Close X

Call: Verifiable robustness, energy efficiency and transparency for Trustworthy AI: Scientific excellence boosting industrial competitiveness (AI, Data and Robotics Partnership)

Acronym HE-CL4-HUMAN
Type of Fund Direct Management
Description of programme
"Horizon Europe - Cluster 4 - Destination 6: A Human-centred and Ethical Development of Digital and Industrial Technologies"

This destination will directly support the following Key Strategic Orientations, as outlined in the Strategic Plan:

  • KSO D, Creating a more resilient, inclusive and democratic European society, prepared and responsive to threats and disasters, addressing inequalities and providing high-quality health care, and empowering all citizens to act in the green and digital transitions

Proposals for topics under this Destination should set out a credible pathway contributing to the following expected impact:

  • A human-centred and ethical development of digital and industrial technologies, through a two-way engagement in the development of technologies, empowering end-users and workers, and supporting social innovation.

As Europe takes the lead in the green and digital transitions, workers, regions, and societies are faced with extremely fast transformations, and will be differently affected by these changes. The rapid adoption of new technologies offers an immense potential for improved standards of living, safer mobility, better healthcare, new jobs, or the personalisation of public services. At the same time, it presents risks such as skills mismatches, digital divides, customer lock-in, or serious breaches of security or privacy.

As Europe sets off on its path to recovery towards a greener, digital and more resilient economy and society, the need to improve and adapt skills, knowledge and competences becomes all the more important. Developments in digital and enabling technologies have the potential to enhance social inclusion, can inform up-skilling training programmes and ensure a two-way engagement with society with regard to developing technologies.

The issue of trust has become central in the use of technologies, following revelations about the exploitation of personal data, large-scale cybersecurity and data breaches, and growing awareness of online disinformation. As outlined in the White Paper on Artificial Intelligence (COM(2020)65), for AI technologies, trust requires in particular improving transparency (explainability, expected levels of performance). For the Internet, increasing trust requires new tools and services to ensure that GDPR is a reality for end-users.

It is also an opportunity for Europe to re-gain presence on the consumer electronics market, by developing new interactive applications in various sectors with solutions meeting European values and requirements in terms of privacy and security. The COVID-19 crisis has also shown how important distance and innovative learning is for society.

Actions under this Destination will support EU objectives of inclusiveness, by supporting a human-centred approach to technology development that is aligned with European social and ethical values, as well as sustainability. These actions will further contribute to addressing the challenges faced by European industry and support the creation of sustainable, high-quality jobs by targeting skills mismatches, the need to empower workers, and ethical considerations relating to technological progress.

Actions should devote particular attention to openness of the solutions and results, and transparency of the research process. To ensure trustworthiness, public awareness and support, wide adoption by user communities for the benefit of society, actions should promote the highest standards of transparency and openness. Actions should ensure that the processes and outcomes of research and innovation align with the needs, values and expectations of society, in line with Responsible Research and Innovation.

This Destination is structured into the following headings, which group topics together with similar outcomes to address a common challenge:

Leadership in AI based on trust

The objective of this heading is to ensure autonomy for Europe in AI, leading the way in research, development and deployment of world-class technologies that are beneficial to humans individually, organisationally and societally, and that adheres to European values, such as the principles reflected in our fundamental rights and environmental sustainability. Technologies need to be developed that industries and citizens will trust, so and that they could be applied in a wide range of applications and industrial sectors. Trustworthy AI is particularly key in applications such as (but not limited to) healthcare or in diverse critical infrastructures such as energy and transportation.

Some topics of this heading are under the co-programmed Partnership ‘AI, Data and Robotics’.

Proposals are encouraged to link with relevant European Institute of Innovation and Technology (EIT) and its Knowledge and Innovation Communities (KICs), in particular the EIT Digital.

EIT Digital plays role in shaping technologies and innovations that work for people. At least two of its focus areas, Digital Wellbeing and Digital Cities, address directly topics such as ethical artificial intelligence, predictive analytics or augmented and virtual reality that are relevant to this areas. The solutions will benefit from the increasing will of citizens to participate in the sharing economy. EIT Digital, through projects with cities for example, improves engagement and inclusiveness of the citizens and of the visitors by increasingly organising and exposing data, especially in real time and along with analytics and machine learning. Augmented and virtual reality of the cities are another facet of exposing or simulating city data from the past, present or future to the benefit of citizens. ​

An Internet of Trust

The issue of trust in the internet has become central, following revelations about the exploitation of personal data, large-scale cybersecurity and data breaches, and growing awareness of online disinformation. A 2019 survey[[]] shows that half of the global internet users are more concerned about their online privacy compared to a year previously. Distrust in the Internet is causing people to change the way they behave online, for example by disclosing less personal information. Users also express an increasing level of distrust of social media platforms.

