Our new piece on Tech Policy Press – The UN Scientific Panel on AI’s Preliminary Report Does Not Establish Its Independence
See our piece in Tech Policy Press on the importance of establishing the independence of the United Nations International Independent Scientific Panel on AI, and our recommendations for how they can do so 👇
Our goal is to provoke new ideas, debate and discussion at the intersection of technology, democracy and policy, with a particular focus on: • Concentrations of power: the interaction of tech platforms, governments and the media and the future of the public sphere; • Geopolitics of technology: how nation states approach technology in the pursuit of advantage; • Technology and the economy: the relationship between markets, business, and labor; • Racism, bigotry, violence oppression: how tech exacerbates or solves such challenges; • Ethics of Technology: how technology should be viewed alongside existing democratic ethos, especially with regard to privacy, surveillance and personal freedoms; • Election integrity participation: mechanisms of democracy, problems such as disinformation and how citizens come to consensus.
We explored the book’s eight AI paradoxes and reflected on what they mean for education, governance and society.
🧠 One discussion focused on the Intelligence Paradox: The more AI can do, the more it highlights the irreplaceable nature of human intelligence. Rather than asking whether AI is intelligent, we considered a Competence Paradox. What is a system actually capable of? How robust, trustworthy and reliable is it?
🎓 Education sparked one of the longest discussions. Generative AI creates a new educational grey zone. It can support learning and reduce unnecessary workload. It can also create an illusion of competence, shallow learning and what one participant called metacognitive laziness. A key idea was productive friction. Learning should not be effortless. The challenge is not to remove struggle, but to ensure that struggle leads to understanding.
This raises a difficult question: should education move away from assessing products and focus more on assessing processes, reasoning and reflection?
👩🎓 Another important point was that students should be part of the solution. They often understand how these tools are used in practice better than institutions assume.
⚖️ The Solution Paradox: Solving problems with technology often creates more problems, lead to an interesting conversation. New tools alone do not transform education. Smartboards did not. Computers did not. AI will not either. Technology without training, support, strategy and institutional change risks becoming an expensive distraction.
🏗️ We also touched upon the material side of AI. Discussions about responsible AI often focus on models andc ompaniex, and pay less attention to energy use, exploitation of labour and governance. Responsible AI cannot be only about models and companies. It must also address the systems, power structures and resources that make AI possible.
⏳ Another theme was speed. In AI, faster is often assumed to be better. But is it? AI forces urgent decisions, yet responsible decisions often require time. Perhaps moving more slowly can sometimes lead to better and more democratic outcomes.
🌍 Some of the takeaways were: – AI is not something that is happening to us. It is something we are actively building, shaping and governing. – That means responsibility sits with researchers, educators, institutions, companies and policymakers alike. – Who gets access to powerful AI systems? Who benefits? Who bears the costs? And who takes responsibility for shaping the future of technology and society?
🙏 Thank you to everyone who joined the discussion and shared their perspectives. Interdisciplinary conversations like these remind us that the future of AI is not only a technical challenge. It is a human one.
Virginia Dignum receives 2026 Nordic DAIR Awards Lifetime Achievement Award in AI
On May 7, 2026, Virginia Dignum, Director of the AI Policy Lab and Professor of Responsible Artificial Intelligence at Umeå University, has been named the 2026 Nordic DAIR Awards Lifetime Achievement winner in AI!
The DAIR Awards, Data and AI Readiness Awards, recognize achievements in data, analytics and AI across the Nordic region. In 2026, the awards are integrated into the Data Innovation Summit in Stockholm, bringing recognized work in AI and data directly into one of the region’s major meeting places for practitioners, leaders and innovators.
This year’s awards focus on maturity and real-world impact in AI and data.
Against this backdrop, Virginia’s recognition highlights her long-standing contribution to responsible AI, AI ethics and AI policy. Her work has helped shape international discussions on how AI can be developed and governed in ways that place human values, accountability and societal benefit at the center.
In its award citation, DAIR writes: “There are few individuals whose work has shaped the ethical and technical landscape of AI as profoundly as Virginia Dignum. As a world-renowned researcher and a leading voice in Responsible AI, Virginia has spent her career ensuring that as we build more powerful systems, we do so with human values at the center.”
