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Justicia algorítmica en América Latina y el Caribe: Investigación, políticas públicas y ética de la inteligencia artificial

Consejo Latinoamericano de Ciencias Sociales (CLACSO); CIESPAL; UNESCO (2026), 105 pp.

"El volumen reúne los policy briefs elaborados en el marco de la convocatoria Justicia Algorítmica. Una inteligencia artificial ética para América Latina y el Caribe, lanzada conjuntamente por UNESCO Ecuador y el Consejo Latinoamericano de Ciencias Sociales (CLACSO), en el marco de una colaborac ... ión intensa, sostenida y productiva que ambas instituciones han consolidado en los últimos años. A ella se sumó El Centro Internacional de Estudios Superiores de Comunicación para América Latina, CIESPAL, responsable de la edición del libro en alianza con CLACSO y UNESCO, reafirmando la convicción de que la cooperación interinstitucional regional constituye un instrumento fundamental para pensar críticamente la tecnología, fortalecer la cultura democrática y promover políticas públicas capaces de atender a los grupos más vulnerables. Los trabajos seleccionados y aquí publicados son el resultado de un proceso riguroso, sistemático y situado: se recibieron 35 postulaciones, evaluadas en primera instancia por un Comité Internacional integrado por nueve especialistas provenientes de Ecuador, Argentina, Brasil y Francia. Posteriormente, UNESCO y CLACSO realizaron la revisión final atendiendo a la calidad técnica y científica, la coherencia metodológica, la consistencia del plan de trabajo y la pertinencia de los temas en relación con la Recomendación sobre la Ética de la IA y el equilibrio regional. El proceso concluyó con la selección de cinco propuestas, varias de ellas con participación de investigadoras e investigadores con trabajo en y sobre Ecuador. Los policy briefs que conforman este libro abordan problemas urgentes de la agenda regional sobre IA. Uno de los núcleos críticos es la transformación del trabajo y la desigualdad digital, un fenómeno particularmente agudo en América Latina y el Caribe, donde históricas brechas educativas, económicas y territoriales se ven amplificadas por una automatización que concentra oportunidades en sectores altamente especializados y desplaza tareas tradicionalmente realizadas por trabajadores menos calificados. La región enfrenta una doble asimetría: la del acceso desigual a tecnologías avanzadas y la de las capacidades necesarias para utilizarlas de modo significativo, reproduciendo patrones de exclusión que atraviesan género, etnia y condición socioeconómica. Otro foco central es la privacidad y la vigilancia algorítmica, ámbitos donde los riesgos son crecientes. La implementación de sistemas opacos —las conocidas “cajas negras” algorítmicas— que procesan datos personales a gran escala ha generado nuevas formas de discriminación, como el racismo algorítmico, sesgos de género, o modelos predictivos que penalizan a grupos históricamente vulnerados. Los casos de identificación errónea en sistemas de reconocimiento facial o la clasificación automatizada de supuestos “riesgos sociales” muestran que, sin marcos éticos y normativos sólidos, la IA puede reforzar desigualdades en vez de corregirlas." (Introducción, páginas 8-9) more

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The People-Centered AI Playbook. Playbook Capsule

Dalberg Data Insights (2026), 44 pp.

"This people-centered playbook [...] is designed to give you the essentials of AI adoption in a quick, accessible format, with core concepts, foundational steps, and key frameworks without overwhelming detail. Built for impact-driven teams in low-resource or non-tech-first contexts, it answers the m ... more

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Toward AI Governance Alignment in Africa, Middle East, and Türkiye (AMET) Region

Emma Ruttkamp-Bloem, Fola Adeleke, Jake Effoduh, Kebene Wodajo, Nagla Rizk, Olubayo Adekanmbi, Rachel Adams, Rami Alkarmi, Seani Rananga, Seydina Ndiaye, Shikoh Gitau, Tami Koroye

Global Center on AI Governance (GCG) (2026), 54 pp.

