Responsible AI Innovation
"Responsible AI innovation means developing and using technology in a way that is ethical, human-centred, and aligned with the goals of industry, and society. We combine state-of-the-art research with practical experience in technology transfer, governance of emerging technologies, and multi-stakeholder engagement to promote AI for the common good"
Expertise and Services
Expertise
- Responsible research, innovation and AI governance and certification
- Trustworthiness-by-design in AI systems and AI risk management
- Stakeholder engagement, AI literacy and scientific diplomacy
- High-impact AI applications: neurotechnology, health and critical infrastructure
The "Responsible AI Innovation" (RAI) group focuses on the technical, governance and ethical aspects of AI. Our work develops both technical and non-technical approaches that enable organisations to successfully turn AI technologies into solutions that create both economic and societal value. We are particularly interested in AI applications with a strong impact on people and society, such as healthcare, neurotechnologies, human–machine interaction, and automated decision-making. Our work explores all aspects of AI governance, covering organisational practices, regulatory and certification requirements, socio-technical standards, Trustworthy AI, and human-centred technology. Responsible Innovation depends on close collaboration between different stakeholders and disciplines. RAI works with a wide network of national and international organisations, including: SCRAI, CAIRNE, ADRA, SATW, IEEE Standards Organization, IEEE Brain, The Geneva Center for Security Policy, GESDA, OECD, and the Institute for Neuroethics.
Services
- Insight: keynotes, trainings, public outreach, scientific diplomacy
- AI consultancy: workshops, expert support, advise, technology and ethical assessment
- Research and development: small to large-scale collaborative projects, third party-funded research, student projects, commercially applicable prototypes
Responsible AI Innovation
Team
Head of Research Group
Projects
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Trustworthy AI Circle (TAIC)
In a time when artificial intelligence is rapidly moving from experimentation into everyday practice, the gap between high-level principles and real-world implementation is becoming increasingly visible. While frameworks for trustworthy AI are evolving, their translation into concrete decisions,…
current, 05/2026 - 10/2027
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A data-driven solution that optimizes ankle-foot-orthopedic braces for children (OrthoSense)
OrthoSense by Leg&airy revolutionizes ankle-foot orthotics by turning subjective brace fitting into data-driven care. Embedded sensors capture pressure data, enabling AI driven biomechanical algorithms to tailor each brace’s shape and fit to the individual patient while enabling patients tracking.
current, 01/2026 - 12/2027
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SCRAI – A Think-and-Do-Tank for Responsible Development and Societal Alignment of Artificial Intelligence Systems
SCRAI brings responsible AI to the ground by bridging the gap between societal values and development of AI technology and solutions. The SCRAI Think-and-Do Tank will help organizations to exploit the potential of AI while complying with legal requirements and being compatible with societal…
current, 04/2025 - 12/2029
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Certification program for assessing ethics of Autonomous Intelligent Systems (IEEE CertifAIEd Assessor Training)
ZHAW is offering, in partnership with IEEE SA, the IEEE CertifAIEd (TM) Authorized Assessor Training. IEEE CertifAIEd is a certification program for assessing ethics of Autonomous Intelligent Systems (AIS) to help protect, differentiate, and grow product adoption. The resulting certificate and mark…
expired, 05/2024 - 07/2025
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Brain Research International Data Governance & Exchange – Phase II
The goal of this project is to develop an International Data Governance Framework (IDGF) that can advance responsible international brain research and innovation. This will start with the identification of the technical, legal, ethical and organizational challenges to IDGF and the development of…
expired, 04/2024 - 04/2025
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Apéro Digital: Event Series