At the AI Policy Lab, we are proud to see Virginia’s work recognized in this way. Her leadership continues to inspire researchers, policymakers, students and partners working toward responsible and trustworthy AI.
Warm congratulations, Virginia!
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About DAIR
The DAIR Awards (Data and AI Readiness Awards) recognize organizations that lead the way in using data, analytics, and AI to drive measurable business and societal impact. Focused on organization achievements, the awards highlight companies that demonstrate strategic vision, innovation, mpact and maturity in their data, analytics and AI practices. Through the recognition of real-world success stories, the DAIR Awards aim to accelerate the adoption of data-driven technologies, inspire others to follow best practices, and benchmark progress across the Nordic region’s most advanced organizations.
Before you adopt AI, ask the right question first. Not “Which AI should we use?” But: “Under what conditions should an AI system be adopted, if at all? “That is Question Zero (Q0). We live in an era of AI hype. Governments are pouring huge resources into AI acceleration. Organisations are rushing to adopt. But speed is not a strategy. And technology is not destiny.
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The Dutch childcare benefit scandal shows what happens when we skip Question Zero. An algorithm accused tens of thousands of innocent parents of fraud, destroying jobs, families and lives. Q0 was never asked. Next up: figuring out what situated AI looks like not just as critique, but as practice, that is, research that is itself accountable to the communities it studies.
Q0 is a practical, free assessment tool developed at the AI Policy Lab at Umeå University with five categories of questions. Below we list some of the questions under each category (see the full version of the tool – below).
WHY? Motivation
Why do you plan to adopt an AI system?
What problem(s) is your organisation trying to solve with a new AI system?
What are the available alternatives, incl. human, other technical non-AI solutions, etc.?
WHO? Stakeholders and inclusion
Which stakeholders could benefit if the AI system is adopted and how?
Which stakeholders could potentially experience any risks/harms after adopting the AI system and how?
Does the AI system offer an opt out option for all impacted stakeholders?
WHAT? Type of AI system
What type of AI system are you planning to adopt?
How does this choice match the specific problem your organisation aims to solve?
HOW? Adoption and governance
How do you plan to monitor/analyse the new AI system’s outputs and performance?
How will you ensure the security of your organisation’s and your clients’ data?
WHERE? Infrastructure and control
Where does the training data originate from?
Where will the AI system run and data be stored?
Where is the AI system’s provider based?
During the workshop, participants worked in groups and applied the Q0 assessment tool to realistic AI adoption scenarios, including:
an AI system for emotional music personalisation on streaming platforms
automated hiring screening systems used in recruitment
workplace analytics tools analysing employee activity and productivity
AI systems for prioritising drug discovery in pharmaceutical research
Q0 is not anti-AI. It is pro-thinking. Technology is a human endeavour. We create it. We shape it. We can choose differently.
Our theme this year was Situated AI: grounding AI research in place, community, and lived knowledge rather than a view from nowhere that mascarades as objectivity. We talked about solarpunk visions for AI at community scale: whose resilience, whose future, built on whose knowledge? We sat with the uncomfortable truth that participation can be co-opted, that inviting more voices into a process doesn’t redistribute power, and can even become a new form of data extraction.
And we turned the lens on ourselves. The publish-or-perish pressure of academia doesn’t just shape what gets said, it shapes who gets to say it, and on what timeline. The incentive structures of academic AI research can reproduce the very dynamics we critique from the outside.
Our working conclusion, borrowed from Donna Haraway: “stay with the trouble”. Sometimes not resolving tensions prematurely, but staying in them long enough, is the most honest thing we can do.
Next up: figuring out what situated AI looks like not just as critique, but as practice, that is, research that is itself accountable to the communities it studies.
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AI Policy Lab Day 2025: Highlights and Reflections (Recording Available)
Date & Location: November 19, 2025, Umeå University, Västerbotten, Sweden
The AI Policy Lab Day 2025 was rich in insight and exchange.
Sennay Ghebreab delivered a keynote that grounded Question Zero in lived experience, reminding us that the decision to use, or not use AI is never a static checkpoint. He urged us to think in terms of Question Infinity:a continuous, reflective process in which risks and opportunities are held in tension rather than framed as opposites.
Daniel McQuillan‘s talk added a powerful systemic lens. By framing contemporary AI as a product of deeper structural failures, he challenged us to confront the material and social realities beneath technological optimism. His proposal of decomputing, a combination of degrowth, conviviality, and care, called us to imagine responses that prioritise collective well-being over speed or scale.
