The U.S. National Science Foundation's "10 Big Ideas for Future NSF Investments," first announced in 2016, focused on driving important aspects of NSF's research agenda, pushing forward the frontiers of U.S. science and engineering research, and leading to discoveries and innovations.
Six of the Big Ideas were research ideas, building upon the foundation of NSF-funded research over the past 70 years. The research ideas were complemented by four enabling ideas, which focused on improving the way science is done, from impacting the workforce to developing the infrastructure that will drive the discoveries and aid the discoverers of tomorrow's science.
While the Big Ideas ended as a unifying concept in 2023, NSF continues investments in many of the Ideas through its core programs. Current funding opportunities and recent news relating to the 10 Big Ideas can be found on this page.
On this page
Future of Work at the Human-Technology Frontier
A research Big Idea
The Future of Work at the Human-Technology Frontier Big Idea focused on responding to challenges and opportunities for the future of jobs and workers in a landscape with rapid social and technological changes. It aimed to:
- Understand and develop the human-technology partnership.
- Design new technologies to augment human performance.
- Illuminate the emerging socio-technological landscape and understand the risks and benefits of new technologies.
- Understand and influence the impact of artificial intelligence on workers and work.
- Foster lifelong and pervasive learning.
NSF's investments in this area continue through a number of programs. Click the links below to learn more.
Growing Convergence Research
An enabling Big Idea
The grand challenges of today — like protecting human health; understanding the food, energy and water nexus; and exploring the universe at all scales — will not be solved by one discipline alone. They require convergence: the merging of ideas, approaches and technologies from widely diverse fields of knowledge to stimulate innovation and discovery.
The Growing Convergence Research Big Idea focused on building a system that supports convergent science through research projects and programs motivated by both intellectual opportunities and important societal problems.
NSF's investments in this area continue through the Growing Convergence Research program and others. Visit the links below to learn more.
Harnessing the Data Revolution
A research Big Idea
The increasing speed at which researchers collect data, as well as the increasing volume and variety of that data, are profoundly transforming research in all fields of science and engineering.
The Harnessing the Data Revolution Big Idea focused on:
- The pursuit of fundamental research in data science and engineering.
- The development of a cohesive, federated, national-scale approach to research data infrastructure.
- The development of a 21st-century data-capable workforce.
NSF's investments in this area continue through a number of programs. Visit the links below to learn more.
Mid-scale Research Infrastructure
An enabling Big Idea
The Mid-scale Research Infrastructure Big Idea focused on funding experimental research capabilities in the mid-scale range, a "sweet spot" for science and engineering that has been challenging to fund through traditional NSF programs.
NSF's mid-scale research programs are designed to address the research community's growing needs for contemporary research infrastructure to support the advancement of science and engineering research, as well as science, technology, engineering and mathematics (STEM) education research.
NSF's investments in this area continue through the Mid-scale Research Infrastructure programs and others. Visit the links below to learn more.
Navigating the new Arctic
A research Big Idea
Arctic change will fundamentally alter climate, weather and ecosystems globally in ways that are not yet fully understood but will profoundly impact the world's economy and security.
The Navigating the New Arctic Big Idea focused on establishing an observing network of mobile and fixed platforms and tools across the Arctic to document and understand the Arctic's rapid biological, physical, chemical and social changes.
NSF's investments in Arctic research and education continue across many programs. Visit the links below to learn more.
NSF 2026
An enabling Big Idea
The NSF 2026 Big Idea was framed around the year 2026 to tie into the nation's 250th anniversary.
Through the NSF 2026 Idea Machine Prize competition, NSF sought input from the community into bold foundational research questions that are large in scope, innovative in character, originate outside of any particular directorate, and require a long-term commitment. Click the accordions below to learn more about the competition.
The Idea Machine encouraged individuals from all walks of life, age 14 or older, to submit pressing "grand challenges" in fundamental research or STEM education that have the potential for great impact.
NSF received about 800 entries from nearly every state in the U.S. This included established researchers, undergraduate and graduate students, teachers on behalf of their classes, and even high school and middle school students.
The top seven entries and contest entrants to the NSF 2026 Idea Machine were recognized in an official ceremony on Feb. 4, 2020, at the NSF headquarters. At the ceremony, four entries received the Grand Prize of $26,000 per team and three entries were awarded the Meritorious Prize, receiving $10,000 per team.
