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How-to note: Co-designing AI solutions with crisis-affected communities (beta version)

Sarah W. Spencer, Helen McElhinney, Michael Tjalve, Anjali Mazumder

CDAC Network; Alan Turing Institute; Humanitarian Advisory AI (2025), 17 pp.

"This how-to note offers practical guidance for humanitarian actors seeking to co-design AI solutions with crisis-affected communities. This is related to, though not intended to support the technical co-design of AI models, though there is a significant amount of research on this subject. This how- ... more

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Inclusive and Secure Artificial Intelligence: A Global Perspective on Policy and Technical Developments
Deep Insights

Saiph Savage, Lili Savage

Stuttgart: Institut für Auslandsbeziehungen (ifa) (2025), 84 pp.

"As AI systems are developed and deployed, they often reflect and reinforce dominant cultural norms, marginalizing non-Western languages, epistemologies, and communities. This report explores the systemic risks associated with algorithmic bias, digital colonialism, and cultural homogenization, while ... more

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Guía de implementación de protección de datos y uso responsable de inteligencia artifical en Bolivia

Estefani Cabrera Rojas, Nicoel Angel Sanchez Rojas

La Paz: InternetBolivia; Consorcio InDiCo Global (2025), 63 pp.

"En Bolivia, aunque no existe una ley integral de protección de datos personales, el marco constitucional y normativas sectoriales reconocen el derecho a la privacidad, lo que refuerza la necesidad de avanzar hacia políticas institucionales de cumplimiento voluntario, con base en estándares inter ... more

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Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs)
Key Guides

Hamburg: Hamburg Sustainability Conference; UNDP (2025), 7 pp.

"As global stakeholders from governments, international organizations, the private sector, academia, and civil society, we convene in Hamburg to shape a human-centric, human-rights-based, inclusive, open, sustainable, and responsible AI future. We commit to advancing AI for the SDGs, aligning with o ... more

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LAO P.D.R. Artificial Intelligence Readiness Assessment Report

Paris: UNESCO (2025), 72 pp.

"• In the legal context, Lao PDR’s regulatory framework for AI is still nascent. While the government is drafting a National AI Strategy, there are currently no laws addressing core AI issues such as transparency, accountability, or algorithmic redress. Existing frameworks like the Cybercrime La ... w, Data Protection Law and the Digital Government Decree cover general data and computing use but lack AI-specific provisions. AI is referenced in recent constitutional amendments and draft digital transformation policies, but there’s room for improvement in transforming those acknowledgements to clear legal mechanisms to protect citizens and bolster innovation. • For the sociocultural domain, despite progress in gender inclusivity, rural communities in Laos still face limited access to digital technologies due to infrastructure gaps, affordability, and low digital literacy. Successful collaborations with international organizations highlight what’s possible but also stress the need for ongoing investment in local capacity, outreach, and trust-building. Digital initiatives in health and efforts addressing concerns about technology’s environmental impact are evident, but they have not been specifically focused on AI. Digital transformation must also prioritize cultural preservation, including the development of culturally-aware datasets and NLP tools. Currently, most Lao language datasets and NLP tools are lagging participation from native Lao researchers, risking linguistic sovereignty and underrepresenting local dialects, norms, and values. • AI talent and innovation development in Laos needs strong support from its education and research ecosystems. University departments like Computer Science and Software Engineering are small and often siloed, with little crossdisciplinary collaboration. Research output needs some improvement. Promising developments in AI/ICT curricula in K-12 level are welcome, although their effectiveness must be closely monitored. • Laos’s digital economy remains small, constrained by a large informal sector, limited digital infrastructure, and low ICT investment, factors that hinder AI adoption and innovation. While some private companies in sectors such as telecom, banking, logistics, and manufacturing are beginning to use AI tools, and urban populations are gradually adopting app-based lifestyles, broader progress is limited by lagging human capital pipelines, minimal domestic investment, and an underdeveloped startup ecosystem. Foreign-developed platforms still continue to dominate the market, which if continued can limit local developers from developing capabilities and use cases. Aside from that, most Foreign Development Investment (FDI) remains concentrated in resource extraction, and budget shortfalls undermine the sustainability of e-government initiatives. • There is a critical need for a strong commitment to funding both the hard and soft infrastructure that supports AI. This includes enhancing cybersecurity capacity, reliable networks, and data centers and ensuring affordable access to computing infrastructure for AI practitioners and stakeholders." (Executive summary) more

