It is our distinct pleasure to inform you that Assessment for Responsible AI has been selected by the ISSIP Awards Committee as the winner of Excellence in Service Innovation with Distinguished Recognition – Impact to Society.
This prestigious award is given once each year to a company or organization that has designed, developed, or deployed a novel solution that, in the judgment of the ISSIP Awards Committee, is the most innovative of all the submissions for that year in its category.
The categories are ‘impact to business,’ ‘impact to society’ and ‘impact to innovation.’
💡 Your project came first in the category of ‘Distinguished Recognition – Impact to Society.’
The judging criteria is based on the uniqueness, creativity, technical merit, value generation and impact of the innovative solution.
ISSIP is proud to recognize the outstanding commitment of your team and Rijks ICT Gilde (Dutch Ministry of the Interior and Kingdom Relations (BZK)), Province of Fryslân, The Netherlands, and Z-Inspection® Initiative to service innovation which should serve as an inspiration to other innovators across the globe.
Again congratulations! Haroon Abbu, Chair of the ISSIP Awards Committee cc Michele Carroll, Jim Spohrer
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2025-03-31 02:31:392025-03-31 02:38:50Our pilot project: “Assessment for Responsible Artificial Intelligence” together with Rijks ICT Gilde -Ministry of the Interior and Kingdom Relations (BZK)- and the province of Fryslân (The Netherlands) is the Winner of the 2025 ISSIP Awards Excellence in Service Innovation with Distinguished Recognition – Impact to Society.
Our multi-disciplinary team has already grown to 32 experts, covering various disciplines, including computer science, explainable artificial intelligence, software engineering, psychiatry, law, ethics, philosophy, and other areas of medicine and social sciences.
Our aim is the co-design of a Trustworthy Explainable AI system for mental health monitoring using speech.
The motivation behind ExplainMe stems from the observation that most state-of-the-art systems supporting remote mental health monitoring lack transparency in their reasoning and decision-making. At the same time, research confirms that acoustic features extracted from speech serve as valid markers for assessing the severity of manic and depressive symptoms. ExplainMe addressed this gap and aims to design an Explainable AI system for mental health monitoring using speech.
The project “ExplainMe: Explainable Artificial Intelligence for Monitoring Acoustic Features Extracted from Speech” (FENG.02.02-IP.05-0302/23) coordinated by Katarzyna Kaczmarek-Majer is carried out within the First Team programme of the FNP Foundation for Polish Science co-financed by the European Union under the European Funds for Smart Economy 2021-2027 (FENG).
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2025-03-21 09:10:572025-03-31 02:34:17In March of this year, we started the trustworthiness assessment of the ExplainMe project using the Z-Inspection® methodology.
” “The pilot we as the Dutch government conducted together with the Z-Inspection® Initiative and Trustworthy AI Labs was one of the best experiences in my professional life so far”, I said as a panelist at the Z-Inspection World Conference in Hamburg last Friday, and with that I was not exaggerating.” — Willy Tadema, AI Governance & AI Ethics at Rijksoverheid
” Last week I had the pleasure to be part of the second world Z-Inspection® Initiative and Trustworthy AI Labs conference – such a great opportunity to discuss ideas on responsible AI with like-minded experts from all around the world!” — Jean Enno Charton, Director Digital Ethics & Bioethics, Merck Group.
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2024-09-01 08:53:572024-09-15 09:24:32Successfully completed the Second World Z-inspection® Conference, Friday, August 23 and Saturday, August 24, 2024 Hamburg, Germany
I am super proud of our work together and very happy to share with you that the big report for our pilot project is now public online in ArXiv!
” This report is made public. The results of this pilot are of great importance for the Dutch government, serving as a best practice with which public administrators can get started, and incorporate ethical and human rights values when considering the use of an AI system and/or algorithms. It also sends a strong message to encourage public administrators to make the results of AI assessments like this one, transparent and available to the public.”
