Artificial Intelligence

Emerging technologies are changing the way we work, think, and behave. With the fast-paced nature of modernization, researchers and policy makers are being asked to move faster, process more information, and make decisions quickly. Artificial intelligence (AI) tools can address the needs of the evolving research landscape, enabling researchers to approach their work in new and effective ways.   

RTI’s team of experts have applied AI technologies to a wide variety of projects—from implementing natural language processing algorithms to study the influence of JUUL’s marketing efforts on underage youth to leveraging machine learning to track the effects of COVID-19 university shutdowns on the early-careers and lives of doctoral students to building dashboards to consolidate data for faster decision making. With a track record of making sense of data, we are positioned to fill the gaps in understanding how technology can be used to solve complex problems.

Establishing Responsible AI Research Practices

While AI provides many benefits for everyone, researchers must promote the responsible, secure, and impactful development and use of groundbreaking AI in their work. Our experts are leading conversations on a national level about managing AI risk, ensuring equity, and preventing harm. Through the National Institute of Standards and Technology U.S. AI Safety Consortium, we have joined other subject matter experts on a shared mission to develop national generative AI standards, working in unity towards the safe and trustworthy use of AI in research and beyond. Setting a solid foundation for future AI use will allow researchers to answer the call to clients and partners in all areas of research.   

Generative AI in Research to Advance Insights

RTI utilizes recent developments in generative AI (GenAI) to enhance research and insights, while still focusing on ethical and responsible usage for maintaining research integrity and data security. We’ve evaluated GenAI’s use in automating information extraction for evidence synthesis, employed large language models as qualitative coders, and tested AI's capability in plain language writing for diverse audiences. These advancements aim to expedite research processes, maintain accuracy, and improve readability of complex information, supporting our mission and helping to effectively address multifaceted challenges.

Learn how we're driving innovation in with generative AI.