The Translational Data Analytics Institute's 2024 Fall Forum brought together researchers, students, staff and more to discuss interdisciplinary, data-enabled research around the topic AI, Policy, People, and Society. Details about featured sessions are below, and you can click here for a recap including poster session and flash talk winners.
Shown above: Dr. Elham Tabassi delivers the opening keynote talk at the 2024 Fall Forum
Thursday, November 7
9:00-9:15 AM: Welcome
Dr. Tanya Berger-Wolf
Faculty Director, Translational Data Analytics Institute
Professor of Computer Science Engineering; Electrical and Computer Engineering; and Evolution, Ecology, and Organismal Biology
The Ohio State University
Dr. Cathie Smith
Managing Director, Translational Data Analytics Institute
The Ohio State University
9:15-10:15 AM: KEYNOTE SPEAKER
Elham Tabassi, Chief AI Advisor at NIST, Associate Director for Emerging Technologies Information Technology Laboratory, National Institute of Standards & Technology
In addition to serving as NIST Chief AI Advisor and Associate Director for Emerging Technologies in NIST’s Information Technology Laboratory (ITL), Elham Tabassi leads NIST’s Trustworthy and Responsible AI program that aims to cultivate trust in the design, development, and use of AI technologies by improving measurement science, standards, and related tools in ways that enhance economic security and improve quality of life.
She has been working on various machine learning and computer vision research projects with applications in biometrics evaluation and standards since she joined NIST in 1999. Tabassi is the principal architect of NIST Fingerprint Image Quality (NFIQ), an international standard for measuring fingerprint image quality which has been deployed in many large-scale biometric applications worldwide. Among her other roles at NIST, Tabassi has served as ITL Chief of Staff.
She is a member of the National AI Resource Research Task Force, the US Government’s AI Standards Coordinator, a senior member of IEEE, and a fellow of Washington Academy of Sciences. In September 2023, Tabassi was named by TIME magazine as one of the "100 Most Influential People in AI."
10:15-10:30 AM: Break
10:30-11:15 AM: Panel Discussion
To NIST and Back: Connecting TDAI Responsible Data Science Expertise to National AI Safety Priorities
301 Pomerene Hall
Panelists:
Mike Rayo
Associate Professor, Integrated Systems Engineering, The Ohio State University
Esra Gules-Guctas
Assistant Professor, John Glenn College of Public Affairs, The Ohio State University
David Landsbergen
Associated Professor, John Glenn College of Public Affairs, The Ohio State University
Huan Sun
Associated Professor, Computer Science and Engineering, The Ohio State University
Summary:
The Ohio State University’s representatives on the National Institute of Standards and Technology (NIST) AI Safety Institute (AISI) Consortium will introduce themselves and their role on the AISIC. We will discuss the current mission of the AISIC, the AISI, and the current structure. We will then share how we are utilizing our shared expertise, but also serving as a conduit to our OSU communities, including the TDAI Responsible Data Science (RDS) Community of Practice (CoP). We will share the results of a recent RDS CoP survey probing our community on their current work and how they are thinking about responsible data science.
11:15-11:30 AM: Break
11:30 AM-12:30 PM: Dr. Ayanna Howard, Dean of Engineering
Are We Trusting Our Systems Too Much? Hacking the Human Bias in AI
301 Pomerene Hall
12:30 PM - 2:00 PM: Poster Presentations & Research Partner Table Session & Year-long Themes Proposal Poster Presentations
320 Pomerene Hall
Students and postdocs will present posters, while representatives from researcher resources at Ohio State and beyond will be available to discuss offerings and opportunities.