The objective of this heading is to develop a trustworthy digital environment, built on a more resilient, sustainable, and decentralised internet, to empower end-users with more control over their data and their digital identity, and to enable new social and business models respecting European values.

eXtended Reality (XR)

Due to its low presence in the consumer electronics industry, Europe is increasingly dependent on external providers in this area. This raises concerns about its digital sovereignty in crucial domains such as digital interaction services that are being adopted by a growing number of European users and industries. The COVID-19 crisis has shown how important distance and innovative learning is for society, our children, their parents and their teachers, maintaining social and educational links under challenging circumstances. Emerging technologies such as virtual reality, eXtended Reality or immersive environments provide numerous opportunities for personalised, innovative, efficient and inclusive learning, for learners of all ages, gender and condition

The objective of this heading is to gain industrial leadership in eXtended Reality technologies and immersive environments, while ensuring the European values of privacy, ethics and inclusiveness. It also aims to support the digital transformation of education through these technologies in particular.

Systemic approaches to make the most of the technologies within society and industry.

This heading promotes various systemic approaches to encourage creativity and make the most of the technologies developed elsewhere within society and industry. They include testing ideas in local communities; support for IP, standardisation and industry-academia exchanges; art-driven design; and assessments of complex socio-economic systems. These are complemented by support for a network of National Contact Points (NCPs), with a special emphasis on engaging with new actors.

Activities beyond R&I investments will be needed to realise the expected impacts: testing, experimentation, demonstration, and support for take-up using the capacities, infrastructures, and European Digital Innovation Hubs made available under the Digital Europe Programme; further development of skills and competencies via the European Institute of Innovation and Technology, in particular EIT Digital and EIT Manufacturing; upscaling of trainings via the European Social Fund +; use of financial instruments under the InvestEU Fund for further commercialisation of R&I outcomes; and links to the thematic smart specialisation platform on industrial modernisation

Expected impact

Proposals for topics under this Destination should set out a credible pathway to contributing to a human-centred and ethical development of digital and industrial technologies, and more specifically to one or several of the following impacts:

  • Increased inclusiveness, by supporting a human-centred approach to technology development that is aligned with European social and ethical values, as well as sustainability;
  • Sustainable, high-quality jobs by targeting skills mismatches, the need to empower workers, and ethical considerations relating to technological progress[[2019 CIGI-Ipsos Global Survey on Internet Security and Trust]].
Link Link to Programme
Verifiable robustness, energy efficiency and transparency for Trustworthy AI: Scientific excellence boosting industrial competitiveness (AI, Data and Robotics Partnership)
Description of call
"Verifiable robustness, energy efficiency and transparency for Trustworthy AI: Scientific excellence boosting industrial competitiveness (AI, Data and Robotics Partnership)"

Expected Outcome:

Proposal results are expected to contribute to at least one of the following expected outcomes:

  • World-class transparent, explainable, accountable and trustworthy AI, based on smarter, safer, secure, resilient, accurate, robust, reliable and dependable solutions.
  • Improved AI solutions aiming to meet the industrial requirements in terms of autonomy, accuracy, safety, repeatability, robustness, resilience, security, etc.
  • Greener AI.
  • Next level of AI-based solutions, exploiting the intelligence embedded in the edge-to cloud infrastructure
  • Advances in complex systems & socially aware AI


Develop trustworthy AI technology, key for acceptance, to take full advantage of the huge benefits such technology can offer, and demonstrate the benefits in particular applications. This will require improvement in transparency: explainability, accountability and responsibility, safety, expected levels of technical performance (accuracy, robustness, level of ‘intelligence’ and autonomy, etc.) which are guaranteed/verifiable and with corresponding confidence levels.

Build the next level of “intelligence” and autonomy, essential to scale-up deployment, in solving wider set and more complex problems, adapting to new situations and context knowledge, addressing real-time performance requirements and data and energy efficiency, also for greener AI and robotics solutions. This will investigate approaches such as integration of both learning and reasoning, causality, contextualization and knowledge discovery, hybrid semi-parametric models (combining laws of physics with observations, aka physics-informed machine learning), human-in-the loop approaches, etc.

