The Center for Advancing Human-Machine Partnership

Category: News

CAHMP Summer 2025 GRA Fellowship Now Open for Applications

Call for Applications: CAHMP Summer 2025 GRA Fellowship   

We are inviting applications for a limited number of summer GRAs from Mason doctoral students who do not already have Mason summer funding. If accepted, each awardee will receive a stipend of $9,000 this summer. Applying students should provide a short summary of what project they will be working on over the summer. While we will consider all projects concerning human-machine partnerships, special consideration will be given to transdisciplinary projects centering around CAHMP thematic thrusts: 

  • Fairness, Accountability, Transparency, Inclusion, and Equity in AI 
  • AI Policy and Governance  
  • Human-Computer Interaction (human-machine teaming) 
  • Assistive Technology  
  • Learning Technology 
  • Community Informatics  
  • Generative AI and applications 

 (including AR/VR, computer vision, wearable tech, robotics, cyber, data science, digital humanities, etc.) 

Recipients of this summer funding may be invited to present their projects at a CAHMP social event during the next academic year. 

Application Instructions:  

Applicants, please submit the following here – https://forms.office.com by 11:59pm Thursday, March 27th, 2025:

  1. A project title and a 250-word proposal that describes your project.
  2. A CV.
  3. One of the faculty mentors must be a CAHMP faculty member. Applicants are encouraged to have more than one mentor from different departments. 
Eligibility requirements:  

–Applicants must be Mason doctoral students listed in university records as full-time during Spring 2025 and must plan to return as a doctoral student in Fall 2025.  

–GPA 3.0 and good standing  

–Receive no other funding from Mason over the summer. Faculty mentors will be asked to provide confirmation that the applicant has no other funding at Mason over the summer.  

–This fellowship is more for doctoral students who are well on their way in their degree completion.

  

AI and Data-Driven Decision-Making for Education Policy and Equity: Convening at George Mason University Highlights Key Insights for School Leaders


Fairfax, VA – George Mason is bridging research and practice on AI for education. On October 8, 2024, leading educators, policymakers, and AI experts gathered at George Mason University for the “AI and Data-Driven Decision-Making for Education Policy and Equity” convening. The event, held at Merten Hall on GMU’s Fairfax campus, focused on the rapidly growing role of AI in education and its potential to reshape school systems, streamline administrative tasks, promote data-driven decision-making, and prepare teachers and students for an AI-enabled learning environments.

At 9am, the fully packed Merten Hall Room 1201 was welcomed by Mason’s professor of education, Anne Holton, who together with Dean of College of Education and Human Development, Ingrid Guerra- López, and Mason’s inaugural Chief AI Officer, Amarda Shehu, opened up the event with inspiring open remarks. The event followed with a wide range of expert presentations and panel discussions. Roberto J. Rodriguez, Assistant Secretary for the Office of Policy Planning and Development at the U.S. Department of Education, provided insights on how federal education policy is responding to the rise of AI. David Myers, Deputy Superintendent and CIO of the Virginia Department of Education, shared their perspectives on how AI can be responsibly implemented to address specific challenges in education.

Throughout the day, panelists and experts provided key insights for school and district leaders, underscoring the importance of thoughtful AI integration. School leaders are increasingly adopting AI tools to reduce administrative burdens and enhance classroom efficiency. However, speakers cautioned that the implementation of these tools must prioritize student privacy and compliance with existing data governance policies, such as FERPA. Districts were encouraged to evaluate their current data infrastructure, ensure that AI tools are compatible with privacy regulations, and carefully pilot these technologies before implementing them on a larger scale.

The event also highlighted the importance of providing teachers with professional development to navigate the integration of AI in their work. This includes training on the safety and privacy aspects of AI tools, particularly when compared to widely available, free alternatives, and on how AI can be used to enhance teaching and learning. GMU faculty showcased promising research on the ways AI can enrich classrooms, such as generating differentiated learning materials and serving as virtual collaborators for students in subjects like mathematics. Still, attendees were reminded that while AI offers exciting opportunities, its integration must be done thoughtfully to avoid unintended consequences, particularly with regard to data privacy and educational equity.

