AI + Policy Research & Compliance Fellow

About FairwAI
FairwAI is building the AI bias detection and compliance platform that industries will rely on to ensure fairness in hospitality, and healthcare. We operate at the intersection of AI, policy, and accountability — backed by a team from MIT, CMU, Oxford, and Harvard. Our work blends rigorous research, thoughtful product development, and ethical innovation at global scale.

Team

Shaurjya Mandal – Head of Research, AI Systems; Clinical Innovation
Role: Shaurjya leads FairwAI's research function and the development of its AI methodology — including structured retrieval architectures, sentiment and bias detection systems, and validation frameworks for fairness in clinical and high-stakes AI environments. He ensures FairwAI's research meets the standards of peer-reviewed clinical AI while remaining accessible and useful in real-world deployment.

Bio: Shaurjya Mandal is a machine learning research scientist at Mass General Brigham and Harvard Medical School, where he develops and evaluates AI systems for clinical settings. His research sits at the intersection of responsible AI, healthcare equity, and applied machine learning — with published and applied work in algorithmic bias, fairness in clinical decision support, and AI safety for vulnerable populations. He holds an M.S. in Artificial Intelligence from Carnegie Mellon University, where he conducted research at the Robotics Institute on machine perception and learning systems. Prior to his work at Harvard, Shaurjya served as a research engineer at India's Defence Research and Development Organisation (DRDO) and contributed to AI policy and infrastructure projects across the MENA region, including the design of responsible AI deployment frameworks for healthcare and insurance systems in the United Arab Emirates. He is a Nucleate Pittsburgh fellow, a recognized convener in early-stage biotechnology and AI commercialization. At FairwAI, Shaurjya bridges frontier clinical AI research with practical, ethical deployment — ensuring that what we build for the most underserved populations is also held to the highest scientific standard

Mr. Dixon –Chief Strategist
Role: Visionary founder of FairwAI, Mr. Dixon leads overall strategy, mission alignment, institutional partnerships, and compliance innovation. He ensures the platform remains focused on real-world fairness, risk mitigation, and public accountability—rather than abstract DEI.
Bio:
Mr. Dixon is a serial founder, public interest technologist, and global strategist known for building impact ventures at the intersection of technology, governance, and equity. He is currently a strategic advisor at MIT, where he collaborates across departments such as the MIT Media Lab and Martin Trust Center. Mr. Dixon has served as a policy strategist to President John Mahama of Ghana, worked with the U.S. Department of Energy on distributed energy infrastructure, and led multi-million-dollar public-private partnerships with organizations like GE Healthcare, USAID, and UNICEF.
Mr. Dixon is the founder of SolarFi, a social enterprise that builds portable solar-powered infrastructure for clinics, schools, and underserved communities across Africa providing energy to over 600,000 people. Under his leadership, SolarFi was awarded major U.S. government contracts and featured by MIT and the UN. He has also advised on diplomatic and philanthropic partnerships.

FairwAI is Mr. Dixon’s most urgent venture yet. Inspired by lived experiences of racial bias and systemic discrimination in global travel, hiring, and healthcare systems, he founded FairwAI to reframe fairness as a compliance and safety issue, not a corporate DEI trend. Antonio brings a rare combination of field-tested grit, institutional access, tech, diplomacy, and global coalition to ensure accountability becomes enforceable.

Dr. John Cooley –
Role: Leads FairwAI’s technical architecture as advisor, AI compliance engine, and research partnerships.
Bio: Dr. John Cooley is a renowned technologist and serial entrepreneur who holds five degrees from MIT: B.S. in Electrical Engineering, B.S. in Physics, M.S. in Electrical Engineering, an Engineer’s Degree, and a Ph.D. in Electrical Engineering. He earned the David Adler Memorial Thesis Prize and the Morris Joseph Levin Award, recognizing his groundbreaking work in engineering and systems design. John was the CTO and later CEO of Nanoramic Laboratories, where he led the company to raise $44M+ in capital and developed cutting-edge battery and nanotechnology solutions. With 15+ years of experience at the frontier of hardware-software integration and AI systems, John brings a rare blend of research rigor and venture-scale execution. He now advises FairwAI on tech architecture, compliance logic, and academic research integration across MIT and international institutions.

Dr. Ryan Chin – Strategic Advisor, Urban Tech & Mobility Systems
Role: Ryan advises FairwAI on systems architecture, urban integration, and commercial strategy. He brings expertise in AI-driven mobility, sensor networks, and resilient infrastructure to inform how FairwAI scales across physical environments like hotels, hospitals, and cities.

