Howard University AI Safety Summit & Policy Hackathon
Organized by Howard University
This event has ended.
Entries
- 1st place by peer reviewView project: Promoting School-Level Accountability for the Responsible Deployment of AI and Related Systems in K-12 Education: Mitigating Bias and Increasing Transparency
Promoting School-Level Accountability for the Responsible Deployment of AI and Related Systems in K-12 Education: Mitigating Bias and Increasing Transparency
This policy memorandum draws attention to the potential for bias and opaqueness in intelligent systems utilized in K–12 education, which can worsen inequality. The U.S. Department of Education is advised to put Title I and Title IV financing criteria into effect that require human oversight, AI training for teachers …
- View project: AI Monitoring as a Rapid and Scalable Policy Solution: Weekly Global Bulletins on AI Developments
AI Monitoring as a Rapid and Scalable Policy Solution: Weekly Global Bulletins on AI Developments
Team 1
Weekly AI monitoring bulletins that disseminated through official national and international channels aim to keep the public informed of both the positive and negative developments in AI, empowering individuals to take an active role in safeguarding against risks while maximizing AI’s societal benefits.
- View project: Implementing a Human-centered AI Assessment Framework (HAAF) for Equitable AI Development
Implementing a Human-centered AI Assessment Framework (HAAF) for Equitable AI Development
Team Humans for Human-Centered AI
Current AI development, concentrated in the Global North, creates measurable harms for billions worldwide. Healthcare AI systems provide suboptimal care in Global South contexts, facial recognition technologies misidentify non-white individuals (Birhane, 2022; Buolamwini & Gebru, 2018), and content moderation systems …
- View project: A Fundamental Rethinking to AI Evaluations: Establishing a Constitution-Based Framework
A Fundamental Rethinking to AI Evaluations: Establishing a Constitution-Based Framework
Team Unit 1112
While artificial intelligence (AI) presents transformative opportunities across various sectors, current safety evaluation approaches remain inadequate in preventing misuse and ensuring ethical alignment. This paper proposes a novel two-layer evaluation framework based on Constitutional AI principles. The first phase …
- View project: National Data Privacy and Governance Act
National Data Privacy and Governance Act
This research examines how AI recommender systems can be regulated to balance economic innovation with consumer privacy.
- View project: Community-First: A Rights-Based Framework for AI Governance in India's Welfare Systems
Community-First: A Rights-Based Framework for AI Governance in India's Welfare Systems
Team Sanjnah
A community-centered AI governance framework for India's welfare system Samagra Vedika, proposing 50% beneficiary representation, local language interfaces, and hybrid oversight to reduce algorithmic exclusion of vulnerable populations.
- View project: A Critical Review of "Chips for Peace": Lessons from "Atoms for Peace"
A Critical Review of "Chips for Peace": Lessons from "Atoms for Peace"
The "Chips for Peace" initiative aims to establish a framework for the safe and equitable development of AI chip technology, drawing inspiration from the "Atoms for Peace" program introduced in 1953. While the latter envisioned peaceful nuclear technology, its implementation highlighted critical pitfalls: a partisan …
- View project: Grandfather Paradox in AI – Bias Mitigation & Ethical AI1
Grandfather Paradox in AI – Bias Mitigation & Ethical AI1
Team Savitar Tech
The Grandfather Paradox in Artificial Intelligence (AI) describes a self-perpetuating cycle where outputs from flawed AI models re- enter the training process, leading to recursive degradation of model performance, ethical inconsistencies, and amplified biases. This issue poses significant risks, particularly in …
- View project: User Transparency Within AI
User Transparency Within AI
Team Cool Team
Generative AI technologies present immense opportunities but also pose significant challenges, particularly in combating misinformation and ensuring ethical use. This policy paper introduces a dual-output transparency framework requiring organizations to disclose AI-generated content clearly. The proposed system …
- View project: Advancing Global Governance for Frontier AI: A Proposal for an AISI-Led Working Group under the AI Safety Summit Series
Advancing Global Governance for Frontier AI: A Proposal for an AISI-Led Working Group under the AI Safety Summit Series
Team AI Safety Turkiye
The rapid development of frontier AI models, capable of transformative societal impacts, has been acknowledged as an urgent governance challenge since the first AI Safety Summit at Bletchley Park in 2023 [1]. The successor summit in Seoul in 2024 marked significant progress, with sixteen leading companies committing …
Overview
Organized by Howard University
Shaping the Future of AI Policy
The hackathon kicks off Tuesday, November 19th at 6 PM with an inspiring keynote panel. While attendance is not mandatory, we strongly encourage you to join us for an evening of collaboration, problem-solving, and networking with like-minded peers. Whether you choose to participate virtually or in-person, you'll have the opportunity to:
- Learn from expert speakers from government, emerging tech, and academia- Engage in interactive workshops and hands-on learning sessions- Receive mentorships from leading professionals- Compete for prizes- Build your professional network and explore new career paths
Located in Washington, D.C. or online via Discord. Final deliverables can be a technical demo or policy paper. No coding experience is required and all backgrounds are welcomed! Whether you're a computer science expert, policy enthusiast, or passionate about social impact, this interdisciplinary hackathon offers a unique platform to shape the future of AI governance.
