRCSC, FAANS
Neurosurgeon, Neuroscientist, AI and Surgical Education Researcher
Assistant Professor, Adult and Pediatric Neurosurgery, Stony Brook University

12:30- 1:15pm Lunch
Provided by the Stony Brook University Hospital Institutional Ethics Committee

Panel Discussion and Interactive Ethics Case Presentations
1:30- 3pm "Healthcare AI: Designed to Assist, Not Resist Human Judgement"
Moderator: David N. Hoffman, JD

Distinguished Panelists
Ahmad Aljobeh, MD
Julie Luengas, DNP, MBA, RN, NI-BC, FHIMSS
Tauhid Mahmud, MD, MPH
Pons Materum III, MD
Neil J. Patel, MD, MBA
Carolyn Santora, RN, NEA-BC, CPHQ
Caitlyn Tabor, JD, MBE
Matthew Tharakan, MD, MBA, FACP
Alexander Winkler-Schwartz, MDCM, PhD, FRCSC, FAANS

3- 3:45pm Poster Awards and Rapid-Fire Sessions
Carolyn Santora, MS, RN, NEA-BC, CPHQ
1st, 2nd and 3rd Place Posters and Colleagues Choice Award

3:45- 4pm Summary and Closing Remarks
Carolyn Santora, MS, RN, NEA-BC, CPHQ