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Just Hiring! How to counter discrimination in AI-assisted recruiting at the governance level. A toolkit for policymakers

M. Daviet, A. Mueller, N. Baranowska, G. Meijers, C. Castillo, J. Saldivar, A. Gatzioura

FINDHR Fairness and Intersectional Non-Discrimination in Human Recommendation (2025), 67 pp.

"In this Toolkit, we offer introductory information and concrete recommendations on how to mitigate the risk of discrimination in algorithmic hiring systems on a governance level. This Toolkit addresses policymakers and people working in regulatory bodies, as well as civil society organisations inte ... more

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Just Hiring! How to counter discrimination in AI-assisted recruiting within your organisation. A toolkit for HR professionals

M. Daviet, A. Mueller, N. Baranowska, C. Castillo, J. Saldivar, A. Gatzioura

FINDHR Fairness and Intersectional Non-Discrimination in Human Recommendation (2025), 73 pp.

"In this Toolkit, we offer introductory information and concrete recommendations on how to mitigate the risk of discrimination in algorithmic hiring systems within organisations. This Toolkit addresses HR professionals and recruiting agencies and intends to help them gain a better understanding of w ... more

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The State of AI in Africa Report

Nairobi: Strathmore University, Centre for Intellectual Property and Information Technology Law (CIPIT) (2025), 67 pp.

"The State of AI in Africa Report 2025 offers a critical reflection on how AI ecosystems across the continent have evolved since 2023, highlighting advances in infrastructure, regulatory frameworks, capacity building, and sectoral innovation, while also surfacing enduring structural disparities. Thi ... s report reveals a continent that is no longer on the margins of AI development but actively reshaping how AI is conceived, deployed, and governed. Kenya, South Africa, Nigeria and Ghana have made notable strides in anchoring AI within national digital strategies, strengthening local innovation ecosystems, and investing in foundational infrastructure such as data centres and broadband connectivity. The growing presence of indigenous datasets, grassroots NLP initiatives, and AI models tailored to African realities reflects a broader shift from consumption to creation. Yet this progress remains uneven. While pockets of excellence are emerging, many regions continue to grapple with limited access to reliable electricity, fragmented regulation, data governance challenges, and critical skill shortages. Central Africa, in particular, still faces infrastructural and institutional constraints that hinder meaningful participation in the continental AI space. This report also documents how AI is being embedded in key sectors; agriculture, health, law, and the creative economy to address uniquely African challenges – from crop failure and disease surveillance to language preservation and cultural expression. These use cases affirm the value of locally informed, contextsensitive AI innovation. On the governance front, the adoption of the AU-AI Continental Strategy and the development of national AI policies signal a growing awareness of the need for harmonised, responsible and inclusive AI development. However, effective implementation remains a central concern, particularly around enforcement mechanisms, ethical guardrails, and regional coordination. This report presents a nuanced picture of AI in Africa: one of ambitious experimentation, uneven capacity, and deep potential. Africa’s future in AI depends not only on technological advancement but on the continent’s ability to embed equity, local relevance, and sustainability at the heart of its AI agenda." (Executive summary) more

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Die intelligente Täuschung: Über die Fähigkeiten Künstlicher Intelligenz

Frank Jäkel

Bielefeld: transcript Verlag (2025), 246 pp.

"Der Einzug von Künstlicher Intelligenz (KI) in unser Leben wird gleichermaßen von Heils- und Unheilserwartungen begleitet: Die einen erhoffen sich Produktivitätssteigerungen, die anderen befürchten, dass Europa den Wettlauf mit den USA und China längst verloren hat. Autohersteller setzen auf a ... more

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United Nations Activities on Artificial Intelligence (AI)

Geneva: ITU (2025), xvi, 500 pp.

"If 2023 was the year of generative artificial intelligence, 2024 was marked by the rapid expansion and adoption of AI, driving waves of innovation across nearly every conceivable domain. The United Nations system has kept an encouraging pace, redoubling efforts to harness the power and potential of ... 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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Intelligence artificielle et emploi en Afrique: Analyse des impacts de la digitalisation du travail

Ibrahim Kalil Konaté, Michel Boukar

Robert Beugré Mambé (preface)

Paris: L'Harmattan (2025), 267 pp.