Lessons Learned in Performing a Trustworthy AI and Fundamental Rights Assessment
This report shares the experiences, results and lessons learned in conducting a pilot project “Responsible use of AI” in cooperation with the Province of Friesland, Rijks ICT Gilde-part of the Ministry of the Interior and Kingdom Relations (BZK) (both in The Netherlands) and a group of members of the Z-Inspection® Initiative. The pilot project took place from May 2022 through January 2023. During the pilot, the practical application of a deep learning algorithm from the province of Frŷslan was assessed. The AI maps heathland grassland by means of satellite images for monitoring nature reserves. Environmental monitoring is one of the crucial activities carried on by society for several purposes ranging from maintaining standards on drinkable water to quantifying the CO2 emissions of a particular state or region. Using satellite imagery and machine learning to support decisions is becoming an important part of environmental monitoring. The main focus of this report is to share the experiences, results and lessons learned from performing both a Trustworthy AI assessment using the Z-Inspection® process and the EU framework for Trustworthy AI, and combining it with a Fundamental Rights assessment using the Fundamental Rights and Algorithms Impact Assessment (FRAIA) as recommended by the Dutch government for the use of AI algorithms by the Dutch public authorities.
Comments: On behalf of the Z-Inspection® Initiative
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2024-04-23 07:44:272024-04-23 07:44:28Lessons Learned in Performing a Trustworthy AI and Fundamental Rights Assessment
The Z-inspection® initiative lead Roberto V. Zicari on Wednesday December 6th announced the creation of a 12-member advisory body to address Generative AI for Higher Education in Practice.The advisory board will support the Z-inspection® initiative international community’s efforts to assess the risks, opportunities of using Generative AI in higher education in practice, within the pilot project “Assessing the use of Generative AI in Higher Education” .
The project follows the UNESCO guidance for policymakers on Generative AI and education: Pilot testing, monitoring and evaluation, and building an evidence base
The members are listed below:
Kiran Bhujun, Professor, Director of the Tertiary Education and Scientific Research Division of the Ministry of Education, Tertiary Education, Science and Technology of the Republic of Mauritius.
Yves Deville, Professor, Université catholique de Louvain. Senior Advisor to the President for the Digital University at UCLouvain. Belgium
Julio Cesar Duhalde, Technical, economic and legal advisor at the Ministry of Economy – Buenos Aires, Argentina.
Erja Heikkinen, PhD, Director General (temp), Ministry of Education and Culture, Helsinki, Finland
Lambert Hogenhout, Chief Data, Analytics and Emerging Technologies, United Nations, New York, USA.
Jonathan Michie OBE FAcSS, Professor of Innovation and Knowledge Exchange, University of Oxford, Pro-Vice-Chancellor (without portfolio), President of Kellogg College, University of Oxford, UK.
Irina Mirkina, AI Lead, Office of Innovation, UNICEF, Stockholm, Sweden.
Victor Ochen, The African Youth Initiative Network (AYINET). Member of the Advisory Group to the United Nations High Commissioner for Refugees at United Nations- Lira, Uganda.
Sung Jae Park, Ph.D. Research fellow, Korean Educational Development Institute (KEDI). Former Senior Advisor to the Deputy Prime Minister and Minister of Education of the Republic of Korea. Seoul, South Korea.
Gerald Santucci, President, EUROPEAN EDUCATION NEW SOCIETY ASSOCIATION (ENSA)- France.
Willy Tadema, AI Ethics Lead, Rijks ICT Gilde (RIG), Ministry of Interior and Kingdom Relations; AI policy advisor, Ministry of Interior and Kingdom Relations; Member of the Dutch National Standards Body for AI (NEN), The Netherlands.
Peter J. Wells, Head of Education Southern Africa, UNESCO- Harare, Zimbabwe.
Find out more on Pilot Project: Assessing Trustworthiness of the use of Generative AI for Higher Education at:
Z-Inspection® is a holistic process based on the method of evaluating new technologies, where ethical issues need to be discussed through the elaboration of socio-technical scenarios. In particular, Z-Inspection® can be used to perform independent assessments and/or self-assessments together with the stakeholders owning the use case.
Z-inspection® is a registered trademark.
This work is distributed under the terms and conditions of the Creative Commons (Attribution-NonCommercial-ShareAlike CC BY-NC-SA) license.
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http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2023-12-06 04:56:002023-12-08 08:33:53The Z-inspection® initiative creates an Advisory Body to address Generative AI for Higher Education in Practice.
lWe published the Lessons Learned from Assessing Trustworthy AI in Practice.
Dennis Vetter, Julia Amann, Frederick Bruneault, Megan Coffee, Boris Düdder, Alessio Gallucci, Thomas Krendl Gilbert, Thilo Hagendorff, Irmhild van Halem, Dr Eleanore Hickman, Elisabeth Hildt, Sune Holm, George Kararigas,Pedro Kringen, Vince Madai , Emilie Wiinblad Mathez, Jesmin Jahan Tithi, Ph.D , Magnus Westerlund, Renee Wurth, PhD, Roberto V. Zicari & Z-Inspection® initiative (2022)
Building artificial intelligence (AI) systems that adhere to ethical standards is a complex problem. Even though a multitude of guidelines for the design and development of such trustworthy AI systems exist, these guidelines focus on high-level and abstract requirements for AI systems, and it is often very difficult to assess if a specific system fulfills these requirements.
