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On 28 September 2026, in observance of the International Day for Universal Access to Information, this Future of Evaluation dialogue discussed how evaluation can make evidence more accessible, understandable and actionable for citizens. Access to information is fundamental to transparency, accountability and meaningful participation. Yet, evaluation evidence tends to remain within technical reports, institutional platforms and specialist audiences, limiting its potential as a public good. The dialogue examined strategies for extending evidence to citizens, highlighting practical approaches across knowledge translation, storytelling, open data and artificial intelligence (AI) driven innovations. In case you missed the conversation, watch the recording. Seven takeaways from the dialogue Making evidence public is only the first step towards making it accessible. A report can be public and still out of reach for citizens. It may be written in technical language, available only online, or leave citizens unsure what the findings mean for them and what should change as a result. Access can be better judged by whether people can find evidence, understand it and act on it. The number of reports published says little about whether an evaluation reached its audience, while tracking who reached the evidence and which decisions it informed says more about the success of an evaluation. Accessibility depends on language, format and where evidence is placed. Most evaluation reports are out of reach for the communities served by the programmes. The reports can be long, dense with technical and statistical jargon, often published in one language, and posted on institutional websites that few citizens visit. Making evidence accessible means providing short summaries in plain language, translations into local languages and using formats like infographics, short videos, radio and audio. It also means going where people already gather, like community meetings, local radio, youth groups, or community councils. However, simplification needs care—over-simplifying evaluation results risks distorting the evidence, requiring evaluators to strike a thoughtful balance between accessibility and accuracy. Recognize communities as knowledge partners rather than data sources. Evidence is gathered from communities, analysed in evaluation offices, discussed at conferences and stored in reports. The evidence rarely returns to the communities who provided it. Involving communities in defining evaluation priorities, setting criteria, and interpreting findings leads to evidence that reflects local priorities, draws on contextual knowledge, and drives meaningful action. Build evaluation literacy across the ecosystem. Evidence cannot be utilized to its full extent when the people receiving it are not equipped to interpret it. Evaluation literacy, meaning the ability to read evidence critically, weigh and apply it to decision-making, should be developed across the full development ecosystem rather than within evaluation offices alone. This includes programme staff, government officials, civil society organizations, academia and think tanks. Local government deserves particular attention, since it is closest to communities and often the channel through which evidence reaches them. The barriers to accessibility are institutional and political, not only technical. Evaluation is often seen as technocratic, with questions, criteria and methods set by technical specialists and funders, leaving little room for the affected communities to shape any of it. Institutional discomfort with poor performance also restricts what gets shared, and political sensitivities can further narrow access. Multi-country and meta-level evaluations add a different barrier, surfacing national and regional findings that override local context and leaving people unable to recognize their own situation in the evaluation. There is no single approach to sharing evaluation evidence that fits every setting and audience. AI can bring evidence to more people, but it cannot replace evaluators' judgement. AI offers evaluation an opportunity to make evidence available at scale, such as condensing a hundred-page report into a one-page summary, translating it into local languages, and presenting the findings in whichever format an audience prefers, from audio to a visual scorecard. AI can also help draw lessons across large numbers of evaluations far faster than manual review. The risks arise when AI is used to analyse and interpret evidence without proper human oversight. Entering sensitive evaluation data into these tools also raises privacy concerns. AI can also reproduce epistemic bias, marginalize local languages and knowledge, and create data-governance risks. If not used appropriately, it may also shift control over evidence away from communities. AI should therefore remain an assistive tool, not an evaluator or decision-maker. Close the feedback loop, provide equitable access and safeguard youth in evaluation. The Youth in Evaluation champion from UNICEF highlighted the organization's experience in engaging young people in evaluation processes. While young people are often consulted in evaluations through advisory groups or digital polling, they rarely receive updates on how their contributions were used. Meaningful youth engagement requires clear purpose and defined feedback loops. Furthermore, while digital channels expand reach, they risk excluding youth without access to the internet and digital platforms. Finally, in some contexts, contributing to an evaluation can expose young people to risk, so their protection should be built into the evaluation design. The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse. This was the third dialogue of Season 2. The fourth dialogue will take place on 15 October 2026 in observance of the International Day for the Eradication of Poverty. Register. This article was written with AI support with human authors in the lead.

By Nea-Mari Heinonen Ministry for Foreign Affairs of Finland Artificial intelligence (AI) is increasingly presented as a solution to a wide range of organisational challenges in public administrations and multilateral organisations. Across sectors, there is growing pressure to adopt AI, often accompanied by assumptions that it will automatically improve efficiency. For the evaluation community, this raises new questions, such as: How do we prevent the emergence of a Wild West of AI use that can lead to pseudo-evaluation and pseudo-evidence? Figuratively, ‘the Wild West’ refers to “something that is chaotic and uncontrolled especially due to a lack of regulation or oversight”. Using this metaphor, this blog raises four key concerns. Coincidentally, around the time of publication, others have also found the metaphor apt for describing AI-related challenges. There is no such thing as "The AI" Firstly, ”AI” is often discussed as though it were a single technology or autonomous actor, despite encompassing a diverse range of human-designed tools, methods and techniques. In many discussions, AI has become shorthand for generative AI, and for specific chat-based tools such as Copilot or ChatGPT. This lack of precision creates conceptual confusion. Different people understand AI differently, depending on the technologies available in their organisation and their own level of familiarity with them. When "AI" is used as a catch-all term, there is a risk of creating a Wild West of concepts in which people are discussing different things while believing they are talking about the same thing. This can obscure which tools are appropriate for specific tasks and data types, potentially leading to a Wild West of conceptual confusion. The evaluation community needs to become more specific about the technologies that are being discussed and the purposes for which they are used. Who decides what appropriate use looks like? The second concern relates to decision-making in organisations: How to avoid hasty decisions about AI use and manage unrealistic or misinformed expectations? Who decides what appropriate use is, and will the subject-matter experts be involved in such decisions? Many evaluation experts can envisage a situation where someone with limited evaluation knowledge proposes an apparently simple solution: "Why not ask a chatbot whether the project was successful?" While well-intentioned, such suggestions underestimate the nature of evaluation. At present, many decisions about AI use are made at the level of individual users. People experiment with tools as part of their personal AI uptake, often without guidance, standards or oversight. At the same time, senior decision-makers in different organisations face pressure to increase efficiency. This can result in a fragmented environment in which AI application emerges through ad hoc decisions. Without appropriate governance, this creates a real risk of producing what might be called a Wild West of pseudo-evaluation: activities that resemble evaluation on the surface but lack the methodological, quality and other requirements to meet evaluation standards and principles. The cart is being put before the horse when AI tools are increasingly used to analyse information as method choices rather than purposeful complementary tools. As organisations move towards agentic AI systems, this challenge becomes even more complex. The evaluation community should not take the demand for rigorous evaluations for granted. When accepted uses collide Thirdly, even if evaluation professionals are successfully engaged to define appropriate uses of AI, another problem remains. Different organisations reach different conclusions about what is acceptable use. Internal regulations, policies and risk tolerances vary considerably. A practice considered appropriate by one organisation may be prohibited by another – for example, AI-assisted analysis of interview transcripts. This creates practical challenges for evaluators, commissioners, and informants, potentially leading to a Wild West of accepted use. Informed consent will not solve this multi-layered problem alone, assuming all informants are able to make informed choices about such highly technical matters. Informed rejection, on the other hand, can lead to unequal representation in the data. Navigating the rules becomes increasingly difficult, and will require ongoing dialogue, transparency and collaboration across organisations. It will also require willingness to revert to traditional evaluation methods when necessary to ensure adequate representation. Selection and differing uses generate pseudo-evidence Perhaps the greatest risk concerns the long-term quality of evidence itself. Much of the public debate around AI has focused on hallucinations and bias. These are important concerns, but equally important is the issue of selection. When tools such as Copilot or Claude summarise information, they make choices about what to highlight, prioritise and omit. Many users assume these processes are objective and systematic. In reality, it is not possible to know exactly how information is selected, nor does the same task produce identical outputs over time. Most users understand that AI-generated outputs should not be accepted uncritically but many overlook a subtler issue. Summaries can be factually correct while emphasising different aspects of the source material. A small experiment using three different large language models (LLMs) to summarise evaluation findings showed that all outputs were factually correct, yet they differed in formulation, emphasis, presentation and balance of content. One also generated recommendations, although recommendations were not part of the materials. Summarising evaluation findings passages with different LLMs Description: A set of 11 text passages on evaluation findings were extracted and tested using three different LLMs. Prompt: Summarise the content of the document in about 100 words. The results were cross-checked against the original passages. All were factually correct but differed in what became emphasized through selection and choice of words, framing, level of detail, and in balance of substantive elements, detectable through manual color-coding. One LLM also generated recommendations to maximise impact (in its opinion), although not requested nor was such content included in the original materials. Bold added by author to highlight some such