Autonomous systems

Autonomy and autonomous systems

Artificial intelligence (AI) is transitioning from relatively low-risk consumer applications to mission-critical industrial contexts, i.e. autonomous vehicles, industrial robotics, smart grids, critical infrastructure control, and autonomous maritime systems. This transition introduces unprecedented challenges for safety, reliability, and trustworthiness. As autonomous technologies become embedded in critical infrastructure, transportation, energy systems and industrial processes, the ability to rigorously quantify, manage, and mitigate AI-specific risks becomes essential to societal resilience and safety.

This call targets the fundamental scientific challenges associated with enabling safe and trustworthy AI-enabled autonomous systems and managing the risks they introduce. Specifically, it focuses on understanding and controlling emergent capabilities in alignment with intended objectives as complexity and autonomy increase, and on how to rigorously assess the risks of deploying such systems in complex real-world environments. To achieve this will require foundational advances in complexity science, risk science, and AI safety and alignment research, coupled with practical approaches that equip society to deploy autonomy with confidence.

Projects should be domain-agnostic and consider how the outcomes can contribute to ongoing international standards, policy and regulatory initiatives such as the EU AI Act’s requirements for high-risk systems. Projects will provide the scientific foundation for risk-informed design, operation, and governance of autonomous systems, to ensure that these systems behave in ways that are safe, predictable, and beneficial for individuals and society – accepting that what is deemed to be beneficial is itself a rich area of research within AI ethics. The project outcomes will transform how autonomy is designed, operated, regulated and governed across sectors.

Activities within scope of the project:

Activities are expected to achieve TRL 1-3 by the end of the project, and projects are expected to address at least one of the following:

  • Emergence in autonomous systems

What causes emergent capabilities in autonomous systems, and can emergent capabilities be predicted and controlled?

In autonomous and complex engineered systems, emergent behaviour refers to system-level capabilities or outcomes that arise from interactions among components and that cannot be attributed to any single element alone. These behaviours, such as sudden capability onset, collective adaptation, or unintended global effects, often appear only when systems operate at scale, or under specific interaction patterns. Such emergence poses challenges in both design and operation, especially for safety-critical applications.  

The scientific challenge is to advance the theory of emergence for autonomous systems that explains, predicts, and bounds collective behaviours. This involves developing a fundamental understanding of complexity, dynamical systems, multi-agent interaction, and information flows, and establishing approaches to handle emergence-driven risks in the development and operation of autonomous systems.

  • Alignment of autonomous AI systems

How can autonomous AI systems be designed and governed so that their goals, decisions, and behaviours remain consistently aligned with their intended objectives and constraints, even as they become more capable and operate in complex real-world contexts?

The alignment problem refers to the core scientific and engineering challenge of ensuring that an AI system’s performance remains consistent with its intended objectives and constraints, rather than diverging in unexpected or harmful ways as complexity and capability grow. Misalignment occurs when an AI system optimises for proxies or unintended objectives that do not faithfully represent its intended objectives or operational constraints. Current AI systems already exhibit misalignment in narrow domains, and this challenge becomes increasingly acute as systems gain autonomy, adaptivity, and influence across socio-technical environments.

The scientific challenge is to advance foundational theories and methods that enable autonomous AI systems to faithfully represent and pursue intended objectives under real-world operational conditions.

  • Quantifying risk and uncertainty in autonomous AI systems

How can risk be estimated for autonomous AI systems when complexity, learning behaviour, and novel technologies create new types of failure and “unknown unknowns”?

In complex AI-enabled systems, risk cannot always be inferred from past data or known failure modes, as experience data is often scarce and the space of possible behaviours may itself change as systems learn and interact. Autonomous systems may operate in environments characterized by multiple sources of uncertainty, including incomplete data, changing operational contexts, model limitations, and complex interactions with human and technical systems.

The scientific challenge is to develop rigorous frameworks for quantifying uncertainty and representing system risk. This includes advancing methods that distinguish between different sources and types of uncertainty, and understanding how these uncertainties propagate through AI-enabled systems to influence decisions and outcomes, and ultimately the likelihood of system failure.

Activities outside the scope of the project:

The following activities are explicitly out-of-scope:

  • Applied product development, commercialization, or market deployment
  • Domain-specific applications without fundamental research contributions
  • Data collection, labelling, or dataset creation as the primary result
  • Incremental improvements to existing methods without paradigm shifts
  • Purely empirical testing and validation without theoretical foundations

Expected outcome and impact

The successful proposal will contribute to

  • Fundamental scientific advances in understanding and managing autonomous AI-enabled systems, including theoretical and methodological breakthroughs related to emergent system behaviour, alignment of autonomous decision-making with intended objectives and operational constraints, and the rigorous quantification of uncertainty and risk in complex socio-technical systems. Research may focus either on developing methods that enable these capabilities by design or on approaches that demonstrate, verify, or provide formal guarantees about them.
  • New frameworks, methods, and tools for the safe and trustworthy deployment of autonomous systems, framed such that these can eventually feed into the normative frameworks that govern design, operation, assurance and governance of AI-enabled systems in critical domains.