2:00-3:20 PM: Panel Discussion
Analyzing the Impact of the 2024 US General Election: A Multidisciplinary Panel Discussion
350 Pomerene Hall
Organizers:
Robert Bond
Associate Professor, Communications, The Ohio State University
William Minozzi
Professor, Political Science, The Ohio State University
Speakers:
Eric Schoon
Associate Professor, Sociology, The Ohio State University
Ryan Kennedy
Professor, Political Science, The Ohio State University
Brian Weeks
Associate Professor, Communication and Media, College of Literature, Science, and the Arts, University of Michigan
Abstract:
The 2024 U.S. general election will be held on November 5th, just two days before the Fall Forum begins. The election marks a pivotal moment in American political history, with far-reaching implications for domestic and global policy. This panel discussion will bring together experts from Political Science, Sociology, Psychology, and Communication to discuss the election's outcomes and their impact on various facets of society. We will explore key issues such as voter behavior, the influence of social media, economic implications, and shifts in domestic and foreign policy. Our interdisciplinary approach aims to provide a comprehensive understanding how data informs scholars and the public about the election's consequences, fostering a dialogue that bridges academic research and public discourse. By examining the intersection of these diverse fields from a data science perspective, this session will offer valuable insights into the dynamics of contemporary electoral politics and its broader societal implications. Attendees will gain a nuanced perspective on the election's significance, informed by empirical research and expert analysis. This panel is particularly relevant for those interested in the interplay between politics, society, and the economy in a rapidly evolving global landscape.
3:20-3:35 PM: Break
2:00-3:20 PM: Panel Discussion
Beyond Bias: Lesser-discussed aspects of AI injustice
301 Pomerene Hall
Organizer:
Esra Gules-Guctas
Assistant Professor, John Glenn College of Public Affairs, The Ohio State University
TDAI Core Faculty
Moderator:
Megan LePere-Schloop
Associate Professor, John Glenn College of Public Affairs, The Ohio State University
Speakers:
Kevin De Liban
Founder, TechTonic Justice
Michele Gilman
Venable Professor of Law, School of Law, University of Baltimore
Abstract:
As AI technologies increasingly permeate every aspect of our lives, they are not only changing the way we live but also how we understand our justice problems. This workshop will explore the complex justice issues presented by artificial intelligence that extend beyond the common focus on bias. Participants will explore case studies highlighting lesser-discussed aspects of AI injustice and the challenges of ensuring accountability in opaque algorithmic decision-making processes. The session aims to equip attendees with a broader perspective of AI's impact on society through interactive discussions, collaborative problem-solving and facilitated discussion on developing effective advocacy strategies and policy recommendations.
3:35-5:00 PM: Panel Discussion
AI and Work: Productivity, Adoption, and Displacement
350 Pomerene Hall
Organizers and Speakers:
Andrea Contigiani
Assistant Professor, Fisher College of Business, The Ohio State University
Hun Whee Lee
Associate Professor, Fisher College of Business, The Ohio State University
Xin Wen
PhD Candidate, Fisher College of Business, The Ohio State University
Speakers:
Rajeev Chhajer
Chief Engineer/Research Domain Leaders - Software-defined Intelligence, Honda Research Institute USA, Inc
Mimi Chizever
Vice President, Technology Innovation and Organizational Strategy, Nationwide
Dee Pai
Managing Director, CCB Chief Data Scientists, Chase
Abstract:
This panel explores how AI is fundamentally reshaping work. In the first section, we present research from management and related areas, shedding light on how AI is transforming three central aspects of the workplace: performance, adoption, and displacement. We start by discussing the impact of AI on productivity. We explore whether and how AI can support humans in creative tasks, throughout the entire spectrum of knowledge production, from creation, to synthesis, evaluation, and translation. We then move on to discussing adoption of AI. We explore the traits of employees who embrace AI and the consequent dynamics of AI communication. We present evidence on the factors influencing AI adoption and how individuals convey their AI usage. Finally, we discuss the effect of AI on displacement. We explore avenues to foster employee upskilling, improve the working environment, and develop leadership ensuring psychological safety, resilience, and trust in this new workplace. In the second section, in the interdisciplinary nature of the event, a group of industry practitioners with expertise on AI and work will share their perspective on these topics, contextualizing and interpreting the research presented. The ultimate goal of the event is to collectively generate a series of open questions for future interdisciplinary research.