"The analysis begins by identifying the core “centric approaches” that guide Artificial Intelligence (AI) national strategies. These include security-anchored models driven by state control, innovation-led frameworks that prioritise competitiveness, rights-based regimes centred on fundamental pr ... otections, and developmental approaches focused on public service delivery and technological catch-up. Each approach expresses incentives, risk perceptions and administrative capacities. Out of these foundational choices, there are different groupings. Various regions within AMET are adopting recognisable patterns of regulation that reflect their political economies, institutional structures and geopolitical positions. These groupings are not static categories, but evolving alignments shaped by domestic pressures, supply-chain dependencies and shifting global power dynamics. Across all regions, a set of cross-cutting issues consistently shapes the regulatory landscape. Data protection and interoperability remain central, alongside growing demands for accountability, explainability and robust auditing. Standards and certification are emerging as tools for both trustbuilding and geopolitical influence. Sector-specific rules in finance, health, education and public administration are increasingly decisive. Capacity constraints, fiscal limits and uneven institutional strength continue to define what is realistically possible for many governments. Geopolitical tensions and cloud concentration reinforce questions around sovereignty, infrastructure control and long-term strategic autonomy. This report translates these insights into practical implications for states, regional bodies and technology firms. It highlights workable pathways for reconciling innovation with safety, managing cross-border data flows, and building resilient digital infrastructure. It also identifies areas where architecture choices such as regional cloud centres, culturally calibrated testing layers and tiered sovereignty models can support both regulatory goals and developmental priorities. The recommendations emphasise flexible alignment, cooperation through standards, and the need for shared mechanisms that accommodate political diversity while reducing fragmentation. Taken together, the framework provides a stable and operational way of understanding global AI regulation. It clarifies the interests driving different jurisdictions, the pressures that shape convergence or divergence, and the strategic considerations that technology firms and policymakers must navigate as the regulatory environment continues to evolve." (Executive summary) more

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Promoting and advancing human rights in global AI ecosystems: The need for a comprehensive framework under international law

Alexander Kriebitz, Caitlin C. Corrigan (eds.)

Globethics Foundation; Responsible AI Network – Africa (RAIN-Africa) (2026), 33 pp.

"In response to far-reaching societal impacts of AI, policymakers are increasingly adopting a human rights lens for AI governance. However, the regulatory landscape remains fragmented and characterized by Western led initiatives as well as inconsistent enforcement. To address these limitations, a un ... ified and binding international framework is urgently needed. The proposed Convention on AI, Data, and Human Rights (drafted as the “Munich Convention on AI, Data, and Human Rights”) is an initiative toward such a framework. Developed with contributions from over 50 global experts, it proposes an international convention to align AI governance with human rights principles. This whitepaper explores the underlying rationale behind the convention, emphasizing its alignment with the norms and principles articulated in the Universal Declaration of Human Rights and the UN Charter. It examines the relevance of safeguards against AI’s misuse in facilitating human rights violations, with particular focus on protecting underrepresented or marginalized groups, including indigenous peoples, and addressing collective rights. It furthermore points to the necessity to codify rights that empower individuals to opt out, be forgotten, seek explanations, and access remedies to maintain adequate human rights standards in the context of AI. The urgency to act arises from the escalating impact of AI and the rapid pace of political and technological advancements. The UN Human Rights Council (UNHRC) is particularly well poised to play a leading role in initiating global discussions on a binding convention for AI governance, grounded in human rights principles. Drawing on its established mandate to uphold human rights globally, the UNHRC has a record of successfully embedding human rights principles into international frameworks, as demonstrated by its endorsement of the UN Guiding Principles on Business and Human Rights and the recognition of the right to a clean, healthy and sustainable environment. Through dedicated action around promoting a convention on AI and human rights, the UNHRC can foster international consensus and proactively shape the future of AI in a manner that prioritizes the values and principles enshrined in the key documents of international human rights law." (Executive summary) more

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European AI Competitiveness Beyond Frontier Models: Insights From AI Startups in Five Strategic Markets

Nicole Lemke

Berlin: Interface – Tech Analysis and Policy Ideas for Europe (2026), 37 pp.