Grand prize winners
Emergence: Complexity from Bottom Up
Abraham Herzog-Arbeitman – Undergraduate Student, University of Chicago
The intricate design of a snowflake, a school of fish swimming in unison, the thought patterns of a human mind. Each of these are complex systems that began with something simple — a water molecule, a minnow, a single neuron. As groups of these elements interact, a complex structure unfolds with new characteristics. Out of chaos, a sophisticated order seems suddenly to emerge without effort or guidance. But this is far from chance. It is an efficient and versatile process prevalent throughout nature known as Emergence — a phenomenon that describes how simple components interact to form elaborate things.
Emergence is found wherever complexity is. It is a process relevant to all the sciences and the humanities — as prominent in computing or cryptography as it is in predicting traffic patterns or viral videos. Virtually every intricacy in our world depends upon Emergence, and evidence suggests that these complex systems rely on it in a similar way. That means that the more we understand how Emergence works, the more we can understand and influence all kinds of elaborate systems. Ultimately, harnessing emergent design could help us create our own complex systems or behaviors with the same efficiency as nature.
This deeper understanding of Emergence promises far-reaching impacts for science and society. It could help us to influence economic trends or to untangle the cellular interactions that lead to cancer. The efficiency of emergent design is especially useful when creating ordered systems affected by limited resources. For example, energy grids, postal services, factories, and waste-management plants could all be designed to produce more and waste less. Entire cities could be planned with greater efficiency, inviting a new era of urban design inspired, ironically, by nature.
To predict the complex behavior of emergent systems, we must understand how their components communicate and interact with each other over time. This may require analyzing massive amounts of data. Like many modern research ideas, advancements in machine learning and supercomputing stand to greatly enhance our study of Emergence, making now an optimal time to explore this idea and to build on existing efforts.
Perhaps more than any other research question, the study of Emergence has interdisciplinarity at its core. Researchers must work across scientific and social disciplines to gather and compare examples of emergent systems, helping them to understand their common elements and to develop a unified vocabulary for describing them. Through this careful but universal lens, we can begin to extract general design principles that could be applied to various fields and societal priorities.
As our challenges grow more and more complex, so too must our solutions and our understanding of complexity itself. Fortunately, in nature we have a blueprint for complexity that is both efficient and effective, promising new emergent solutions for challenges of every kind.
Engineered Living Materials
Neel S. Joshi – Associate Professor, School of Engineering and Applied Sciences, Harvard University
Anna Duraj-Thatte – Wyss Institute Postdoctoral Fellow, Harvard University
Avinash Manjula Basavanna – Wyss Institute Postdoctoral Fellow, Harvard University
Consider the power of a single seed. Within its tiny walls is genetic information that tells the seed how to replicate itself. As it grows, it draws energy from the sun, and its cells learn to sense and respond to changes in the environment. Over time, that tiny seed develops into a towering Redwood, knowing how to grow, to adapt to its surroundings and to propagate. This is the process nature has perfected for building and sustaining our biological world.
Unlike nature, our modern world relies on countless products and technologies, from indoor plumbing to life-saving devices. This human-made environment is composed of materials like steel, glass, concrete, and plastic – built materials that are the result of advancements in science, engineering, and manufacturing. While enabling our way of life, the production and disposal of built materials causes a significant impact to our environment, the full extent of which is still yet to be seen.
This research idea will address those challenges by harnessing the engineering power of nature and that tiny seed. It envisions a new class of materials that combine the properties of living organisms with the applications of built materials. Like organic cells, these Engineered Living Materials would have the ability to respond to changes in their environment and to heal and regulate themselves. With these properties, Engineered Living Materials could add new and powerful capabilities to the products we depend on, better serving our modern world and helping to preserve our environment.
The applications are vast — clothing made of cells that sense perspiration and help to breakdown odor. Shelters built with concrete capable of sealing its own cracks. Protective armor that detects and adapts to external pressures or bioplastics that decompose after use. Concept-proofing efforts to make materials with biological attributes are just beginning, and we have only scratched the surface of their potential. Engineered Living Materials promises to transform virtually every modern endeavor from healthcare to architecture to transportation. The result may be a new generation of technologies that achieve the same or greater functionality but with less costs or maintenance.
Recent advancements in synthetic biology have enabled researchers to engineer living cells, which are already used in the making of everyday products like, medicine, food, and biofuels. We have only just begun to apply these developments to the world of materials technology. Simultaneously, we must explore the ethical, legal, and social implications of these new materials to ensure that they are designed and used in an ethical and acceptable manner.
