AI Ethics Grants

SBIR Phase I — US Small Business Innovation is sponsored by Defense Advanced Research Projects Agency (DARPA). This program provides early-stage funding for highly innovative R&D projects, with active funding areas including blockchain for federal applications, decentralized identity, AI safety, and quantum computing. It is non-dilutive and open to US-based small businesses.

Iliad Fellowships in Applied Mathematics for AI Safety – Fall 2026 is sponsored by Iliad (managed by Lightcone Infrastructure). This fellowship supports individuals passionate about mathematics and building safer AI systems, focusing on theory-driven research on ReLU networks and projects that raise the epistemic bar of AI safety. Mathematicians are especially welcome, regardless of prior AI experience.

Applications open for Anthropic Wellbeing Research Grants is sponsored by Anthropic. Anthropic offers grants for research related to AI safety and alignment, and understanding the long-term impacts of AI. While not exclusively focused on Bangladesh, proposals from or involving researchers in Bangladesh may be considered if they align with the program's goals.

NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.

Long Range Broad Agency Announcement (BAA N00014-25-S-B001) is sponsored by Office of Naval Research (ONR). This BAA is ONR's primary solicitation for basic and applied research proposals in areas relevant to naval needs. ONR's AI priorities center on autonomous maritime systems, human-machine teaming, and machine learning for sensor fusion, including research in trustworthy AI.

IDRC AI4D: Responsible AI, Empowering People Program for AI Governance and Innovation in the Global South is sponsored by International Development Research Centre (IDRC, Canada) with the UK Foreign, Commonwealth and Development Office (FCDO). A multi-year program investing over CAD 100 million to strengthen responsible AI governance, study AI's socioeconomic impacts, and build local compute infrastructure in low- and lower-middle-income countries across South Asia, Southeast Asia, and the Pacific, with projects begin…

Polyphonic AI Fund QuickFire Challenge is sponsored by Johnson & Johnson MedTech. This fund supports the use of artificial intelligence in surgery, with a focus on proposals that support AI model development, data engineering and management, and AI governance. While primarily focused on surgery, AI innovations in medical imaging could be relevant.

Funding grants for new research into AI and teen development is sponsored by OpenAI Group PBC. OpenAI is committing $5 million to support independent research on how generative AI affects the lives and development of young people ages 13–17. This grant focuses on AI's impact on social and emotional development, relationships, wellbeing, and safety, aiming to inform product decisions, regulatory policy, and future safeguards.

Mathematical Foundations of Artificial Intelligence Research is sponsored by Not explicitly stated (listed on The Grant Portal as a research funding opportunity). This research funding opportunity supports nonprofit academic organizations, research institutions, and eligible U. S. -based organizations conducting interdisciplinary research on mathematical and theoretical foundations for sustainable, trustworthy, and socially responsible AI.

Mathematical Foundations of Artificial Intelligence is sponsored by U.S. National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), and Engineering (ENG). This grant aims to address foundational gaps in AI through interdisciplinary research on mathematical and theoretical foundations for sustainable, trustworthy, and socially responsible AI.

Defending Digital Rights and Civic Space Online is sponsored by International Center for Not-for-Profit Law (ICNL). This call for proposals seeks to support organizations working to protect fundamental freedoms in the digital realm across five thematic areas: Artificial Intelligence (AI) Governance; Surveillance/Right to Privacy; Data Protection; Freedom of Expression; and Access and Inclusion Online. It emphasizes the crucial role of civil society in promoting accountability and good governance as governments grapple with emerging technology laws.

Development and Testing of a Multi-use Frameworks Playbook for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (U01 Clinical Trial Not Allowed) is sponsored by NIH Common Fund. This grant supports teams in designing, developing, and preliminarily validating frameworks and a shared playbook for multimodal AI clinical decision support tools that combine medical imaging with other health data. The goal is to establish standard processes to support responsible AI use, data management, and regulatory readiness within the PRIMED-AI program.

Small Business Innovation Research (SBIR) Program (DoD) is sponsored by Defense Advanced Research Projects Agency (DARPA), U.S. Department of Defense (DoD). The DARPA SBIR program funds U.S. small businesses to develop innovative technologies that advance national security. This includes high-risk, high-payoff research that goes beyond current military capabilities. There are specific topics such as 'Influence Benchmarks for AI Systems' which aims to develop a testbed utilizing economic frameworks to benchmark AI biases in dynamic environments.