"AI development is frequently described as a race for frontier models. But considerable economic value will also be generated by AI development and adoption in existing markets. This data brief examines where EU competitiveness stands in the five applied markets where most of the EU’s AI startup a ... ctivity in our dataset takes place – horizontal enterprise software, healthcare and life sciences, manufacturing and supply chain, finance and insurance, and research and development tools. Drawing on data from Dealroom.co covering 24,468 active AI startups launched between 2012 and 2025 across the EU, Switzerland, the UK, and the U.S., we compare geographic patterns at the level of regions, countries, and cities through original analysis [...] Manufacturing and supply chain is the only market where the EU accounts for a larger share of AI startups than the U.S., though our data likely underestimates the number of U.S. startups in general. This suggests the competitiveness gap across applied AI markets may be even larger than our data indicates [...] AI startup activity in the EU is geographically dispersed: 75 percent of analysed EU AI startups are spread across 95 cities, with no single hub dominating any market. Paris, Berlin, Amsterdam, Munich, and Stockholm are the largest hubs but together account for only a quarter of EU AI startups. EU city rankings across markets largely reflect general AI startup hub sizes rather than genuine market specialisation – but specialised niches do begin to emerge at the local level, e.g. Munich in manufacturing and supply chain and Barcelona in healthcare and life sciences. As our data skews towards larger startup hubs, specialisation patterns in smaller cities and regions may not be fully captured. Our findings have important implications for policymakers. Europe's challenges in AI competitiveness extend well beyond frontier models. The manufacturing and supply chain market, a strategic priority for the European Commission, presents grounds for cautious optimism, where existing industrial strengths align with national and regional specialisation signals based on AI startup activity, especially in Germany and Munich. The geographically distributed startup activity in the EU can support AI adoption across diverse regional economies and existing industrial strengths. At the same time, it raises questions about whether European hubs can achieve the scale and specialisation needed to compete globally. The technological diversity of AI also presents competitive opportunities that go beyond market specialisation alone. Whether the emerging specialisation patterns identified in this analysis develop into globally competitive positions will depend on continued access to growth capital, compute resources, and cross-border market integration." (Executive summary, pages 3-4) more

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How Russia Is Reshaping Command and Control for AI-Enabled Warfare

Kateryna Bondar

Washington, DC: Center for Strategic and International Studies (CSIS) (2026), 20 pp.

