The primary goal of the READ Research Foundation is to advance practical, design-oriented approaches to responsible AI that can be adopted by engineers, institutions, and policymakers. We aim to move ethical AI from abstract principles into implementable technical and governance frameworks.
Our work is guided by three long-term goals:
- To shape how AI systems are designed, evaluated, and governed before they are deployed at scale
- To contribute technically grounded insights to public policy and standards discussions
- To cultivate a global research community capable of addressing AI risks with rigor and responsibility
Scope of Work
READ’s research scope spans the full AI lifecycle, with particular attention to areas that are underrepresented in current AI governance discourse. This includes:
- Design-time responsibility in AI systems, including architectural and system-level considerations
- Explainability and accountability in non-LLM AI systems, such as edge, embedded, and infrastructure AI
- Interactions between AI models, hardware, and system constraints
- Engineering-informed policy analysis relevant to emerging AI regulation and standards
- Context-specific research informed by real-world deployments, field studies, and on-site surveys where appropriate
READ does not engage in political advocacy, commercial product development, or proprietary consulting. Our focus remains on independent research and public-interest knowledge creation.
Values
READ Research Foundation is guided by the following core values, which inform our research practices, collaborations, and public engagement:
Responsibility by Design
We believe responsibility must be embedded at the earliest stages of AI system design, not added retrospectively. Ethical considerations should influence architectural choices, performance trade-offs, and deployment decisions.
Technical Rigor
Our research is grounded in sound engineering and scientific methods. Claims, frameworks, and recommendations must be defensible, reproducible where possible, and supported by evidence.
Transparency
We value clarity in both technical and non-technical communication. Our work aims to make complex AI systems and design decisions understandable to diverse stakeholders without oversimplification.
Independence
READ operates independently of political parties, commercial interests, and lobbying efforts. Research conclusions are driven by evidence and analysis, not external influence.
Global and Inclusive Perspective
We recognize that AI systems operate across borders and social contexts. Our work seeks to incorporate diverse perspectives and avoid one-size-fits-all assumptions.
Ethics Charter
Purpose
This Ethics Charter defines the principles that govern how READ conducts research, collaborates with partners, and disseminates knowledge. It applies to all members of the community, including researchers, fellows, collaborators, and advisors.
Research Integrity
All research conducted under READ must adhere to high standards of integrity. Data sources, assumptions, limitations, and potential conflicts of interest must be disclosed transparently. Plagiarism, misrepresentation, or selective reporting of findings is not permitted.
Human-Centered Consideration
Research activities must account for potential impacts on individuals and communities. Where research involves human subjects, field studies, or on-site surveys, appropriate consent, privacy protection, and ethical review processes must be followed.
Accountability and Explainability
The organization prioritizes research that advances accountability and explainability in AI systems. We avoid endorsing opaque or unverifiable claims about AI performance, safety, or societal benefit.
Responsible Collaboration
Collaborations with academic, industry, or public-sector partners must align with READ’s mission and values. We do not engage in partnerships that compromise research independence or ethical standards.
Public Interest Commitment
READ’s outputs are intended to serve the public interest. Research findings are shared openly wherever possible and communicated responsibly to avoid misuse or misinterpretation.
Continuous Reflection
AI technologies evolve rapidly. READ commits to ongoing ethical reflection, periodic review of its research practices, and adaptation of this charter as new challenges and insights emerge.