This is the EuroHPC access mode built specifically for AI workloads, and it is the most direct route for European researchers who need serious compute without a Horizon Europe grant behind them. Allocations are made in node hours across four petascale and pre-exascale systems - LUMI in Finland, Leonardo in Italy, MareNostrum5 in Spain and MeluXina in Luxembourg - for six-month access periods. The stated scope is explicit about modern AI: ethical artificial intelligence, machine learning, and cutting-edge foundation models and generative AI including large language models, which means training and fine-tuning runs are in scope rather than being squeezed into a traditional simulation-oriented HPC framing. Eligibility is deliberately wide. All scientific users qualify whether or not their work is funded by national or European programmes, as do public sector users, and industrial users participating in EU-funded research and innovation projects such as Horizon Europe or the Digital Europe Programme. The one important boundary: industrial users not involved in an EU research project are directed instead to the AI for Industrial Innovation access modes, so a commercial applicant with no EU project affiliation should check which door they are meant to use before drafting. The call operates on rolling cut-offs rather than a single deadline, with 2026 cut-offs at 27 February, 30 April, 30 June, 31 August, 30 October and 11 December, each at 10:00 CET. That cadence means an unsuccessful application can be revised and resubmitted roughly two months later, and a team that misses one window is never waiting long for the next. As with all compute schemes, no money is awarded - staff and data costs must come from elsewhere.

The Foresight Institute's AI for Science and Safety Nodes request for proposals funds work at the intersection of accelerating science with AI and making AI systems safe, and it is structured less like a conventional grant than like admission to a research hub. Successful applicants receive a cash grant, typically 30,000 to 100,000 US dollars, together with access to a private compute cluster and office space at Foresight's San Francisco or Berlin nodes. Three focus areas are named: Local Compute, concerning decentralised and locally-run AI capability; Coordination and Accountability, covering mechanisms such as AI insurance and open governance; and AI-First Science across biology, neuroscience and nanotechnology. The programme is deliberately open to individuals, teams and organisations, both non-profit and for-profit, which makes it one of the few credible funding routes for unaffiliated researchers and very small teams working on AI safety and AI-for-science questions that fall outside university and large-foundation structures. Two conditions shape what the award is good for: overhead is capped at 10 per cent of direct research costs, which effectively rules out hosting the work inside a high-indirect-rate university, and all work products including code, data and outputs must be open source. Selection prioritises applicants who will be active in-person contributors at the physical nodes. The application deadline is 31 October 2026 at 23:59 Pacific time, which makes this one of the few AI safety opportunities currently open.

Foresight's AI for Science and Safety Nodes RFP is a small-cheque, high-variance programme aimed at work that conventional funders will not touch, and it is one of the few AI safety calls verifiably open with a future deadline of 31 October 2026. The framing joins two problems: ensuring a safe transition to highly capable AI, and using AI to unlock scientific breakthroughs. Proposals sit in one of three layers. Local compute covers community-owned and controlled computational infrastructure - an explicitly decentralist counterweight to frontier-lab concentration. Coordination and accountability covers human-AI interaction, supercollaboration and AI risk assessment mechanisms. AI-first science covers automated nanotechnology, whole-brain emulation and frontier biotechnology. The single most important screening criterion is stated plainly: Foresight wants projects where AI is the primary engine of progress, not projects where AI is, in its words, tapped onto an existing research program - so an established lab adding a machine learning component to ongoing work is the archetype of what gets rejected. Evaluation weights alignment with a focus area, impact on AI existential risk reduction, feasibility within short AGI timelines, execution capability, and high-risk high-reward potential. Two conditions are non-negotiable: all outputs must be open-sourced, and applicants must commit to active participation at Foresight's San Francisco or Berlin nodes, which makes this poorly suited to a purely remote team. Application is a single Airtable form with a roughly three-month review.