"This paper examines how Russia is transforming its command and control (C2) architecture under wartime pressure, how these changes shape the country’s incremental move toward battlefield-required software solutions, and what lessons U.S. policymakers can learn from Russia’s experiences. Focusin ... g on both strategic ambitions and battlefield practice, the takeaways below summarize how automated C2 systems, unmanned platform management software, and emerging AI applications are being developed, adapted, and scaled within Russia’s military ecosystem. 1. Russia is no longer prioritizing the construction of a single, comprehensive automated C2 architecture comparable to Western joint concepts; instead, it is reallocating effort toward tactical, task-specific software, driven by battlefield necessity. Prolonged, high-intensity combat in Ukraine exposed the limits of centralized, system-wide C2 modernization and elevated the importance of accelerating the tactical kill chain. The emergence of systems such as the “Svod” Tactical Situational Awareness Complex and other integrated reconnaissance-strike tools reflects a pragmatic shift in which operational control of unmanned systems and real-time battlefield management now deliver greater military value than achieving end-to-end C2 integration. 2. Because unmanned systems now conduct up to 80 percent of Russian fire missions, the center of gravity in C2 innovation has shifted toward software that manages drones and integrates them with artillery and other fire units. Civilian engineers and volunteer developers have focused on closing this gap by building tools that provide situational awareness, automate fire correction, and link unmanned aircraft systems (UAS) operators directly to firing units. Russia’s “Glaz/Groza” software complex demonstrates this trend, functioning as a unified reconnaissance-strike workflow that converts drone footage into targeting data and compresses the time from detection to impact from hours to minutes. 3. The Russian military assesses its AI capabilities for visual and audio data processing as relatively mature, placing computer vision, sensor fusion, and signal analysis at technology readiness level (TRL) 6–9, while natural-language processing remains at an early, experimental stage, TRL 1–3. This disparity reflects a deliberate prioritization of AI applications that deliver immediate battlefield utility—such as target recognition, guidance, and autonomous terminal functions for unmanned systems—and where abundant data and combat validation are available. By contrast, text analysis AI, which underpins document processing and higher-level C2 decision support, remains constrained by immature architectures, limited certified software, and organizational barriers, slowing progress toward fully AI-enabled command workflows. 4. Within Russian C2 systems, AI is primarily envisioned as a support function rather than a replacement for human decisionmaking. Russian military doctrine assigns AI two core roles: enhancing the processing and interpretation of sensor data and providing predictive decision support through forecasting, scenario generation, and recommendations for commanders. Across strategic and tactical levels, AI is intended to augment situational awareness and analytical capacity, while formal authority and responsibility for decisions remain firmly with human commanders. 5. Russia began its C2 digitalization effort by building a dense layer of standards governing terminology, system architecture, hardware-software integration, and information management. This standardization drive, coupled with the transition to the domestically controlled Astra Linux operating system, reflects an attempt to create a unified technical foundation capable of supporting data integration, interoperability, and future AI insertion across the command hierarchy. While this framework provides structural coherence, it has not, on its own, resolved deeper institutional and methodological constraints that continue to limit system-wide C2 integration. 6. To enable AI-driven tactical software, the Russian military launched a systematic data collection effort in 2025 focused on unmanned operations and strike outcomes. The emerging data infrastructure aggregates UAS video feeds, operator telemetry, strike effects, and individual pilot performance metrics, each linked to unique personal identifiers. These datasets serve multiple functions simultaneously: operational analysis, training evaluation, and the creation of labeled data for AI model development, establishing a feedback loop that ties battlefield performance directly to software refinement. 7. Despite efforts to reduce dependence on foreign commercial technologies, Russia’s military AI development remains heavily reliant on open-weight models and civilian software ecosystems. The transition from tools such as AlpineQuest and Discord toward domestic alternatives like ZOV Maps and Astra-based platforms reflects a push for security and sovereignty at the application layer. At the same time, Russian developers actively adapt open-weight and commercially available AI models, including Mistral, Qwen, LLaMA, YOLO, and related architectures, for military use, embedding them into on-premise, tightly controlled environments. This hybrid approach allows Russia to mitigate sanctions and accelerate AI adoption without building foundational models from scratch." (Executive summary) more

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Navigating risks and rewards: How South African journalists use AI in the newsroom

Karen Allen, Herman Wasserman, Nande Mbekela

Johannesburg; Stellenbosch: Konrad-Adenauer-Stiftung (KAS), Media Programme Sub-Saharan Africa; Centre for Information Integrity in Africa (CINIA) (2026), 33 pp.

"This study demonstrates impressively how widely AI is already used in South African newsrooms – often, however, without systematic training, without editorial guidelines, and without tools adapted to African languages and contexts. The interviews make it clear that journalists stand between curio ... more

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Preserving Human Voices and Faces. Message of his Holiness Pope Leo XIV for the 60th World Day of Social Communication

Leo XIV (Pope)

Vatican City: Holy See, January 24 (2026)