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AI and Data Science Bootcamp for Women and Minoritised Groups: Impact Report

Luisa Olaya, Deshni Govender, Abeera Dubey, Jocelyn Mukamisha, Mary Seiwah

Bonn; Eschborn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward; Intel (2025), vii, 35 pp.

"The AI and Data Science Bootcamp for Women and Minoritised Groups was designed to actively address the diversity gap in the AI field by lowering the entry barriers that women and minoritised groups face and empowering them with advanced technical and personal development skills to succeed in the AI ... more

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State of Internet Freedom in Africa 2025: Navigating the Implications of AI on Digital Democracy in Africa

CIPESA (2025), 74 pp.

"While AI offers potential benefits across various sectors, its deployment by businesses and governments and application by individuals present new opportunities while raising significant concerns. More specifically, most African countries do not have legal or regulatory measures on the ethical and ... more

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Trust, Responsibility, and Digital Governance: Regulation of AI and Blockchain Technology from a Capacity-Based Perspective

Sebastian Bücker, Marcus Düwell, Andreas Kaminski, Michael Leyer (eds.)

Bielefeld: transcript Verlag (2025), 229 pp.

"Numerous ethical guidelines and regulatory frameworks have been developed to assess and shape digital systems. However, these efforts often rest on the dubious assumption that individuals and organisations possess the necessary capacities to assess such systems in terms of justice, reliability, and ... more

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Antiqua et Nova: An Exposition of its Philosophical Intervention on Artificial Intelligence and its Relevance to Catholic Education

Rhoderick John S. Abellanosa

Kaabigan, volume 3, issue 1 (2025), pp. 16-34

"The essay is an exposition of Antiqua et Nova (AeN), a Church document that provides philosophical, theological, and pastoral reflections and guidelines on the understanding and use of artificial intelligence (AI). It is this work’s position that AeN’s significant contribution is its emphasis o ... more

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Bias in der künstlichen Intelligenz

Jonas Ditz, Elmar Lichtmeß

Bonn: Bundesamt für Sicherheit in der Informationstechnik (2025), 34 pp.