Our researchers’ posters reflected a striking level of maturity. Their work is rigorous, thoughtful, and already influencing wider debates on responsible AI. It was encouraging to see how confidently they engaged with participants and how deeply their projects connected to real societal needs (Rachele Carli, Petter Ericson, Jason Tucker, Tatjana Titareva, Themis-Dimitra Xanthopoulou, PhD Mattias Brännström).
Throughout the afternoon, participants brought curiosity, openness, and an eagerness to engage in discussions and informal exchanges between sessions.
The evening screening of Humans in the Loop added an emotional and narrative dimension that tied the day together. The dramatized story, rooted in the real experiences of data workers in India, wove together the daily realities of annotation labour with local culture, personal aspiration, and the power of lived experience. It captured the invisibility of this global workforce while honouring their agency and resilience. The discussion that followed made clear how crucial these perspectives are for any serious conversation on responsible AI.
A full day of insight, critical dialogue, and shared commitment.
Close out AI Policy Lab Day with a special screening of the acclaimed independent documentary Humans in the Loop, a powerful portrait of a young data annotator navigating the rapidly shifting AI industry in India.
Date: Wednesday, November 19 Time: 19:30 to 21:30 CET Location: Rotundan, Universum, Umeå University
Participation is free but registration is required and places are limited.
Film Screening
A groundbreaking 72-minute Hindi-Kurukh film follows Nehma, an Adivasi woman from Jharkhand’s Oraon tribe who trains AI systems as a data labeller. Director Aranya Sahay (FTII) was inspired by journalist Karishma Mehrotra’s exposé, revealing how over 70,000 Indians – mostly rural women – form AI’s invisible workforce.
A striking, human-centered view of AI from the ground up.
The 72-minute film will be followed by a discussion on the hidden role of data workers in AI.
This film screening is a part of the AI Policy Lab Day programme.
Webinar: How can we soften the blow for the public sector when the Gen-AI bubble bursts?
Date: 8 December 2025 | 17:00-18:30 CET Format: Online panel featuring short talks, followed by an open discussion
About the Workshop
With significant public investment and political capital currently riding on AI, particularly generative AI, the socio-economic and political consequences of the hype bubble bursting will be profound. This would be a fork in the road for states, and state authorities who have been championing and adopting GenAI. These actors can either change course, and seek new ways to tackle societal challenges, or continue to implement sub optimal and potentially harmful applications using GenAI. Given that many states have aligned with the techno-solutionist discourses and have framed AI adoption in terms of geopolitical positioning, the latter is more likely.
To prepare for this, and mitigate its potential harms, the workshop will focus on the organisational, technical, and social tools we can develop in advance to cushion the societal impacts of the GenAI bubble bursting. In doing so, we aim to preserve institutional legitimacy, redirect existing AI investments toward salvaging public benefit, and maintain old, and open new, avenues for AI development that aligns with the public interest. We will do so by focusing on a range of scales, from the geopolitical to the local.
We invite participants to reflect on how a range of stakeholders, such as governments, civil society, and academia, can respond to the decline of GenAI in ways that promote resilience, accountability, and long-term public value.
Panel discussion between
Virginia Dignum, Professor in Responsible AI, Director Policy Lab, Department of Computing Science, Umeå University.
Gary Marcus, Scientist, author and entrepreneur, known as a leading voice in AI. Six books including The Algebraic Mind, Rebooting AI, and Taming Silicon Valley; NYU Professor Emeritus.
Wendy Hall, Regius Professor of Computer Science at the University of Southampton and Director of the Web Science Institute. A pioneer in AI policy and web science, she co-chaired the UK Government’s AI Review and now serves on the UN’s High-Level Advisory Body on Artificial Intelligence
Gry Hasselbalch, Danish author and scholar specialising in the politics and power dynamics of technology, with a focus on data, AI ethics, and the historical forces shaping technological development.
Joshua Gans, Professor of Strategic Management, at the University of Toronto; economist who studies innovation, entrepreneurship, and business strategy and author of The Prediction Machine.
Frank Dignum, Professor in socially-aware AI, Department of Computing Science, Umeå University, Director of Umeå University’s research center on Transdisciplinary AI for the Good of All (TAIGA).