"Ce livre étudie les effets de l’intelligence artificielle (IA) et de la digitalisation sur l’emploi en Afrique, en usant d’une méthodologie à deux articulations. D’une part, l’analyse des effets directs de l’IA : destruction d’emplois traditionnels dans des secteurs-clés (agricult ... more

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An Autonomy-Based Classification: AI Agents, Liability and Lessons from the Automated Vehicles Act

Lisa Soder, Julia Smakman, Connor Dunlop, Oliver Sussman

Berlin: Interface; Ada Lovelace Institute (2025), 28 pp.

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Measuring what matters: How to assess AI’s environmental impact

Geneva: ITU (2025), viii, 21 pp.

This report synthesizes key findings from a diverse range of sources, including academic literature, corporate sustainability initiatives, and emerging environmental tracking tools. Collectively, these documents provide a thorough overview of current methodologies for evaluating the environmental im ... more

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Índice Latinoamericano de Inteligencia Artificial (ILIA) 2025
Deep Insights

Álvaro Soto, Rodrigo Durán, Antonia Moreno, Sebastián Adasme, Sebastián Rovira, Valeria Jordán, Laura Poveda (coord.)

Santiago de Chile: Comisión Económica para América Latina y el Caribe (CEPAL); Centro Nacional de Inteligencia Artificial (2025), 195 pp.

"El Índice Latinoamericano de Inteligencia Artificial (ILIA) constituye un esfuerzo pionero para medir de manera sistemática el avance de la IA en 19 países de la región. El ILIA busca no solo monitorear el grado de preparación, adopción y gobernanza, sino también difundir buenas prácticas, ... además de ser un instrumento para orientar políticas públicas que incorporen la IA al modelo de desarrollo de los países de manera integral. El índice se organiza en tres dimensiones: Factores Habilitantes (infraestructura digital, talento humano y datos), Investigación, Desarrollo y Adopción, y Gobernanza. A partir de más de cien subindicadores, el ILIA 2025 ofrece un panorama detallado sobre avances, brechas y oportunidades estratégicas en el despliegue de la IA en América Latina y el Caribe. [...] Once hallazgos principales del ILIA 2025: i) El despertar de los adoptantes tardíos. Ecuador, Costa Rica, República Dominicana y Guatemala muestran mejoras aceleradas en conectividad, talento y estrategias de IA, reduciendo distancia con los países líderes, y abriendo oportunidades que parecían improbables para una cooperación regional. ii) Código abierto: la oportunidad para América Latina y el Caribe. El alto desempeño de Honduras, El Salvador y Cuba en producción de software abierto confirma que este modelo ofrece una vía estratégica para desarrollar soluciones locales, fomentar la colaboración regional y el aprendizaje colectivo, además de promover la transparencia algorítmica. iii) Muchos datos, pero poca disponibilidad. La región produce grandes volúmenes de información, pero su apertura y estandarización siguen siendo limitadas. Esto restringe la ciencia abierta, reduce la transparencia y frena el desarrollo de soluciones locales de IA. iv) Talento humano: alfabetización, poca especialización. La alfabetización en IA duplica a la formación profesional y cuadruplica al talento especializado. Aunque se amplían programas escolares y posgrados, persiste un embudo en la formación avanzada que limita el potencial de la región para producir soluciones propias. v) Talento e infraestructura para la soberanía digital. Brasil concentra más del 90% de la capacidad de cómputo de alto rendimiento de la región. Aunque Uruguay, Costa Rica y Colombia muestran mejores indicadores per cápita en Unidades de Procesamiento Gráfico (GPU por sus siglas en inglés), más de la mitad de los países carecen de infraestructura crítica, lo que refuerza asimetrías. Además, 13 de los 19 países no generan habilidades tempranas en IA en el currículo educativo y 11 no cuentan con programas de doctorado en IA en sus universidades. Sin fortalecer estas capacidades endógenas, la región corre el riesgo de generar soluciones de IA sesgadas y con baja pertinencia local. vi) IA Generativa: una oportunidad de democratización del acceso. La IA generativa ha democratizado el acceso y acelerado la adopción gracias a sus bajas barreras de entrada y a interfaces simples que permiten a no expertos usar modelos avanzados. Países como Chile, Costa Rica, Perú, Uruguay, Panamá y República Dominicana destacan en uso, y ALC es ya la tercera región del mundo en descargas de aplicaciones de IA Gen (15%–20%). Esta accesibilidad actúa como catalizador y, junto con el desarrollo de software y el código abierto, compensa déficits de cómputo, abriendo oportunidades para toda la región. vii) IA y participación ciudadana: un cambio de paradigma desaprovechado. Aunque la IA podría revolucionar la democracia digital, su uso se limita en la mayoría de los países a chatbots informativos y no en herramientas de consulta, de rendición de cuentas o de co-creación de políticas públicas. Colombia, México y Perú muestran algunos avances, pero ocho países no registran ningún caso de aplicación. viii) Investigación escasa y concentrada. Brasil y México reúnen el 68% de los investigadores activos en IA y, junto a Colombia, Chile y Argentina, concentran el 90% de las publicaciones. Solo siete países participan en conferencias internacionales de élite, con predominio de Chile y Brasil. La escasa presencia en foros académicos de alto impacto reduce la visibilidad y la transferencia de conocimiento de la IA de la región; la actividad académica sigue rezagada y requiere mayor atención en la mayoría de los países. ix) Gobernanza en IA: mucho plan y poca acción. Nueve países cuentan con estrategias nacionales de IA, pero solo unos pocos han asignado presupuesto, definido planes de implementación o establecidos indicadores de impacto. Sin mecanismos de ejecución, estas estrategias corren el riesgo de quedarse en meras declaraciones. Al mismo tiempo, mientras a nivel global avanza la apertura e interoperabilidad de datos, la región mantiene un ritmo lento, centrado en debates normativos y éticos. El verdadero desafío es equilibrar la regulación con políticas orientadas al desarrollo y a la implementación efectiva de la IA, de modo que esta tecnología genere valor sin frenar la innovación. x) Sustentabilidad: un llamado urgente. Solo cuatro países (Brasil, Chile, Colombia y México) muestran industrias de centros de datos robustas, y uno de cada cinco centros cumple con estándares internacionales de sustentabilidad. La mayoría de las políticas de IA y digitalización omite el impacto ambiental, lo que puede entrar en contradicción con los objetivos de sostenibilidad medioambiental de la región. xi) Emprendimiento en IA: una oportunidad para la región. Los 19 países ILIA concentran sólo el 1,12% de la inversión global en IA y cuenta con empresas unicornios en apenas seis países. No obstante, el ILIA muestra que no es necesaria una matriz productiva compleja para fomentar el desarrollo de empresas de IA locales y el uso de esta tecnología en el sector productivo. Entornos favorables de innovación y emprendimiento, inversión y políticas de desarrollo productivo pueden detonar dinámicas innovadoras." (Resumen ejecutivo, páginas 15-16) more