The Z-Inspection® process provides a holistic and dynamic framework to evaluate the trustworthiness of specific AI systems at different stages of the AI lifecycle, including intended use, design, and development. It focuses, in particular, on the discussion and identification of ethical issues and tensions through the analysis of socio-technical scenarios and a requirement-based framework for ethical and trustworthy AI.
This article is a methodological reflection on the Z-Inspection® process. We illustrate how high-level guidelines for ethical and trustworthy AI can be applied in practice and provide insights for both AI researchers and AI practitioners. We share the lessons learned from conducting a series of independent assessments to evaluate the trustworthiness of real-world AI systems, as well as key recommendations and practical suggestions on how to ensure a rigorous trustworthiness assessment throughout the lifecycle of an AI system.
The results presented in this article are based on our assessments of AI systems in the healthcare sector and environmental monitoring, where we used the framework for trustworthy AI proposed in the Ethics Guidelines for Trustworthy AI by the European Commission’s High-Level Expert Group on AI. However, the assessment process and the lessons learned can be adapted to other domains and include additional frameworks.
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2023-09-19 10:04:052023-09-19 10:04:07Lessons Learned from Assessing Trustworthy AI in Practice.
This pilot project of the Z-inspection® initiative (https://z-inspection.org) aims at assessing the use of Generative AI in higher level education considering specific use cases.
For this pilot project, we will assess the ethical, technical, domain-specific (i.e. education) and legal implications of the use of Generative AI-product/service within the university context.
We follow the UNESCO guidance for policymakers on AI and education. In particular the policy recommendation 6. : Pilot testing, monitoring and evaluation, and building an evidence base.
Expected Output: a white paper and a peer reviewed journal article as best practice and a set of recommendations for each specific use case. Such recommendations could be also useful for helping clarify the Guidelines that each university is creating for this.
An interdisciplinary team of experts will assess the trustworthiness of Generative AI for selected use cases in High Education using the Z-Inspection® process: https://z-inspection.org
Z-Inspection® is a holistic process based on the method of evaluating new technologies, where ethical issues need to be discussed through the elaboration of socio-technical scenarios. In particular, Z-Inspection® can be used to perform independent assessments and/or self-assessments together with the stakeholders owning the use case.
For the context of this pilot project we define ethics in line with the essence of modern democracy i.e. “respect for others, expressed through support for fundamental human rights”. We take into consideration that “trust” in the development, deployment and use of AI systems concerns not only the technology’s inherent properties, but also the qualities of the socio-technical systems involving AI applications.
Specifically, we consider the ethics guidelines for trustworthy artificial intelligence defined by the EU High-Level Expert Group on AI, which defined trustworthy AI as:
(1) lawful – respecting all applicable laws and regulations
(2) ethical – respecting ethical principles and values
(3) robust – both from a technical perspective and taking into account its social environment
And we use the four ethical principles, rooted in fundamental rights defined in [13], acknowledging that tensions may arise between them:
(1) Respect for human autonomy
(2) Prevention of harm
(3) Fairness
(4) Explicability
Furthermore, we also consider the seven requirements of Trustworthy AI defined by the High Level experts group set by the EU. Each requirement has a number of sub-requirements as indicated in Table 1.
Table 1. Requirements and sub-requirements Trustworthy AI.
1 Human agency and oversight Including fundamental rights, human agency and human oversight
2 Technical robustness and safety Including resilience to attack and security, fall back plan and general safety, accuracy, reliability and reproducibility
3 Privacy and data governance Including respect for privacy, quality and integrity of data, and access to data
4 Transparency Including traceability, explainability and communication
5 Diversity, non-discrimination and fairness Including the avoidance of unfair bias, accessibility and universal design, and stakeholder participation
6 Societal and environmental wellbeing Including sustainability and environmental friendliness, social impact, society and democracy
7 Accountability Including auditability, minimization and reporting of negative impact, trade-offs and redress.
While we consider the seven requirements comprehensive, we believe additional ones can still bring value. Two of such additional requirements proposed by the Z-Inspection® initiative are “Assessing if the ecosystems respect values of Western Modern democracy” and “Avoiding concentration of power” .