One of the key concerns discussed was the potential for AI algorithms to perpetuate societal biases present in the data they are trained on. Several experts stressed that AI literacy curricula must address these limitations, ensuring that both students and teachers are aware of the challenges associated with AI-generated materials, including biased content and harmful stereotypes. This is a crucial aspect of preparing students to critically engage with AI, rather than accepting its outputs at face value.

Participants explored case studies where AI is already being used to solve problems in school systems, such as improving transportation logistics and enhancing lesson planning. The event concluded with a discussion on fostering collaboration between school districts and researchers, encouraging knowledge sharing and the development of AI strategies that can be scaled across different educational contexts. As a result of this convening, a community of practice will carry out the much-needed ongoing conversations.

The convening, organized by the AI and Data-Informed Education Policy Initiative (AIEP) at George Mason University, exemplified the university’s commitment to transdisciplinary collaboration and evidence-based policy development. AIEP, in partnership with EdPolicyForward and the Center for Advancing Human-Machine Partnership (CAHMP), leverages AI and advanced data analytics to address pressing challenges in education policy and equity.

CAHMP Summer Doctoral GRA Research Presentation

 

 

Time: 1-3pm, Monday, 9/9

Zoom: https://gmu.zoom.us/j/94054653093

Presentation Details: Each student has up to 8 minutes to present their summer research project. A 2-minute Q&A and feedback session can follow each presentation.

Name Area of Study Presentation Title
1 1:10 1:20 Chahat Raj Computer Science Social Prejudice in Multimodal Generative AI through Visual Question Answering
2 1:20 1:30 Neelam Shukla Public Policy AI and the Future of Taxation
3 1:30 1:40 Liuchuan Yu Computer Science A Collaborative Construction Platform in Virtual Reality
4 1:40 1:50 Minyoung Kim Computer Science A Multimodal Framework for Synthesizing Interactive and Adaptive Narratives in Augmented Reality
5 1:50 2:00 Hao Yan Computer Science Can Code LLMs Be Easily Exploited to Produce Vulnerable Code?
6 2:00 2:10 Irene Feng Human Factors and Applied Cognition Ethical vs. Unethical AI Advisors
7 2:10 2:20 Fairuz Nawer Meem Computer and Information Science Underlying motivations for the adoption of ChatGPT in Software Development tasks
8 2:20 2:30 Gaurab Pokharel Computer Science EvoFair: Navigating the Dynamics of Fairness Evolution
9 2:30 2:40 Md Shafkat R Farabi Computer Science Modelling Fair Assignment of Mediators in Kenya using Multi Armed Bandits
10 2:40 2:50 Vasilii Nosov Public Policy Quality of Regulation and the AI Infrastructure  Depth

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Podcast: LLMs, Learning, and the Law: Navigating the Opportunities and Challenges of AI in Education

2024 Transdisciplinary Center Summer GRA Fellowship now Open for Application

Call for Applications: CAHMP Summer 2024 GRA Fellowship   

We are inviting applications for summer research assistance funding from Mason Master’s and doctoral students who do not already have Mason summer funding. If accepted, each awardee will receive a stipend of $6,500 (Master’s) or $8,500 (Doctor’s). Applying students should provide a short summary of what project they will be working on over the summer. While we will consider all projects concerning human-machine partnerships, special consideration will be given to transdisciplinary projects centering around CAHMP thematic thrusts: 

  • Fairness, Accountability, Transparency, Inclusion, and Equity in AI 
  • AI Policy and Governance  
  • Human-Computer Interaction (human-machine teaming) 
  • Assistive Technology  
  • Learning Technology 
  • Community Informatics  
  • Generative AI and applications 

 (including AR/VR, computer vision, wearable tech, robotics, cyber, data science, digital humanities, etc.) 

Recipients of this summer funding may be invited to present their projects at a CAHMP social event during the next academic year. 

Application Instructions:  

Applicants, please submit the following here – https://forms.office.com/r/QQKJVUR4hx by April 14th, 2024:

  1. A project title and a 250-word proposal that describes your project; 
  2. The student’s level of study (Masters of doctoral), home department, and faculty mentor(s), one of whom must be a CAHMP core or affiliate faculty member; 
  3. A CV. 