"Bias ist eine tiefgreifende Problematik für Systeme der Künstlichen Intelligenz, die eine Gefährdung für den sicheren Einsatz von solchen Systemen darstellen kann. Der richtige Umgang mit Bias ist komplex und erfordert eine umfassende Beschäftigung mit der Thematik. Diese Publikation soll Entw ... ickelnden, Anbietenden und Betreibenden von KI-Systemen eine erste Einführung in die Bias-Thematik geben. Bias-Arten weisen eine hohe Diversität auf und können in unterschiedlichen Phasen des Lebenszyklus eines KI-Systems auftreten. Eine Auswahl der relevantesten Bias-Arten sowie eine Zuordnung zur Phase des Lebenszyklus, in der diese auftreten, wird dargestellt. Die Detektion von Bias ist sowohl in Daten als auch in bereits trainierten KI-Modellen möglich. Eine Auswahl an qualitativen und quantitativen Detektionsmöglichkeiten wird präsentiert. Anschließend gibt das Manuskript eine Übersicht über Methoden, die verwendet werden können, um Bias in einem KI-System zu verhindern. Diese sind aufgeteilt in Prä-, In- und Postprozessierungsmethoden, abhängig von dem jeweiligen Zeitpunkt, zu dem sie angewendet werden können. Zum Abschluss wird die Interaktion zwischen Bias und Cybersicherheit diskutiert. Das BSI fordert von Entwickelnden, Anbietenden und Betreibenden von KI-Systemen folgende Handlungen: • Wissen hilft bei der Lösung des Problems. Es muss ein ausreichender Informationsaufbau zur Bias-Thematik stattfinden, um entscheiden zu können, welche Arten für die eigene Anwendung relevant sind. (Kapitel 2) • Zuständigkeiten müssen geklärt sein. Für verwendete Datensätze und KI-Systeme muss eine für Bias zuständige Person benannt werden. Diese Person muss in der Lage sein, potentielle Bias zu identifizieren und geeignete Gegenmaßnahmen vorzuschlagen. • Bekämpfung von Bias beginnt bei den Daten. Nach Möglichkeit müssen organisatorische und technische Maßnahmen bei der Datenerhebung etabliert werden, die potentiellen Bias in den Daten reduzieren. (Kapitel 3) • Ziel muss die Minimierung von unerwünschten Bias in KI-Modellen sein. Prä- und Inprozessierungsmaßnahmen müssen – falls anwendbar – vorrangig verwendet werden. Vor der Anwendung von vortrainierten KI-Modellen (beispielsweise KI-Systeme mit allgemeinem Verwendungszweck) muss die Notwendigkeit für Postprozessierungsmaßnahmen geprüft werden (Kapitel 4) • Bei Bias heißt es am Ball bleiben. Bias-Detektion und -Mitigation muss als Prozess verstanden werden und fester Bestandteil jeder Phase des Produktzyklus eines KI-Modells sein." (Zusammenfassung, Seite 3) more

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L'uomo è un algoritmo? Il senso dell'umano e l'intelligenza artificiale

Paolo Benanti

Castelvecchi (2025), 60 pp.

"Il mito di Ulisse ci insegna che la ricerca umana di senso è guidata dall’intelligenza, nelle sue due declinazioni: νοῦς e μῆτις, intuizione e pratica. Dalla sinergia di queste facoltà sono nate le grandi invenzioni che segnano la nostra specie, a partire dalla «grande invenzione de ... more

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Terms of (dis)service: Comparing misinformation policies in text-generative AI chatbot

Maria Giovanna Sessa

Eu DisinfoLab (2025), 8 pp.

"● In the 11 chatbots considered, references to misinformation vary (and sometimes are missing). Even when the term is mentioned, it is rarely defined. This is not uncommon: what some platforms call ‘deletion’, others call ‘termination’, though potential nuances remain unclear. Additionall ... y, it is unspecified who enforces practices, how long suspensions last, and what distinguished warnings, suspensions, and terminations. On another note, more stringent prohibitions generally focus on hate speech, highlighting the illegal nature of the issue. ● Overall, ToS violation detection and content moderation processes are unclear. Some platforms mention dedicated moderation teams and processes – typically a mix of automated and human reviews – but the details remain vague. There is no transparency regarding the resources invested in content moderation, including the number of personnel, their locations and language coverage, and the timeline for action. ● Given our focus on misinformation, we concentrated on content reporting. Nevertheless, it is evident that platforms prioritise reporting breaches of and vulnerabilities in their architecture over content-related concerns. ● Law compliance is usually referenced in broad terms as adherence to “all applicable legislation”. Platforms primarily emphasise privacy and data protection, the prohibition of illegal activities (with a particular focus on child protection), restrictions on reverse-engineering platform functions, and using the services for biometric identification. Notably, there is a perception that users bear greater responsibility for providing accurate data and avoiding platform abuse than the platforms themselves do in terms of accountability. This impression arises because the ToS are detailed regarding user obligations but more superficial about platform responsibilities. Uncertainty remains regarding platform incentives and their actual capacity to enforce these rules. ● Most platforms specify that fact-checking is the user’s responsibility as if trying to exempt themselves from liability related to providing false and inaccurate answers. However, it is worth noting that the general provisions of the EU’s Digital Services Act (DSA) require online platforms to remove illegal content expeditiously once they have actual knowledge of its illegality. ● If current platform approaches to misinformation already seem inadequate, there are valid concerns that the situation will deteriorate further. The cross-platform trend of dismantling safety policies and moderation teams reinforces these fears. Examples pointing in this direction include OpenAI’s decision to remove some content warnings on ChatGPT, and xAI’s introduction of “Unhinged Mode” in Grok-2, a beta feature described as intentionally “objectionable, inappropriate, and offensive, much like an amateur stand-up comic who is still learning the craft.” (Concluding remarks, page 8) more