Moderator: Jason Tucker Adjunct Associate Professor at the AI Policy Lab, Umeå University and Researcher at the Institute for Futures Studies.
Participation
The workshop will run for 90 minutes, combining short expert talks with an open discussion. Participation is open to anyone interested in the societal and policy implications of AI, whether you work in government, academia, civil society, or simply want to join the conversation.
Date: Wednesday, November 19 Day Programme: 12:30 to 16:45 CET (free lunch and fika included) Evening Programme: 19:30 to 21:30 CET Location: Galaxen and Rotundan, Universum, Umeå University (see location in mazemap)
Join us on Wednesday,November 19 for AI Policy Lab Day 2025 – an interactive afternoon showcasing the lab’s work on responsible AI and engaging participants in real, practical conversations. The event features highlights from the AIPL’s projects, a keynote on Question Zero in AI and a hands-on clinic where we invite your toughest AI policy questions.
Whether you’re a policymaker, researcher, student, or practitioner, this is a space to learn, challenge ideas, and share insights across sectors.
Keynote speaker: Prof. Sennay Ghebreab (Amsterdam University)
Participation is free but registration is required for logistics and Zoom access: Registration Form
Zoom participation is available for the keynote, talk and AI Policy Lab (AIPL) introduction.
Agenda
12.30 – Lunch & networking
13.00 – Welcome & AI Policy Lab presentation Updates & insights from the Lab’s ongoing work by Virginia Dignum, Director of the AI Policy Lab
13.15 – Keynote: Prof. Sennay Ghebreab (University of Amsterdam)
Title:
Abstract:
Rethinking Question Zero in AI
Question Zero – the question of whether AI is the right answer to a problem – has become more prominent in discussions of Responsible AI. This is encouraging, since AI is often adopted as a quick fix, sometimes with harmful consequences for people and the environment. At the same time, there is a growing risk that organizations and governments may misuse Question Zero as a reason not to apply AI in cases where it benefits people and the environment. In this talk, I will explore cases from the Dutch context that highlight different ways of engaging with Question Zero and discuss why it is worth rethinking how we approach this question in AI.
14.30 – Poster Presentations
15:15 – Talk by Dan McQuillan
Title:
Abstract:
16.00 – AI Policy Café – Drop-in Clinic
Explore research from Lab members Topics: AI and human rights, healthcare, education, anti-capitalist perspectives, transparency & explainability
Decomputing
This talk will characterise contemporary AI as the broken product of an already-broken system. While AI sucks more of everything into its cycle of simulated solutions, it diverts us from the underlying structural and environmental crises. By focusing on energy as the conjunction of materiality and hype at the heart of the AI question, the talk will outline ‘decomputing’ as possible response to technocratic nihilism. Decomputing combines degrowth and conviviality into a policy for post-collapse liveability, where the cybernetic may still find a place in support of the common good.
Bring your real-world AI policy or ethics cases, questions, or dilemmas. Our team will offer ideas, support, and resources in an open, informal format. Think: a cross between a helpdesk, repair café, and fika table. No preparation is needed.
16:45 – Wrap-Up
Announcing the AI Policy Lab’s Drop-in Clinic:
A space to discuss real-life cases in AI policy and ethics.
Got an AI policy or ethics challenge or practical implementation questions? Our team will provide pointers, support, and fresh ideas to help you move forward.
Who this event is for: Policymakers, practitioners, researchers, students, or anyone facing AI-related challenges What to bring: Any question, case, or challenge related to AI governance, ethics, or implementation What you’ll get: Practical advice, connections to resources, and space to explore solutions together
Evening Program: Film Screening
Film Humans in the Loop Rotundan, Universum, Umeå University 19:30-21:30 | Wednesday, November 19
Close out AI Policy Lab Day with a special screening of the acclaimed independent documentary Humans in the Loop, a powerful portrait of a young data annotator navigating the rapidly shifting AI industry in India.
A groundbreaking 72-minute Hindi-Kurukh film follows Nehma, an Adivasi woman from Jharkhand’s Oraon tribe who trains AI systems as a data labeller. Director Aranya Sahay (FTII) was inspired by journalist Karishma Mehrotra’s exposé, revealing how over 70,000 Indians – mostly rural women – form AI’s invisible workforce.