"The task laid before us is not to stop digital innovation, but rather to guide it and to be aware of its ambivalent nature. It is up to each of us to raise our voice in defense of human persons, so that we can truly assimilate these tools as allies. This alliance is possible, but needs to be based ... on three pillars: responsibility, cooperation and education. First of all, responsibility. Depending on the role we play, responsibility can be understood as honesty, transparency, courage, farsightedness, the duty of sharing knowledge or the right to be informed. As a general principle, however, no one can elude personal responsibility for the future we are building. For those at the helm of online platforms, this means ensuring that their business strategies are not guided solely by the criterion of profit maximization, but also by a forward-looking vision that considers the common good, just as each of them cares for the well-being of their own children. The creators and developers of AI models are invited to practice transparency and socially responsibility in regard to the design principles and moderation systems underlying their algorithms and the models they develop, in order to promote informed consent on the part of users. The same responsibility is also required of national legislators and supranational regulators, whose task it is to ensure respect for human dignity. Appropriate regulation can protect individuals from forming emotional attachments to chatbots and curb the spread of false, manipulative or misleading content, safeguarding the integrity of information as opposed to its deceptive simulation. [...] We are all called upon to cooperate. No sector can tackle the challenge of steering digital innovation and AI governance alone. Safeguards must therefore be put in place. All stakeholders — from the tech industry to legislators, from creative companies to academia, from artists to journalists and educators — must be involved in building and implementing informed and responsible digital citizenship. Education aims to do precisely this: To increase our personal ability to think critically; evaluate whether our sources are trustworthy and the possible interests behind selecting the information we have access to; to understand the psychological mechanisms involved; and to enable our families, communities and associations to develop practical criteria for a healthier and more responsible culture of communication. For this reason, it is increasingly urgent to introduce media, information and AI literacy into education systems at all levels, as already promoted by some civil institutions. As Catholics, we can and must contribute to this effort, so that individuals — especially young people — can acquire critical thinking skills and grow in freedom of spirit. This literacy should also be integrated into broader lifelong learning initiatives, reaching out to older adults and marginalized members of society, who often feel excluded and powerless in the face of rapid technological change. Media, information and AI literacy will help individuals avoid conforming to the anthropomorphizing tendencies of AI systems, and enable them to treat these systems as tools and always employ external validation of the sources provided by AI systems — which could be inaccurate or incorrect. Literacy will also allow for better privacy and data protection through increased awareness of security parameters and complaint options." (https://www.comunicazione.va/en/giornata-mondiale-comunicazioni-sociali/gmcs-2026/gmcs-2026-messaggio.html) more

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AI is here. Are we ready?

Eva-Maria Verfürth et al.

D+C: Development and Cooperation, issue 4 (2026), pp. 31-58

"AI is already having a profound impact on our daily lives. The key question is who controls the technology. It is not only in conflicts that AI accelerates the spread of deceptively realistic fakes and makes it harder to distinguish reliable information from manipulation. At the same time, it opens ... more

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Digital Media Shadowing Democracy: Technology, Communication, and Power

Auksė Balčytienė, Péter Bajomi-Lázár, Helena Sousa (eds.)

Gothenburg: Nordicom, University of Gothenburg (2026), 282 pp.

"The book’s message is brief: Liberal democracies are at risk. Democratic decay has numerous causes, but technological innovations and profit-driven dynamics are shaping societal relations in ways that intensify disagreements and polarisation, undermining informed citizenship. The growing number o ... more

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Handbook on Data Protection and Privacy for Developers of Artificial Intelligence (AI) in India

Ajey Karthik, Aman Taneja, Sreenidhi Srinivasan, Vidushi Sinha

New Delhi: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All (2026), 117 pp.

"This Handbook is designed as a practical guide for developers of AI systems, especially from early-stage startups, to navigate data protection obligations and ethical considerations, in a clear and actionable manner. Rather than serving as a comprehensive legal or technical manual, the Handbook co ... more

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Reinventing Humanitarian Aid Procurement for the Age of AI

Giulio Coppi

Access Now (2026), 59 pp.

