Welcome to the Responsible AI Guide! In a world where artificial intelligence is becoming more prevelant, understanding how to develop and deploy AI responsibly is more crucial than ever. This guide will serve as a go-to resource for mastering the principles and practices of responsible AI.
In this guide you will find the following:
- Best Practices for Responsible AI Development: Learn the essential do's and dont's to ensure that the AI system is ethical and trustworthy.
- AI Governance: Understanding the importance of AI governance, and its implementation within an organization.
- Frameworks and Guidelines: Explore various frameworks and guidelines to help with the responsible delpyment of AI.
- Case Studies: Providing real-world examples of responsible AI in action and lessons to be learned from these implementations.
- Tools and Resources: Access to a list of tools and resources to learn responsible AI. This includes important papers relating to Responsible AI to essential books.
This guide provides pratical content convering all aspects of responsible AI. This guide should provide information on foundational principles to advanced implementation techniques. Whether you are a developer, policymaker, or researcher, you will find valuable insight in this guide.
In this guide the information will be concise, to help equip you with the essential knowledge needed to navigate the complexities of responsible AI. By following the guidance provided on the website, you can ensure your AI projects are not only robust but ethically system.
Together, let's build AI systems that enhance human wellpbeing and foster trust in technology.
Here are some further resources that you can read to help you on your responsible AI journey!
- 💻 Google's Responsible AI Guidelines Are Available Here
- 🐝 IBM's Pillars of Responsible AI and IBM's Resources Are Available Here
- 📲 Meta's Responsible AI Guide is Available Here
- 🏙️: Responsible AI Institute's Member Application to Join an Industry Backed Community is Provided Here
There are no formal contributing guidelines. If you have any ideas to add to this guide please submit a pull request or create an issue. Any feedback and contributions are appreciated!
This guide was inspired by the Prompt Engineering Guide and the Blind 75 Guide
This repository is under the MIT License