Building an Ethical and Trustworthy Biomedical AI Ecosystem for the Translational and Clinical Integration of Foundational Models
University of California, Los Angeles（加州大学洛杉矶分校）；European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI)（欧洲分子生物学实验室-欧洲生物信息研究所（EMBL-EBI））
Simha Sankar Baradwaj, Destiny Gilliland, Jack Rincon, Henning Hermjakob, Yu Yan, Irsyad Adam, Gwyneth Lemaster, Dean Wang, Karol Watson, Alex Bui, Wei Wang, Peipei Ping
Foundational Models (FMs) are gaining increasing attention in the biomedical AI ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders, especially those involved in or affected by these clinical and translational applications are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem.
Towards Trustworthy AI: A Review of Ethical and Robust Large Language Models
Canizaro Livingston Gulf States Center for Environmental Informatics, the University of New Orleans（新奥尔良大学）；Center for Geospatial Sciences, Naval Research Laboratory（海军研究实验室）；US Army Corps of Engineers, Engineer Research and Development Center（美国陆军工兵部工程师研究与发展中心）
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences
Colorado State University（科罗拉多州立大学）；Cooperative Institute for Research in the Atmosphere（大气研究合作研究所）；National Center for Atmospheric Research（美国国家大气研究中心）；University of Washington（华盛顿大学）
Trustworthy AI and Democracy: A Dual Taxonomy and Operational Framework of Democratic Risks and Contributions
Dept. of Computer Science and Artificial Intelligence, DaSCI, University of Granada, Spain（计算机科学与人工智能系，DaSCI，格拉纳达大学）；Dept. of Philosophy, University of Vienna, Vienna, Austria（哲学系，维也纳大学）；School of Engineering, Cornell University, Ithaca, NY, United States（工程学院，康奈尔大学）；Dept. of Mathematics, Khalifa University of Science and Technology, Abu Dhabi, UAE（数学系，科学与技术大学，阿布扎赫德，阿联酋）；ADIA Lab, Al Maryah Island, Abu Dhabi, UAE（ADIA实验室，阿布扎赫德，阿联酋）；Joint Research Centre, European Commission, Seville, Spain（联合研究中心，欧洲委员会，塞维利亚，西班牙）；Computer Engineering Dept., University of Alcalá, Alcalá de Henares, Spain（计算机工程系，阿尔卡拉大学）
A Framework for Responsible AI Systems: Building Societal Trust through Domain Definition, Trustworthy AI Design, Auditability, Accountability, and Governance
Deparment of Computer Science and Artificial Intelligence and Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada（计算机科学与人工智能系和安达卢西亚数据科学与计算智能研究所（DaSCI），格拉纳达大学）；TECNALIA (BRTA)（TECNALIA（BRTA））；University of the Basque Country (UPV/EHU)（巴斯克大学（UPV/EHU））；School of Engineering, Cornell University（工程学院，康奈尔大学）；ADIA Lab（ADIA实验室）；Computational Research Department, Lawrence Berkeley National Laboratory（计算研究部，劳伦斯伯克利国家实验室）；Intelligent Systems for Robotics and Automation Laboratory, Macau University of Science and Technology（机器人与自动化智能系统实验室，澳门科学技术大学）
Co-design for Trustworthy AI: An Interpretable and Explainable Tool for Type 2 Diabetes Prediction Using Genomic Polygenic Risk Scores
Seoul National University（首尔大学）；Illinois Institute of Technology（伊利诺伊理工学院）；Arcada University of Applied Sciences（阿尔卡达应用科学大学）；Myongji University（明知大学）；Z-inspection® Initiative（Z-inspection®倡议组织）；NYU Grossman School of Medicine（纽约大学格罗斯曼医学院）；Seoul National University School of Law（首尔大学法学院）；Soonchunhyang University Seoul Hospital（顺天乡大学首尔医院）；Østfold University College（厄斯特福尔大学学院）；Intel Corporation（英特尔公司）；Council of Europe（欧洲委员会）；Graduate School of Engineering Practice, Seoul National University（首尔大学工程实践研究生院）；L3S Research Center, Leibniz University of Hannover（汉诺威莱布尼茨大学L3S研究中心）
Trustworthy AI in practice: an analysis of practitioners' needs and challenges
University of Bari "A. Moro"（巴里大学）；Ser&Practices Srl（Ser&Practices有限公司）；Pontifical Catholic University of Rio de Janeiro (PUC-Rio)（里约热内卢天主教大学）；Scuola IMT Alti Studi Lucca（卢卡高等研究院）
ChatGPT: More than a Weapon of Mass Deception, Ethical challenges and responses from the Human-Centered Artificial Intelligence (HCAI) perspective
Institute of Data Science and Artificial Intelligence (DATAI), Universidad de Navarra（纳瓦拉大学数据科学与人工智能研究所）；Information Systems Department, University Center for Economic and Administrative Sciences (CUCEA), University of Guadalajara（瓜达拉哈拉大学经济与行政科学中心信息系统系）；Quantitative Methods Department, Universidad Pontificia Comillas（康普顿斯大学定量方法系）
Enhancing Clinical Decision-Making: Integrating Multi-Agent Systems with Ethical AI Governance
College of Computing（计算学院）；Georgia Institute of Technology（佐治亚理工学院）；University of Illinois（伊利诺伊大学）；Neuro Industry Research（神经产业研究）；Neuro Industry, Inc.（神经产业公司）
Synthesizing the Expert: A Validated Multimodal Dataset for Trustworthy AI-Assisted Swimming Coaching
Multimedia Interaction and Communication Lab（多媒体交互与通信实验室）；Wearables, Biosensing, and Biosignal Processing Research lab（可穿戴设备、生物传感与生物信号处理研究实验室）；Arab Academy for Science and Technology（阿拉伯科学与技术学院）；Department of Sports Training and Movement Sciences, Faculty of Sports Sciences（体育科学学院体育训练与运动科学系）；Alexandria University（亚历山大大学）
TrustFed: Enabling Trustworthy Medical AI under Data Privacy Constraints
Department of Applied Mechanics（应用力学系）；Indian Institute of Technology Delhi（印度理工学院德里）；Grainger College of Engineering（工程学院）；Nuclear, Plasma & Radiological Engineering Department（核物理与辐射工程系）；National Center for Supercomputing Applications（国家超级计算应用中心）；Yardi School of Artificial Intelligence (ScAI)（Yardi人工智能学院（ScAI））；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