 

For the inaugural 2026 call for proposals, we welcome accredited universities in Denmark, Finland, Iceland, Norway and Sweden to apply as host institutions. This initial geographic anchoring provides a focused starting point for the research funding to increase impact and supports operational learning in the first funding cycle. This anchoring is an operational choice for 2026, not a long‑term geographic definition. The Foundation’s long-term ambition is global, and the geographic scope of future calls is expected to be reviewed and may evolve over time as part of the Board’s regular oversight, learning, and strategic development of the programme.

Who can apply

The formal applicant must be an accredited university in Denmark, Finland, Iceland, Norway and Sweden. The principal investigator must have completed a PhD and have a formal affiliation to the host institution. [1]

Anyone can start the application process but to submit, a letter of commitment from the host institution must be attached.

Other recognized research institutes and organizations in the Nordics may participate as collaboration partners in projects but cannot act as the host institution in the 2026 call or receive funding.

What we fund

  • Basic research aligned with the purpose of the thematic calls. By basic research, we mean ‘experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view’ (taken from Frascati Manual 2015 (EN)).
  • A minimum of NOK 5,000,000 and a maximum of NOK 12,000,000. Ten per cent of the awarded amount will be withheld until the final project report has been approved.
  • Projects with a duration of up to 36 months. Projects need to be initiated within 6 months of granting funding.
  • Projects with their main scientific focus in the Nordic region, where at least 50% of the project’s activities by budget must be carried out in Nordic countries.
  • Peer-reviewed publications arising from the grant, and the data and analysis code underpinning these publications must be made openly accessible in accordance with the Det Norke Veritas Foundation’s open research principles.
  • IP generated under a Det Norke Veritas Foundation grant is owned by the host institution(s) and/or the researchers’ employer, not by the Det Norke Veritas Foundation. 
Full details on terms and conditions will be available shortly in the Grant Agreement template.
 

What we do not fund

  • Reimbursement of indirect/overhead costs, such as administration, building space and utility costs.
  • Partial funding of larger projects where the requested amount constitutes less than one third of the total project budget. For example, if applying for NOK 5,000,000, the total project budget (including the requested amount) must not exceed NOK 15,000,000.
  • Overlaps in scope or costs with other funding sources. The same activities or costs cannot be funded by more than one funding source. If overlap occurs, the grant recipient must decide which funding source will support the relevant project components and ensure that budgets and scopes are clearly separated. Failure to resolve overlaps may result in withdrawal or adjustment of funding.

How to apply

Anyone can start the application process.

The application must be completed in its entirety using the application form in the funding portal when open at the end of May 2026.

The application consists of an application form accompanied by a budget, where a preview of the application form and budget template will be available here shortly.

Evaluation of applications

Following submission, applications undergo review in three stages:

1. Eligibility screening by the secretariat

2. Scientific review by the panels of experts

3. Strategic selection by the Research Funding Committee


Eligibility screening by the secretariat

An initial screening by the Det Norske Veritas Foundation Research Funding Secretariat to ensure eligibility and compliance with the call requirements.

Scientific review by expert panels

Applications that pass the screening are assessed by panels of independent external experts, who evaluate each application independently of each other according to the following three criteria:

Excellence

• The clarity, relevance and ambition of the scientific objectives and research questions

• The degree to which the proposed research is original and advances knowledge beyond the current state of the art

• The soundness, credibility and robustness of the scientific approach and methodology

• The extent to which the proposed work is well-founded in relevant theory, concepts and prior research

Impact

• The potential of the project’s results to generate effects within research, society or policy, as specified by the call objectives

• The credibility and realism of the expected outcomes and their contribution to stated goals

• The quality and appropriateness of plans for dissemination, communication and use of results

• The added value of the project compared to existing research, initiatives or funding instruments

Implementation

• The coherence, structure and feasibility of the work plan, including tasks, milestones and deliverables

• The appropriateness of project organisation, including roles, responsibilities and competence of the project team or leadership

• The realism and justification of the project timeline, budget and allocation of resources

• The identification of key risks and the adequacy of proposed mitigation measures

All criteria are weighted equally and scored on a scale from 0 to 5, where 5 is the highest score. Applications are ranked and shortlisted based on the experts’ evaluation.

Strategic selection by the Research Funding Committee

Finally, the shortlisted projects are considered by the Foundation’s Research Funding Committee (RFC) for strategic alignment with the Foundation’s mission and approved program mandate. At this point, all proposals are assumed to meet the required scientific excellence threshold based on expert review.