A striking, human-centered view of AI from the ground up.
The 72-minute film will be followed by a discussion on the hidden role of data workers in AI.
We look forward to welcoming you to the AI Policy Lab Day at Umeå University!
Responsible AI Self-assessment Workshop: Start with Question Zero
Date & Location: August 27, 2025, Umeå University, Västerbotten, Sweden
On 27 August 2025, more than 100 participants joined the AI Policy Lab workshop Responsible AI Self-Assessment: Start with Question Zero at Umeå University and online. Together, we tested and debated the Responsible AI Self-Assessment Tool, designed to help organisations pause, reflect, and ask why before moving into AI adoption.
The workshop brought together voices from academia, industry and the public sector, sparking vibrant conversations around responsible AI. Participants reflected on questions such as:
Should a clear AI clarification step be required before entering Question Zero (“Why do you plan to adopt an AI system?“)
Should organisations complete a process pre-assessment before starting with AI?
What kind of work should remain human-only?
How can transparency and ethics be maintained when deciding between automation and augmentation?
Why might other non-AI solutions not solve the problem at hand?
We are deeply grateful to everyone who joined, shared perspectives and challenged assumptions. Your input is vital to shaping a practical, responsible approach to AI adoption.
Next steps
The tool is still a work in progress. Feedback from this workshop will be implemented directly into the next version of the tool. Future workshops will continue to stress-test and evolve it, ensuring it meets the needs of diverse organisations working with AI.
As Virginia Dignum, Director of the AI Policy Lab, put it:
“Responsible AI isn’t AI-first, it’s people-first. It starts by asking why, not rushing to deploy.”
Interested in taking part in upcoming sessions? Keep an eye on our website and LinkedIn page for updates.
Global AI Policy Research Network Launched at UN IGF 2025 (Recording available)
Workshop #288: An AI Policy Research Roadmap for Evidence-Based AI Policy Date & Location: June 26, 2025, Oslo, Norway
At the UN’s Internet Governance Forum (IGF) 2025 in Oslo, Norway, AI Policy Lab @Umeå University (Virginia Dignum, Jason Tucker, Tatjana Titareva and colleagues) and Mila – Quebec Artificial Intelligence Institute (Isadora Hellegren Létourneau, and colleagues), in cooperation with our partners including Alex Moltzau, Eltjo Poort, Neema K. Lugangira, and many others, launched the Global AI Policy Research Network (GlobAIPol). The network invites diverse stakeholders to share practical knowledge that supports ethical, transparent, and evidence-based practices for shaping inclusive and trustworthy AI policies. The session also encouraged global stakeholders to endorse the Roadmap for AI Policy Research.
“AI does not happen to us! AI is designed by humans. We make the choices.” – Professor Virginia Dignum’s keynote reminded us that before asking how to implement AI, we must ask Question Zero: Is AI the best option here? We need to shift from fragmented, reactive policies to coordinated, evidence-based strategies rooted in ethics and justice.
The interventions and discussion revealed critical lessons from global perspectives:
The EU is demonstrating promising approaches with the European AI Office expanding from 97 to 140 staff by the end of 2025, supporting regulatory sandboxes and international collaboration including a €5 million generative AI initiative with Africa.
In healthcare, we must move beyond treating AI as a “magic pill” and build upon existing regulatory frameworks – just as we trust paracetamol today because of rigorous oversight developed several decades ago.
Well-designed regulation stimulates innovation rather than slows it down. Different countries need diverse legislative approaches harmonised with local values, not a one-size-fits-all global AI governance structure.
The time to act is now. AI is shaping our collective future, and how we act today will define who benefits, who is heard, and who is left behind.
AI Technologies in Public Service: A Workshop for Identifying Needs, Challenges, and Solutions
Date & Location: April 9, 2025, Umeå University, Västerbotten, Sweden
The workshop was organised by the AI Policy Lab in collaboration with the AI Technologies for Sustainable Public Service Co-creation (AICOSERV) project members.
Overview
The workshop brought together more than 50 stakeholders from the public and private sectors, as well as academia, to explore the relationship between barriers to AI adoption in public services and the skills and expertise required to overcome them.
