Trustworthy and Responsible AI at the Global Scale

Disclaimer: This is a concept paper that does not provide any specific or actionable legal advice, policy advice, or other professional guidance. Any references to laws, rules, regulations, and frameworks are illustrative and intended to demonstrate how a purpose-specific framework for Trustworthy and Responsible AI could be created. For any specific framework creation, please do your own research and refrain from relying on this paper for the latest facts.

Executive summary

Artificial intelligence (AI) has been transforming industries for decades. The newest wave of AI is poised to be the most innovative and disruptive in history. It is transforming industries — ranging from healthcare and transportation to public services and scientific research — by driving unprecedented progress, efficiency, and innovation. However, AI's transformative potential comes with significant risks (e.g., ethical dilemmas, algorithmic biases, privacy and security concerns, and socio-economic impacts on the workforce). As governments introduce guidance for safe and responsible AI, the lack of harmonized governance frameworks means organizations must find ways to demonstrate compliance and foster trust in a fragmented regulatory landscape.

World Wide Technology (WWT)'s AI research team has created a Trustworthy and Responsible AI (TRAI) framework that addresses these risks through a comprehensive, lifecycle-focused approach to responsible AI innovation. Since WWT has identified significant gaps in most, if not all, GenAI-specific frameworks, we have created a comprehensive approach that also fits with any sub-set of industry frameworks. TRAI empowers organizations to navigate both technical and societal imperatives by integrating robust trust measures, effective risk mitigation strategies, and strict adherence to ethical and regulatory standards. In doing so, the TRAI framework enables the development of resilient, high-performing AI systems that not only meet user needs but also contribute positively to society and the environment.

By leveraging WWT's TRAI framework, organizations can balance rapid innovation with steadfast responsibility, ensuring a sustainable future for AI. This framework provides a practical, actionable foundation for ethical, transparent, inclusive, and secure AI governance — driving continuous improvement, maintaining stakeholder confidence, and delivering meaningful societal impact at scale. 

This paper outlines a practical approach to developing a global framework or trustworthy and responsible AI that can facilitate cross-border data sharing. By adopting WWT's 5 pillars of TRAI, organizations can develop their own North Star that will remain constant and clear amidst a never-ending sea of change.