In the midst of societal digital transformation, post-pandemic economic recovery, and geopolitical tensions around the globe, the need for a carefully curated space for deliberation and networking presents unprecedented urgency. Against this backdrop, we propose the creation of an intellectually…
expired, 03/2024 - 08/2025
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Brain Research International Data Governance & Exchange
The goal of this project is to develop an International Data Governance Framework (IDGF) that can advance responsible international brain research and innovation. This will start with the identification of the technical, legal, ethical and organizational challenges to IDGF and the development of…
expired, 11/2023 - 04/2024
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AI for REAL-world NETwork operation (AI4REALNET)
The scope of AI4REALNET covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic management) modelled by networks that can be simulated, and are traditionally operated by humans, and where AI systems complement and augment human abilities. It…
current, 10/2023 - 03/2027
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Consulting Service for the preparation of the GESDA Anticipation Observatory
The Geneva Science and Diplomacy Anticipator (GESDA) is developing the “Anticipation Observatory". The observatory is aimed at equipping decision-makers with the necessary navigation tools to best support research and policy-making in technology and their applications in society. By understanding…
expired, 07/2023 - 12/2025
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certAInty – A Certification Scheme for AI systems (certAInty)
Certification of AI Systems by an accredited body increases trust, accelerates adoption and enables their use for safety-critical applications. We develop a Certification Scheme comprising specific requirements, criteria, measures, and technical methods for assessing Machine Learning enabled…
expired, 11/2022 - 12/2024
Publications
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Frischknecht-Gruber, Carmen; Denzel, Philipp; Forster, Oliver; Billeter, Yann; Iranfar, Arman; Repetto, Marco; Reif, Monika Ulrike; Schilling, Frank-Peter; Weng, Joanna; Chavarriaga, Ricardo,
2025.
In:
AI Days @ HES-SO, Geneva and Lausanne, Switzerland, 27–29 January 2025.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-32422
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Frischknecht-Gruber, Carmen; Denzel, Philipp; Reif, Monika; Billeter, Yann; Brunner, Stefan; Forster, Oliver; Schilling, Frank-Peter; Weng, Joanna; Chavarriaga, Ricardo; et al.,
2025.
AI assessment in practice : implementing a certification scheme for AI trustworthiness[paper].
In:
Görge, Rebekka; Haedecke, Elena; Poretschkin, Maximilian; Schmitz, Anna, eds.,
Symposium on Scaling AI Assessments (SAIA 2024).
Symposium on Scaling AI Assessments (SAIA 2024), Cologne, Germany, 30 September - 1 October 2024.
Schloss Dagstuhl – Leibniz-Zentrum für Informatik.
pp. 15:1-15:18.
Open Access Series in Informatics (OASIcs) ; 126.
Available from: https://doi.org/10.21256/zhaw-32423
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Sultana, Mushfika; Jain, Osheen; Halder, Sebastian; Matran-Fernandez, Ana; Nawaz, Rab; Scherer, Reinhold; Chavarriaga, Ricardo; del R. Millán, José; Perdikis, Serafeim,
2024.
Evaluating dry EEG technology out of the lab[paper].
In:
2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE).
IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), St. Albans, United Kingdom, 21-23 October 2024.
IEEE.
pp. 752-757.
Available from: https://doi.org/10.21256/zhaw-32544
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Billeter, Yann; Denzel, Philipp; Chavarriaga, Ricardo; Forster, Oliver; Schilling, Frank-Peter; Brunner, Stefan; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike; Weng, Joanna,
2024.
MLOps as enabler of trustworthy AI[paper].
In:
2024 11th IEEE Swiss Conference on Data Science (SDS).
11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024.
IEEE.
pp. 37-40.
Available from: https://doi.org/10.21256/zhaw-30443
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Denzel, Philipp; Brunner, Stefan; Billeter, Yann; Forster, Oliver; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike; Schilling, Frank-Peter; Weng, Joanna; Chavarriaga, Ricardo; Amini, Amin; Repetto, Marco; Iranfar, Arman,
2024.
Towards the certification of AI-based systems[paper].
In:
2024 11th IEEE Swiss Conference on Data Science (SDS).
11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024.
IEEE.
pp. 84-91.
Available from: https://doi.org/10.21256/zhaw-30439