IDRC EQUAL Compute Network for Closing AI Divides and Spurring Responsible AI Innovation in the Global South is sponsored by International Development Research Centre (IDRC). An IDRC-funded initiative to address compute inequities limiting Global South participation in frontier AI research, supporting researchers, public-interest compute providers, and policy actors in Africa, Latin America, South Asia, and Southeast Asia to evaluate compute needs, b…

This is the one technical area of ARIA's Safeguarded AI programme that remains open - TA1.1, TA1.2, TA1.3, TA1.4, TA2 and TA3 are all archived or cancelled - and it is worth understanding what distinguishes it from the general run of AI safety funding. The work is not empirical alignment research or evaluations. It is building production-grade, security-critical software components whose key security properties are backed by machine-checked proofs, with AI used to assist the formal verification itself. That places it at the intersection of formal methods, systems security and AI, and a team without genuine proof-assistant capability will not be competitive regardless of its AI credentials. The structure is unusual and should be priced in before applying. Work runs in 8-week sprint cycles, and blue teams building the secure components are stress-tested by a funded red team doing adversarial penetration testing. This is an adversarial, milestone-driven programme rather than a research grant that pays out and waits for a paper. The solicitation is rolling, assessed in quarterly batches, with the documented final deadline 31 October 2026 at 14:00 GMT - so applying early is materially better than applying at the deadline, since capacity fills as batches are decided. Eligibility is genuinely international: single organisations or teams spanning academia, industry and non-profits may apply, and there is no requirement to be UK-based, which distinguishes this from many UK government research schemes. Applications go through ARIA's grant platform at aria.grantplatform.com. Anyone considering this should read the full technical area description rather than relying on the summary, because the boundary between what counts as machine-checked and what counts as AI-assisted-but-unverified is exactly where proposals are won and lost.

EQUAL Compute Network is an IDRC-funded initiative to address compute inequities limiting Global South participation in frontier AI research. The network supports researchers, public-interest compute providers, and policy actors in Africa, Latin America, South Asia, and Southeast Asia to evaluate compute needs, build shared compute infrastructure, develop pooled access models, and inform national AI compute strategies. Sub-grants fund research nodes, pilot deployments of shared compute clusters, and policy analysis on compute access. Aligns with the wider AI4D portfolio and complements Canadian and EU compute sovereignty initiatives.

Foresight Institute's AI for Science and Safety Nodes programme funds small projects at the intersection of AI safety and AI-accelerated science, and it is structured around physical hubs in San Francisco and Berlin that opened 1 April 2026 rather than around distributed remote work. That is the single most important thing to understand before applying: Foresight states a strong preference for applicants committed to active, in-person participation at one of the two hubs, and the non-cash benefits - office workspace, a private compute cluster, travel-paid field-building events, access to advisors - are only realisable on site. A remote applicant is competing for a 30,000 to 100,000 dollar grant while forgoing most of what the programme offers. Three focus areas are named: local compute infrastructure; coordination and accountability systems; and AI-first science in biology, neurotechnology and nanotechnology. Funding is not distributed evenly across them, with smaller grants going to Human Empowerment and to AI Insurance and Open Governance, and larger grants to the rest. Eligibility is unusually broad for AI safety funding - individuals, teams and organizations may apply, nonprofit or for-profit, with no stated geographic restriction, though for-profit applicants must justify their need for grant rather than investment funding. There is no institutional affiliation requirement, which makes this one of the few routes available to independent researchers working on AI safety. Applications go through an Airtable form and are reviewed monthly, with deadlines on the last day of every month running to a final documented deadline of 31 October 2026 at 23:59 PDT. Review takes roughly three months after the deadline. Because Foresight reviews monthly until the nodes reach capacity, applying early rather than at the final deadline is a real advantage.

HORIZON-CL3-2026-01-FCT-02: Open topic on preventing and countering the misuse of emerging technologies for criminal purposes, including issues related to lawful access to data is sponsored by European Commission (Horizon Europe Cluster 3 - Civil Security for Society). Research and Innovation Actions addressing misuse of emerging technologies (including AI) for criminal purposes, with emphasis on legal/ethical outcomes, fundamental rights, privacy, and responsible research. Relevant for AI governance, ethics, and security implications.

DARPA's Information Innovation Office (I2O) office-wide BAA (HR001126S0001) is the widest entry point for AI researchers seeking defense funding. It organizes interests around four thrust areas: transformative AI (trustworthy, explainable, ethically-aligned systems), resilient and secure software, offensive and defensive cybersecurity, and fighting in the information domain, with AI threads running through all. It is a standing invitation for disruptive R&D concepts in information science, accepting proposals outside current program priorities.

