Artificial intelligence (AI) is rapidly transforming how we measure learning and skills — from classrooms to workplaces, from formative feedback to high-stakes testing. Just as the relationship between measurement science and assessment has evolved over time, we are now seeing the relationship between AI and human learning develop. Yet as AI adoption accelerates, the questions that matter most, the very questions ETS has been tackling for nearly eight decades, remain as relevant and critical as ever:
- How do we ensure every learner is treated fairly?
- What standards and practices guarantee validity and reliability?
- Who provides independent evidence that leaders, policymakers, and communities can trust?
The moment: rapid AI adoption meets urgent questions
While AI-based capabilities have been used for decades, over the past few years, new AI-powered tools have surged into education and workforce assessment. Educators and employers alike are eager for solutions that promise efficiency and personalization, but the risks are real: bias in algorithms, “black box” decision-making, and the potential to exclude rather than empower. With AI touching many aspects of daily life, we must remind ourselves that AI is only a tool — and its integration must be ethical, transparent and human-centered.
Yet, most stakeholders lack clear guidance on how to select, implement and evaluate these tools responsibly. The need for independent, evidence-based standards has never been greater. That’s where we step in.
Why the Center for Responsible AI in Learning and Assessment — and why now?
Launching the Center is a direct response to this urgency. The Center’s mission is bold:
- Advance the responsible use of AI for human learning and assessment by conducting rigorous research, developing practical tools and setting actionable global standards.
- Foster fair, reliable and inclusive solutions — empowering learners, educators and decision-makers to make their education and work more productive, informed and tailored to meet their needs.
- Translate research into actionable guidance for education and workforce leaders, policymakers, funders and the public.
This is not just about technology — it’s about building public-interest frameworks that put fairness, validity and transparency at the core of every AI-enabled assessment and solution.
ETS measurement science: the differentiator
What sets the Center apart is its foundation in measurement science. For nearly eight decades, ETS has set the global standard for fairness, validity and reliability in assessment. As AI reshapes the landscape, ETS’s expertise ensures that new tools are not just innovative, but also trustworthy, evidence-based and research-backed.
- Independent evaluations and purpose-built auditing tools help organizations reduce risk and ensure fairness.
- Standardized benchmarks and evidence-based guidance translate research into scalable impact.
- Impact dashboards, risk and fairness safeguards, and best practices provide transparency and accountability for all stakeholders.
Building for the public good
The Center’s launch is more than a milestone — it’s a public commitment to serve as a nonpartisan steward for responsible AI in assessment. By convening cross-sector partners, publishing open research, and offering practical resources, the Center aims to:
- Close educational and social disparities
- Support lifelong learning and workforce mobility
- Ensure that every learner’s achievements are visible, valued and a gateway to opportunity
Looking ahead
As AI continues to evolve, the Center for AI and Human Learning will remain focused on what matters most:
- Fairness and inclusion — so no learner is left behind
- Transparency and accountability — so every decision is clear and defensible
- Continuous improvement — so standards and practices keep pace with innovation
The future of assessment is being written now. With the launch of the Center for Responsible AI in Learning and Assessment, ETS is ensuring that responsible AI is not just an aspiration, but a reality — grounded in science, shaped by evidence and built for the public good.