In every scientific field, researchers draw conclusions by managing the generation, organization and analysis of data — whether that information comes from computer simulations or experiments.

Artificial Intelligence, or AI, is an essential tool for streamlining this discovery process. It is revolutionizing the domains of scientific discovery and complex systems, experimental facilities and national security. Advancements in AI enable scientists to work with far larger datasets and do so far more quickly than ever before.

Two of the most promising AI techniques are machine learning, in which sophisticated algorithms learn from data to ensure accurate decision-making, and deep learning, which is a subset of machine learning that focuses on training artificial neural networks to learn about and understand complex patterns and representations in data.

These tools help make sense of modern research projects, which tend to generate so much data that learning complex patterns and extracting insights from the results would be impossible without AI.

Experts at the Department of Energy’s national laboratories are working with university and industry partners to improve this process by reducing costs and times to solution. And as AI systems become increasingly integral to critical decision-making processes and more deeply integrated into research workflows, ensuring their reliability and accuracy is more important than ever.

Establishing safe and trustworthy AI systems will enable researchers to pursue scientific discovery while earning the confidence of researchers, policymakers and members of the public by providing safeguards against incorrect and improper use. To address AI’s continually escalating computational demands, scientific institutions must also adopt energy-efficient methods that not only align with sustainability goals but also enhance the longevity and scalability of AI-driven accomplishments. By developing and strengthening the foundations of these three pillars of AI — safety, trustworthiness and energy-efficiency — we aim to ensure that any progress made in this promising field remains ethically and environmentally responsible.