Research NewsletterIssue: ORN-2024-31

Advancing Trust in Science: Institutional Obligations to Promote Research Integrity

October 10, 2024; 8:00am - 4:30pm • Hybrid - Registration is required. RSVP here

Hosted by the Department of Medical Ethics & Health Policy and the Institute for Translational Medicine & Therapeutics, University of Pennsylvania Perelman School of Medicine

Several high-profile examples of research misconduct, defined as fabrication, falsification, and plagiarism, have recently come to light, amidst a moment of already precarious and waning public trust in science. The issues are not new, although there are now novel tools for identifying misconduct, proliferating platforms for discussing allegations and publicizing concerns, and growing unease about politically motivated misconduct allegations. In addition, the US Department of Health and Human Services Office of Research Integrity recently proposed new regulations to revise the Public Health Service Policies on Research Misconduct, with a final rule expected this year. Against this churning backdrop, how should institutional stakeholders – including universities and publishers – address concerns about research misconduct, from prevention to response? How should institutions build and maintain a culture of scientific integrity? When problems arise, how should they ensure procedural protections for those accused of misconduct, protect accusers from retaliation, conduct comprehensive investigations, facilitate rapid resolution, and promote transparency? Should responses differ when institutional leaders are accused of misconduct or when misconduct arises outside the health sciences? This symposium, which will be published in an open access special issue of the Journal of Law, Medicine, and Ethics in Spring 2025, will present commentaries on these issues and others from leading experts in ethics and law, those with experience identifying research misconduct, and those sharing relevant stakeholder perspectives, including researchers, academic leadership, and journal editors and publishers.

NSF: Planning Grants to Create Artificial Intelligence (AI)-Ready Test Beds; NSF Graduate Research Fellowship Program (GRFP); Engineering Research Initiation (ERI); Computer and Information Science and Engineering : Core Programs; NSF National Quantum Virtual Laboratory - Quantum Testbeds (NQVL)

NIH: Revolutionizing Innovative, Visionary Environmental Health Research (RIVER) (R35); Tissue Chips in Space 2.0: Translational Multi-Organ Tissue Chip Systems for Drug Efficacy, Toxicity Testing, and Personalized Medicine in Human Health, Aging and Associated Diseases (UG3/UH3); Bridges to the Doctorate Research Training Program (T32)

Department of Defense/US Army/DARPA/ONR: DoD Combat Readiness - Medical, Translational Research Award; Research and Development (RAD) Directed Energy (RD) University Assistance Instruments

Department of Energy: Offshore Wind National and Regional Research and Development; Smart Manufacturing Technologies for Material and Process Innovation; Geothermal Resources’ Value In Implementing Decarbonization (GRID)

NASA: Heliophysics U.S. Participating Investigator; Heliophysics: Living With a Star Science

National Endowment of Humanities: Spotlight on Humanities in Higher Education; Humanities Connections; Summer Stipends

Energy looks to balance AI electricity demands and clean energy goals: Energy consumption for artificial intelligence technologies is a “critical” emerging mission area for the Department of Energy as the agency looks to advance the benefits of AI and machine learning systems while minimizing the technologies’ carbon footprint.  Speaking at an Axios forum on Tuesday, Helena Fu, the director of the Office of Critical and Emerging Technologies at Energy, said that her agency sees automated systems’ burgeoning demand on the power grid as a way to usher in more clean firm power — clean energy solutions that are not dependent on weather as solar and wind are — with help from industry partners. Fu said that through various internal initiatives — namely the Frontiers in Artificial Intelligence for Science, Security and Technology program — her agency is looking to address the energy challenges posed by AI-enabled computing. She noted that, apart from AI, other digital services coming online and more manufacturing work based in the U.S. are also two leading burdens on U.S. power sources. More information is posted on the NextGov website.

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Los Alamos charts a new path on AI research with Venado launch: Researchers at the Los Alamos National Laboratory are poised to leverage new artificial intelligence technologies across scientific domains that impact national security research through the deployment of internal large language models and sophisticated data processors, a preview for the future of research in state-run laboratories.  In an exclusive interview with Nextgov/FCW, staff from Los Alamos discussed the laboratory’s future incorporating AI analyses into aspects of its scientific research process, from subjects like climate change to molecular dynamics.  This initiative began with the April installation of a new supercomputer from NVIDIA and Hewlett-Packard Enterprises. The machine, Venado, is the latest hardware installation in LANL’s computing portfolio and marks a new chapter for the lab: introducing AI-powered computation into scientific modeling and simulation.  Central to the new system is NVIDIA’s proprietary Grace Hopper computer processing chips and associated hardware. More information is posted on the NextGov website.

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Senators seek to advance AI capabilities at national labs: Two senators are working to usher more artificial intelligence systems and technologies into the U.S. national laboratory network through new legislation introduced last week. Sens. Joe Manchin, I-WV, and Lisa Murkowski, R-AK, introduced the Department of Energy AI Act to expand AI computing capabilities across the 17 national laboratories, with a focus on deploying frontier — or leading-edge — AI models to help researchers visualize the myriad, and often classified, datasets in multiple scientific domains. One key component of the bill authorizes the Frontiers in Artificial Intelligence for Science, Security, and Technology, an internal initiative within Energy that unlocks funding to bring AI capabilities into multiple department domains. Authorizing this program would let Energy further develop its workforce, data and computing capabilities, and expand its Exascale Computing Project partnerships with industry entities. The bill authorizes $12 billion in spending over five years to launch the FASST program. More information is posted on the NextGov website.