"Our research reveals that the organisational use of AI and algorithmic systems often happens through a process of unstructured integration rather than formal adoption. More precisely, cloud-based, algorithmic-enhanced functionalities and processes are making their way into humanitarian entitiesʼ t ... ech stack through updates and add-ons to preexisting products, slowly but inexorably seeping into most internal systems. A price-based procurement process designed around the static idea of digital asset purchase is inadequate to ensure adequate protection from hyperdynamic tech product development. This is especially evident looking at the growing power imbalances between private actors and nonprofits, and among nonprofits themselves. Digital technology is often heralded as key to democratise and equalise the playing field between humanitarian actors, by finally unlocking local actorsʼ access to resources traditionally reserved for international entities. But emerging trends seem to disprove such claims. The lack of adequate legal frameworks and safeguards, lagging investments in humanitarian funding for information and communication technology (ICT) resources and connectivity, and inadequate dedicated funding for digital programmes are thwarting these opportunities. More broadly, virtuous and responsible procurement practices are proving inadequate for protecting human rights alone, as tech companiesʼ commitments to human rights are replaced by defence-oriented pitches and the size of their human rights teams keeps shrinking. Preexisting digital divides are enhanced by several deep and subtle changes in traditional tech business models, resulting from the gradual cloudification of most common digital systems and the fast-paced, distributed nature of modern digital development. Even more worryingly, we are seeing new forms of digital divide well beyond the traditional gaps in digital capacity between local and small non-governmental organisations (NGOs) and international non-governmental organisations (INGOs) or UN entities. Cloud-based companiesʼ takeover of generic coordination platforms creates a constantly broadening chasm between the few organisations that are digitally mature, those who are barely retrofitting their processes to fit the new reality, and the broad majority forced to access the promised land of digital humanitarianism through the predatory gates of algorithmic and cloud servicesʼ free tech licensing. Our findings highlight how organisation-led digital development, building on open-source systems (despite some “openwashing” practices) and trusted external providers, remains the best option for risk reduction when it comes to algorithmic systems. However, in the short to medium term, this might not be financially and technically feasible for the majority of humanitarian actors, especially considering the catastrophic funding environment. To fill this gap, we propose a toolkit in an appendix to this report. This is a foundational governance model for transforming digital procurement from a transactional into a strategic business function, integrated across key organisational departments. By doing so, protection-mandated aid groups could move from running purchase-centred processes, to adopting a dynamic, proactive, and rights-based approach to tech management. This report also contains a set of recommendations for states and donors, the humanitarian community, tech companies, local aid actors and communities, research centres, and cyber experts." (Executive summary, pages 2-3) more

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AI in the media: Kenya and South Africa

Karen Allen, Herman Wasserman, Nande Mbekela

Bonn; Stellenbosch (ZA): Deutsche Welle DW Akademie; Centre for Information Integrity in Africa (CINIA) (2026), 27 pp.

"This study shows that AI remains largely an underexplored, and often misunderstood, topic for journalism in South Africa and Kenya. Stories can be framed in overly positive terms, such as the potential AI holds for development and social change, or negative terms, by highlighting the extractive nat ... ure of big tech firms or the potential of AI to foster disinformation. Either way, these reports frequently lack a more nuanced understanding of the impacts of AI in African contexts. Fear of the impact of AI on the media workforce may also explain why reporters say they often face resistance by editors when seeking to get AI and tech stories commissioned. AI articles tend to be siloed and reactive, framed as business, security or technology stories. Seldom is AI presented in terms of its multidimensional, layered impact on society. Furthermore, the geopolitical aspect of AI rarely gets interrogated in mainstream media. Journalists interviewed for the study admitted that many of their stories were reactive, and identified areas where synergies could be harnessed from other parts of the world. On issues of AI and social media regulation, for example, where precedents have been set by countries such as Australia, South African and Kenyan media could use such precedents to develop locally focused stories. AI reporting often adopts a framing promoted by technology vendors who derive interest from presenting a one-dimensional, optimistic view of AI. The unintended consequences often go unreported unless supported by an investigation, such as the CCTV camera surveillance reportage by Swart referenced above. Furthermore, the topic is often presented through a Global North lens, with little contextualisation or interrogation of these issues from an African point of view amid resource and access constraints. This occurs against a background of under-developed policy frameworks for AI on the continent generally, and in newsrooms in particular. Consequently the playing field can be tilted in favour of AI and tech vendors who fill the vacuum with hyperbole and hype about what the technology is capable of delivering. At the same time, more nuanced and specialised reporting on AI is constrained by the familiar obstacles of journalism, such as lack of resources, over-stretched newsrooms and story competition. To enhance coverage of AI in Africa, a multifaceted strategy is needed. While training and AI literacy programmes can deepen the knowledge needed by African journalists to investigate the topic more comprehensively, increased investment in newsrooms can provide the structural support to provide more context-specific coverage of AI on the continent. Crucially, training and education of African journalists should be done from within the African context, as solutions cannot be imposed from newsroom contexts in the Global North." (Conclusions, page 21) more