Mentors, please provide your quick endorsement here – https://forms.office.com/r/RTiRimH1k3 by April 14th, 2024. The endorsers must confirm that there are no alternative means of supporting the applicant over the summer.  

Eligibility requirements:  

–Applicants must be Mason students listed in university records as full-time during Spring 2024 and must plan to return as a graduate student in Fall 2024.  

–GPA 3.0 and good standing  

–Receive no other funding from Mason over the summer  

–We will give preference to new applicants who have not received previous CAHMP GRA support.  

  

 

CAHMP Receives Funds for Collaborative Research in Ed Policy and Artificial Intelligence

Pictured above are the research team with FCPS Superintendent, Michelle Reid and FCPS CIO, Gautam Sethi. (From left to right, Michelle Reid, Anne Holton, Sanmay Das, Peng Warweg, Seth Hunter, and Gautam Sethi)

 

Two centers at George Mason University—EdPolicyForward in the College of Education and Human Development and the Center for Advancing Human Machine Partnership (CAHMP), a transdisciplinary research center—will collaborate on a project that aims to better connect research to practice in education policymaking, and support school divisions in improving student and teacher performance and enhancing the effectiveness and fairness of resource allocation through data-driven decision making.

The collaboration is supported by a generous gift from the William and Flora Hewlett Foundation is a nonpartisan, private charitable foundation that advances ideas and supports institutions to promote a better world. The collaboration between EdPolicyForward and CAHMP manifests the power and opportunities that transdisciplinary research can bring to Mason’s research and practice community.

The Education Program at Hewlett Foundation makes grants to help educators, schools and communities turn schools into places that empower and equip students for a lifetime of learning and to reach their full potential.

The core Mason project team includes Sanmay Das, professor of computer science and co-director of CAHMP; Anne Holton, professor of public policy and education; Seth B. Hunter, assistant professor of education leadership; David Houston, director of EdPolicyForward and assistant professor of education; and Peng Warweg, assistant director of CAHMP.

The project will leverage the core team’s expertise in education policy research, artificial intelligence, and advanced data analytics, as well as partnerships with local school divisions, to better connect research to practice, with the goal of helping all students succeed through efficient, effective, and equitable use and distribution of school resources.

Over the next 16 months, the team will deliver a series of policy briefs to communicate relevant research findings to state and local leaders on matters of importance to their decision-making, creating a two-way dialogue between researchers and policymakers, and a dissemination strategy to inform the policymaking decisions of local, state, and national audiences.

The project is also expected to enhance the capacity for data-driven decision-making in school divisions, especially in the use of methods from artificial intelligence (AI) and advanced data analytics to support and enhance equity in access to programs that benefit student outcomes and improve student and teacher performance.

EdPolicyForward, the Center for Education Policy, promotes equity and improved educational outcomes for all students, from preschool through college and beyond. The center connects research to policy and practice, develops and advances effective and pragmatic solutions, and drives meaningful public discourse addressing persistent inequalities in U.S. public education.

Founded in 2019, the transdisciplinary CAHMP facilitates research, teaching, and innovation in understanding and leveraging human-machine partnership to solve current and emerging societal problems. CAHMP’s network of researchers work on cross-disciplinary topics, such as responsible AI, learning technology, education policy and analytics, and generative AI for education.

2023 AI and Tech Policy Summer Institute Opening Reception

 

 

AI Strategies 5-22 Panel - Twitter Graphic 230510

2023 CAHMP Mini Seed Funding

Overview and Purpose

The purpose of this mini seed funding is to enable pilot research that will lead to submissions to externally funded research programs in the broad area of “human machine partnership.” We seek to identify and support interdisciplinary teams planning to pursue novel convergent research. The seed grant can support new or existing teams to perform activities, such as faculty effort, preliminary research, team building, and project scoping, that are necessary to enable the submission of a competitive larger proposal in the future. Funded projects should lead directly to an external proposal submission as a next step.