REMINDER! The hackathon will be fully virtual on Wednesday.
Welcome to the inaugural AI Policy Hackathon at the Howard University AI Safety Summit! The purpose of this hackathon is to foster innovative policy solutions addressing the complex landscape of AI governance and safety, with a particular focus on practical implementations and regulatory frameworks.
We are seeking comprehensive policy papers that examine and propose solutions to critical challenges in AI development, deployment, and oversight. Participants are encouraged to explore various policy domains, from algorithmic accountability and bias mitigation to data privacy and ethical AI development.
While the primary deliverable is a detailed policy paper, participants have the option to supplement their submissions with technical implementations or prototypes that demonstrate the feasibility and impact of their proposed policies. This hybrid approach allows for a deeper exploration of how policy frameworks can be effectively implemented and enforced in real-world scenarios.
The hackathon aims to bridge the gap between theoretical policy development and practical implementation, encouraging participants to consider both the governance structures needed to regulate AI systems and the technical requirements to enforce such regulations.
Whether addressing issues of transparency in AI systems, proposing new standards for model evaluation, or developing frameworks for responsible AI scaling, submissions should demonstrate a clear understanding of both policy implications and technical feasibility in today's rapidly evolving AI landscape.
Resources
AI Policy Hackathon Resources 📚
Essential Policy Frameworks: Global AI Governance Guidelines ⚖️
OECD AI Principles / G20 AI Guidelines
UNESCO Recommendation on AI Ethics
US Executive Order on AI
EU AI Act
Council of Europe AI Treaty
UN Resolution on AI
Continental AI African Union Strategy
Esential : Policy Development 📖
12 Tentative Ideas for US AI Policy by (Open Philanthropy)
A comprehensive overview of concrete policy proposals for managing AI risks, from export controls to safety testing requirements. Essential reading for understanding the current policy landscape.- Concrete policy proposals- Risk management strategies- Implementation roadmaps
Speaking to Congressional Staffers about AI Risk
A firsthand account of engaging with policymakers on AI safety. Invaluable insights for participants interested in how policy ideas get translated into action.- Stakeholder engagement strategies- Communication best practices- Policy advocacy techniques
Thoughts on Responsible Scaling Policies
Critical analysis of how industry self-regulation and government oversight can work together. Useful for understanding the interplay between private and public sector approaches.- Industry self-regulation- Government oversight- Public-private partnerships
Practical Resources 🛠️
Getting Started
Connect With Us 🤝
to: - Connect with mentors- Collaborate with participants- Access additional resources- Share ideas and feedback
Support & Questions ❓
- Email: dschowardu@gmail.com- Technical Support: operations@apartresearch.com- Emergency Contact: GDG GroupMe
Upcoming Apart Sprints
All Sprints- Oct 23 - 25, 2026Online and in person
AI Collusion Research Sprint
A weekend research sprint on collusion between AI agents: when it emerges in markets and everyday workflows, how to detect and audit it, how it is carried, and what breaks it. Co-organized with Poseidon Research and AE Studio, online with in-person hubs at Collider in New York City and AI Safety Hong Kong. Top teams are invited to apply to the Apart Fellowship.
Read the brief: AI Collusion Research Sprint - Nov 13 - 15, 2026Online
AI x Epistemics Research Sprint
A weekend research sprint on AI for epistemics: evaluating whether models know how solid their claims are, building trust infrastructure that people and agents can consume, and shipping epistemic products that improve real decisions. Online, four tracks including an open track. Top teams are invited to apply to the Apart Fellowship.
Read the brief: AI x Epistemics Research Sprint