Small Business Innovation Research (SBIR) (DARPA) is sponsored by Defense Advanced Research Projects Agency (DARPA). DARPA's SBIR program funds high-risk, high-reward scientific breakthroughs with the potential to transform national security. It focuses on disruptive engineering concepts and platform-level breakthroughs across various technologies, including AI and autonomy, with dual-use commercial and DoD applications. Active funding areas include blockchain for federal applications, decentralized identity, AI safety, and quantum computing.

Bridge2AI Stage 2 advances NIH's flagship biomedical AI initiative from creating ethically sourced, machine-learning-ready datasets to delivering deployable AI tools for specific health challenges. Stage 2 funds Innovation Funnels that use the Stage 1 AI-ready datasets (voice biomarkers, clinical cardiology, salutogenesis, AI/ML for precision public health) to build diagnostic algorithms, drug discovery platforms, and clinical decision support systems. It also establishes a Network for AI Health Science to develop safety protocols, responsible AI implementation guidance, and ethics frameworks for biomedical AI. Strong emphasis on FAIR data principles, transparent model documentation, equity, and public trust.

Broad Agency Announcement (BAA) for Information Innovation Office (I2O) is sponsored by Defense Advanced Research Projects Agency (DARPA). An open solicitation accepting white papers in various research interests, explicitly including offensive and defensive cybersecurity, trustworthy AI, and complex software systems. This BAA is a potential avenue for sustained DARPA funding.

The Omidyar Network Tech Journalism Fund supports U.S.-based journalists pursuing in-depth stories that illuminate the social, economic, and political impacts of emerging technologies including artificial intelligence, generative AI, algorithmic decision-making, surveillance, content moderation, and AI labor markets. The fund prioritizes investigative reporting, accountability journalism, narrative features, and explanatory pieces that surface how AI systems affect communities, workers, and democratic institutions. Part of Omidyar's broader $30 million responsible generative AI investment alongside the Responsible Technology Youth Power Fund and AI governance grants.

AI-ENGAGE launched by NSF in early 2026 as a Quad-nation collaboration with Australia, India, and Japan supporting multinational research teams developing AI tools for agriculture, engineering, scientific discovery, and societal benefit. The inaugural cohort of six awards totaled $6M+ across the four partner countries. Funded research includes precision agriculture AI, AI for crop disease detection in tropical climates, multinational AI safety benchmarks, and AI for scientific discovery. Strong fit for U.S. universities with established collaborations in Quad partner countries. The program expects continued cycles in 2026-2027 with growing scope. Strong fit for AI faculty working in food systems AI, climate-resilient crop AI, AI for scientific discovery, and engineering AI with international research partners.

The Ethics and Governance of AI Fund is a multi-funder coalition that supports applied research on AI bias, fairness, and accountability; educational programs building public understanding of AI; fellowship programs for emerging scholars; and collaborative cross-disciplinary projects on AI policy and governance. The fund channels $27M+ from Knight Foundation, Omidyar Network, Reid Hoffman, the Hewlett Foundation, and Jim Pallotta. Rockefeller Philanthropy Advisors administers pooled grantmaking; each funder also maintains separate application processes. Funded work includes algorithmic accountability research, AI policy and governance fellowships, civil society capacity-building, and interdisciplinary scholar networks. Strong fit for academics, civil society organizations, journalists, policy think tanks, and law schools researching responsible AI.

The Survival and Flourishing Fund (SFF) is a virtual fund organizing grant applications and recommending grants to organizations addressing the long-term survival and flourishing of sentient life. SFF runs main S-Process rounds plus themed rounds, with the 2026 cycle featuring three new themed S-Process rounds in addition to the Main Round. Strong focus on AI safety, AI alignment, biosecurity, existential risk research, longtermist policy, and technical AI governance. Funded organizations include leading AI safety nonprofits and university research groups. Grant recommendations are made via SFF's distinctive S-Process collaborative evaluation. Rolling and round-based application accepted.

