This open-source AI assessment tool from AI4Belgium, based on the European Commission's ALTAI questionnaire, can help you make your AI system more transparent, robust and trustworthy

The Digital Ethics Compass toolkit includes several questions, recommendations and a workshop to learn more about how to design digital products in an ethical way and how to use this as a competitive advantage.

How can you avoid replicating societal biases, prejudices and structural disparities in your AI healthcare system? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots healthcare card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

How can you take into account possible prejudices and structural inequalities before, during and after the development of your AI application? In order to help you do this, the Knowledge Centre Data & Society developed the AI Blindspots card set.

The AI Ethics Lab has developed a toolbox that gives an overview of the different existing sets of principles that you can integrate and/or evaluate in your AI system.

In the cooperative card game Ethics Inc. you design ethically responsible AI applications together.

You’d like to develop products that would make the world a bit better? Omidyar offers a tool to help you with the development of responsible technology. Bonus: you also receive a guide to actually change the way your organisation develops tech.

A good way to get acquainted with the idea of explainable AI is to look at IBM Research's AI Explainability 360 Open Source Toolkit. In addition they offer multiple algorithms as a possible start of using explainable AI (XAI).

The approach to guidance ethics aims to start the dialogue about the connection between ethics and technology through a workshop.

The Aequitas tool performs an audit for your project. This method is intended to analyze whether there are prejudices in the data and in the models you use. You can perform the audit via the desktop or online tool.

Do you want to know how ethical your AI application is? The AI systems Ethics Self-Assessment Tool helps you to estimate four ethical principles yourself.

This tool by FAT/ML ( ‘Fairness, Accountability and Transparency in Machine Learning’) has as goal to promote the following ethical principles: responsibility, explainability, accuracy and accountability.

This tool was created by and for data scientists. It consists of various methodologies that all can be applied at the start of a project. The aim is to document ethical issues and decisions in this regard, for example, to provide accountability towards stakeholders.

The Ethics framework of Machine Intelligence Garage consists of seven principles, each with a set of questions that can lead to a better understanding of how to deal with ethics in your design.