features. “[Country] is leveraging high‑level advocacy, strategic partnerships with tech giants and targeted financing to embed gender equality in global digital‑development policies and projects. While it has achieved notable policy wins (e.g., gender clause in the [name of compact]) and piloted innovative solutions that benefit women and vulnerable groups, inclusion outcomes remain uneven—especially for low‑income, women‑led micro‑enterprises. The main challenges are rigid financing tools, limited visibility of [country’s] solutions, and insufficient grassroots digital literacy. To maximise impact, [country] needs more flexible, harmonised funding mechanisms, stronger SME engagement, and intensified capacity‑building for the poorest and most marginalized users.” (LLM1) “[Country] has strongly promoted inclusion, gender equality, and digital development through multilateral influence and bilateral projects. Its leadership in the [name of campaign] and co-leading of the [name of coalition] helped address the digital gender divide and online safety. [Country] contributed to shaping the [name of compact] and supported digital public goods, AI governance, and connectivity. Bilateral initiatives, such as digital land administration in [country] and innovation ecosystem support in Africa and [country], showed significant impact. However, challenges persist, including mixed inclusion outcomes, limited benefits for disadvantaged groups, difficult SME mobilisation, underfunded instruments, and reduced visibility in multilateral programmes.” (LLM2) “[Country] has played a leading role in promoting inclusive digital development, particularly through multilateral engagement. It has influenced global processes such as the [name of compact] and co-led the [name of coalition], advancing gender equality, digital inclusion, and online safety. Bilateral initiatives, including digital land registries in [country], have supported women’s rights and access to finance. However, inclusion outcomes remain mixed, especially in entrepreneurship and job creation, with limited benefits for the most vulnerable groups. Challenges include underfinanced multilateral instruments, reduced visibility, limited SME engagement, and persistent global digital divides in connectivity, affordability, electricity access, and digital skills.” (LLM3) Legend [blue=description] [green=positive results] [yellow=mixed results] [red=challenges] [purple=LLM-generated recommendations] Analysis and summarisation are inherently processes of selection. Evaluators make such choices deliberately, guided by purpose, context and methodological judgement. AI systems also make selections, but often through processes that remain opaque to users. The effects are multiplied by the various types of accepted uses of AI. The danger is not necessarily just incorrect information but the gradual erosion of nuance, context and complexity. As AI-generated summaries are used to create further summaries, over time, there is a risk creating a chain of "summaries of summaries" in which essential details are lost, causing the fourth concern, a Wild West of pseudo-evidence, through selection and the cumulative loss of context and meaning over time. This bears profound consequences, altering the very nature of evidence. Towards thoughtful application The use of AI technologies in evaluation raises important questions regarding their intended purposes, the boundaries of acceptable applications, and the implications of differing interpretations across organisations. While definitive answers may not yet exist, it is essential that the evaluation community begins to engage with these issues. The evaluation community has much to gain from engaging with various applications of AI. As initiatives such as OpenEval.fi demonstrate, there are genuine opportunities to support evaluative work in new ways. However, the future will not be determined by the technology alone but also by the human ability to govern its use. The key question is whether evaluation professionals will have an active role in defining appropriate uses of AI within various organisations. The evaluation community must also continue to raise awareness of "what evaluation is". AI applications may increasingly outperform humans at processing data. However, evaluation entails much more: interpreting significance, meaning and value; and answering evaluation questions that are complex, contested, value-laden, influenced by context, and open to multiple interpretations. The ultimate challenge is not whether AI should be used in evaluation, but how it can be thoughtfully employed in ways that strengthen the quality, credibility and integrity of evidence on which decisions are based. Failure risks entering a Wild West of pseudo-evaluation and pseudo-evidence due to unthoughtful application of AI. Success can help establish AI as a valuable tool in service of rigorous evaluation, rather than a poor substitute for it. Nea-Mari Heinonen (MA, MSSc) is the Lead Evaluation Specialist and Deputy Director of the Development Evaluation Unit of the Ministry for Foreign Affairs of Finland. With 20 years in international development, she has piloted AI and data science approaches and is currently pursuing a PhD in social data science at the University of Helsinki. Connect with Nea-Mari on LinkedIn. The views expressed in this blog post are those of the author and do not necessarily reflect the views of her affiliated organisations. Acknowledgement of the use of AI: Copilot was used to create the first draft of this blog post based on the author’s original panel speeches prepared for gLocal, June 2026. All content is original by the author. Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.

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On 19 August 2026, in observance of World Humanitarian Day, a Future of Evaluation dialogue was held on how evaluation can accelerate learning in humanitarian action. The discussion highlighted that crises are becoming more frequent, interconnected and unpredictable while humanitarian funding contracts sharply. However, evaluation practice has not changed nearly as fast as the situations it seeks to evaluate. The value of a humanitarian evaluation lies in its usefulness, not its methodological complexity. Humanitarian evaluations must be fast, flexible, and grounded in the needs of affected populations. In case you missed the conversation, watch the recording. Seven takeaways from the dialogue Shorten the distance between evidence and action. Humanitarian evaluations must become more agile, locally led, and tailored to the context. Evaluation results that arrive after the situation has changed offer hindsight rather than insight. Rapid evaluations and shorter learning cycles let humanitarian actors see what is changing, who is being missed and what needs adjusting while there is still time to act. The methods for this already exist. The current context calls for using these methods more deliberately, rather than searching for new ones. Adaptive evaluation needs rigour without rigidity. Armed conflict and access restrictions can constrain planned evaluation approaches; adapting the methodology is often the only way to generate evidence at all. For example, working through community representatives and local actors can ensure women and young people are still included. Speed and adaptation must not compromise ethics, inclusion, or data credibility. Rigor requires adjusting to a changing environment rather than clinging to a design that no longer fits. Keep affected populations at the centre, and use locally led evaluation to strengthen accountability and shift power. Donors have a legitimate interest in knowing how funds are used and who is reached. The difficulty arises when donor requirements determine almost entirely what is evaluated, who is asked and what counts as success. This reflects a power imbalance, since donors hold the funding and with it the questions, while affected populations hold neither. This way evaluation drifts towards compliance rather than change. Crisis-affected populations are not a single group. Women, girls, older people, people with disabilities and displaced people each experience a response differently, so accountability to them means tracing whose voice is heard and who is still missed. Correcting this needs system-level change rather than better evaluation practice alone. Locally led evaluation, grounded in local leadership, context and knowledge, as well as meaningful engagement with affected communities, offer more effective routes to shifting the balance. Involve decision makers from the start, or the evidence will go unused. Without leadership buy-in, even an excellent evaluation can have little influence, because those with the authority to act were not part of the process. Identifying decision makers at the outset, understanding what they can actually decide, and designing evaluation questions around what they can act on makes use far more likely. Their information needs also change as a crisis changes, and in humanitarian settings that can happen within weeks. So staying in contact with decision makers throughout the evaluation allows the questions to remain relevant. Beyond any single evaluation, leadership behaviour also determines whether an organization treats evidence as a source of learning or as a requirement to be met. Strengthen system-level evaluations. Evaluation recommendations often highlight issues that require coordinated action beyond the remit of a single organization. System-level evaluations offer potential for creating a shared sense of responsibility and accountability for coordinated responses across donors and agencies. This approach also helps reduce the duplication and mandate competition that frequently surfaces in evaluation work. While this shift requires coordination, organizational buy-in, and comparable data across organizations, it would make humanitarian evaluation vastly more useful. Do no harm is the first test for AI and digital data in evaluation. As more evaluators adopt AI and digital data collection to speed up their work, ethical obligations remain the same, but the risks increase. "Do no harm" remains the primary standard for any method, and exposing participant identities is a direct form of harm. Ethical principles, such as data protection and confidentiality, do not need rewriting for AI; they need extending to govern how data is used and handled by AI. While guidelines on the ethical and responsible use of AI in evaluation are now widely available, guidance only matters when applied. This means integrating it directly into training and mentoring of evaluators. Lessons from the Youth in Evaluation champion. The Champion's Corner brought the institutional experience of an international organization engaging young people in humanitarian evaluation. Young people are among the most vulnerable and left behind groups in crises, and their absence from evaluations limits what a response is able to see. In an ongoing evaluation of UNFPA’s approach to localization in humanitarian action, young and emerging evaluators were paired with senior experts to co-lead country case studies. This generated two-way learning, with senior evaluators also learning from junior colleagues particularly on AI. Young and emerging evaluators often possess strong digital skills but many lack field experience; they need direct exposure to data collection with communities and a firm grounding in established evaluation methods. However, effective mentoring takes time that rapid humanitarian evaluations can rarely afford. A genuine commitment to mentoring, offering concrete roles and leadership opportunities for young people can make a difference. At the same time, engagement with affected communities including young people, must start early to ensure their voices are heard throughout the evaluation process. Ultimately, both young people and communities need to be involved when the next programme is designed, not just when it is evaluated, to bridge the gap from youth-led evidence generation to youth-led action. The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse. This was the second dialogue of Season 2. The third dialogue will take place on 28 September 2026 in observance of the International Day for Universal Access to Information. Learn more and register. This article was written with AI support with human authors in the lead.

