RAND's divisions conduct research on a uniquely broad front for clients around the globe.
Researchers evaluate large language model (LLM) responses to questions about suicide and examine how LLMs identify appropriate responses to suicidal ideation.
In a recent panel discussion on artificial intelligence (AI) governance and liability, participants examined AI’s rapid growth and the risks it creates, and proposed six tools to align innovation with public safety.
RAND researchers explore the human factors related to cyber incidents and propose techniques to better assess and reduce vulnerability to human-centric cyber threats.
How might lessons from past technology transformations, like the Industrial Revolution, inform today's AI governance challenges? Researchers use a method called backcasting to explore pathways to hopeful futures and use historical analysis to refine those pathways.
Corporate stakeholders identify and align on common practices, discuss challenges, and share lessons learned in establishing and evaluating metrics in AI governance.
Foundation models—artificial intelligence models trained on large and diverse datasets and capable of performing many tasks—have the potential to have a large effect in shaping the economic and social effects of AI. Identifying whether the market for them is a natural monopoly is critical to selecting an appropriate policy response.
Researchers find that AI developers face considerable liability exposure under U.S. tort law for harms caused by their models, particularly if those models are developed or released without utilizing rigorous safety procedures and industry-leading safety practices.
What can be done to maximize AI's benefits while minimizing its potential risks? The approaches to governing four earlier technologies—nuclear technology, the internet, encryption products, and genetic engineering—may provide valuable insights.
One aspect of artificial intelligence (AI) that makes it difficult to regulate is the potential lack of understanding of how an algorithm may use, collect, or alter data or make decisions based on the data. Focusing on the data that’s used, why AI is being used, and the AI outcomes can potentially alleviate this concern.
The European Union (EU)'s Artificial Intelligence (AI) Act regulations will apply to U.S. companies seeking to operate in the EU market. These regulations include several obligations specific to general-purpose AI (GPAI) models—the most-advanced and most-powerful AI models. The U.S. government has several options to consider in response to the EU AI Act.
Will people continue to use the court system to defend their rights in the era of AI? And if so, do existing legal standards cover the right to contest decisions made by an AI?
As artificial intelligence algorithms become incorporated into more decision processes that affect individuals' welfare and well-being, public perceptions of the technology will have many implications, including for jury judgments about algorithmic liability and support for AI regulation.