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From Crisis to Renewal: Addressing AI’s Impact on Our Information Ecosystem

Lena Maria Böswald, Roa Powell, Tyreese Calnan

Berlin: Interface – Tech Analysis and Policy Ideas for Europe (2025), 18 pp.

"AI-driven search-summary features, with Google's AI Overviews (AIOs) being the most promiment example, are rapidly transforming how people access news, with profound implications for our information ecosystem. While AI holds potential to improve access to information, its current deployment risks u ... ndermining the sustainability, diversity, and reliability of news. As AI summaries summarise information directly within search results, they can significantly reduce traffic to news publishers. Evidence suggests users are less likely to click through to original sources when AIOs are present on Google, threatening the financial viability of journalism. These impacts from AI summaries and AIOs in particular are unlikely to be evenly distributed and will play out in different ways across the news sector across Europe, with smaller and ad-funded outlets particularly vulnerable, raising concerns about declining media plurality. At the same time, AI-generated summaries often fail to provide accurate and diverse information. Research shows that AI tools disproportionately rely on a narrow set of sources, marginalising smaller publishers. In addition, persistent issues with accuracy – including misleading or incorrect outputs – risk distorting public understanding and weakening trust in information systems. Current regulatory frameworks in both the EU and UK are struggling to address these challenges effectively. While multiple legal instruments are relevant and already in place – including competition law, platform regulation, copyright, and AI governance – none are fully equipped to respond quickly and comprehensively to the harms of monopolisation and the lack of remuneration for media outlets posed by AI summaries. We argue that competition policy offers the most effective and immediate route to intervention, with digital regulation serving as a secondary lever. The UK’s approach, based on flexible, case-specific competition rules, enables faster action through tailored conduct requirements for dominant firms like Google. In contrast, the EU’s framework is broader but slower, relying more heavily on traditional, time-intensive antitrust investigations and ongoing debates around copyright and remuneration for publishers. Both systems offer complementary strengths, and policymakers should learn from each other’s approaches. We therefore recommend a “competition-first” policy package to ensure fairer outcomes. Key measures include enforcing fair ranking and attribution practices, preventing unauthorised use of publisher content, and potentially requiring platforms to compensate news organisations. However, competition policy alone is not the key. We therefore propose additional long-term interventions, including greater transparency through “nutrition labels” for AI-generated content and increased public or democratic funding for journalism. These measures aim to strengthen the resilience and independence of the news sector, ensuring that trustworthy information remains accessible in an information ecosystem shaped by AI." (Executive summary) more

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Atlas der KI: Die materielle Wahrheit hinter den neuen Datenimperien

Kate Crawford

Bonn: Bundeszentrale für politische Bildung (bpb), Sonderausg. (2025), 336 pp.

"Ist Künstliche Intelligenz nur eine weitere Entwicklung der Digitalisierung des Alltags, eine effiziente Software in einer „Cloud“? Die KI-Forscherin Kate Crawford entlarvt diese verharmlosende Vorstellung und beleuchtet die konkreten Auswirkungen der Technologie auf die physische Welt. Ihre R ... more

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Zwischen Wertschätzung und Widerstand: Algorithmische Kompetenz junger Menschen am Beispiel der Kurzvideoplattform TikTok

Leonie Alatassi, Sascha Hölig, Philipp Kessling

Hamburg: Hans-Bredow-Institut (2025), 64 pp.