3:35-5:00 PM: Panel Discussion
AI Governance on the Ground: What We Know
301 Pomerene Hall
Organizers:
Dennis Hirsch
Professor, Data and Governance, College of Law | Computer Science & Engineering, College of Engineering, The Ohio State University
TDAI Core Faculty
Angie Westover-Muñoz
Program Manager, Data and Governance
Speakers:
Shontael Starry
Lead Statistical Modeling and AI/ML Ethicist, Nationwide
Matthew Reisman
Director, Privacy and Data Policy, Centre for Information Policy Leadership (CIPL)
Müge Fazlioglu
Principal Researcher, Privacy Law and Policy, International Association of Privacy Professionals
Abstract:
Governments, academics, advocates and others call for more and better governance AI. But what, specifically, is "better governance"? What management and technical measures should we push for and the law require? One step towards an answer is to study and understand how organizations are governing AI today. Current practice is not necessarily best practice. But it does provide a baseline that academics and policymakers can evaluate and, perhaps, draw on, in their search for better governance. This panel will bring together the scholars and civil society members who have conducted the leading empirical work on AI governance, including a team from OSU/TDAI itself. The panel will explain what we know about AI governance today, and will identify important questions for future research on AI governance.
5:00-7:00 PM: Networking Reception & Year-long Themes Proposal Poster Presentations
Friday, November 8
8:30-9:00 AM: Light breakfast
320 Pomerene Hall
9:00-9:15 AM: Dr. Peter Mohler, Vice President for the Enterprise for Research, Innovation & Knowledge (ERIK)
301 Pomerene Hall
9:15-10:35 AM: Panel Discussion
Trustworthy Model Compression
301 Pomerene Hall
Organizer:
Mahdi Khalili
Assistant Professor, Computer Science & Engineering, The Ohio State University
TDAI Core Faculty
Speakers:
Ferdinando Fioretto
Assistant Professor, Computer Science, University of Virginia
Wujie Wen
Associate Professor, Computer Science, North Carolina State University
Zhiqun Zuo
PhD Candidate, Computer Science and Engineering, The Ohio State University
Abstract:
Large-scale machine learning (ML) models are increasingly being used in critical domains like education, lending, recruitment, healthcare, criminal justice, etc. However, the training, deployment, and utilization of these models demand substantial computational resources, such as Graphics Processing Units (GPUs) along with access to large-scale datasets which are not universally available. Therefore, it is important to reduce the computational and memory costs associated with large machine-learning models. While several model compression techniques have been proposed to reduce memory and computation costs, these techniques generally come with certain side effects on the model's trustworthiness including fairness and robustness. This workshop aims to bring together researchers and practitioners to discuss the recent advances and challenges in developing efficient and trustworthy machine learning models for real-world applications. We will explore novel techniques for model compression, acceleration, and hardware-aware neural network design, with a focus on mitigating the trade-offs between efficiency, fairness, and robustness.
10:35-10:50 AM: Break
9:15-10:35 AM: Panel Discussion
AI in Digital Health: Challenges and Opportunities in AI Policy and Patience Preferences
350 Pomerene Hall
Organizer:
Lang Li
Professor and Chair, Biomedical Informatics, The Ohio State University
Speakers:
Courtney Hebert
Associate Professor, Biomedical Informatics, College of Medicine | Attending Physician, Internal Medicine, Infectious Diseases, The Ohio State University
Andrew Hampton
Senior Licensing Officer, AI, ML and Digital Health, Office of Innovation and Economic Development, The Ohio State University
John F. P. Bridges
Professor, Biomedical Informatics, Surgery, The Ohio State University
Abstract:
In this session, we will focus on the AI policy and patient preference when AI technology is developed and implemented in biomedical research and patient care. Recent advancement in AI has led to a great number of innovations in digital health. It also brings many challenges and opportunities. For examples, do we worry about patient privacy when we use generative AI technology, such as large language models, in processing and share patient data? How do we test and validate machine learning based predictive analytic models across multiple health institutes, if individual patient data cannot be shared? How do patients feel if their electronic health record data are integrated and linked for AI model development? In this session, we have three wonderful speakers who will talk on the following topics: (1) AI model and device test and implementation policy in OSU Medical Center (Hebert); (2) Patient acceptability of linking multiple data sources for suicide risk machine learning models in a large health system (Bridges); (3) FDA regulatory pathway for AI/ML medical devices (Hampton)