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By Junhua Qu and Lan Wu EvalYouth China Climate injustice is nowhere more visible than in small island states. As the canary in the coal mine of climate catastrophe, they are particularly vulnerable to the impacts of climate change on the marine environment. As for the formal request submitted by the Commission of Small Island States (COSIS) in December 2022, the International Tribunal for the Law of the Sea (hereinafter “the Tribunal”) issued Advisory Opinion No. 31 (hereinafter “the Advisory Opinion”) on May 21, 2024. Small island states had asked the Tribunal to clarify what legal obligations countries have under the UN Convention on the Law of the Sea (UNCLOS, hereinafter “the Convention”). The Advisory Opinion concluded that anthropogenic greenhouse gas (GHG) emissions can constitute pollution of the marine environment. States therefore have a stringent due-diligence obligation to take all necessary measures to prevent, reduce, and control marine pollution, including ocean warming, rising sea levels, and acidification. For the first time at the international judicial level, the Tribunal addressed the intersection of climate change and the law of the sea. The evaluative method in the Advisory Opinion helped clarify basic scientific facts and ground “necessary measures” according to the best available science. It underlined that scientific uncertainty cannot justify inaction where serious or irreversible harm is at stake. Evaluation here bridges the gap, enabling courts to advance climate justice through juridical practice. The evaluative work behind “best available science” The Advisory Opinion establishes a verified causal chain more than “climate change is real”. It traces anthropogenic GHG emissions from atmospheric accumulation through ocean absorption to concrete marine harms (ocean warming, acidification, and deoxygenation) to determine whether such emissions qualify as “pollution” under the Convention and whether States have fulfilled their obligations. As the Tribunal deeply recognized that “the phenomenon of climate change is central to the Request and the questions contained therein necessarily have scientific aspects”,[1] an inherently evaluative approach has been adopted. By its extensive and structured engagement with scientific evidence, the Tribunal linked greenhouse gas (GHG) emissions to marine harm, to determine whether such emissions constitute “pollution” under the Convention and whether states have met their obligations under Part XII. The Tribunal is a judicial body established under the Convention, to interpret and apply the Convention (Article 288(1)) and “other rules of international law not incompatible with this Convention” (Article 293).[2] It does not generate scientific knowledge itself, nor its advisory function does not qualify as an “evaluation” in the technical sense used by the OECD Development Assistance Committee (DAC) or the World Bank.[3] This is why the Intergovernmental Panel on Climate Change (IPCC) mattered. Their assessment reports, as a systematic evaluation of global climate science, are almost universally accepted by participants in the proceedings at the Tribunal.[4] The Tribunal first summarized substantive conclusions, such as the deleterious effects of anthropogenic GHG emissions. But the Tribunal did more than repeat scientific conclusions. It paid attention to how the IPCC assesses evidence, including its use of confidence levels and likelihood language to communicate certainty and uncertainty.[5] By this epistemic evaluation, the Tribunal treated the IPCC as a factual basis for legal reasoning. “Best available science” now became more than a general reference as the Tribunal effectively evaluated whether state conduct met the standard under the Convention Article 194. The Tribunal therefore demonstrates evaluative legal reasoning, as it assesses the credibility of evidence, verifies causal links between GHG emissions and marine harm, as well as judge the significance of state conduct under the Convention.[6] In this sense, evaluation is not what the tribunal does, but it is the rational infrastructure that makes the tribunal’s climate justice reasoning possible. Scientific evidence as evaluative enabler of the five pillars of climate justice Climate justice in international law requires more than moral commitment, as well as requiring evidence. The Advisory Opinion demonstrates how scientific evaluation makes climate harm legally visible, responsibility measurable, and legal obligations adaptive. This triple evaluative function operationalizes climate justice without reducing it to the abstract principle of climate justice. The UNU Institute for Environment and Human Security identifies five key dimensions of climate justice[7]: recognitional, procedural, distributive, restorative and transformative justice. Each dimension represents a different just way in climate governance.[8] These dimensions should be adopted in law with an evidentiary infrastructure instead of abstract moral aspirations. The Advisory Opinion illustrates precisely how evaluation furnishes this infrastructure: Recognitional justice: The Tribunal’s quantification of marine harm renders small island states’ vulnerability legally visible. Evaluation thus grants vulnerable actors’ epistemic authority to define climate harm on the global stage. Procedural justice: By relying on IPCC findings, the Tribunal imports evaluative norms of transparency and systematic review into the judicial sphere, reinforcing participatory and accountable climate governance. Distributive justice: IPCC metrics theoretically link emissions to marine harm, satisfying OECD-DAC and World Bank evaluative standards. Yet this does not mean that scientific attribution automatically produces legal obligation or material remedy. Evaluation here in the Advisory Opinion thus serves a dual function: measuring causal responsibility while exposing the accountability gap between scientifically established harm and politically realized reallocation. Restorative justice: The IPCC’s projections of irreversible change establish the forensic foundation required for reparation. Based on that, the Tribunal’s evaluation of damage magnitude, duration and irreversibility creates the legal predicate for restorative finance and institutional remedies. Transformative justice: By linking the obligations under the Convention to the IPCC’s iterative cycles, the Tribunal gives international law a more adaptive character. States’ climate-related duties should not remain fixed at a single point in time, compelling continuous reassessment as new risks emerge. The Convention is thereby transformed from a static treaty into an evidence-based governance framework that simultaneously advances climate action and a fairer international community. The enabling processes are shown below: Historical legal pathway: how science interacted with the international environmental law system The role of scientific evidence in climate advisory opinions did not emerge in a vacuum. International environmental law has long used assessment to act under scientific uncertainty. A useful precedent is the ozone regime. The ozone regime is remarkable as it happened to first address a long-term problem which effects are not evident for decades hence.[9] It required decisions based on probabilities, flexibility of being adapted to new sciences assessments and maximum international cooperation. The 1985 Vienna Convention created a framework for scientific cooperation, systematic observation, and information exchange. The 1987 Montreal Protocol went further by institutionalizing periodic assessment. Article 6 requires parties to review control measures based on available scientific, environmental, technical, and economic information.[10] The history shows that evaluation can be part of law-making itself as it identifies risk, justifies precautionary action, and allows legal obligations to evolve as knowledge improves. The 1990 London Amendment strengthened controls on CFCs and halons and expanded regulation to additional substances based on “the most recent scientific evidence” at that time.[11] In this sense, the Tribunal concluded that States must take all “necessary measures” to control marine pollution associated with anthropogenic GHG emissions and said that what constitutes necessary measures “should be determined objectively” taking into account, among other things, “the best available science”.[12] It now helps define the content of state obligations.[13] The Tribunal also affirmed that duties of scientific cooperation under the Convention, also apply to GHG-related marine pollution.[14] The tribunal act anticipatory as it urged States to take preventive measures even in the absence of absolute scientific certainty.[15] Conclusion: evaluation for climate justice The Advisory Opinion is not merely a legal document about the law of the sea. It reveals something far more useful for evaluators: it shows how rigorous, credible evaluation of evidence can turn abstract vulnerability into enforceable justice. For evaluators, the Advisory Opinion offers three interconnected lessons: Evaluation as a recognition tool. Just as IPCC reports made small island states visible to the court, evaluations can make differential vulnerability visible across gender, geography, age, disability, or displacement status, performing recognitional justice in the process. Process integrity builds credibility. The Tribunal trusted the IPCC not merely for its conclusions but for its transparent, peer-reviewed, multi-stakeholder procedures. This illustrates a broader principle: the legitimacy of evidence depends on the integrity of the producing process. For evaluators, the lesson is that credible evidence depends on methods suited to the purpose. Where participatory evaluation is appropriate, credibility can be further strengthened by engaging affected communities in defining indicators, interpreting findings, and validating recommendations. In that case, the process remains open to scrutiny and methodological challenge. Evaluation should remain responsive to new evidence. The Advisory Opinion clarified that the measures expected of States must reflect the best available science as it develops. It reads the Convention considering evolving science, reminding us that evaluation should not be limited to end-of-project reporting. For evaluators, the parallel is limited but useful: evaluation should create opportunities to revisit findings and assumptions when conditions change. Ultimately, the ITLOS Opinion reminds us that evaluation is not a back-office compliance exercise. When it is independent, credible, and useful, evaluation becomes part of the infrastructure of justice. The emerging hierarchy of scientific evidence in climate litigation places IPCC Assessment Reports at the top following the Advisory Opinion.