Description:This entry highlights how to align AI research with societal challenges—health, climate, education—using open data, responsible deployment, and cross-sector partnerships that maximize public benefit. Key Resources:• “AI for Good” (Global) – aiforgood.itu.intUN/ITU platform showcasing projects, datasets, and partnerships aligned to SDGs. • “OECD.AI Policy Observatory” (Global) – oecd.aiComparable country policies, metrics, and the OECD AI […]
Description:This entry focuses on model documentation, interpretability tools, and communication strategies (model cards, data statements) so AI decisions are understandable to non-experts and accountable to society. Key Resources:• “Model Cards & System Cards” (Global) – huggingface.co/docsTemplates and guides for documenting models, limitations, data sources, and intended use. • “The Turing Way – Explainability & Communication” […]
This entry covers methods to design AI with the people affected by it—users, domain experts, and communities. It emphasizes participatory design, prototyping, and continuous feedback loops to ensure AI systems are beneficial, inclusive, and socially robust. Key Resources:• “Ethics Guidelines for Trustworthy AI” (EU) – digital-strategy.ec.europa.euGuidelines defining human agency, technical robustness, privacy, transparency, diversity, societal […]
This entry examines the potential of blockchain technology in revolutionizing the management, sharing, and protection of research data. It highlights how blockchain can enhance transparency, security, and accessibility in research, leading to more efficient and reliable scientific workflows. Key Resources: • "Blockchain for Research Data Management" ( Global) – www.blockchain.com/ A detailed resource on how blockchain […]
This entry explores the growing role of artificial intelligence (AI) and automation in the research landscape. It highlights how these technologies are reshaping the way research is conducted, from data analysis to experimental design, and the potential implications for innovation and productivity in various fields. Key Resources: • "AI in Scientific Research: Opportunities and Challenges" […]
Description: The OECD’s Principles on Artificial Intelligence, adopted in May 2019, are the first intergovernmental standard for AI ethics and governance. While specific to AI, they encapsulate ORRI-aligned governance values at a global level. The OECD AI Principles promote innovative and trustworthy AI that respects human rights and democratic values. Among the five key principles […]
Description: Microsoft’s Responsible AI Standard (latest Version 2 released in 2022) is an internal rulebook that translates the company’s AI principles into actionable steps for teams. It represents a comprehensive corporate governance approach to ORRI, covering roles, responsibilities, and processes to ensure AI systems are developed in line with ethical principles. Microsoft’s framework highlights fairness, […]
Description: In 2018, Google published a set of AI Principles as an internal policy guiding the development of artificial intelligence. This is a corporate example of ORRI governance in practice. The Google AI Principles commit to objectives like socially beneficial AI, avoiding unfair bias, being accountable to people, and incorporating privacy and security by design. […]