Contribute to making AI and robotics solutions meet the requirements of Trustworthy AI, based on the respect of the ethical principles, the fundamental rights, including privacy. Ethics principles needs to be adopted from early stages of AI development and design.

In this topic, solid scientific developments will be complemented, as relevant, by tools and processes for design, testing and validation, certification (where appropriate), software engineering methodologies, as well as approaches to modularity and interoperability, aimed at real-world applications. Where appropriate proposals are encouraged to propose standardisation methods to foster AI industry, helping to create, and guarantee trustworthy and ethical AI, and in support of the Commission regulatory framework.

Scientific proposals are expected to focus on advancing the state of the art in one of the major research areas below:

  1. Novel or promising learning (such as unsupervised, self-supervised, representational learning capable of contextualization, transfer learning, life-long and continual learning, etc.) as well as symbolic and hybrid approaches. The objective is to advance “intelligence” and autonomy of AI-based systems, essential to scale-up deployment, in solving a wider set of more complex problems, adapting to new situations (making them “smarter”, more accurate, robust, dependable, versatile, reliable, secured, safer, etc.), and addressing real-time performance requirements, where relevant, for both robotics and non-embodied AI systems. This will include, among others, integration of both learning and reasoning, combining data-driven and knowledge-based models, causality, contextualization and knowledge discovery. Approaches can build on simulation and digital twins, or include data augmentation, knowledge modelling, federation of AI systems – including the use of distributed data – federated learning, and new AI methods ensuring scalability and re-usability. This topic also supports innovative or promising approaches addressing functional and performance guarantees.
  2. Advanced transparency in AI, including advances in explainability, in transparency (with guaranteed/verifiable levels of performance, confidence levels, etc.), investigating novel or improved approaches increasing users’ understanding of AI system behaviour, and therefore increasing trust in such systems.
  3. Greener AI, increasing data and energy efficiency. This covers research towards lighter, less data-intensive and energy-consuming models, optimized learning processes to require less input (data efficient AI), or optimized models, data augmentation, synthetic data, transfer learning, one-shot learning, continuous / lifelong learning, and optimized architectures for energy-efficient hardware, framework that optimises calculations for energy reduction in big data analytics. This also build on latest results in self-configuring, low-power or energy harvesting capable sensor devices, and low power data transmission and energy reduction in big data analytics (e.g. a framework that optimises calculations, leading to decreasing use of energy, etc.).
  4. Advances in edge AI networks, bringing intelligence near sensors, in embedded systems with limited computational, storage and communication resources, as well as the integration of advanced and adaptive sensors and perception (including multi-modal sensing and active perception, distributed sensing, etc.), but also optimising edge vs cloud AI to maximise the capabilities of the overall system (both globally and for individual users). This builds on latest hardware development (for which synergies with the European Partnership for Key Digital Technologies (KDT) is encouraged), but does not cover such hardware developments.
  5. Complex systems & socially aware AI: able to anticipate and cope with the consequences of complex network effects in large scale mixed communities of humans and AI systems interacting over various temporal and spatial scales. This includes the ability to balance requirements related to individual users and the common good and societal concerns, including sustainability, non-discrimination, equity, diversity etc.

Proposals should clearly identify its focused research area among the 5 listed above.

Proposals should include, as appropriate, the development of tools and processes for design, testing and validation, deployment and uptake, auditing, certification (where relevant), software engineering methodologies, as well as approaches to modularity and interoperability.

To complement the impressive progress in developing individual AI algorithms and components, proposals could also address the development of scientific foundations for designing, modelling, analysing, operating, monitoring, integrating, maintaining and extending AI systems.

In all these topics, involvement of multidisciplinary teams and transdisciplinary research, including SSH as appropriate, will be essential. The consortia should involve world-class research labs and top scientists, joining forces to address these major scientific challenges, and they are strongly encouraged to team up with European companies (large and small) representing major industrial sectors for Europe, genuinely interested in S&T progress in these fields, and which consider adoption of AI “made in Europe” key for their competitiveness.

While the proposals should address scientific foundations, relevance to real-world applications should be demonstrated, in particular through use-cases used to demonstrate scientific progress.

All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, demonstrators, benchmarking and progress monitoring), and share communicable results with the European R&D community, through the AI-on-demand platform, a public community resource, to maximise re-use of results and efficiency of funding.

Activities are expected to achieve TRL 4-5 by the end of the projects.

Proposals should foresee activities to collaborate with projects stemming from topics relevant to AI, Data and Robotics, primarily in destinations 3, 4 and 6, but also in other destinations and clusters (in particular Cluster 3 on cybersecurity where relevant), and share or exploit results where appropriate.

