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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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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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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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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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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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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

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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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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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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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The Essential Convergence: Global Compact on Extreme AI Risks

Sundeep Waslekar, Ilmas Futehally, Jayantika Kutty

Mumbai: Strategic Foresight Group (2026), 90 pp.

"Supply-Side Governance: Progress and Limitations: Most existing AI governance frameworks focus on the supply side of the technology ecosystem. These measures regulate developers, model providers, and infrastructure operators responsible for building advanced systems. Supply-side mechanisms include: ... pre-deployment safety testing and red-teaming; model evaluation and capability assessments; transparency and reporting obligations; incident response mechanisms; restrictions on certain high-risk uses. Several jurisdictions are experimenting with these tools in different combinations. China has implemented regulatory standards for generative AI systems; the European Union has adopted a risk based regulatory framework; Brazil and South Korea are developing legislative approaches; and the United States has introduced a mixture of executive measures and sectoral rules. These frameworks represent important progress. However, they face two structural limitations. First, supply-side regulation depends heavily on the cooperation of a small number of developer states. Second, the growing distribution of AI models, through open-weight releases, cloud APIs, and downstream applications, means that many systems reach global markets beyond the jurisdiction where they were originally developed. This reality limits the effectiveness of purely supply-side approaches. Demand-Side Governance: A New Dimension of AI Regulation: The paper introduces a second dimension of governance that has received far less attention: demand-side oversight. Demand-side governance shifts the locus of control from the point of creation to the point of deployment. Instead of relying solely on developer-state regulations, importing countries can establish safety requirements for any AI systems operating within their markets. These requirements may include risk assessments, certification standards, procurement rules, insurance obligations, and infrastructure safeguards. The central insight is that states controlling large consumer markets, digital infrastructure, financial systems, or public procurement channels possess significant leverage over global AI deployment, even if they do not develop frontier models themselves. This demand-side leverage can reshape incentives across the global AI ecosystem. Developers seeking access to major markets must comply with the safety conditions imposed by importing states. This approach represents a strategic shift in global AI governance: from a developer-centric model to a market-driven model of safety enforcement. Countries across different regions possess different forms of demand-side power. Brazil and South Africa represent large emerging markets; the United Arab Emirates plays a major role in AI infrastructure investment; South Korea combines technological capability with advanced regulatory institutions. When coordinated, these forms of leverage could help establish global safety norms. The Case for a Global Compact: Given the limitations of purely national approaches, the paper proposes the development of a Global Compact on Extreme AI Risks. The Compact would not aim to harmonise all aspects of AI regulation. Instead, it would focus narrowly on the most severe risk categories and establish shared mechanisms for prevention, monitoring, and response. Five institutional pillars form the backbone of the proposed Compact. The five pillars in the Global Compact should not be treated as isolated measures but designed as an interoperable system in which each pillar reinforces and informs the others through shared definitions, compatible standards, and coordinated implementation mechanisms. To address extreme risks effectively, the Compact should rest on a small set of guiding principles: a human-centric principle to ensure protection of humanity and human dignity as the primary objective; technological neutrality so that safeguards apply across methods and architectures rather than specific tools; interoperability to enable national and regional AI frameworks to exchange information, align risk classifications, and coordinate responses; and mutual cooperation to institutionalize cross-border collaboration in prevention, incident reporting, and crisis management. These can be complemented by principles of proportional risk governance, scientific integrity, and shared responsibility, creating a coherent normative base that allows diverse governance models to function together as a connected global safety architecture." (Executive summary, pages 5-6) 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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Principled caution: How AI is used in public-interest media in Asia

James Gomez

Bonn: Deutsche Welle DW Akademie (2026), 52 pp.

"In conclusion, this research has provided a systematic understanding of AI adoption within public-interest media across Afghanistan, Bangladesh, Bhutan, Cambodia, Indonesia, Myanmar, Pakistan and Uzbekistan. By identifying concrete areas for strategic intervention, this research seeks to strengthen ... journalistic quality and prepare the sector for an AI-integrated future. The findings reveal that the AI adoption is currently taking place within public-interest media, but it is one of “principled caution” where adoption is careful, selective and highly varied. This evolution unfolds within a structurally precarious media environment where AI regulation is often absent or actively restrictive. While adoption remains cautious to protect journalistic credibility from risks such as hallucinations and biases, newsrooms are increasingly embracing AI as a powerful toolset to alleviate severe capacity and resource constraints. Currently, organizations primarily utilize AI for assistive, routine tasks such as translation, transcription, summarization, and early-stage content ideation and the final language editing stage rather than for broader organizational transformation. The research highlights deep capacity deficits in the governance framework, institutional training, and leadership. These gaps often prevent individual AI literacy from translating into consistent, organization-wide policy formulation and enforcement. This challenge is further exacerbated by the funding instability and resource constraints that characterize the region’s independent media, restricting the long-term investment necessary for ethical and responsible AI adoption. Despite these legal, political, technical, capacity, and operational constraints, localized and innovative AI workflows are emerging. While AI has not yet generated entirely new, revenue-generating business models, strategic investments in customized AI infrastructures, such as in-house dashboards and media monitoring systems, present a critical pathway toward long-term operational resilience. To support this trajectory, the report recommends coordinated action among media organizations, governments, technology companies, donors and media development funders to invest in long-term AI capacity, governance frameworks, and secure technological infrastructure." (Conclusion, page 39) more

