AI Principles

AI Principles

A guiding framework for our responsible development and use of AI, alongside transparency and accountability in our AI development process.

AI Policy - Taylor & Francis

Learn about Taylor & Francis' AI Policy, which provides guidelines on the ethical use of artificial intelligence in research, publishing, and content creation to maintain integrity and transparency.

AI Standards Lab

AI safety standards worldwide must keep up with the rapid development and deployment of AI technology. Our mission is to help accelerate the writing of AI safety standards.

Responsible AI Principles and Approach | Microsoft AI

Discover Microsoft AI tools, industry-specific governance solutions, and responsible AI practices to make smarter, more informed decisions about AI implementation.

Responsible AI

Discover how AWS is committing to developing AI responsibly – to built trust, promote the safe development of AI, and act as a force for good.

Tapping Into AI’s Conservatism

AI favors established frameworks. Knowing that will change how you develop your information systems.

Guest Post — Now is the Time for AI in Peer Review, and Publishing Policies Need to Recognize This - The Scholarly Kitchen

Today's post asks us to acknowledge the role of AI in peer review and ensure practical guidance and policies that help scholars respond with consistency and confidence.

BBC AI Principles

Our BBC AI Principles are at the heart of our approach to using AI responsibly and apply to all use of AI at the BBC. They underpin the BBC’s public commitments about how we will use Generative AI.

AI Can Write More of the Code. We Still Have to Engineer the System.

Durable decisions, relevant context and verifiable increments: a pragmatic perspective on keeping engineering judgment in AI-assisted development.

Building the safety foundations for India’s agentic future

Last year, through Google’s Safety Charter for India’s AI-led transformation, we set out our commitment to building trust into India’s digital growth. We also showed how…

39 principles for designing human-AI interaction

An applied framework for designing AI interfaces that support appropriate reliance, user control, transparency, and responsible autonomy.

Why I don’t trust most human-AI interaction experimental research – Jason Collins blog

Behavioural economics, data science and artificial intelligence.

How to build an AI scientist: first peer-reviewed paper spills the secrets

AI Scientist, an autonomous research tool, first released in 2024, has now undergone peer review, highlighting its strengths and limitations.

Responsible use of AI in the military? US publishes declaration outlining principles

12 "best practices" for using AI and autonomous systems emphasize human accountability.