[16] For future evaluation practice, the challenge is to balance scientific authority with responsiveness to emerging evidence, so that courts do not overlook fast-developing climate harms. Junhua Qu is an Energy Analyst at Pratus Group. Her professional experience spans energy modelling, climate policy analysis, carbon markets, and biodiversity protection across both NGO and private-sector contexts. With a continued interest in energy transition, climate governance, and SDG evaluation, she has participated in SDG evaluation workshops organized by EvalYouth China. Dr. Lan Wu is a Lecturer at the Faculty of Law, Ocean University of China, where she teaches environmental and natural resources law. Her research focuses on the legal and regulatory frameworks essential to facilitating the clean energy transition amidst the global climate crisis. Dr. Wu holds a PhD from The Chinese University of Hong Kong and previously served as an Energy and Climate Fellow at UNDP China. Her recent work includes identifying regulatory barriers and crafting innovative legal solutions to advance climate action and sustainable energy governance. She has published book chapters on related topics with De Gruyter and Palgrave Macmillan. AI Disclaimer : AI tools were used solely to bring the blog to the required length and to correct grammatical issues. The blog's content, ideas, and narrative were authored by the human writer, not generated by AI. References [1] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 46. [2] UNCLOS Article 286-288 (1), 293 and Article 16 and 21 of Annex VI. [3] Organisation for Economic Co-operation and Development (OECD). “Evaluation Criteria.” Development Co-operation, Evaluation and Effectiveness, https://www.oecd.org/en/topics/sub-issues/development-co-operation-evaluation-and-effectiveness/evaluation-criteria.html, OECD, accessed 24 May 2026; World Bank Group. World Bank Group evaluation principles. https://ieg.worldbankgroup.org/world-bank-group-evaluation-principles, accessed 24 May 2026. [4] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 51. [5] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 49, 50, 54-61. [6] Organisation for Economic Co-operation and Development. (2023). Glossary of key terms in evaluation and results-based management for sustainable development (2nd ed.). OECD Publishing. https://doi.org/10.1787/632da462-en-fr-es. [7] See for example,Weiss, E.B. In Fairness to Future Generations, Hotei Publishing: Leiden, The Netherlands, 1988; Schlosberg, D. (2004). Reconceiving Environmental Justice: Global Movements And Political Theories. Environmental Politics, 13(3), 517–540; Schlosberg, David and Lisette B. Collins. From environmental to climate justice: climate change and the discourse of environmental justice. Wiley Interdisciplinary Reviews: Climate Change 5 (2014) 359–374; Newell, P., Srivastava, S., Naess, L. O., Torres Contreras, G. A., & Prize, R. (2021). Toward transformative climate justice: An emerging research agenda. Wiley Interdisciplinary Reviews: Climate Change, 12(6). [8] United Nations University Institute for Environment and Human Security. (2025). 5 key dimensions of climate justice. https://unu.edu/ehs/article/5-key-dimensions-climate-justice, United Nations University, accessed 24 May 2026. [9] Vienna Convention for the Protection of the Ozone Layer. (n.d.). https://legal.un.org/avl/ha/vcpol/vcpol.html [10] Laboratory, N. C. S. (n.d.). NOAA CSL: Scientific Assessment of Ozone Depletion: 2014. https://csl.noaa.gov/assessments/ozone/2014/preface.html. [11] Cordis, C. (1992, February 25). Montreal Protocol: Amendment increases CFC/halon controls. CORDIS | European Commission. https://cordis.europa.eu/article/id/748-montreal-protocol-amendment-increases-cfchalon-controls/de. [12] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 243. [13] https://blogs.law.columbia.edu/climatechange/2024/05/22/the-itlos-advisory-opinion-on-climate-change-an-introduction-into-the-joint-blog-symposium/. [14] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 312–320. [15] Request for Advisory Opinion submitted by the Commission of Small Island States on Climate Change and International Law, Advisory Opinion, 21 May 2024, para 212 and 213; Torre-Schaub, M. (2024, December 19). Why climate science matters for international Law. Climate Law Blog. https://blogs.law.columbia.edu/climatechange/2024/06/06/why-climate-science-matters-for-international-law/. [16] Walker-Crawford, N., Reyes, J. J., Petkov, N., Palazzo Corner, S., Grantham Research Institute on Climate Change and the Environment, & Grantham Institute - Climate Change and the Environment. (2026). Science in the courtroom: evidentiary needs in climate litigation. Grantham Research Institute on Climate Change and the Environment, London School of Economics and Political Science and Grantham Institute - Climate Change and the Environment, Imperial College London. https://doi.org/10.21953/researchonline.lse.ac.uk.00137472. Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.

On 15 July 2026, in observance of World Youth Skills Day, the Future of Evaluation series launched its second season with a dialogue on the core skills young evaluators need to be future-ready. The discussion highlighted that while technical competence remains the backbone of evaluation—alongside emerging areas like AI literacy, systems thinking, and foresight—it is non-technical competencies that will set the next generation apart. Skills such as empathy, connection, sound judgement, communication, adaptability, and a commitment to continuous learning, were identified as equally vital for shaping the future of young evaluators. In case you missed the conversation, watch the recording. Seven quick takeaways from the dialogue Move from measuring the past to informing the future. Evaluation has traditionally asked what happened and whether a programme worked. The dialogue argued that tomorrow's evaluator also has to ask what could happen, whether an intervention will still be relevant in five years, what emerging risks decision makers should prepare for and how programmes should adapt. Foresight, the practice of using evidence to think through possible futures, is moving from a specialist add-on to a core evaluative competency alongside methods, systems thinking and communication. Work with AI, not for AI. AI literacy featured as one of the defining skills of the next decade. The competency required is critical AI literacy, meaning the ability to question what technology delivers, verify its outputs and know when to use a tool and when to hand the task back to human judgement. Evaluative reasoning, the work of weighing evidence and deciding what has merit, is the part of the process that must remain human. Emerging evaluators were urged to experiment with the tools, get familiar with them, and use that familiarity to shape how evaluation uses AI, rather than letting AI shape evaluation. Empathy is core evaluative practice, not a soft skill. An evaluator's primary role is to bridge conflicting belief systems, ideologies, and politics—far beyond translating technical jargon or data platforms. As global divisions increasingly center on how data is interpreted rather than what it shows, the ability to hold multiple perspectives and build common ground between data creators and users has become an indispensable evaluative skill. Stay close to the work, and give back to the ecosystem. Evaluators who understand how programmes actually run on the ground make better judgements. That means spending time with programme designers, communities and frontline staff, rather than working only from reports and data at a desk. It also means giving back through sharing findings, methods and lessons across evaluations, and through building communities of practice, so that each evaluation builds on the ones before it, rather than repeating work already done in the same context by another organisation. Evaluation cannot grow what it cannot see. Evaluation's biggest risk is often described as a lack of future-ready evaluators. A fundamental gap is that evaluation as a profession does not know its own ecosystem. Basic questions such as how many evaluators work in a given country, where they are trained and what pathways lead them into leadership have no clear answer. The next generation cannot be grown into a system that has not been mapped. Undertaking this mapping, and understanding the supply and demand for evaluators in each region is an overdue exercise. Beyond methods and models, human qualities set the next generation of evaluators apart. In addition to methods and frameworks, young evaluators must hone skills like adaptability, influence, curiosity, judgment, entrepreneurial thinking, connection, and empathy. While rarely listed in a standard job description, these competencies are what turn technical proficiency into evaluations that drive real action. They are what separate a proficient evaluator from a future-ready one. Lessons from the Youth in Evaluation champion. A new feature of Season 2 is a dedicated segment in every dialogue where a Youth in Evaluation champion shares their experiences alongside the panel. In this session, the champion—speaking from an academic perspective—turned the focus toward higher education. They proposed five core competencies for a modernized curriculum: systems thinking, digital and AI literacy, foresight, communication, and interdisciplinary collaboration. The takeaway was clear: universities can no longer update a curriculum every five years and expect it to remain relevant. What matters now is a living curriculum—supported by faculty who learn alongside their students. The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse. This was the first dialogue of Season 2. The second dialogue will take place on 19 August 2026 in observance of World Humanitarian Day. Register. This article was written with AI support with human authors in the lead.

