Editors Note: This post is a part of a series on Ethics of Artificial Intelligence.
Thank you for coming to my Microsoft Ignite talk on the ethical impact of AI and the practical steps we can make to improve the experience for everyone. A few links to have available are:
- fairlearn: A Microsoft template for improving the ability to structure and monitor an AI model for fairness. This is a start at a variety of templates to start improving how we manage the AI lifecycle.
- MLOps: Maintaining a controlled lifecycle of ML release and improving our ability to monitor and improve based on gathered data from the model around ethics & fairness.
- Excavating AI: A breakdown of the flaws in AI models based on flawed data. This reinforces the need to better align data to use and ensure that a mechanism exists to regularly evaluate the data
- Inclusive Design: Visit the Microsoft Inclusive Design site to learn about practical ways you can build your apps to work for everyone and engage everyone.
- FATE: Fairness, Accountability, Transparency, and Ethics in AI is Microsoft’s organization to drive Ethical use of AI technologies and contribute to the research community.
- Interpret ML: A model built by Microsoft Research (open source) to improve the managability of a black box model.
- Improving Fairness Research Paper: A great research paper on understanding what practitioners need and how we arrive at it.
- Guidelines for Human AI Interaction: How do we understand the relationship between humans and AI and build guard-rails around it? This is a good start.
Here is the video of the transformative impact of AI on the lives of disabled people. This project will be launched to GitHub. Contact me for questions and how to implement it in your business.
Thank you for coming to my session. See you next time!