10:50 AM-12:10 PM: Panel Discussion
AI-enabled mechanistic modeling based on novel sensing and surveillance data for pandemic prevention and preparedness
350 Pomerene Hall
Organizers:
Michael Oglesbee
Director, Infectious Diseases Institute | Professor, College of Veterinary Medicine, The Ohio State University
Vanessa Varaljay
Chief Research Officer, Infectious Diseases Institute
Speakers:
Andrew Bowman
Professor, College of Veterinary Medicine, The Ohio State University
Courtney Herbert
Associate Professor, Biomedical Informatics, College of Medicine | Attending Physician, Internal Medicine, Infectious Diseases, The Ohio State University
Jiyoung Lee
Professor, Environmental Health Sciences, College of Public Health, The Ohio State University
Ellie Graeden
Research Professor, Center for Global Health Science and Security, Georgetown University
Eben Kenah
Associate Professor, Biostatistics, College of Public Health, The Ohio State University
Srinivasan Parthasarathy
Professor, Computer Science & Engineering, Biomedical Informatics, College of Engineering, The Ohio State University
Abstract:
We envision a novel approach to prevention of pandemics caused by emerging viral pathogens. The approach is based upon a framework of AI-enabled mechanistic modeling of spillover and transmission risk grounded in comprehensive and novel sensing platforms and surveillance data. Risk assessments can then trigger responses that prevent outbreaks or prevent outbreaks from progressing to pandemics. The discussion will focus on validated mechanistic models for influenza viruses and coronaviruses, recognizing their continued high potential for spillover from animal reservoirs to drive pandemics. Goals of the discussion are to define how to develop data ingest and model runs that are tiered temporally, with initial emphasis on environmental surveillance data and subsequent incorporation of both human and animal data sources and iterative modeling cycles as risk increases. The discuss will further define composition of a broadly interdisciplinary team, and how data can be integrated in a shared ontology to feed into both machine learning and mechanistic models working synergistically in a feedback loop, with machine learning models used to test and scale hypotheses established through iterative cycles of mechanistic models that, in turn will be used to validate outputs of machine learning. The design should be such that modeling outcomes define/affirm essential data sources, collection, and types. The ultimate goal is to establish an approach in which results can be communicated to policy makers and public health implementers at the federal, state, local, and tribal levels through user-tested decision support tools developed in close collaboration with both the modeling and practitioner communities.
10:50 AM-12:10 PM: Panel Discussion
Machine learning under strategic behavior and social dynamics
301 Pomerene Hall
Organizer:
Xueru Zhang
Assistant Professor, Computer Science & Engineering, The Ohio State University
Speakers:
Kun Zhang
Associate Professor, Philosophy, Carnegie Mellon University
Yuekai Sun
Associate Professor, Statistics, University of Michigan
Bingjie Liu
Associate Professor, School of Communications, The Ohio State University
Abstract:
In recent years, machine learning (ML) has been increasingly used in social domains to make decisions about humans. Examples include learning economic policies from data, recommending personalized items to users, ranking candidates for admission, hiring, and lending, etc. When ML is used in these tasks, humans, as strategic agents, often have various incentives to adapt their behaviors in response to the learning system. Learning in this context calls for a new vision for machine learning that aligns with the interests of social needs and is robust to strategic behavior and social dynamics.
The goal of this workshop is to address current challenges and opportunities that arise from interactions of learning systems with social and strategic human agents. We aim to bring together members of different communities, including machine learning, economics, and human-computer interactions, to share recent research outcomes, discuss important directions for future research, and foster collaborations.
1:00-1:30 PM: Researcher Flash Talks
301 Pomerene Hall
1:30-1:45 PM: Awards Ceremony for Student Posters and Flash Talks
301 Pomerene Hall
1:45-2:00 PM: Closing Remarks
301 Pomerene Hall
2:00 PM: The Investiture of President Walter "Ted" Carter Jr.
We will be streaming the Investiture in 301 Pomerene Hall