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By Irasha Jayasekara EvalYouth Sri Lanka What if evaluation was not only about measuring outcomes, but about listening deeply, continuously and at scale? Traditionally evaluation has often focused on numbers: indicators, targets, and measurable results. While these are essential, they often overlook something equally important: the human experiences behind those numbers. Today social media platforms offer a new space where people openly share their concerns, questions and lived realities. This creates an opportunity for evaluators to move beyond measurement and toward meaningful listening. This blog explores how AI-assisted qualitative analysis of social media conversations can strengthen the evaluation of HIV testing promotion in Sri Lanka by bringing real voices into evidence. The blog argues that listening-centered evaluation is essential for designing more inclusive, effective and people-centered health interventions. Limitations of traditional evaluation in HIV testing promotion Evaluation practices in HIV-related programmes have often relied on structured tools designed to capture measurable change. However, in sensitive public health areas such as HIV, this approach has clear limitations. In Sri Lanka, HIV testing uptake among key populations continues to be influenced by stigma, fear and concerns about confidentiality. These are not easily measurable factors, yet they play a decisive role in shaping health-seeking behavior. Numbers can tell us how many people accessed a service, but they cannot fully explain why others hesitate or avoid it altogether. This highlights a critical gap in evaluation within HIV programmes; one that requires a deeper understanding of human emotions, perceptions and social contexts. Evaluation risks producing incomplete or misleading conclusions without this understanding. The rise of social media as a source of evaluation evidence The rapid expansion of digital platforms has transformed how people access and share information. Social media is no longer just a communication tool; it has become a space where individuals seek guidance, express uncertainty and interact in real time. For many people, especially those from marginalized communities, these platforms offer a sense of anonymity and safety that encourages openness. This shift presents a powerful opportunity for evaluation. Instead of relying solely on designed data collection tools, evaluators can now learn from naturally occurring conversations. These interactions provide immediate and authentic insights into user needs and behaviors, opening the door to a more responsive and adaptive form of evaluation that evolves alongside the intervention itself. Case example: The Know4Sure digital platform in Sri Lanka The Know4Sure digital platform in Sri Lanka illustrates how this opportunity can be translated into practice. As an online initiative promoting HIV testing among key populations, it generates a continuous stream of user interactions, including comments, messages and inquiries. These interactions reflect real concerns and experiences, often expressed in users’ own words and shaped by their social realities. By applying AI-assisted qualitative analysis, large volumes of such data can be systematically examined to identify patterns and emerging themes. However, the true value of this approach lies not only in its analytical capacity but in its ability to transform evaluation into an ongoing process of listening. Instead of producing static reports, evaluators can engage with real-time feedback, enabling timely adjustments, improved communication strategies and more responsive interventions. Key user insights: Information needs and decision-making Listening to these conversations reveals important insights into how individuals think about HIV testing. A dominant pattern is the strong demand for clear and trustworthy information. Many users ask questions about testing procedures, timelines and outcomes, reflecting uncertainty and hesitation. (Example: “I want to get an HIV test. Can you tell me how and where I can do it?”) These information needs are not simply gaps in knowledge; they are part of a broader decision-making process where individuals weigh risks, fears and expectations. Understanding this process is critical for designing interventions that respond to user needs and support informed decision-making. Barriers to HIV testing: Fear and trust in digital spaces Fear remains a persistent and powerful barrier. Even within the relative anonymity of digital spaces, users’ express concerns about being identified, judged or stigmatized. (Example: “Is there a safe and anonymous way to get tested for HIV?”) This highlights that increasing service availability alone is not sufficient. Emotional and social dimensions must also be addressed if interventions are to be effective. Closely linked to this is the issue of trust. Users continuously assess the credibility of the platform through its tone, responsiveness and clarity of communication. While quantitative metrics such as reach and engagement rates are useful, they fail to capture this qualitative dimension of user experience. Meaningful engagement depends not just on how many people interact, but on how they perceive and trust the platform, which ultimately influences their willingness to act. From engagement to action: Understanding user transitions Importantly, some interactions signal moments of transition, where users move from curiosity toward readiness to act. Questions about where and how to get tested suggest a shift from passive interest to active intention. These moments are particularly valuable from an evaluation perspective, as they highlight opportunities for timely intervention and tailored support. However, the conversations also reveal a gap in continuity. While initial engagement is often strong, there is limited evidence of sustained interaction beyond first contact. This raises important questions about follow-up, long-term engagement and the overall effectiveness of digital interventions in supporting users throughout their journey from awareness to action and beyond. Protecting user privacy, ensuring responsible data use and maintaining transparency are critical for building trust and safeguarding participants in digital environments. AI-enabled continuous evaluation and human interpretation These insights point to a broader shift in how evaluation should be understood and practiced. Rather than being a one-time activity conducted at the end of a project, evaluation can become a continuous learning process embedded within programme implementation. AI plays an important role in enabling this shift by making it possible to process large volumes of qualitative data efficiently and consistently. However, human interpretation remains essential to ensure that findings are meaningful, contextually grounded and ethically sound. In sensitive areas such as HIV, where behaviors are shaped by complex social and emotional factors, qualitative evidence provides a depth of understanding that quantitative data alone cannot achieve. At the same time, ethical considerations must remain central. Challenges and ethical considerations in AI-based evaluation Despite its potential, this approach is not without challenges. Digital platforms may not equally represent all segments of the population, particularly those with limited access to technology or digital literacy. Privacy concerns are especially significant when dealing with sensitive health-related information, requiring careful and responsible data management practices. In addition, social media environments are often saturated with large volumes of information, including misinformation and contradictory content. In some cases, individuals may rely on inaccurate online information for self-diagnosis or decision-making, which can influence both behaviour and the interpretation of online discussions. The use of AI tools also demands technical capacity and ongoing oversight to ensure accuracy, fairness, and the minimization of bias. To address these challenges, evaluators need to apply critical and context-sensitive approaches, including triangulating social media data with other data sources, validating findings with stakeholders and maintaining human oversight in AI-assisted analysis. Clear ethical guidelines, digital literacy considerations, and transparent analytical processes are essential to ensure that insights generated are both credible and responsible. These considerations highlight the importance of combining technological innovation with human judgment and ethical awareness in AI-based evaluation. Conclusion: Evaluation as an act of listening Ultimately, evaluating social media interventions in Sri Lanka; such as the Know4Sure platform, which uses social media channels like Facebook, WhatsApp and YouTube to promote HIV testing demonstrates that evaluation can be more than measurement; it can be an act of listening. By engaging with the voices expressed through digital platforms, evaluators can better understand the complex realities that shape health behaviors. AI makes it possible to listen at scale, but it is the responsibility of evaluators to interpret these voices thoughtfully and use them to inform meaningful action. As the field of evaluation continues to evolve in support of the Sustainable Development Goals, approaches that center on listening, learning and responsiveness will become increasingly important. Meaningful evaluation is not just about generating evidence; it is about understanding people and using that understanding to create more inclusive, responsive and effective systems that meet their needs. As HIV-related stigma remains a global challenge, how can we make evaluation systems more inclusive of the voices and lived experiences of those most affected? Irasha Jayasekara is a Monitoring and Evaluation professional at the Family Planning Association of Sri Lanka and Co-Leader of EvalYouth Sri Lanka. She is passionate about digital evaluation, AI-assisted research and youth-led evaluation approaches. Her work focuses on HIV prevention, social media analytics and strengthening evidence-based public health interventions. AI Disclaimer : AI tools were used solely to bring the blog to the required length and to correct grammatical issues. The blog's content, ideas, and narrative were authored by the human writer, not generated by AI. Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.

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In observance of the World Day of Creativity and Innovation, the ninth Future of Evaluation dialogue was convened on 21 April 2026 to explore how innovative approaches are reshaping evaluation in response to complexity, uncertainty, and rapid change. The dialogue called for creativity and innovation to be seen as part of evaluation's long history. For eighty years, evaluators have kept changing and improving their methods to answer new questions, and today is no different. The discussion argued that the main challenge now is not finding new evaluation tools. It is about asking better questions about a more complex world, making room for more people to decide which questions matter, and updating the organizational rules so that evaluation processes and methodologies have flexibility. In case you missed the conversation, watch the recording. Seven quick takeaways from the dialogue Creativity has shaped evaluation for decades, not just since AI. The discussion walked through eighty years of change in evaluation. In the 1960s and 1970s, evaluators learned to combine formative and summative methods and to link evaluation with policy. In the 1990s, the long debate between qualitative and quantitative methods was settled by mixing both. The 2000s brought systematic reviews and evaluation mapping. From 2010 onwards, developmental, systems and transformative approaches took shape, and transformative evaluation is now the defining mode of the present era, with rapid evaluation, big data and AI emerging as tools that operate within it. For young and emerging evaluators, the message is clear: learn this history before reaching for the newest tool. To think outside the box, you first have to know the box. Start with the evaluation questions, not the toolkit. What matters is not how innovative the methods are, but how well they fit the questions. Familiar tools still work well for familiar questions, for example, whether a programme achieved its results or used its resources well. The problem comes when evaluators try to use the same old tools to answer new kinds of questions. Evaluation practitioners today face situations that did not exist ten years ago, such as people moving because of climate change, communities left behind by digital technology, overlapping crises, and programmes that must continue through elections, wars, and natural disasters. The first act of creativity is to choose the method that fits the question, rather than starting from a fixed toolkit and forcing every evaluation through it. Agility should be built into the contractual framework of the evaluation, not only into its methodological design. Evaluation frameworks are already becoming more flexible when it comes to methodology (more adaptive inquiry frameworks). Several United Nations agencies and the European Commission now include feedback loops, adjustable questions, and real-time learning in their evaluations. The bigger problem lies elsewhere. Contracts and administrative rules tend to be designed for traditional summative evaluations, with fixed deliverables, set payment schedules, and locked terms of reference. These rules do not fit evaluations that need to adapt as they go. Until the contracts change, evaluators trained in adaptive methods cannot use what they have learned in practice. Treat foresight as a distinct evaluation skill. Foresight is not the same as adaptive or creative evaluation. Foresight uses data to project trends and to build possible future scenarios. For example, it can show what small-scale farming in Africa might look like if large corporations keep taking over, and how that picture changes if specific policies or conditions shift. With the large amount of data and the analysis tools now available, evaluators can do this kind of forward-looking work for the first time. But foresight has been developed in other disciplines, and evaluators should learn from those disciplines instead of trying to build it from scratch. Use AI as an evaluation thought partner, with humans always in the loop. AI is useful for handling the large volume of open data that evaluators now have access to. But AI is not a neutral authority. It is trained on data that can be incomplete or biased, and it can argue either side of a question depending on how it is asked. What keeps evaluation trustworthy is the human contribution of values, context, and ethical judgment. Organizations need clear policies on AI use, and evaluators need the habit of questioning AI outputs rather than accepting them. Ground evaluation innovation locally. Creativity and innovation are not shared equally. Most innovation happens in well-funded institutions and in the Global North. Left unchecked, this widens the gap with local practitioners, civil society organizations, and indigenous communities. Keeping innovation grounded means using local languages, avoiding technical jargon, and recognizing that oral histories, community traditions, and indigenous systems of accountability are already rigorous and innovative. It also means involving young and emerging evaluators in the design and analysis of evaluations, not only in data collection. Innovation that ignores these realities risks worsening existing inequalities. Put power considerations at the centre of evaluation, and recognize evaluators as agents of change. The dialogue named power as the issue most often left out of conversations about innovation, even though it shapes them. Innovation is not only about tools. It is about who decides what counts as innovative, whose questions are asked, whose knowledge is taken seriously, and who gets to share the findings. Evaluators were encouraged to see themselves as part of the change they measure, not as outside observers. The call to action is practical: let go of old assumptions, stay open and humble in the face of different viewpoints, and treat evaluation as a practice that helps programmes improve, not only one that judges whether they worked. The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse. The ninth dialogue marks the end of the first season of Future of Evaluation dialogues. The second season will start with the tenth dialogue in July 2026. Meanwhile, registration is open for the Youth in Evaluation Forum 2026, to be held from 19 to 21 May 2026. Learn more This article was written with AI support with human authors in the lead.