"In der vorliegenden Studie wurde untersucht, was Jugendliche und junge Erwachsene über die Funktionsweise des algorithmischen Empfehlungssystems (AES) von TikTok wissen, inwiefern sie damit interagieren und welche Emotionen dabei involviert sind. Dazu wurden sechs Fokusgruppen (n=31) in drei deuts ... chen Großstädten mit jungen Menschen im Alter zwischen 16 und 24 Jahren sowie Follow-up-Einzelinterviews (n=12) durchgeführt. Es zeigt sich ein übergreifend hohes Bewusstsein für algorithmische Empfehlung bei TikTok als erlebter Zustand („knowing“), der sich aus der eigenen Nutzungserfahrung ergibt. Es gibt altersbezogene Unterschiede beim Wissen um Einflussfaktoren und insgesamt ein begrenztes Wissen zur Datensammlung und -verarbeitung sowie damit einhergehend geringe Bedenken und Reflexionen über die Preisgabe personenbezogener Daten. Such-, Video-, Profil- und Sozialinteraktionen sind in die alltägliche Nutzung der Plattform eingebettet und finden größtenteils unbewusst, ohne explizite Steuerungsabsicht, statt. Die Teilnehmenden können innerhalb der von der Plattform vorgegebenen Strukturen agieren und Handlungsziele durchsetzen, erleben die (technischen) Grenzen jedoch als kaum beeinflussbar. Häufig fehlen Wissen und Motivation, um tiefergehende Einstellungen, etwa zum Datenschutz, der personalisierten Suche oder Profileinstellungen, aktiv zu verändern. Emotionen spielen in der Interaktion mit der For-You-Page (FYP) eine große Rolle. Die Teilnehmenden erleben positive Gefühle der Wertschätzung, indem der Algorithmus als personalisierter Begleiter erlebt wird, der individuelle Vorlieben erkennt, inspiriert und das Nutzungserlebnis angenehm gestaltet. Gleichzeitig entstehen negative Emotionen wie Genervtheit, Unbehagen oder Kontrollverlust, insbesondere bei unpassenden Inhalten, einer wahrgenommenen Übersteuerung durch den Algorithmus oder der eigenen Nutzungsdauer. Diese Gefühle führen teils zu Widerstand in Form von aktiven Interaktionshandlungen oder zu selbstregulativen Strategien (z. B. Löschen der App) und sind Ausdruck eines Autonomiestrebens. Die Unterscheidung zwischen passiven Kontakten mit politischen Informationen auf TikTok (push: „ich schaue mir politische Videos an, die mir gezeigt werden“) und aktiven Informationshandlungen durch Kuratierungspraktiken wie das Liken von Videos, das Folgen und Nachschauen von Profilen oder die Nutzung der Suchfunktion (pull: „ich nutze die Plattform, um mich zu informieren“) ist essenziell. Grundsätzlich empfinden es die meisten Teilnehmenden als praktisch, wenn Nachrichten oder politische Themen in Form von kurzen Videos auf der FYP angezeigt werden, weil das passive Scannen dieser Inhalte das Gefühl erzeuge „auf dem aktuellsten Stand“ zu sein. Die wenigsten Teilnehmenden konsumieren gezielt politische Inhalte, indem sie nach Themen suchen, politische Videos favorisieren oder politische Profile anschauen und diesen folgen. Die Beschäftigung mit Nachrichten und Politik im Kontext der TikTok-Nutzung widerspricht dem Eskapismus- und Unterhaltungsbedürfnis vieler Teilnehmender. Es gibt eine Grundskepsis gegenüber TikTok, die sich zum einen auf das Image der Plattform, „nicht vertrauenswürdig“ zu sein, stützt, und zum anderen auf die Angst vor „falschen Informationen“ und die damit zusammenhängende Wahrnehmung, dass es sich bei TikTok nicht um eine „seriöse“ Quelle, sondern eine reine Unterhaltungsplattform handle." (Überblick über die wichtigsten Ergebnisse, Seite 5) more

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The Influence Evolution: Harnessing AI Innovation While Preserving Human Connection in Social Media

Katja Muñoz, Maria Pericàs Riera

German Council on Foreign Relations (DGAP) (2025), 10 pp.