Bio:
Dr. Ryan Chin is a globally recognized expert in smart cities, urban mobility, and sustainable design systems. He co-founded Optimus Ride, a leading autonomous vehicle company spun out of MIT, where he served as CEO and led the development of self-driving tech for campuses, cities, and business districts. Prior to that, Ryan was Managing Director of the City Science Initiative at the MIT Media Lab, where he pioneered AI-integrated mobility systems and urban computing platforms.
Ryan holds a Ph.D. and two Master's degrees from MIT in Media Arts and Sciences and Architecture. A serial entrepreneur and systems thinker, Ryan has advised Fortune 100 companies, U.S. government agencies, and international city governments on emerging technologies, sustainability, and mobility innovation. He is a frequent keynote speaker at Davos, Smart City Expo, and the UN.
At FairwAI, Ryan supports us with building out our advisory team and the integration of computer vision, IoT, and AI fairness protocols into real-world infrastructure, ensuring our platform is adaptable, sensor-compatible, and aligned with the future of ethical urban technology.

The Role
We’re seeking a high-performing intern to support our compliance design, technical writing, and thought leadership efforts. This role is ideal for students or early-career professionals in public policy, law, international affairs, or AI governance who want to shape how fairness is operationalized in AI systems.
You will design, validate, and stress-test the quantitative framework that determines how AI systems are scored against our assessment criteria.
This is not a data entry position. You will be making methodological decisions that determine how
fairness is measured across industries. The scoring system you help build will be referenced in
legislative testimony, foundation grant applications, and enterprise compliance programmes.

What You'll Do

Conduct statistical validation of the scoring methodology — sensitivity analysis, robustness
testing, edge case identification
• Stress-test the Bias Risk Index against simulated assessment data to identify where the
formula breaks or produces counterintuitive results
• Evaluate disparate impact measurement approaches (four-fifths rule, statistical significance
testing, Bayesian methods) and recommend which to incorporate
• Review and validate the regulatory mapping table to ensure each quantitative criterion traces
correctly to its legal source
• Analyze major regulatory frameworks (e.g. EU AI Act, NYC Local Law 144, Algorithmic Accountability Act)
•Map policy risks to industry-specific applications (e.g. hiring algorithms, facial recognition, customer reviews)
•Draft concise, strategic briefing memos for external stakeholders
•Support development of our compliance risk scoring frameworks and internal ethics audits
•Contribute to white papers, grant applications, and presentations for major funders and institutions.

Required Qualifications
• Currently enrolled in or recently completed a graduate programme in statistics, econometrics,
biostatistics, quantitative social science, or a related field
• Strong foundation in statistical inference, hypothesis testing, regression analysis, and model
validation
• Proficiency in R or Python for statistical analysis
• Understanding of disparate impact measurement concepts (four-fifths rule, confidence
intervals, effect size)
• Ability to communicate quantitative methodology decisions in plain language to non-technical
audiences
• Comfort working independently with minimal supervision within a structured research
framework

Preferred Qualifications
• Familiarity with algorithmic fairness metrics (demographic parity, equalized odds, calibration)
• Experience with scoring system design, index construction, or composite indicator
methodology
• Exposure to employment discrimination law, EEOC guidelines, or AI regulation
• Prior research publication or conference presentation (any field)
• Coursework in causal inference or experimental design

Who You Are
Curious, self-directed, and systems-minded
Required Qualifications
• Currently enrolled in or recently completed a graduate programme in statistics, econometrics,
biostatistics, quantitative social science, or a related field
• Strong foundation in statistical inference, hypothesis testing, regression analysis, and model
validation
• Proficiency in R or Python for statistical analysis
• Understanding of disparate impact measurement concepts (four-fifths rule, confidence
intervals, effect size)
• Ability to communicate quantitative methodology decisions in plain language to non-technical
audiences
• Comfort working independently with minimal supervision within a structured research
framework

Preferred Qualifications
• Familiarity with algorithmic fairness metrics (demographic parity, equalized odds, calibration)
• Experience with scoring system design, index construction, or composite indicator
methodology
• Exposure to employment discrimination law, EEOC guidelines, or AI regulation
• Prior research publication or conference presentation (any field)
• Coursework in causal inference or experimental designStrong writer who can translate legal and technical language clearly

Interested in algorithmic fairness, AI governance, human rights, tech accountability, or digital rights

Bonus: Experience with grant writing, academic research, compliance, or policy analysis

What You’ll Gain
Exposure to real-world AI compliance and regulatory tech

A voice in how emerging rules are interpreted and applied across industries

Mentorship from a global leadership team with roots in MIT, Harvard, the UN, and impact-driven startups

Opportunities to contribute to major policy and funding deliverables (e.g. Ford, Gates, MacArthur).

We welcome international students with CPT or OPT authorization.

This is not a theoretical fellowship. You’ll be working directly with our leadership team on real-world compliance innovation. We move fast, ask hard questions, and care deeply about impact.

This role doesn't offer a salary but can offer school credit. We will offer a special certificate at the end of the fellowship. This will be administrated through our non-profit.

Top-performing interns can be:
Referred to graduate fellowships or full-time impact AI roles.
Eligible for future paid positions with FairwAI or its nonprofit arm if funding is available.
Supported in publishing or presenting findings at tech and policy forums.