“Large artificial intelligence (AI)-based language models such as Chat GPT, Google Bard, and DeepL have evolved to the point where they can produce human-like text and conversations and correct and transform text at such a high level that it can be difficult to distinguish the result from human- generated text. It is foreseeable that more such models will emerge, and their functionalities will continue to evolve, so their existence should be taken into account in university teaching and research.
The existence of large language models should be seen as an opportunity. Degree programmes and teachers are encouraged to use AI in their teaching and to prepare students for a society of the future where AI methods will be widely used.
As AI brings new possibilities for producing text whose origin and reliability is unclear, they should be used in a controlled way. Use may be restricted in teaching in situations where the use would not promote student learning.
At EU level, an AI regulation is under preparation, which will also apply to AI systems in education. In addition, there is an ethical policy on AI and its use, as well as an ethical code for teachers1 . The University’s guidelines may be further specified in the light of future regulation and technological developments.”
1.Policy paper. Generative artificial intelligence in education. UK: The Department for Education’s (DfE) position on the use of generative artificial intelligence (AI) in High Education.Link to .PDF
2. Do Foundation Model Providers Comply with the Draft EU AI Act?Stanford researchers evaluate foundation model providers like OpenAI and Google for their compliance with proposed EU law on AI. Link
They identified a final list of 12 requirements and scored the 10 models using a 5-point rubric. The methodology for the study can be found here.
3. Leading universities in the UK (the Russell Group universities)have developed a set of principles on the use of generative AI tools in education. Here is the link.
4. Frontier AI Regulation: Managing Emerging Risks to Public SafetyarXiv:2307.03718 [cs.CY] LINK
5. Zhaki Abdullah, Students, teachers will learn to properly use tools like ChatGPT: (Singapore Education Minister) Chan Chun Sing, Straits Times, 12 February 2023, LINK
6. U.S. Department of Education, Office of Educational Technology, Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations, Washington D.C., May 2023, LINK
7. Japanese schools to be allowed limited use of generative AI, Kyodo News, 22 June 2023, LINK
8. Higher Education Webinar: Implications of Artificial Intelligence in Higher Education, Tuesday, June 27, 2023, Council on Foreign Relations, LINK
9. Novelli, C., Casolari, F., Rotolo, A. et al.Taking AI risks seriously: a new assessment model for the AI Act. AI & Soc (2023). LINK
10. Academic without Borders, Bimonthly Newsletter n°59, July 2023.
11. On the use of artificial intelligence and in particular of ChatGPT in higher education. (UNESCO). Link to .PDF
12. KU Leuven, Responsible use of Generative Artificial Intelligence (GenAI) in research. These guidelines will be updated with new information and insights to keep them in line with the rapidly evolving technology (last updated June 24, 2023). The further integration of teaching and research guidelines is still on the agenda. LINK
21. Council of Europe: ARTIFICIAL INTELLIGENCE AND EDUCATION A critical view through the lens of human rights, democracy and the rule of law.November 2022
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2023-07-14 15:51:172023-09-08 08:17:10Announcing a New Pilot Project: Assessing Trustworthiness of the use of Generative AI for higher Education.
STARTING PERIOD FEB 2023 EXPECTED GRADUATION APR 2024
The eXplainable Artificial Intelligence in Healthcare Management Masters is developed within an xAIM project supported by a Connecting Europe Facility in Telecom (project INEA/CEF/ICT/A2020/2276680). Our aim is to advance development of highly qualified professionals to address the lack of highly specialized digital skills in AI. The master is designed for anyone interested in understanding the needs of xAI in healthcare, and, in particular for health-related professionals, with a particular focus on the exploitation of the possible applications.