"Social media stands at a pivotal juncture where technology and humanity converge. From productivity tools to fully autonomous AI agents, we are witnessing a fundamental shift in how content is created, distributed, and consumed. This evolution presents dual futures: one in which AI influencers and ... more

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AI in Africa: A Landscape Study

Rachel Adams, Fola Adeleke, Leah Junck, Samule Segun, Ayantola Alayande, Selamawit Abdella, Mark Gaffley, Fabio Andres Diaz Pabon, Funbi Salami

Global Center on AI Governance; African Observatory on Responsible AI (2025), 44 pp.

"Though comprehensive AI regulation is still nascent in Africa, there is an increased focus on national AI strategies, ethical guidelines and international collaborations. Over 40 countries have already established data protection and privacy laws, creating opportunities for harmonised regulations a ... nd a supportive environment for AI innovation. Key continental governance instruments and initiatives also include the African Union’s AI Strategy, the African Continental Free Trade Area and the African Commission on Human and Peoples’ Rights. This report found that the increasing application of AI in key sectors across Africa, such as health, education, finance, agriculture, public services and the environment, necessitates a collaborative approach to ethical AI development and use. This requires addressing persistent infrastructural gaps, developing regional regulatory frameworks, investments in AI research and capacity building efforts as well as promoting multi-stakeholder AI governance initiatives. Key strategies identified include joint investment and funding, pooling resources and supporting sustainable and fair open-source projects, which will help direct efforts toward innovation and regional independence. Open Source AI models are particularly important in Africa where local tech startups can leverage global open-source initiatives to build context-specific solutions. However, concerns regarding data ownership, privacy and ethical AI deployment call for more robust policies for open source AI on the continent. To foster responsible AI innovation, African countries should establish comprehensive AI governance frameworks while adhering to existing laws as well as strengthen regulatory institutions to provide oversight over AI technologies. Regulatory sandboxing also offers a viable approach to enable sage experimentation with appropriate oversight. Regional and international cooperation as well as leveraging public-private partnerships can promote funding for expanding AI research and development initiatives, resolve talent shortages and promote infrastructure development. Africa has a unique opportunity to leverage AI, along with its resources and local young talent, for socioeconomic development. However, to ensure inclusivity and sustainable innovation, it is essential to address infrastructure challenges and establish regulatory frameworks that protect societal wellbeing. Embracing collaborative efforts, including open source initiatives, regional and international partnerships are critical for achieving the continent’s ambitious goals without leaving anyone behind." (Executive Summaty, page 3) more

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Investigating AI datasets: A journalist's guide

Kathleen Siminyu, Christo Buschek

Bonn: Deutsche Welle DW Akademie (2025)

"Algorithms today are more complex than ever. With the rise of large language models (LLMs), they have become increasingly unexplainable and non-deterministic. Even experts often fail to understand why an algorithm yields a particular outcome. It is through the datasets used to train those algorithm ... more

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AI Tools Radar
Key Guides

UNESCO; International Research Centre on Artificial Intelligence (IRCAI) (2025)

"AI tools Radar is designed to map and showcase innovative and impactful AI tools from around the world, with a particular focus on applications in the public sector, media, and judiciary. This platform is a global initiative born out of a collaboration between UNESCO and the International Research ... more

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Artificial Humanities: A Fictional Perspective on Language in AI

Nina Beguš

Ann Arbor: University of Michigan Press (2025), 283 pp.

"Artificial Humanities explores how the humanities-literature, history, and art-can deepen our understanding of artificial intelligence and its development. By examining fictional representations of AI in parallel with actual technological developments, Nina Beguš presents a novel interdisciplinary ... more

Inclusive and Secure Artificial Intelligence: A Global Perspective on Policy and Technical Developments Deep Insights

Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs) Key Guides

AI Tools Radar Key Guides

Inclusive and Secure Artificial Intelligence: A Global Perspective on Policy and Technical Developments
Deep Insights

Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs)
Key Guides

AI Tools Radar
Key Guides