This topic implements the co-programmed European Partnership on AI, Data and Robotics.

All proposals are expected to allocate tasks to cohesion activities with the PPP on AI, Data and Robotics and funded actions related to this partnership, including the CSA HORIZON-CL4-2021-HUMAN-01-02.

Link Link to Call
Thematic Focus Research & Innovation, Technology Transfer & Exchange, Capacity Building, Cooperation Networks, Institutional Cooperation, Clustering, Development Cooperation, Economic Cooperation, Digitisation, ICT, Telecommunication, Energy Efficiency & Renewable Energy, Green Technologies & Green Deal, Health, Social Affairs, Sports, Consumer Protection, Disaster Prevention, Resiliance, Risk Management
Funding area EU Member States
Overseas Countries and Territories (OCTs)
Origin of Applicant EU Member States
Overseas Countries and Territories (OCTs)
Eligible applicants Research Institution, International Organization, Small and Medium Sized Enterprises, SMEs (between 10 and 249 employees), Microenterprises (fewer than 10 employees), NGO / NPO, Public Services, Other, Start Up Company, University, Enterprise (more than 250 employees or not defined)
Applicant details

eligible non-EU countries:

  • countries associated to Horizon Europe
At the date of the publication of the work programme, there are no countries associated to Horizon Europe. Considering the Union’s interest to retain, in principle, relations with the countries associated to Horizon 2020, most third countries associated to Horizon 2020 are expected to be associated to Horizon Europe with an intention to secure uninterrupted continuity between Horizon 2020 and Horizon Europe. In addition, other third countries can also become associated to Horizon Europe during the programme. For the purposes of the eligibility conditions, applicants established in Horizon 2020 Associated Countries or in other third countries negotiating association to Horizon Europe will be treated as entities established in an Associated Country, if the Horizon Europe association agreement with the third country concerned applies at the time of signature of the grant agreement.

  • low-and middle-income countries

Legal entities which are established in countries not listed above will be eligible for funding if provided for in the specific call conditions, or if their participation is considered essential for implementing the action by the granting authority.

Specific cases:

  • Affiliated entities - Affiliated entities are eligible for funding if they are established in one of the countries listed above.
  • EU bodies - Legal entities created under EU law may also be eligible to receive funding, unless their basic act states otherwise.
  • International organisations - International European research organisations are eligible to receive funding. Unless their participation is considered essential for implementing the action by the granting authority, other international organisations are not eligible to receive funding. International organisations with headquarters in a Member State or Associated Country are eligible to receive funding for ‘Training and mobility’actions and when provided for in the specific call conditions.
Project Partner Yes
Project Partner Details

Unless otherwise provided for in the specific call conditions , legal entities forming a consortium are eligible to participate in actions provided that the consortium includes:

  • at least one independent legal entity established in a Member State;and
  • at least two other independent legal entities, each established in different Member States or Associated Countries.
Further info

Proposal page limits and layout:

The application form will have two parts:

  • Part A to be filled in directly online  (administrative information, summarised budget, call-specific questions, etc.)
  • Part B to be downloaded from the Portal submission system, completed and re-uploaded as a PDF in the system

Page limit - Part B: 45 pages

Type of Funding Grants
Financial details
Expected EU contribution per projectThe Commission estimates that an EU contribution of around EUR 4.00 million would allow these outcomes to be addressed appropriately. Nonetheless, this does not preclude submission and selection of a proposal requesting different amounts.
Indicative budgetThe total indicative budget for the topic is EUR 36.00 million.
Typ of ActionResearch and Innovation Actions (RIA)
Funding rate100%

Activities are expected to start at TRL 2-3 and achieve TRL 4-5 by the end of the project.

To ensure a balanced portfolio covering a broad range of AI research areas and approaches, grants will be awarded to applications not only in order of ranking but at least also to the three highest ranked proposals in the research area addressing novel or promising approaches to advance “intelligence” and autonomy of AI-based systems, and at least to the top ranked proposal within each of the four other research areas, provided that the applications attain all thresholds.

Submission Proposals must be submitted electronically via the Funding & Tenders Portal Electronic Submission System. Paper submissions are NOTpossible.

Register now and benefit from additional services - it is free of cost!


Published on 23.09.2022

Interreg Maritime - 5th Call

Interreg Maritime

Link to Call

Published on 14.09.2022

Perform EU

Creative Europe - Culture Strand

Link to Call
Loading Animation