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By Erica Mattellone Senior Evaluation Specialist, UNICEF Evaluation Office The recent Future of Evaluation dialogue left me reflecting on a simple but transformative idea: evaluation can accelerate gender equality, but only if we rethink what evaluation is for. For many years, evaluation has primarily served accountability, assessing results at the end of programmes. Yet in a world shaped by rapid technological change, climate shocks, and persistent inequalities, this approach is no longer enough. Evaluation must move beyond retrospective judgement and become a driver of learning, voice, and action. One of evaluation’s most powerful roles, and one of reasons I chose a career in evaluation, is making inequalities visible. Many barriers facing women and girls, such as unpaid care burdens, restrictive social norms, digital exclusion, or technology-facilitated gender-based violence, remain hidden in aggregated data. Gender-responsive and intersectional evaluation helps reveal who is being left behind, why exclusion persists, and how power structures influence outcomes. Evidence, in this sense, becomes a tool for transformation rather than measurement alone. This shift became especially tangible during my recent experience managing the Evaluation of the implementation of the UNICEF Gender Policy and Gender Action Plans where elevating young people’s voices was not an add-on but a central objective. We wanted to understand change not only through indicators, but through lived experience. Across countries, adolescent girls and boys who had participated in UNICEF programmes joined participatory focus group discussions designed as safe and engaging spaces for reflection. One activity, inspired by Roger Hart’s Ladder of Participation, proved particularly powerful. A ladder was drawn at the center of the room, each rung representing a different level of participation, from being informed to influencing decisions. Young people reflected on their roles in programmes, writing words or drawing images that represented their experiences before placing them on the ladder. What followed were stories rather than answers. A participant described being invited to speak but unsure if adults truly listened. Another shared how contributing ideas to programme design made her feel respected and capable of creating change. As discussions unfolded, some even moved their placements, realizing their agency had grown over time. The ladder became more than a tool; it became a space for collective reflection on voice, power, and decision-making. These conversations complemented an appreciative inquiry approach, helping us understand not only whether change occurred, but how UNICEF contributed to expanding young people’s agency and aspirations. Young people also shaped the evaluation itself through a Youth Advisory Group that contributed insights throughout the process, strengthening the relevance and credibility of findings. Their engagement reinforced a key lesson: evaluation becomes more meaningful when participants are co-creators of knowledge rather than sources of data. The dialogue also challenged a common assumption that timeliness and rigour are in tension. Future-fit evaluation requires both. Adaptive approaches such as real-time learning and continuous feedback allow programmes to adjust as contexts evolve, while transparency and methodological clarity safeguard credibility. Ultimately, evaluation has impact when it is designed for use, not simply for proof. Its purpose is to help systems learn earlier, listen better, and act more fairly. The future of evaluation lies in evidence that is credible enough to trust, inclusive enough to reflect lived realities, and timely enough to shape decisions. When these elements come together, evaluation becomes more than assessment – it becomes a catalyst for gender equality and lasting change for every woman and every girl. Erica Mattellone is a senior leader in international development with over 20 years of experience advancing organizational effectiveness and evidence-informed change. As Chief of Institutional Effectiveness at UNICEF’s Evaluation Office, she leads global evaluations that translate evidence into action to protect children’s rights and expand opportunities for women and girls worldwide. This blog was co-published on the UNICEF website. Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.

By Yuanyuan Zang & Cheng Wang EvalYouth China SDG 11 gives cities sixteen indicators to track urban sustainability — yet a decade into implementation, informal settlements persist, and displacement continues. In this blog, we ask an uncomfortable question: has SDG 11's measurement framework become a ceiling on ambition rather than a floor for action? Drawing on Guangzhou's decade-long effort to extend public housing access, we show one example of how a city can move from perfunctory compliance to genuine inclusion and push further and ask: in your city, what does standard measurement fail to capture? Who remains present but uncounted? What institutional responses have been deferred — and what would it take to finally begin? There is a paradox at the heart of global urban sustainability: the more comprehensively we try to measure it, the less political momentum we seem to muster to govern it. SDG 11, which commits to inclusive, safe, resilient, and sustainable cities, is one of the most ambitious goals in the 2030 Agenda — tracked through 16 indicators spanning housing, transport, cultural heritage, disaster risk, air quality, and rural-urban linkages [1]. Yet the crises it was designed to prevent continue to persist: informal settlements grow, displacement accelerates, and climate shocks outpace urban resilience. A decade into implementation, the more pressing question is no longer how comprehensively we are measuring — but what we are fundamentally doing to address these issues. The problem, we argue, runs deeper than a lack of monitoring tools or political will. When cities are evaluated through a fixed set of visible indicators, they begin to optimize for what is measurable rather than what is meaningful — and the framework meant to guide urban sustainability quietly becomes a ceiling on ambition. Real cities function as dynamic ecosystems where housing, labor mobility, and climate resilience are inseparable; a framework that treats them as isolated entries does not just fail to capture urban complexity, it actively narrows the vision of what better cities could look like. This problem is self-reinforcing. Top-down policy directives and bottom-up implementation challenges feed into each other, creating a feedback loop that breeds inertia. As Simon et al. (2016) caution, when SDG indicators fail to align with the policy agendas of local authorities, reporting compliance risks can drift toward becoming an end in itself rather than a stimulus for meaningful urban sustainability transitions — a dynamic that is especially pronounced where institutional capacity is already strained [2]. What the decade of implementation since 2015 has revealed is not that this problem has been resolved — but rather that we now understand far more clearly the implementation challenges accumulating across country-specific contexts, and what the actual problem entails. At the top-down policy level, the indicator architecture still treats the inherently cross-cutting agenda of sustainable urbanization as a series of isolated entries. Without coordinated land use planning (SDG 11.3), improved transport accessibility (SDG 11.2) can fuel urban sprawl; without tracking displaced residents, reporting slum reduction (SDG 11.1) can mask deepening exclusion. The pursuit of global comparability systematically underweighs these interdependencies further. When these universal indicators confront the administrative hierarchies and statistical systems of different countries, they may prove ill-suited for purpose. At the bottom-up implementation level, where monitoring meets governance, three structural bottlenecks compound these top-down failures:  Traditional methods relying on censuses, sample surveys, and administrative registrations function like expensive snapshots of a fluid city, forever lagging behind evolving realities; Indicators remain fragmented across data sources, methodologies, and statistical units, making it impossible to track distributional dynamics or learn across cities; Knowledge and action remain persistently decoupled: indicators accumulate in annual reports rather than informing the planning decisions and investment sequences that actually shape urban trajectories. From "compliance competition" to "confronting paradoxes": Lessons from Guangzhou The experience of megacities in the Global South further illustrates these limitations on an unprecedented scale. Taking Guangzhou—one of the world's most dynamic migrant-receiving cities—as an example, its urban renewal tells a story of significant physical progress. By 2025, the city had mobilized massive investments in renovating old residential communities and improving urban infrastructure (Guangzhou Municipal Government, 2026) [3]. If measured strictly against the "physical indicators" of SDG 11—such as the volume of housing supply and infrastructure resilience—Guangzhou represents a narrative of remarkable compliance.  