Strengthening cybersecurity capacities of European SMEs with cybersecure AI-powered solutions is sponsored by European Commission — Digital Europe Programme. Expected Outcome: Support the adoption of market-ready innovative AI-powered cybersecurity solutions, including solutions developed in the framework of EU-supported research and innovation projects. Provide and deploy up to date AI-powered tools and services to organisations (in particular SMEs) to prepare, protect and respond to cybersecurity threats. Integrate AI technologies into cybersecurity processes to improve the security of ICT solutions, including providing innovative approaches to training employees to use AI solutions for cybersecurity. Deployment of cybersecure tools and technologies relying on trustworthy AI; AI driven cybersecurity tools; Integration of tools to protect and secure AI solutions. Objective: To support the market uptake and dissemination of innovative AI-powered cybersecurity solutions (notably in SMEs, possibly using results stemming from Horizon Europe projects or similar) and improve knowledge and auditing of cybersecurity preparedness. SMEs often lack the resources to assess cyber risks, develop cybersecurity strategies and implement solutions, leaving them vulnerable to cyberattacks. The resilience of organisations that fall into this category is key to the prosperity of the EU single market. Cyber risk assessment and management can be significantly enhanced and simplified with the application of AI-based tools and solutions. However, this requires an understanding of the evolving technology landscape, of the benefits of technology integration and of deployment prioritisation. Faced with organisational and financial constraints, the SMEs may be missing the opportunity to fully harness AI-powered solutions to advance their cybersecurity and resilience. Cybersecurity is the precondition for reliable, secure and resilient AI models and algorithms. Cybersecurity of AI is not just about protecting AI systems against threats such as poisoning and evasion attacks, as it also involves ensuring they have trustworthiness features such as human oversight and robustness – the ability to resist cyberattacks, as required by the EU’s AI Act for high-risk AI systems. The need for human oversight of AI has also been emphasised by experts. Also, the use of AI at the SME level supporting the integration of predictive algorithms can greatly support to a bottom-up approach when dealing with vulnerability detections, threat mitigation and more efficient coordinated incident response. Scope: This action aims to increase the maturity of cyber risk management and improve the cyber resilience and ultimately foster a technologically advanced culture of cybersecurity for SMEs in the EU. Actions in this topic should develop and deploy AI-powered products, tools and services for European SMEs, also enabling the detection/discovery of attack patterns. Proposals should cover the development or adaptation of the software/hardware and the validation of the solutions. It foresees the automation of fundamental cybersecurity processes, in particular in small market organisations, through a SaaS toolkit tailored to the needs of SMEs. This toolkit should allow SMEs to improve the key aspects of their cybersecurity by providing user-friendly tools for risk management [1], threat detection, incident response and notification, to improve their cyber hygiene and mitigate potential threats while protecting personal data. The cyber toolkit should also provide cyber-incident prediction and response functions to improve SMEs’ resilience. Activities should include at least one of the following: Uptake/adoption of AI-powered cybersecurity tools in organisations where this has not yet taken place. Development of user-friendly sets of tools (e.g. toolkit) based on AI to automate main cybersecurity processes in SMEs. Such a toolkit could provide automated functions such as: A function that supports the assessment and management of an SME’s cybersecurity risks. This function should perform a risk assessment, provide recommendations for risk miti Programme areas: DIGITAL Keywords: Analytics tools, Artificial Intelligence & Decision support, Artificial intelligence, Assessment, Capacity building, Continuing professional training, Cybersecurity, Cybersecurity-aware culture (e.g. including children education), Data Security and Privacy, Data protection, Education and Training, IT skills and competence, Innovation, Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video), Managerial, procedural and technical aspects of network security, Privacy, SME support, Sme Business Development, Technological innovation, Training, AI-powered Cybersecurity, Capacity Building, Cyber Hygiene, Cyber Resilience, Cyber Risk Management, Incident Response, SME Digital Transformation, SME Support, SaaS Security Tools, Security Awareness, Trustworthy AI, Vulnerability Detection

AI Safety Fund is sponsored by Various, administered by Frontier Model Forum (supported by philanthropic funders including Schmidt Sciences, Chan Zuckerberg Initiative, and Sloan Foundation). The AI Safety Fund supports global research projects advancing responsible and safe development of advanced AI systems, focusing on urgent challenges like evaluation, biosecurity, cybersecurity, and governance.