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Fundamentos en competencias digitales

Marianella Sánchez Sobrino, Amado Vásquez Sanez, Carlos Tanaka Palao

Lima: Universidad San Ignacio de Loyola, Fondo Editorial (2025), 169 pp.

"[... ] la presente guía se fundamenta en el marco [conceptual europeo] DigComp 2.2, que establece un estándar claro sobre las competencias digitales necesarias para interactuar en el mundo actual. A lo largo de este documento, abordamos cinco competencias clave: búsqueda y gestión de informaci� ... more

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Antiqua et Nova: Note on the Relationship Between Artificial Intelligence and Human Intelligence

Dicastery for the Doctrine of the Faith, Dicastery for Culture and Education

Vatican City: Dicastery for the Doctrine of the Faith; Dicastery for Culture and Education (2025)

"[...] it is crucial to know how to evaluate individual applications of AI in particular contexts to determine whether its use promotes human dignity, the vocation of the human person, and the common good. As with many technologies, the effects of the various uses of AI may not always be predictabl ... more

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Considerations and Practical Applications for Using Artificial Intelligence (AI) in Evaluations

D. Cekova, L. Corsetti, S Ferretti, S. Vaca

Rome: CGIAR Independent Advisory and Evaluation Service (IAES) (2025), 42 pp.