Investigator Specification

Proposals should come from teams of at least two investigators from at least two different departments or disciplines. CAHMP Affiliate members must collaborate with a Core member to submit an application. In addition to listing the investigators, proposals should identify additional faculty members, disciplines, or external partners, if applicable, that the team will engage during the seed grant period.

Activities Eligible for Support

The mini seed grants aim to support a range of planning activities intended to foster a convergent research team that can effectively integrate multiple disciplinary perspectives, explore the research theme in depth, build collaborations with relevant stakeholders, and hone specification of research gaps, questions, and hypotheses. Activities within scope include, but are not limited to, workshops, stakeholder meetings, literature reviews, data collection, preliminary experiments, prototypes, and pilots. In all cases, the proposed activities should be designed as a step along the path to a future external grant.

Budget Guidelines

Teams should propose a budget commensurate with the scope of their proposed activities and their intended next steps. The maximum allowable budget for a proposal is $20,000. The total requested amount, as well as the individual line items, should be clearly justified in the budget section of the proposal.

Eligible budget categories include faculty time (summer salary and/or AY course buyout), student assistantships and/or wages, travel (for team building), equipment, materials & supplies, and participant support costs. There is no need to budget indirect costs.

Funds will be transferred to the PI’s home department. Unspent funds must be transferred back to CAHMP within 45 days of the project’s end date. Project periods should end before June 30, 2024.

Proposal Content

Proposals should be no more than three (3) single-spaced pages (please use the template provided attached), using Times New Roman 12-point font. Proposals should address the following topics:

  • Definition of the research theme/area and motivation for its importance
  • History and current status of the research theme (literature/conceptual review)
  • Vision for development of the research theme
  • Qualifications of the interdisciplinary team
  • Specific external grant objective and target source
  • Timeline (projects should not extend past June 30, 2024.)
  • Budget and budget justification

Review Criteria

  • Strength and potential of the interdisciplinary team
  • Importance and potential of the research theme
  • Opportunity for the team to create a distinct and compelling research niche
  • Clarity and feasibility of the plan to achieve external funding
  • Overall potential return on investment
  • Relevance of the theme to the vision and interests of CAHMP and Mason

Submission Process

Email a PDF copy of your submission to Peng Warweg at [email protected] by 5:00 p.m. EDT on Wednesday, May 31, 2023.

Proposals will be reviewed, and funding decisions will be made by the CAHMP leadership team and external advisors by no later than June 30, 2023 (earlier if possible).

2023 CAHMP Spring Mini-symposium

 

Please mark your calendar and come to join our 2023 spring mini-symposium next Wednesday (4/19) at 1-3pm. We have lined up four exciting talks by three new CAHMP members, Jonathan Auerbach, Erion Plaku, and Xiaokuan Zhang, as well as Matthew Steinberg, Director of EdPolicyForward here at Mason. Please check out their abstracts below. The symposium will end with a panel joined by all four speakers and moderated by CAHMP co-director, Sanmay Das.

Time: 4/19/23 Wednesday, 1-3pm

In-person Location: Research Hall 440A. Light refreshments will be served.

For online participants – Please contact Peng Warweg for joining information.

 

Speaker: Jonathan Auerbach, Assistant Professor, Department of Statistics, George Mason University 

Topic: Computer-Assisted Selection of Board Members to Improve Equity and Inclusion 

Abstract: From local governments to international corporations, there has been increased demand for diverse governing boards. In many cases, the number of members who identify as women and people of color have increased substantially. But diverse membership does not automatically mean inclusive or equitable participation. Members can be excluded from the conversation by procedures that favor the majority group or behaviors such as interruptions, bullying, and discriminatory harassment. 

In this presentation, we propose a methodology that models the interactions among board members. The model can be used to assess barriers to participation among current members and select new members to promote inclusion and equity. We demonstrate the proposed approach using more than twenty-four hours of video footage from meetings of Manhattan’s Community Boards in addition to an extensive follow-up survey. We find a large gap between nominal representation on boards and actual representation in terms of participation in activities (e.g., speaking time at meetings). We then show how a more thoughtful selection of board members can greatly reduce this gap. 

This is joint work with Catherine DeLazzero and Ashley Maria Garcia-Parra (Columbia University) and Eric Auerbach and Sidonia McKenzie (Northwestern University). 