Quantum Machine Learning is sponsored by European Commission — Horizon Europe. Expected Outcome: Integration of quantum computing into data pre-processing pipelines and learning workflows for data-heavy or computationally intensive tasks, demonstrating clear improvements in processing speed, computational complexity, modelling accuracy, and reduced sample requirements at scales achievable with NISQ-era devices, Reliable and scalable Quantum Machine Learning (QML) models and algorithms, integrated with existing AI frameworks and pipelines, enabling faster data processing, improved prediction accuracy, and enhanced computational capabilities, Validated quantum-enhanced AI methods demonstrating measurable improvements over classical baselines in terms of speed, accuracy, data efficiency, complexity, or scalability, supported by rigorous benchmarking and complexity analysis, Robust, noise-aware QML techniques suitable for NISQ hardware , including error-mitigation strategies and algorithmic adaptations that improve reliability, performance, and reproducibility on real quantum processors, Demonstrators or proof-of-concept applications showcasing the relevance of QML for real-world challenges (e.g. climate and environmental modelling, Earth observation, healthcare and life sciences, materials discovery, finance, robotics, manufacturing, and cybersecurity), Strengthened European leadership and technological sovereignty in quantum computing and trustworthy AI, supported by cross-sector collaboration, knowledge transfer, and contributions to emerging standards, benchmarks and best practices. Enhanced collaboration across quantum computing, machine learning and application domains, fostering a coordinated European QML research and innovation community. Scope: Proposals are expected to address multiple key research directions in Quantum Machine Learning (QML), targeting both scientific excellence and industrial relevance. Proposals should clearly outline how to contribute to the development, validation and demonstration of quantum-enhanced AI approaches, with clear pathways towards practical applications. The proposed work should strengthen Europe’s scientific and technological capabilities in quantum computing and accelerate the industrial uptake of quantum-enhanced AI solutions. Activities may include, but are not limited to design and analysis of quantum, quantum-inspired or hybrid QML algorithms, performance modelling, complexity analysis and benchmarking of quantum-enhanced AI methods, development of error-mitigation and noise-aware strategies tailored to QML workloads, Proposals should advance scalable QML algorithms capable of addressing large-scale, computationally intensive problems, this includes approaches that can manage massive data volumes and complex computational tasks, enable faster data processing and improved predictive performance in relevant application domains (e.g. hydrologic research, climate modelling, terrain classification from satellite remote sensing, drug discovery, and image-based medical diagnosis). Many current QML methods remain closely inspired by classical algorithms and therefore do not yet achieve genuine quantum advantage, requiring further developments in quantum-native learning models, efficient quantum kernels and quantum feature mappings, algorithms demonstrating provable or empirical advantages over classical approaches. Proposals may also include formal complexity analyses, identification of problem classes that can benefit from quantum acceleration. Developments should address multiple of the following key research directions : Quantum Supervised Learning (QSL) : Quantum Supervised Learning investigates how quantum algorithms can accelerate or improve the training of supervised learning models, offering novel opportunities to explore quantum–classical learning theories and enabling industry to shorten development cycles and enhance performance in data-intensive domains such as finance, healthcare, and Earth observation. Integrating QSL into existing pipelines may help o Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Digital, Industry and Space

Defense Sciences Office (DSO) Office-Wide Broad Agency Announcement (HR001125S0013) is sponsored by Defense Advanced Research Projects Agency (DARPA) - Defense Sciences Office (DSO). This BAA solicits proposals for innovative approaches enabling revolutionary advances in science, devices, or systems for national security applications, which can include areas related to AI safety and trustworthiness.

The DEVCOM Army Research Laboratory issues a rolling Broad Agency Announcement (W911NF-23-S-0001) soliciting white papers and full proposals for foundational research aligned to ARL's essential research programs. Explicit AI and ML priorities include the Artificial Intelligence of Maneuver and Mobility (AIMM) program, autonomous ground systems, AI-enabled sensing and perception, human-autonomy teaming, reinforcement learning for tactical decision-making, and trustworthy AI for the future battlefield. The BAA supports basic and applied research relevant to the Army Modernization Priorities including next-generation combat vehicles, networked sensors, and soldier lethality. ARL's extramural program engages universities, federally funded R&D centers, nonprofit organizations, and U.S. industry of all sizes through cooperative agreements, grants, and contracts. The rolling BAA structure allows submission at any time and offers a low-friction entry point for new performers seeking long-term partnerships with the Army's principal land warfare laboratory.