Responsible AI Framework

AI is transforming organizations, but with it have come ethical, legal, and reputational concerns that can’t be ignored. As governments around the globe work to address these concerns with regulations, the central question for practitioners remains: How can we ensure AI systems are designed and used ethically, fairly, and safely?

At Elder Research, we’ve developed a Responsible AI (RAI) framework shaped by three decades of tackling complex data challenges. It’s an aspirational guide to how we approach RAI in our own work and with our clients, recognizing this is a journey of continuous learning and evolution.

As AI continues shaping our world, we hope this framework serves as a starting point for crucial conversations around using it responsibly.  

Framework Purpose

This framework is designed to:

• Build alignment by establishing a core vision, set of principles, and common vocabulary.
• Define tangible ways practitioners can incorporate RAI practices into a variety of circumstances.
• Provide critical questions that all AI stakeholders can use to assess risks and maximize effectiveness.

In short, this framework reflects our vision for Responsible AI grounded in principles that aspire to ensure AI solutions deliver measurable results without compromising trust or integrity.  

7 Principles of RAI

Our framework defines the following 7 principles of RAI.

Core Evaluation Questions

The framework provides essential questions for business leaders, technical practitioners, and end users—from AI goals and governance to testing strategies and data accuracy.

While not exhaustive, these questions are a productive starting point for addressing risks and guiding solutions toward trust, safety, and meaningful impact throughout the AI lifecycle.

Responsible AI isn’t a standalone initiative—it’s a mindset. By embedding responsible practices into every stage of development, organizations can create solutions that are ethical, trustworthy, and aligned with evolving societal and legal expectations.

Success depends on clear roles and collaboration between business leaders, technical teams, and end users. It’s an ongoing journey that requires adapting to advances in technology and emerging challenges.

At its core, Responsible AI fosters trust and long-term value. We’re committed to learning, evolving, and sharing insights to help organizations confidently navigate this journey.