 

Speaker: Erion Plaku, Associate Professor, Department of Computer Science, George Mason University 

Topic: Toward Supervised Autonomy: Enhancing Automation and Human-Robot Collaboration 

Abstract: Advances in AI and robotics are giving rise to systems that can see, hear, communicate, act, and learn, seeking to extend and enhance every aspect of human life.  This progress has been driven by the pursuit of fundamental questions that continue to drive much of our research: how do you enhance the autonomy and capability of robots to work alongside and collaborate with humans? Toward this goal, my group’s research brings together concepts from AI, robot motion planning, and logic, to develop planning frameworks that enable human supervisors to describe tasks in high-level structured languages and have the framework automatically plan actions and motions for robots to safely and effectively complete assigned tasks.  This line of research has the potential to establish a novel paradigm for supervised autonomy that increases productivity and capabilities. Applications in marine robotics will be highlighted. Finally, I will discuss emerging challenges and opportunities, as well as share my vision of the way forward. 

 

Speaker: Xiaokuan Zhang, Assistant Professor, Department of Computer Science, George Mason University 

Topic: Security and Privacy Concerns in Computer Systems: Exploring the Human Connection 

Abstract: Computer systems have been rapidly evolving over the past several decades, with the emergence of new technologies such as smartphones and blockchains transforming the way humans interact with these systems. Since computer systems often need to process, transmit and store sensitive user data, it is crucial to ensure the security and privacy of such systems. However, these challenges are not solely technical, but are also impacted by human factors. This talk will delve into the security and privacy concerns in computer systems, and how human behavior and decision-making can affect these issues. The presentation will begin with an exploration of side-channel attacks, which can reveal otherwise protected information from computer systems by observing traces (e.g., timing, power, or resource usage). It will then move on to examine security issues in two emerging platforms, blockchain Decentralized Finance (DeFi) and virtual reality systems, while considering the impact of human factors on their security. The talk aims to highlight the importance of considering human behavior and decision-making in the development of secure computer systems. 

 

Speaker: Matthew Steinberg, Associate Professor of Education and Public Policy, George Mason University 

Topic: Ed Policy at Mason 

Abstract: Dr. Steinberg, Director of EdPolicyForward: The Center for Education Policy at George Mason University, will provide a high-level discussion of the Education Policy program at George Mason University and an overview of his education policy research projects. A few recent research projects will be highlighted, including: (a) What explains the race gap in teacher performance ratings? Evidence from Chicago Public Schools; (b) The effects of closing urban schools on students’ academic and behavioral outcomes: Evidence from Philadelphia; (c) Fiscal federalism and K–12 education funding: Policy lessons from two educational crises; and (d) Do suspensions affect student outcomes? 

CAHMP HCI Group Meeting – December 8, 2022

 

The Center for Advancing Human-Machine Partnerships (CAHMP) held a HCI group meeting on December 8th, 22. About a dozen participants from CEC and CHSS joined this hybrid (on-line and in-person) meeting. This event was a follow-up on the June HCI workshop, which signaled the beginning of a new stage in interdisciplinary research and community building around HCI at Mason.  The HCI group is one of several community-building initiatives at CAHMP to foster faculty collaborations and meaningful outreaches with industry partners.

At this meeting, two Army Research Laboratory (ARL) HCI researchers, Dr. Alfred Yu and Dr. Katherine Cox, joined the group online and debriefed on ARL’s recent HCI related initiatives, including the Cross-Mission Team Evolution (CMTE) Research Thrust within the ARL Human Autonomy Teaming Essential Research Program (HAT ERP) which is developing capabilities to improve Soldier-system team performance in missions through adaptation and learning via after-action review and mission planning. Many other ARL research focuses, including the development of wearables for real-world assessment of warfighter performance, data mining of large behavioral datasets to understand real-world visual search, augmented perception in extended reality, and computational modeling of the biophysical mechanisms of neurostimulation, find overlaps with the current research and work by CAHMP faculty members.

The meeting wrapped up with a plan to continue engage ARL for future collaborations. Participants also exchanged some insightful thoughts on upcoming HCI funding opportunities.