arXiv subjects

Rachel Adams

Publications and source records attributed to Rachel Adams.

3 recordsLinked to original sources

arXiv2026

Global Index on Responsible AI: 2026 Report

Grounded in human rights-based frameworks such as the UNESCO Recommendation on the Ethics of AI, the Global Index on Responsible AI (GIRAI) examines how countries translate responsible AI commitments into enforceable protections, institutional capacity, and redress mechanisms. GIRAI 2026 assesses these across five dimensions: Inclusion and Diversity, Ethics and Sustainability, Labour and Skills, Trust and Safety, and AI Use in Public Service. A global network of 135 country-level researchers collected and assessed 68,138 data points on 38 indicators organised across three pillars: government AI policy and implementation (17 indicators), civil society engagement (5), enabling conditions (15), and documented cases of government deployment of unacceptable-risk AI systems. The data covers November 2023 to September 2025. A score of 100 is derived from the indicators to rank all countries. Findings show that while responsible AI governance is expanding, with 126 of 135 countries having at least one government policy or initiative across the 17 AI Policy indicators, this does not often translate into meaningful protection. For instance, Global South countries account for 203 of 306 new cases of indicators with frameworks since the first edition, yet 78% of their frameworks remain non-binding compared with 42% in the Global North. Government commitment to AI governance also does not extend to their own algorithms: whereas Transparency and Explainability is one of the strongest performing indicators, with 58% of countries having some framework, only 18% require Public Disclosure of Government Algorithms. Credible evidence of government deployment of unacceptable-risk AI systems was also found in 35 countries. These findings show that responsible AI governance must move beyond framework adoption toward enforceable rights-based protections, resourced oversight institutions, and accessible redress.

cs.AI↗

arXiv2026

Global Index on Responsible AI 2026 : Conceptual Framework and Methodology

This report presents the methodology of the Global Index on Responsible AI (GIRAI), 2nd Edition. This edition refines the 1st Edition by strengthening the distinction between framework existence and implementation, restructuring dimensions from three to five thematic areas, introducing more granular variables for framework quality, and applying a multi-stage review and validation process. An independent statistical pre-audit was conducted to assess the coherence and robustness of the framework. GIRAI assesses responsible AI governance across five dimensions: Inclusion and Diversity, Ethics and Sustainability, Labour and Skills, Trust and Safety, and Use of AI in Public Service. Each dimension has a number of indicators (38 in total), organised into three pillars, namely AI Policy (17 indicators on government frameworks and implementation, assessed through primary data), CSO Engagement (5 indicators, primary data), and Enabling Conditions (15 indicators on the structural factors shaping responsible AI governance, assessed through secondary data), and a government Use of Unacceptable Risk AI (URAI) indicator (primary data), applied separately as an accountability penalty to the final score. Data was collected by 135 country-level researchers through a structured global survey, complemented by secondary datasets. The count, scope, enforceability, thematic coverage, and implementation levels of the data points are coded into numerical variables, normalised to a scale of 100, aggregated through pillar weights of 60% (AI policy), 10% (CSO Engagement), and 30% (Enabling conditions). A deduction penalty is applied for countries with evidence of URAI. This documentation enables systematic cross-national comparison, supporting policymakers, civil society, and AI developers to identify where commitments are translating into enforceable protections and where critical gaps remain.

cs.CY↗

arXiv2025

Toward an African Agenda for AI Safety

This paper maps Africa's distinctive AI risk profile, from deepfake fuelled electoral interference and data colonial dependency to compute scarcity, labour disruption and disproportionate exposure to climate driven environmental costs. While major benefits are promised to accrue, the availability, development and adoption of AI also mean that African people and countries face particular AI safety risks, from large scale labour market disruptions to the nefarious use of AI to manipulate public opinion. To date, African perspectives have not been meaningfully integrated into global debates and processes regarding AI safety, leaving African stakeholders with limited influence over the emerging global AI safety governance agenda. While there are Computer Incident Response Teams on the continent, none hosts a dedicated AI Safety Institute or office. We propose a five-point action plan centred on (i) a policy approach that foregrounds the protection of the human rights of those most vulnerable to experiencing the harmful socio-economic effects of AI; (ii) the establishment of an African AI Safety Institute; (iii) promote public AI literacy and awareness; (iv) development of early warning system with inclusive benchmark suites for 25+ African languages; and (v) an annual AU-level AI Safety & Security Forum.

cs.CY↗