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2023-06-17 12:16:402023-06-17 12:16:41Z-Inspection® is a mandatory course for the new Online Master Program xAIM
George Ulrich (Academic Director, Global Campus of Human Rights),
Elisabeth Hildt (Director, Center for the Study of Ethics in the Professions, Illinois Institute of Technology, and L3S Research Center, Leibniz University Hannover)
Emilie Wiinblad Mathez (Senior Ethics Adviser)
Frédérick Bruneault (adjunct professor, École des médias Unive, Université du Québec,Montréal)
Peter G. Kirchschlaeger (Ethics-Professor, Director of the Institute of Social Ethics ISE, University of Lucerne)
Giovanni Sartor ( Professor in Legal Informatics at the University of Bologna)
Moderator: Holger Volland CEO brand eins, Germany)
Moderator: Holger Volland CEO brand eins, Germany)
10:00 am
– Welcome remarks
Gianpaolo Scarante, Past President Ateneo Veneto
10:10 “Singing tuning with Ahhh.” Alessandro Donati
10:15 am
– Pilot Project “Responsible use of AI” with Rijks ICT Gilde ( Ministry of Interior and Kingdom Relationships) , and the Province of Friesland, The Netherlands
Willy Tadema (AI Ethics Lead, Rijks ICT Gilde, The Netherlands),
Marijke Steege, Marijke (Senior Consultant Strategy Innovation and Data, Rijks ICT Gilde, The Netherlands),
Gerard Kema (Innovator Manager, Province of Friesland, The Netherlands),
Coffee break (11 a.m.)
11:30am
– Trustworthy AI in Practice: Best practices
Mattia Savardi. Davide Farini, Alberto Signoroni
Alberto Signoroni, (University of Brescia, Italy),
Mattia Savardi, (University of Brescia, Italy),
Davide Farina (University of Brescia, Italy),
Hanna Sormunen (Finnish Tax Administration),
Vince Madai (QUEST, Berlin)
Lunch (1:00 p.m.)
2.30pm
– Panel: “How do we trust AI? “
Panelists:
Jean Enno Charton (Director Bioethics & Digital Ethics, Merck),
Bryn Roberts (Global Head of Data &Analytics, Roche),
Sarah Gadd (Head of Data & Artificial Intelligence Solutions, Credit Suisse),
Lisa Bechtold, (Global Lead AI Assurance & Data Governance · Zurich Insurance Company)
Roberto V. Zicari (Lead Z-inspection® initiative),
Sergio Pascolo (President, Venice Urban Lab)
Aperitif (6 p.m.)
Frédérick Bruneault and Pedro Kringen in front of an original Tintoretto.
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2023-03-21 05:18:002023-03-21 10:13:43Impressions of the First World Z-inspection® Conference: Ateneo Veneto, March 10-11, 2023, Venice, Italy.
Artificial Intelligence (AI) is in more and more aspects of our lives. The technology – based on algorithms and data – is in numerous devices and can be useful in solving social issues. For example, about energy, sustainability or poverty. As a government, we have an exemplary role. If we want to seize the opportunities of AI, then important questions about ethics, technology, transparency and the possible effects of AI applications on our society must be answered.
The pilot “Assessment for Responsible AI” is a step in this process. During a three-month pilot, the Rijks ICT Gilde (Ministry of the Interior and Kingdom Relations (BZK)) , in cooperation with the province of Fryslân and AI authority Prof. Dr. Zicari and his team, is investigating a deep learning algorithm in practice.
Reason for the pilot During the conference “AI and the future of Europe” in Brussels on March 30, 2022, Secretary of State Alexandra van Huffelen told us that the digital transition and the use of AI should always be human-centered and based on our democratic values and rights. Governments should lead by example in this regard.
As a government, we want to seize the opportunities of AI, but the technology still raises many important questions. How reliable are algorithms? Can an algorithm discriminate? What are the ethical and social effects of AI and how transparent is its use? In addition, the use of AI must always be human-centered and based on our democratic values and rights.
With that comes an impressive amount of rules, frameworks and frameworks in the field of AI. How do you apply them in practice? What do you need to pay attention to? And how do you integrate them into the development and use of AI?
With the pilot “Assessment for responsible AI” we hope to get answers to these questions and more. First, to stimulate awareness and dialogue about AI within government. And then to be able to confidently deploy the technology for the questions of tomorrow.
Background for the pilot
During this six-month pilot, the practical application of a deep learning algorithm from the province of Fryslân will be investigated and assessed. The algorithm maps heathland grassland by means of satellite images for monitoring nature reserves. The testing of this algorithm is done in collaboration with an international interdisciplinary team, based on the ‘Z-Inspection® method’ – a process to assess Trustworthy AI in Practice.
This involves testing the algorithm for social, ethical, technical and legal implications. This is done in interdisciplinary teams according to a holistic methodology: it looks at the coherence, arrangement and interaction of the features to a system. The holistic nature of the method leaves room for different dimensions and views, and focuses in particular on the interpretation and discussion of ethical issues and tensions.
Pilot objectives The pilot has multiple objectives, so each party can get its own win from the pilot:
A science-based assessment in practice based on a concrete AI application; To understand how to carefully and responsibly organize your processes for developing and using AI; Learning which frameworks, laws, and regulations are important and must be tested in the different phases of development and use; Increasing insight and overview through recommendations; Stimulating dialogue and increasing awareness about applying reliable AI.