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Societies at an AI Crossroads: Choices and Value Conflicts

Ignas Kalpokas, Julija Kalpokienė

London; New York: Routledge (2026), 116 pp.

"As contemporary societies undergo profound transformations driven by artificial intelligence and related technologies, a unilinear vision of inevitable ‘progress’ and development increasingly dominates public discourse. This book offers a counterpoint, challenging such deterministic narratives ... more

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Standardization of AI Ethics: Stakeholders, Values and Profit

Nicholas Kluge Corrêa, Julia Maria Mönig (eds.)

Bielefeld: transcript Verlag (2026), 161 pp.

"[...] what a certification could look like is only one of the questions that should be asked when discussing ethical certification of AI. Furthermore, how all potentially concerned parties (stakeholders) can be included, which values might be affected, and what this means for those actors who (righ ... tfully) need and want to profit from AI applications were central questions that the philosophy team of the KI. NRW-flagship project „Zertifizierte KI“ (Certified AI) investigated. Further key questions raised in the contributions and throughout the project period include: Can ethics be standardized? Who audits the auditors? How can auditing institutions be aligned with actual societal concerns? What can an assessment look like for a specific area (e.g., human resources)? How are law and ethics intertwined? Which contribution can philosophy provide, now that there is a European regulation on Artificial Intelligence (e.g., in the discussion whether robots in elderly care should be considered as deceptive technology under the AI Act)? Finally, what role do standardization bodies play in ensuring trustworthy AI? Answers to these questions are presented in this book, as well as in the project’s central outcomes: the 'Catalogue of General Ethical Requirements for AI Certification' and the 'Catalogue of Field-Specific Requirements for AI Certification'. The 'Catalogue of General Ethical Requirements for AI Certification' provides a structured framework for trustworthy AI development, identifying overarching ethical requirements for AI certification and outlining six ethical values: fairness, privacy, robustness, sustainability, transparency, and truthfulness. For each value, the project team researched existing tools, metrics, and approaches to help developers, programmers, and other practitioners build trustworthy AI systems. The 'Catalogue of Field-Specific Requirements for AI Certification' offers a list of requirements, an ethical stakeholder analysis, and a discussion of potential value tensions for six exemplary fields: arts, biometric profiling, industry and critical infrastructure, law enforcement, medicine and care and social media, a list of requirements, an ethical stakeholder analyses and a discussion of potential value tensions. The volume at hand collects the contributions to the final conference of the sub-project philosophy of the KI.NRW-Flagship-Projekt “Zertifizierte KI”. (Introduction, pages 11-12) more

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AI Companions Reduce Loneliness

Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp, Stefano Puntoni

Journal of Consumer Research, volume 52, issue 6 (2026), pp. 1126–1148

"Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications (apps) are effective at alleviating lonel ... more

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Indic Voice Technologies for an Inclusive Digital India: Toolkit for Developers

Nihar Desai, Sujith P., Harleen Kaur, Dona Mathew, Jyotsna Jayaram, Padmavathi Prasad, Thomas Vallianeth

Bhashini; Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All (2026), 70 pp.

"This toolkit sets out a layered, lifecycle-oriented approach to building inclusive and robust speech artificial intelligence (AI) systems. It brings together strategies for diverse and representative data collection, linguistically informed model training, rigorous quality control, and deployment o ... more

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Step by Step: How SAFE AI contributes to trustworthy AI

CDAC Network; Alan Turing Institute; Humanitarian AI Advisory (2026), 8 pp.

"Based on the National Institute of Standards and Technology (NIST) AI Risk Management Framework, the seven characteristics of trustworthy AI are: 1. Valid and Reliable: The AI system should perform as intended, delivering accurate results consistently across different situations. 2. Safe: The sy ... more