" Guided by the CGIAR-wide Evaluation Framework, integrating AI tools requires a governance approach to balance innovation with ethical responsibility, ensuring transparency, fairness, accountability, and inclusivity. This Technical Note encourages and guides CGIAR evaluators to ethically explore, n ... egotiate, and experiment with AI tools: Explore: Evaluators are invited to discover how AI, especially GenAI, can enhance evaluation efficiency, from scoping and data analysis to reporting. The Note provides practical guidance on AI applications and examples to support creative yet responsible exploration. Negotiate: Integrating AI should be openly discussed with commissioners, stakeholders, and teams. The Note prioritizes jointly defining boundaries, expectations, and ethical parameters (transparency, accountability, and data sensitivity) at each phase of evaluation. Use AI Responsibly: While AI tools are evolving, evaluators are encouraged to pilot and iterate their use. The document supports experimentation through practical tips, prompt examples, and tool selection criteria, all while emphasizing documentation and learning from each use case. Effective AI governance is grounded in core principles: Transparency requires clear documentation of AI tool usage, data sources, model limitations, and decision-making processes. Accountability involves assigning responsibility for AI decisions and outputs and establishing oversight and redress mechanisms. Fairness and inclusion must proactively mitigate bias and discrimination, with particular attention to underrepresented groups and data gaps. Data privacy and security must align with applicable data protection regulations and ensure secure handling practices. Human oversight ensures that evaluators retain control over processes and can intervene as needed. In operationalizing ethical AI governance in CGIAR evaluations, due diligence is required in assessing AI tools for ethical alignment before deployment: reviewing the transparency of vendors, the documentation of models, and their intended use cases. Where relevant, components involving AI—especially those engaging human subjects or sensitive data—should undergo ethics review. AI applications must be adapted to the local and cultural contexts in which evaluations are conducted, as what is suitable in one setting may be inappropriate in another. Additionally, participants should be informed about the use of AI systems and the implications of data collection or processing to ensure informed consent. Ethical AI governance should be embedded in the entire evaluation lifecycle. During the design phase, evaluators should define AI tools to use, why they are selected, and assess risks. In data collection, AI tools should be used in ways that uphold data privacy and protection standards and avoid reinforcing harmful stereotypes or excluding groups. During the analysis phase, the role of AI in supporting interpretation should be documented, with an acknowledgment of limitations or biases. In dissemination, documentation, and reporting, AI’s contribution, limitations, and human validation should be disclosed. By rapid adaptation of content across formats, languages, and complexity levels, AI opens possibilities for broader, more inclusive communication of findings. Finally, the follow-up phases should include a reflection on the ethical implications observed and how these lessons can improve future evaluations." (Executive summary) more

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Antiqua et nova: Note über das Verhältnis von künstlicher Intelligenz und menschlicher Intelligenz

Dikasterium für die Glaubenslehre, Dikasterium für die Kultur und die Bildung

Bonn: Sekretariat der Deutschen Bischofskonferenz (2025), 83 pp.

"Es ist daher von entscheidender Bedeutung, einzelne Anwendungen in bestimmten Kontexten kritisch zu bewerten, um festzustellen, ob sie die Würde und Berufung des Menschen und das Gemeinwohl fördern oder nicht. Wie bei vielen Technologien sind die Auswirkungen der verschiedenen KI-Anwendungen zu B ... 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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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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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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2025 Technology and Innovation Report: Inclusive Artificial Intelligence for Development

New York: United Nations Conference on Trade and Development (UNCTAD) (2025), xiii, 168 pp.

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Intelligence artificielle et robotique autonome: Enjeux et défis contemporains dans l’espace francophone

Etienne Damome, Moustapha Ben Ismïila Diaby (eds.)

Paris: L'Harmattan (2025), 358 pp.

"Cet ouvrage propose une analyse nuancée des transformations induites par l'IA et la robotique autonome dans l'espace francophone. Il insiste sur son potentiel à façonner durablement les sociétés contemporaines. S'appuyant sur des exemples concrets et des études de cas, l'ouvrage fournit un ca ... more

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Just Hiring! How to counter discrimination in AI-powered software for recruitment. A toolkit for software developers

M. Daviet, N. Baranowska, A. Mueller, C. Rus, C. Castillo, J. Saldivar, A. Gatzioura

FINDHR Fairness and Intersectional Non-Discrimination in Human Recommendation (2025), 86 pp.

"In this Toolkit, we offer introductory information and technical recommendations on how to mitigate the risk of discrimination in software development of systems used for recruitment. This Toolkit addresses software developers and product managers working or interested in this field, and it intends ... more

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

Índice Latinoamericano de Inteligencia Artificial (ILIA) 2025 Deep Insights

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

Índice Latinoamericano de Inteligencia Artificial (ILIA) 2025
Deep Insights