The RFC members will evaluate applications independently of each other according to the following two criteria, again scored from 0 to 5:

The Det Norske Veritas Foundation’s priorities

• A clear rationale for how the proposed research contributes to the Det Norske Veritas Foundation’s purpose of safeguarding life, property and the environment 
• The extent to which the proposal advances basic scientific research within the call’s defined priority areas

Strategic fit to the funding programme portfolio

• Responsible and proportionate use of the available grant envelope and opportunity cost
• Integrity, ethical and reputational robustness of the projects granted

The aggregated expert scores form the basis for a preliminary ranking of proposals. This ranking serves as the starting point for the RFC’s final deliberations. In the final decision meeting, the RFC’s task is to select the set of projects that together constitute a coherent, high quality and balanced portfolio within the scope of the call and the available budget. This includes ensuring diversity across research approaches, topics and disciplines, and precluding unnecessary concentration or duplication.

The RFC may, in justified cases, prioritize a scientifically fundable proposal that is ranked slightly lower over a higher ranked proposal, where this is necessary to achieve an overall stronger and more balanced portfolio. Such decisions are taken within the published criteria and documented.

Further information on the review and evaluation process will be provided in the Review and decision process document here shortly.

Deadlines and decisions

End March 2026: Call for proposals published
End May 2026: Application portal opens
5 July 2026 midnight CET: Application deadline
End October 2026: Public announcement of funding decisions

Generative AI policy

Applicants may use generative AI tools when preparing proposals but remain fully responsible for the content, including accuracy, originality and compliance with legal and research integrity standards. Any use of generative AI must be transparent and must not compromise confidentiality, privacy or intellectual property rights.

Applicants are encouraged to consult the European Commission’s Living guidelines on the responsible use of generative AI in research.

 

If you have questions related to the call, please contact: researchfunding@detnorskeveritas.com

 

[1] These universities are formally recognised and granted degree-awarding powers by the competent national education or accreditation authorities in their respective countries (e.g. ministries or national higher education authorities). All applicants must include a commitment letter confirming institutional support, signed by the Head of Faculty (or equivalent authority) at the host university.

FAQ

  • The Det Norske Veritas Foundation is a free-standing, autonomous and independent foundation whose purpose is to safeguard life, property and the environment. This purpose is achieved through its ownership of companies – of which the most important is the DNV group, which is 100% owned by the foundation and the newly established funding for basic scientific research.

     

  • For the first year of the initiative, the Foundation has chosen to focus on accredited Nordic universities to ensure a clear, manageable, and high-quality starting point. These universities are formally recognized by national education authorities and granted degree-awarding powers, providing a consistent and trusted quality framework across countries. This approach allows the Foundation to establish robust processes before considering a broader institutional scope.
  • This initial geographic anchoring provides a focused starting point for the research funding to increase impact and supports operational learning in the first funding cycle. This anchoring is an operational choice for 2026, not a long-term geographic definition. The Foundation’s long-term ambition is global, and the geographic scope of future calls is expected to be reviewed and may evolve over time as part of the Board’s regular oversight, learning, and strategic development of the programme.
  • The funding is designed to support excellent basic scientific research carried out at Nordic universities, but collaboration and co‑funding are not requirements. Projects may be fully funded by the funding initiative. Applicants may include co‑funding from other sources where relevant, but the presence or absence of co‑funding will not determine eligibility. Applications are evaluated on their own merits according to published evaluation criteria, regardless of co-funding or whether the research is conducted by a single institution or involves multiple universities.
  • One researcher initiates the application in the portal and may involve other researchers as collaborators. The accredited Nordic university acts as the formal applicant and host institution.
  • The Board of Stiftelsen Det Norske Veritas has established the Research Funding Committee (RFC) to help ensure that the Foundation’s funding of basic scientific research is carried out in a structured, transparent and well‑governed way. The RFC supports the Board by assessing applications and preparing recommendations within the frameworks the Board has approved.
     
    The Board sets the overall direction for the research funding programme. This includes defining the themes for funding, the criteria used to assess applications and the annual budget. All decisions made by the RFC are taken within these Board‑approved parameters, and the Board retains full oversight of the programme.
     
    The RFC may include external experts to secure strong scientific insight and breadth of perspective. Their involvement does not change that the RFC and ultimately the Foundation Board remains fully responsible for the programme and can provide guidance or make changes whenever needed. 
     
    Through this model, the Foundation combines high scientific quality with clear governance: expert input where it matters, and firm Board ownership to ensure that the programmes are aligned with the Foundations’ purpose, priorities and integrity. 
Autonomous

Autonomous systems call

Basic research to understand risks and uncertainties to ensure that autonomous systems can operate safely, reliably and ethically.

Autonomous

Critical raw materials call

Basic research on strategic raw materials, related to discovery, extraction and processing, as well as the development of new alternatives and circular solutions.

Societal Risk

Societal risks call

Basic research on how climate hazards and growing digital dependence increase climate risk for critical infrastructure, and what this means for its reliability, availability, safety, and security.