However, this "numerical success" also brought the city to a critical "wall of conflict between indicators and reality" earlier than most. As a megacity, by 2020, Guangzhou's usual resident population had reached 18.68 million — of whom roughly half were classified as part of the floating population, broadly referring to residents living in Guangzhou away from their place of household registration. (Guangzhou Municipal Bureau of Statistics, 2021) [4][5]. This demographic reality is also a governance challenge. Without local registration, this population faces systematic barriers to accessing publicly provided welfare, and housing is where that exclusion is felt most acutely. Recent research drawing on Guangzhou survey data constructs a Housing Precarity Index (HPI) across six dimensions — tenure security, housing affordability, housing quality, commuting burden, access to public education and healthcare, and access to surrounding living facilities — and finds that the inability to access public rental housing leaves young low- and middle-income renters significantly more exposed across all of these dimensions simultaneously (Chen et al., 2026) [6]. Housing, in this framework, is not merely shelter: it is the entry point into the city's broader social infrastructure. The significance of Guangzhou’s case lies in its proactive shift toward "governing areas invisible to indicators”. Recognizing that social sustainability cannot be achieved through physical construction alone, Guangzhou initiated a series of iterative reforms. Since 2016-17, Guangzhou has progressively opened its public rental housing system to non-registered residents, allocating a substantial share of its housing security resources specifically to migrants — a meaningful departure from the local-registration-tied allocation logic that has historically governed urban welfare. Strikingly, evidence suggests this approach achieves genuine inclusion: once inside public rental housing, migrants experience reductions in housing precarity comparable to, and in some service-access dimensions more pronounced than, those of local residents — because access to public housing grants migrants equal entry into services from which they would otherwise be institutionally excluded (Chen et al., 2026) [6]. Taken together, these reforms suggest a city willing to name the institutional contradictions embedded in its own system — and to build policy responses around them. In its most recent steps, Guangzhou further extended housing security to newly employed non-registered workers (Guangzhou Municipal Housing and Urban-Rural Development Bureau, 2025) [7] and promoted equalization of education and healthcare access regardless of registration status (Guangzhou Daily, 2026) [8]. Beyond measurement, toward inclusive urban governance These are not finished stories — and that incompleteness is precisely what makes them valuable. What Guangzhou's experience ultimately demonstrates is a particular governance mindset: identify the constraint blocking inclusion, name it honestly, and build an institutional response — rather than waiting for a perfect monitoring framework to tell them what to optimize. The broader challenge for the global evaluation community mirrors Guangzhou's experience. As assessment frameworks grow more sophisticated, the more pressing question may not be how to measure more precisely, but how to adequately integrate evaluation into implementation — moving beyond principles to identify the specific binding constraints that limit people's welfare in particular places. The bottleneck is rarely universal; it is embedded in local institutions, histories, and political economies that aggregate indicators, by design, were never built to surface. We close not with a transferable model but with a provocation. SDG 11 will not be achieved by cities that build more; it will be achieved by cities that govern better, for everyone within them. So we leave you with the questions that should precede any indicator under SDG 11: in your city, what does standard measurement not capture? Who is present but uncounted? What institutional response has been deferred? And what would it take to begin? Yuanyuan Zang is a member of EvalYouth China and the 7th Cohort of the Horizon Global Youth Development Program. She focuses on global brand communication, advancing sustainable impact. She previously served as an Urban Designer at Surbana Jurong from 2021 to 2023, specializing in community development and sustainable master planning. Cheng Wang is the Founder of EvalYouth China and a master’s in public administration / international development candidate at Harvard Kennedy School. He is also a member of the 6th cohort of the Horizon Global Youth Development Program. He previously served as a Monitoring and Evaluation Specialist at UNDP from 2022 to 2025. Connect with Cheng Wang on LinkedIn . AI Disclaimer: This blog was researched and written with the assistance of AI tools. All ideas, analysis, and editorial decisions reflect the authors' own thinking; AI was used solely to support the research process. References [1] United Nations Statistics Division. “SDG Indicators Metadata Repository: Goal 11. Make Cities and Human Settlements Inclusive, Safe, Resilient and Sustainable.” SDG Indicators, https://unstats.un.org/sdgs/metadata/?Goal=11   [2] Simon, David, et al. “Developing and Testing the Urban Sustainable Development Goal's Targets and Indicators: A Five-City Study.” Environment and Urbanization, vol. 28, no. 1, 2016, pp. 49–63. SAGE Publications, https://doi.org/10.1177/0956247815619865 [3] Guangzhou Municipal Bureau of Housing and Urban-Rural Development. “Guangzhou Municipal Bureau of Housing and Urban-Rural Development 2025 Work Summary and 2026 Work Plan.” Guangzhou Municipal Government , 12 Feb. 2026, [4] Guangzhou Municipal Bureau of Statistics, and Office of the Leading Group of the Seventh National Population Census of Guangzhou. “Guangzhou Seventh National Population Census Bulletin (No. 1): Situation of City’s Permanent Population.” 18 May 2021. [5] Guangzhou Municipal Bureau of Statistics, and Office of the Leading Group of the Seventh National Population Census of Guangzhou. “Guangzhou Seventh National Population Census Bulletin (No. 6): Urban-Rural Population and Floating Population.” 18 May 2021. [6] Chen, L., et al. “Does Access to Public Rental Housing Alleviate Housing Precarity among Young Low- and Middle-Income Renters? Evidence from Guangzhou, China.” Cities, vol. 171, 2026, article 106780. https://doi.org/10.1016/j.cities.2026.106780 [7] Guangzhou Municipal Housing and Urban-Rural Development Bureau. "Notice on Extending the Validity of the Guangzhou Public Rental Housing Security Measures for Newly Employed Housing-less Workers". Guangzhou Municipal People's Government Portal , 20 Dec. 2024, www.gz.gov.cn/gfxwj/sbmgfxwj/gzszfhcxjsj/content/post_10038128.html . Effective 1 Mar. 2025. [8] Guangzhou Daily. Guangzhou Uses 'Small Breakthroughs' to Drive 'Big Changes': A New Vision for People's Livelihoods. Guangzhou Municipal People's Government Portal, 22 Jan. 2026, www.gz.gov.cn/zt/gzlfzgzld/gzgzlfz/content/post_10657232.html . Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.

In observance of International Women’s Day, the eighth Future of Evaluation dialogue was convened on 10 March 2026 to explore how evaluation can serve as a mechanism for accelerating rights, justice, and transformative action for all women and girls. The dialogue called for transforming evaluation from a “measurement of progress” into a profession that actively confronts power and highlights systemic inequalities. A fundamental shift was advocated: moving beyond "improving averages," which often masks the fact that marginalized groups are being left behind even when overall statistics look positive, toward a model that prioritizes disaggregated data and centers the voices of women and girls as equal partners in development. This transformation is presented as essential for ensuring evaluation remains a relevant tool for justice in a world facing a polycrisis of climate change, economic instability, and the rapid rise of technologically facilitated gender-based violence. In case you missed the conversation, watch the recording. Five quick takeaways from the dialogue Focus intentionally on structural causes and hidden inequalities through intersectional lenses.  It is recognized that aggregated data often masks the specific barriers faced by women and girls, such as social norms, unpaid care burdens, and digital exclusion. To avoid reinforcing the status quo, evaluations must be intentionally designed to investigate the "why" behind persistent inequalities by utilizing gender-responsive, intersectional frameworks. By analyzing how factors like disability, age, ethnicity, and class intersect with restrictive laws and household power relations, evaluators can transition from merely documenting inequalities to providing the evidence base necessary for dismantling them. This level of visibility is essential for designing policies that fundamentally transform the unequal systems of power that sustain disparity. Shift from transactional to transformative evaluation practices.  The dialogue emphasized that evaluation serves its highest purpose when it is embraced as a continuous process of learning rather than a transactional end-of-cycle reporting requirement. A transformative approach requires evaluation to challenge prevailing assumptions and build shared ownership of evidence among stakeholders. When evaluation is used as a driver of voice and action, it moves from being a bureaucratic necessity to a strategic asset that supports collective rights and justice for every woman and girl. Integrate lived experience into the definition of success.  The future evaluation practices must center on women and girls defining success for themselves. Rather than "parachuting" into communities with predefined indicators, evaluators are encouraged to use participatory and adolescent-responsive approaches. When findings are grounded in lived experience of women and girls rather than purely institutional perspectives, the resulting evidence gains greater legitimacy and relevance. This ensures that programmes are responsive to the actual needs of women and girls rather than the convenience of the evaluator. Implement real-time and adaptive feedback loops.  In rapidly shifting humanitarian and climate contexts, evaluation lag often means findings are outdated by the time they are published. The necessity of moving toward real-time, adaptive evaluation was highlighted as a means of allowing for immediate course correction. Rapid feedback loops and short learning cycles enable organizations to spot gendered impacts early, such as a drop in school attendance among girls following a natural disaster, allowing for interventions to be scaled or adjusted before the damage becomes irreversible. Drive policy co-ownership by engaging decision makers and marginalized groups as strategic partners.  The transition from evidence to action can often fail because findings are not translated into the language of decision-makers or the realities of the community. It is recommended that evaluation commissioners involve planning and finance ministries from the outset to align recommendations with budgetary processes, while simultaneously approaching marginalized groups as strategic partners in the evaluation process. By empowering local actors and young evaluators to hold leadership roles in evaluation steering committees and co-designing evaluation methodologies, evaluators can ensure that the evaluation insights are both politically influential and rooted in local knowledge. This dual approach ensures that evaluation remains a respectful, inclusive dialogue that drives both high-level policy change and grassroots accountability. For more reflection on this dialogue, read the blog by Erica Mattellone . The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse.  The next dialogue, “Will evaluation's future be shaped by its creativity and innovation in facing emergent challenges?” will take place on 21 April 2026. Register This article was written with AI support with human authors in the lead.

