Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Trustworthy Artificial Intelligence Implementation - TAII Framework Canvas



Trustworthy Artificial Intelligence Implementation - TAII Framework Canvas

Organizations and companies need practical tools and guidelines to kick-off the implementation of Trustworthy Artificial Intelligence (TAI) systems. AI development companies are still in the beginning of this process or have not even started yet. The findings of this article address to decrease the entry level barrier for AI ethics implementation by introducing the Trustworthy Artificial Intelligence Implementation (TAII) Framework. The outcome is comparatively unique given that it considers a meta perspective of implementing TAI within organizations. As such, this research aims to fill a literature gap for management guidance to tackle trustworthy AI implementation while considering ethical dependencies within the company. The TAII Framework takes a holistic approach to identify the systemic relationships of ethics for the company ecosystem and considers corporate values, business models, and common good aspects like the Sustainable Development Goals and the Universal Declaration of Human Rights. The TAII Framework creates guidance to initiate the implementation of AI ethics in organizations without requiring a deep background in philosophy and considers the social impacts outside of a software and data engineering setting. Depending on the legal regulation or area of application, the TAII Framework can be adapted and used with different regulations and ethical principles.
Start using the TAII Framework Canvas for your workshops: https://miro.com/miroverse/taii-framework-canvas 
Website: https://www.socialtechlab.eu 

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.