Z-Inspection® : A method for responsible AI One of the main characteristics of the Z-Inspection® method is its interdisciplinary nature. The complexity of an AI application is reflected in the composition of the team. The diversity of participants provides a more inclusive assessment of the reliability of an AI application.
Another strong feature of this method is its dynamic application. A standard checklist does not adapt to the case. In contrast, the holistic approach determines which issues are central to the use case (real-world application) at different stages of the process. And assesses which aspects of the case are most important, moving back and forth between intra- and interdisciplinary discussions.
With the application of this method, awareness grows within the own organization, a frame of mind (mindset) emerges for responsible data use and the reliable application of AI. Both Province of Fryslan and the Rijks ICT Gilde are testing the method in practice to learn together how to look at an AI application from different dimensions.
Pilot outcome Using the Z-Inspection® method, the advantages and disadvantages of the AI application under investigation are described. This is done using an ongoing and iterative (repeating and increasingly refining) research process. Participants are hereby given space to openly reflect and document what is known (and unknown) about the capabilities of an AI application as a basis for later evaluations.
Participating parties Several parties are working together in the pilot. The Province of Fryslân, AI authority Prof. Dr. Zicari and his team and the UBR| Rijks ICT Gilde are jointly investigating the reliability of AI applications and their responsible use. Leeuwarden municipality, the University of Groningen/Campus Fryslân and policy advisors of the Ministry of the Interior and Kingdom Relations are participating as observers.
Read more about the participating parties below.
Province of Friesland During the pilot project, a deep learning algorithm of the Province of Fryslân will be evaluated. This algorithm visualizes heather grassing for monitoring nature reserves. The Province of Fryslân is investing in the coming years in the smart and effective use of data. The province sees that almost all provincial developments and social tasks contain a data component. This creates urgency in the subject. To be able to responsibly respond to technological developments as a province, a sharp vision on data and AI is needed. Participation in the pilot helps design the future digital infrastructure and outline ethical frameworks.
UBR | Rijks ICT Gilde The Rijks ICT Gilde (RIG) (Ministry of the Interior and Kingdom Relations (BZK) ) is an ambitious tech organization that implements projects across the central government. The organization uses its knowledge and network to create smart partnerships and solutions. It employs specialists with a drive to help the Netherlands move forward in the fields of data, software and security.
Mycelia is a young, dynamic and energetic programme of the Rijks ICT Gilde that uses the responsible use of data and AI to achieve impact. We do this by answering and filling in relevant questions without compromising the public values and fundamental rights that the government stands for.
With enthusiasm and specific knowledge, Mycelia’s data and AI experts work on impactful and ethically responsible projects for the public sector and collaborate with organizations and experts in order to learn, grow and develop from each other.
With the growth of data and the rise of AI, we see a government that will never be the same again. Responsible use of AI and trust is and will therefore become increasingly important. We believe in helping and supporting each other and an honest and transparent government. We want to leave a better world for the next generations.
In the pilot, the RIG provides expertise on AI, ethics and responsible data use within government.
Timeline The Assessment for Responsible AI pilot took place from May 2022 through January 2023.
Project Members:
Sara M. Beery, Marjolein Boonstra, Frédérick Bruneault, Subrata Chakraborty, Tjitske Faber, Alessio Gallucci, Eleanore Hickman, Gerard Kema, Heejin Kim, Jaap Kooiker, Ruth Koole, Elisabeth Hildt, Annegret Lamadé,
Emilie Wiinblad Mathez Florian Möslein, Genien Pathuis, Rosa Maria Roman-Cuesta, Marijke Steege, Alice Stocco, Willy Tadema, Jarno Tuimala, Isabel van Vledder, Dennis Vetter, Jana Vetter, Elise Wendt, Magnus Westerlund, Roberto V. Zicari
Update (July 15, 2023)
Rijks ICT Gilde has recently published (in Dutch):
http://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.png00Roberto Zicarihttp://z-inspection.org/wp-content/uploads/2020/07/zinspection2-2-300x139.pngRoberto Zicari2022-08-22 09:56:442024-01-22 20:32:49Pilot Project: Assessment for Responsible Artificial Intelligence together with Rijks ICT Gilde -Ministry of the Interior and Kingdom Relations (BZK)- and the province of Fryslân (The Netherlands)
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