About

We believe that the development and practice of machine learning should help create a fairer and better World.

Machine learning has advanced rapidly and is now widely practised. However, it has often been operationalised with little regard for its wider societal impact, sometimes resulting in harm and unfair consequences. Through ethical and responsible machine learning, we believe that these consequences can be mitigated and a better World created. That is why we have developed free, open-source, community driven best practices and guides on ethical and responsible machine learning.


We are a team of seasoned data scientists, machine learning engineers, AI ethicists and governance experts, who are enthusiastic about lowering the barriers for pragmatic ethical and responsible machine learning. Our team is passionate about ethical and responsible machine learning and believes that, in order to best promote real change, grassroots, democratic movement is key. We believe this means that everyone working in machine learning must be able to easily access tools and/or concepts associated with ethical and responsible machine learning.


That is why we have chosen to create and facilitate our community driven Best Practices. These open-source guidelines advise on a wide range of best practices - both technical and organisational - that help advance pragmatic ethical and responsible machine learning. We stand for open and inventive work that is why our Best Practices are open-source and freely available for commercial use and/or adaptation via the Creative Commons Attribution license.


Meet the Team

Contributing to our Best Practices


Our Best Practices are open-source and community driven. This means that you can contribute to them too. You can propose new best practices and edit existing ones.


Your contributions can be made through our Wiki portal, where they will be available for everyone to see and discuss. These updates will be periodically reviewed and incorporated into our next release of the Best Practices.


Note that if you do contribute to our Best Practices, you accede that your work will be transferred to The Foundation for Best Practices in Machine Learning so that we can, subsequently, license it under the Create Common Attribution license in order to make it freely available to all. Should you have any more questions in this regard, please feel free to contact us.

Help or Volunteer


We are always looking for volunteers to help us with tasks, such as the administration of the Foundation, community coordination and moderation, improving our platform(s) and content creation. Feel free to send an email to info@fbpml.org if you are interested in volunteering or if you just want to get in touch.