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 toolkit helps designers, creatives and innovators to put the user at the centre of AI and machine learning.

How can people always be put first when designing data and AI systems? IDEO's AI Ethics Cards help you to design with people in mind.

Do you want to quickly test your product, service or concept from different user perspectives? With this simple and practical online cardgame, you can make a quick start on digital inclusion.

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.

A tool to explore the possibilities of machine learning and its advantages and disadvantages.

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.

A role-playing game for companies and governments to get to know people's digital barriers and to test their own digital services.

A playbook for ensuring transparency in data set documentation.

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 Institute for the Future (IFTF) and the Omidyar Network have developed a toolkit to help predict difficult and unwelcome consequences and to prevent these from occurring while you develop products and projects based on AI.

The Data Ethics Canvas provides tools to address ethical questions during the design and development of a project or product based on data, such as an AI application.

A component of designing new technologies is imagining the impacy they will have on the world. In order to facilitate this Artefact created the Tarot Cards of Tech . These cards can. be used during team meeting to perform an informal impact assessment

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

The Artificial Intelligence Impact Assessment (AIIA) is a structured method to clearly identify the (social) benefits of an AI system application. In addition, attention is also paid to analysing the reliability, safety and transparency of the AI system.

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.

With the Building an Algorithm Tool you ask ethical questions during the entire AI process: the design, development, test phase and implementation of the AI application.

This toolkit created by and for young people is meant to share the online experience of young people with policy makers, regulators and the ICT industry.

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.

This ethical framework is intended for government agencies. However, it can also be useful for other organizations.

The authors of this article state that suppliers of AI application must create a fact sheet for each product, demonstrating that the application is 'compliant' (an SDoC or 'supplier's declarations of conformity'), just like that for other products happens.

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.

With this Data Collection Bias Assessment form, you make a few choices from the beginning of the data collection so that you can discover possible biases at an early stage.

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