A central theme of the workshop was the “question zero”, the fundamental inquiry of whether AI should be used at all in a given context. As AI technologies continue to advance and expand into complex public sector tasks, the assumption that AI is always the right or necessary solution must be critically examined. The workshop challenged participants to consider not only how AI can be implemented, but to question whether it should be, emphasizing that responsible adoption begins with questioning the appropriateness and desirability of AI in specific domains.
This foundational concern set the tone for broader discussions about trust, governance, transparency, and the skillsets required to navigate the opportunities and risks of AI in public service.
Keynote Address
Professor Virginia Dignum, Director of the AI Policy Lab, opened the workshop with a keynote titled “Governing AI: Why, What, How?”
She addressed the societal and governance implications of AI, focusing on the need to critically evaluate when and how AI should be integrated into public service contexts. Her talk stressed the importance of not overlooking ethical, legal, and operational challenges in the rush to adopt AI.
Regional Case Study: AI in Västerbotten
Considering the wide range of public services open to AI adoption, a recurring set of challenges consistently emerges. Whether deploying AI-driven diagnostic tools in healthcare or implementing predictive analytics within smart city infrastructures, public and private sector actors, and community stakeholders face diverse barriers. Henry Lopez-Vega, fellow at the AI Policy Lab, presented on the challenges of AI adoption in the Västerbotten region in his session titled “What are the challenges with AI (in Västerbotten)?”
His research identified three core barriers to building a responsible AI ecosystem:
Technological infrastructure and processes within organisations
Organisational culture and resistance to change
Lack of clarity around AI governance and ownership
Group Discussions: Skills and Stakeholder Engagement
In the second half of the workshop, participants engaged in group discussions focusing on organisational challenges, key stakeholders, and barriers to implementation. Each group then mapped the skills and knowledge needed for responsible AI adoption in their contexts.
For example, in the case of AI-supported recruitment processes, participants identified several critical barriers:
Lack of transparency in AI decision-making
Biases in training data
Limited legal and ethical guidelines for automated hiring
To address these issues, participants emphasized the need for professionals with a blend of competences, including:
Knowledge of data protection and anti-discrimination legislation
Skills in evaluating and auditing AI systems
Awareness of ethical considerations in algorithmic decision-making
Findings and Framework
The increasing efforts to implement AI across various public sector domains have led to a critical question: what types of professionals, equipped with what specific skills and competences, should lead the integration of responsible AI? Defining the essential set of skills, knowledge, and professional competences required for the effective and ethical deployment of AI in both public and private sector services becomes a key priority.
A key outcome of the workshop was the identification of a recurring set of challenges affecting. These include:
Low levels of trust
Lack of transparency
Unclear ownership and responsibility
Insufficient stakeholder awareness
Limited AI literacy and governance skills
To address these challenges, we propose the conceptual framework depicted in Figure 1. This framework highlights the urgent need to cultivate professionals who combine technical expertise, ethical sensitivity, and domain-specific knowledge to lead responsible AI integration. It maps the interconnected layers that influence the deployment and responsible use of AI technologies in public services, including:
Contextual Challenges – such as low trust, resistance to change, and limited organisational readiness
Structural Barriers – including unclear project ownership, inadequate governance frameworks, and insufficient infrastructure
Skill and Knowledge Gaps – highlighting the lack of AI literacy, ethical awareness, and domain-specific competences
Stakeholder Roles – outlining the importance of identifying and engaging relevant actors (e.g. policymakers, IT professionals, legal advisors, and citizens) throughout the AI lifecycle
This framework is intended to guide structured reflection and planning around AI deployment, helping ensure that technologies are not only functional but also trustworthy, inclusive, and aligned with public values. As such, it can serve as a practical tool for organisations seeking to integrate AI technologies responsibly. It encourages a systemic perspective, one that moves beyond technical feasibility to consider broader organisational, social, and ethical dimensions.
By applying this framework, decision-makers and project leads can:
Identify context-specific challenges before adopting AI
Map key stakeholders and clarify roles and responsibilities
Recognise skill and competence gaps that must be addressed
Design AI initiatives that align with principles of transparency, accountability, and fairness
Figure 1. The framework summarising the workshop’s thematic discussions
In conclusion, the workshop underscored that a stakeholder-oriented, challenge-driven approach is key to enabling responsible AI adoption. By starting with specific domain needs and mapping corresponding skills and knowledge, organisations can more effectively navigate the complex landscape of AI integration.
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