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In observance of the World Day of Social Justice, the seventh Future of Evaluation dialogue was convened on 19 February 2026 to explore how evaluation can serve as a mechanism for addressing systemic inequalities. The dialogue called for transforming evaluation from a "technocratic box-ticking" exercise into a profession that advances public accountability by actively centering marginalized voices. A fundamental shift was called for: moving from "power over" toward a "power with" model that considers local communities as equal partners in decision-making. This transformation is presented as essential for ensuring evaluation remains relevant in a world facing a polycrisis of climate change, extreme inequality, and the rapid integration of emerging technologies. In case you missed the conversation, watch the recording. Five quick takeaways from the dialogue Prioritize moral judgment and social relevance through downward accountability. Evaluation education must evolve beyond technical mechanics into a comprehensive education framework that considers evaluation as a vital public service. Success of an evaluation is best measured by social impact and the reflection of local realities rather than donor compliance or technical execution alone. Traditional "upward accountability" should shift toward a model of "downward accountability", where evaluation findings are shared back with communities in accessible ways. The ultimate goal of improving lives is at risk if evaluation findings ignore what the community actually needs, or if evaluators focus more on mastering technical tools than on making fair, ethical judgments.By centering the perspectives of the communities, evaluation is moved beyond a "tick-box" exercise to become a bridge between evidence and real-world change. Transition from "human machines" to values-driven evaluators. As generative AI becomes more prevalent in data processing, the unique value proposition of a human evaluator is found in the ability to apply values, context, and ethical foresight. If evaluators act merely as "human machines" following rigid algorithms, they become replaceable. Instead, the profession must be shifted toward "responsible AI" use and human-centric judgment. Evaluators are not neutral observers; they can be viewed as agents of change who must check their own biases and motives to ensure that data is not stripped of its social context. Institutionalize intergenerational "co-creation" spaces. The future of the evaluation is dependent on bridging the gap between senior professionals and youth. Synergy is built into spaces, where methodological wisdom and "business smarts" are provided by seniors to navigate the market, while young evaluators bring a fresh perspective that challenges established assumptions. Youth should not be relegated to data-collection roles; they must be engaged in designing evaluations and reporting to ensure the profession remains adaptive to current social realities and global trends. Decolonize curricula through diverse knowledge systems. Evaluation education must be decolonized to include indigenous, community-based, and local knowledge systems. It was noted that current evaluation frameworks are often biased toward North American and Western perspectives, leading to the misrepresentation of local cultures. Education is made more inclusive by acknowledging "epistemic diversity"—recognizing that oral histories, storytelling, and spiritual practices are rigorous forms of evidence. By incorporating indigenous methodologies and relational accountability, evaluation training is made more globally relevant and respectful of the people it serves. Move from retrospective reporting to evaluative foresight. As global crises like climate migration and digital exclusion accelerate, evaluation must be moved from looking backward to looking forward. Evaluative foresight is utilized, involving the use of future-focused questions and systems thinking to prevent inequities before they become entrenched. By shifting from "what happened" to "what might happen next”, organizations can be helped to adjust in real-time. A "learning loop" is created, allowing for course correction during implementation and ensuring that a better future is shaped rather than just the past being explained. The Eval4Action Future of Evaluation dialogues are a series of forward-looking discussions that explore innovative and adaptive approaches to evaluation. Designed to make evaluation more influential in a rapidly changing and complex world, these dialogues bring together a diverse range of voices—from experts to young evaluators—to share knowledge and highlight ways to future-proof the field of evaluation. Each monthly dialogue is aligned with an international action day, ensuring the conversations are timely and relevant to a global discourse.  The next dialogue, “How can evaluation accelerate rights, justice, action, for all women and girls?” will take place on 10 March 2026. Register This article was written with AI support with human authors in the lead.

By Uugantsetseg Ginchigdorj Former Co-leader, EvalYouth Asia Mongolia, often cited as a "poster child" for democracy among post-Communist societies, stands as a unique case of democratic transition. However, the 21-day "Easy to Resign" protests in 2025, led by youth, signaled that civil society is reclaiming constitutional mechanisms for a more participatory and responsive democratic system . This episode illustrates that democratic consolidation requires more than elections; it requires responsive institutions capable of learning and accountability.   In this context, strengthening the institutional foundations that enable evidence-based learning and accountability becomes essential. This reflects growing attention to the institutionalization of evaluation, the process of embedding evaluation within the legal, social, and professional systems. Institutionalization means that evaluation becomes routine, resourced, credible, and publicly meaningful rather than episodic or donor-driven. To understand Mongolia’s current evaluation landscape, this blog draws on the Evaluation Globe  framework by the Department of Sociology and the academic Center for Evaluation (CEval) at Saarland University , which analyzes the political, social, and professional systems, combined with the insights of the 2025 National Evaluation Capacities Index (INCE) pilot .  The political system: Strong legal mandates, unclear oversight  Following the transition to democracy and market-economy in the 1990s, Mongolia has undertaken multiple efforts to establish and govern monitoring and evaluation (M&E) within the government system. This journey began with the 1996 Parliament Resolution No. 38, which set the policy on government activities and structural reform, followed by the 1999 Government Resolution No. 4, regulating the monitoring and evaluation of administrative bodies and continued subsequent amendments and legislations. Today, Mongolia possesses a robust legal framework for M&E. The Law on Development Policy, Planning and its Management (2020) and the recent Government Resolution No. 43 (2025) mandate M&E across the public sector, which formally regulates evaluation as a distinct function from monitoring. The results of the 2025 INCE pilot in Mongolia reflect this strength. The " Institutional Structure" dimension scored 4.4  out of 10, indicating that institutionalization of the evaluation ecosystem is at a moderate situation. The country has established a regulatory system where the government machinery is active; ministries report against plans and maintain dedicated M&E departments, and executives and decision-makers consume performance data as required by law. However, the system remains heavily centralized. With the Authority for Government Supervision (AGS), the successor to the General Agency for State Inspection, leading these efforts in the absence of a specific National Evaluation Policy or a high-level decision-making body on evaluation, there is a risk that evaluation is perceived merely as a tool for internal administrative control rather than for broad democratic learning. Without safeguards for independence, evaluation can be conflated with supervision rather than learning. The professional system: The missing middle  In the professional system as a sub-system in the Evaluation Globe concept, Mongolia faces a “missing middle”. The INCE pilot revealed a critical gap in the "Evaluation Offer" dimension, specifically a low score of 2.4 for "Training Programmes " , indicating the absence of a formal professional education system to supply evaluators. This weakens the ability and availability to produce independent evaluations and hinders the development of local evaluation practices. Yet, this creates reliance on external expertise and limits the emergence of a locally grounded evaluation profession. The social system: The democratic deficit  In the context of evaluation as a mechanism for government accountability, Mongolia faces a significant challenge. The INCE score for "Multi-agent spaces" was the lowest of all dimensions at 3.25 . Although Mongolia has two Voluntary Organizations for Professional Evaluation (VOPEs), the informal Mongolian Evaluation Network (MEN) and the formal Mongolian Evaluation Association (MEA) and other stakeholders as civil society organizations and international organizations, their integration in state evaluation processes remains limited. This disconnect is illustrated by the protests mentioned above, highlighting unmet demand for participatory evaluation spaces.      The way forward: Gaps to address While Mongolia has made progress, the path from "control" to "doing" and now shifting to "learning", the current landscape shows significant structural and practical gaps. It is insufficient to simply call for professional education or civil society engagement; the multi-level gaps below need to be addressed. 1. The policy gap: A critical gap remains in the absence of a National Evaluation Policy (NEP). While the country possesses laws and resolutions, it lacks a cohesive policy defining the principles of evaluation. Current laws mandate that evaluation occurs, but an NEP is needed to ensure independence and that public interests are prioritized over bureaucratic box-checking. Such a policy should define principles of independence, transparency, ethical standards, stakeholder participation, systematic use of findings, and public disclosure, guiding on how evaluation contributes to decision-making and how evidence is integrated into policy cycles. Though parliamentarians must play a leading role, this high-level strategic vision is currently missing in Mongolia.  2. The governance gap:  While the AGS is currently the government body responsible for implementing M&E across state organizations, relying solely on a single agency to govern the entire system presents a risk to accountability. To ensure true democratic accountability, there is a need for a high-level, multi-stakeholder governance mechanism in the country, perhaps through a high-level body, committee or working group. 3. The utilization gap: Perhaps the most pressing challenge is the disconnect between evaluation findings and policy design at this critical transition moment. Even with the positive step of implementing Resolution No. 43, Regulation on Evaluation, whether the mechanism to ensure that these findings actually alter the next cycle of policy design exists, remains unclear. If the country begins conducting government programme evaluations but fails to use those findings to inform the design of future strategies, the system lacks best evaluation practice. Institutionalization is incomplete if evaluation does not feed back into policy cycles. For Mongolia institutionalizing evaluation is ultimately about deepening democratic governance: ensuring that public institutions not only deliver, but listen, learn, and adapt. Moving from control to learning requires more than mandates; it requires professional capacity, civic engagement, and credible systems that connect evidence to reform. In this sense, evaluation becomes not just a tool of government, but part of democracy’s infrastructure. Uugantsetseg Gonchigdorj is an independent evaluator and consultant with a background in sociology. She specializes in programme evaluation at the intersection of policy, systems, and institutional learning across diverse development sectors. She has contributed to evaluation networks including EvalYouth Asia, EvalYouth Mongolia, and the Mongolian Evaluation Association (2023–2025). Connect with Uugantsetseg on LinkedIn . AI Disclaimer: AI tools were used solely to bring the blog to the required length and to correct grammatical issues. The blog's content, ideas, and narrative were authored by the human writer, not generated by AI. Disclaimer: The content of the blog is the responsibility of the author(s) and does not necessarily reflect the views of Eval4Action co-leaders and partners.