The Trustworthy Artificial Intelligence Implementation - TAII Framework® offers organizations and companies a first orientation in 12 steps for the implementation of trustworthy AI. It also includes a strong focus on the analysis of social implications through the whole AI system development process. Thus, within the iterative framework, additional aspects such as the fulfillment of the Sustainable Development Goals, UN Human Rights, effects on the business model, supply chain, stakeholders, certifications, etc. are included. 

The Trustworthy Artificial Intelligence Implementation - TAII Framework® generates a meta perspective of ethics within the AI system developer's ecosystem, supporting and expanding the trustworthy AI approach of the European Commission by designing social impact.

Rapidly developing Artificial Intelligence (AI) systems hold tremendous potential to change various domains and exert considerable influence on societies and organizations alike. More than merely a technical discipline, AI requires interaction between various professions. Based on the results of fundamental literature and empirical research, it addresses the management’s awareness of the ethical and moral aspects of AI.

The TAII Framework Canvas covers the 12 steps of the holistic framework on the one side and generates many possibilities for group interaction between different stakeholders by using a similar approach as in the Design Thinking methodology. The updated version is available: http://dx.doi.org/10.13140/RG.2.2.20444.72328 

For online collaboration there is also a new Miro TAII Framework Canvas template available.

A deep dive can be found in the book publication of "Trustworthy Artificial Intelligence Implementation - Introduction to the TAII Framework" in the Springer publishing house: https://link.springer.com/book/9783031182747

Baker-Brunnbauer, J. (2021). TAII Framework for Trustworthy AI Systems. ROBONOMICS: The Journal of the Automated Economy, 2, 17. Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3914105

Further information about the TAII Framework is available under https://www.taii-framework.com