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We Have an Artificial Intelligence Definition Problem in ICT4D

Wayan Vota

ICTworks (2026)

"A new study in the International Journal of Research and Innovation in Social Science surveyed 200 women micro-entrepreneurs in Bengaluru and reported that 32.5% of them are “actively using at least one AI-enabled tool” in their businesses. The tools, according to the paper, include KhataBook ( ... more

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Taking a Look at the most common AI myths & debunking them the Superrr way!

Berlin: SUPERRR (2026), 22 pp.

"How do we want to use technology, and when do we hit the brakes? As part of our work in 2026, we held 14 public-facing “AI mythbusting” sessions at libraries across Berlin, Germany. We were astonished by the strong public response and clear need for judgement-free spaces to talk about AI. Colle ... more

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Communicating Sustainable Development Goals in the Age of Artificial Intelligence

Muhammad Jameel Yusha'u

Palgrave Macmillan (2026), xlvii, 523 pp.

"This book is the first scholarly work dedicated to examining the complex relationship between artificial intelligence and communicating the UN Sustainable Development Goals. Moving beyond techno-optimist narratives, the book advances a critical theoretical intervention: the AI Sustainability Exclus ... more

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Relational Futures: Indigenous Sovereignty and the Governance of Artificial Intelligence (AI)

Bronwyn Carlson, Tamika Worrell

Macquarie University (2026), 30 pp.

"Artificial intelligence must be governed as a relational and institutional force, not simply a technical system. Effective policy requires Indigenous leadership, enforceable standards, and a commitment to sovereignty, accountability, and community wellbeing. Failure to act risks embedding inequalit ... more

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How to Talk to AI (And How Not To)

Jamie Bartlett

London: Ebury Publishing (2026), 272 pp.

"[...] Most people still don't really understand how AI works, how to make the most of it – or what the dangers are. As some people use it to turbo-charge their productivity at work, others are falling into dangerous conspiracies, delusions and psychosis. In How to Talk to AI, award-winning techno ... more

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The Protocol Gap: Brazil

Sérgio Spagnuolo, Ester Borges, Bruno Fiaschetti, Paula Miraglia

Journalism Relay Project; Momentum; International Fund for Public Interest Media (IFPIM) (2026), 12 pp.

"An overwhelming majority of news websites in Brazil have either no AI-scraping policy at all or a very permissive approach. As of November 2025, only 7.2% of Brazilian news websites disallow at least one AI crawler through the use of a robots.txt file, even though most news sites (75%) have a robot ... more

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Invisible Workers, Visible Harms: Perils and Precarities of AI Labour

Aapti Institute

Bonn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) (2026), 40 pp.

"Across South Asia, Southeast Asia, and Sub-Saharan Africa, data workers operate within fragmented and opaque supply chains characterised by informal employment arrangements, limited social protections, and a profound imbalance of power between workers, vendors, and the global technology firms that ... more