NSF has supported research to explore fundamental questions about the rules of life and future manufacturing, bolstered by new advancements in artificial intelligence and omics research. Engineered Living Materials builds on this progress by extending these rules beyond individual cells to more complex structures.
Advancements in materials science and technology have already shaped the course of human history, proving vital to our prosperity, security and quality of life. The development of Engineered Living Materials technology could revolutionize our future, laying the groundwork for a modern world made of sustainable, self-regenerating materials inspired by nature – the ultimate engineer.
From Thinking to Inventing
Matthias Scheutz – Professor, Department of Computer Science and Department of Psychology, Tufts University
Vasanth Sarathy – Graduate Student, Department of Computer Science and Department of Psychology, Tufts University
A survivor in the rubble waits. A rescue robot confronts the shifting hazards that characterize a disaster zone. As challenges arise, the robot immediately and independently evaluates strategies, experiments with solutions and ultimately finds a path forward.
The survivor is saved. No lives are risked. This is but one hopeful application of robotic reasoning that may result from the new phase of research that the project "From Thinking to Inventing" envisions.
Currently, Artificial Intelligence (AI) research focuses on enhancing human productivity and efficiency, like working in extreme weather or identifying data patterns with greater speed and accuracy. Generally, machines are tasked with rote objectives and directed by programmers. Essentially, challenges presented to machines don't yet require creative ingenuity.
But what if machines could do more than execute tasks? What if, like their inventors, machines could exhibit enough common sense to evaluate real-world problems, imagine and execute solutions? "From Thinking to Inventing" proposes a new era of AI research, where machines could learn to model human creativity and thought processes in order to evaluate, improvise and ultimately solve new and complex challenges. It asks what can machines invent and how?
NSF investments have contributed fundamentally to modern AI research. Six decades of investments have enabled AI advancements that bear impact on all aspects of society, from severe weather predictions to life-saving interventions. "From Thinking to Inventing" builds upon that foundation.
This research could revolutionize AI from pattern-matching machines to problem-solving allies. It could examine the very nature of problem-solving through computational and cognitive scientific lenses. It will aim to develop a deeper understanding of human creativity and apply that insight to the realm of AI.
Societal benefits thus include a deeper, multidisciplinary understanding of human problem-solving that can inform how we teach and advance our own ingenuity. Creative machines could catalyze scientific progress in multiple fields and lead to plethora applications. Finally, inventive AI could be a tremendous ally in addressing grand, complex societal challenges.
"From Thinking to Inventing" has important implications for the development of AI itself. Researchers ask, could machines develop the human capacity to invent and problem-solve? Could machines one day surpass human capabilities? Certainly, AI advancement toward invention will require governance. But this investment helps seize the promise of a burgeoning field and will nurture its growth into a trusted tool and partner.
Public Carbon Capture and Sequestration
Karin Pfennig – Professor, Department of Biology, University of North Carolina, Chapel Hill
"Many hands make light work." This phrase describes how big challenges can be made less daunting when broken down and shared by many. Global warming is one of the greatest challenges we face today. This research question asks – could the help of many hands make it lighter?
While industrialization made way for our modern world, it has also led to increased emissions of carbon dioxide, which have had enormous impact on our planet and all life on it. In response, we have worked to reduce the amount of carbon already in our atmosphere through a process called carbon capture and sequestration. Large, industrial facilities could extract and contain massive amounts of atmospheric carbon but very few exist, as they are costly and difficult to deploy. Even when combined with technologies to reduce new carbon emissions, these efforts have not been able to keep up with the increasing rate of CO2 production or to reverse the damage already done.
What if we could develop additional tools for carbon capture and storage that borrow the technology of an industrial facility and bring it to our backyards? The Public Carbon Capture and Sequestration idea aims to do just this, by developing new technologies to capture and store small amounts of carbon, that when used by many, could lead to significant reductions in CO2.
In this scenario, we could all play a small but important role in reducing atmospheric carbon. Imagine if every home had a filter system that took in carbon and locked it away. Or if trash bags were made to trap carbon and leave it in landfills where trash is buried. Consumer products, which once contributed to pollution, could be made with new materials that help control it, by extracting carbon and holding on to it once disposed of. Green plants already remove carbon dioxide; and if the plants are buried, the CO2 is not released into the atmosphere right away. There is work under way to safely engineer plants that are even better at this, particularly in their root structures. These small efforts replicated over and over could have a massive impact.
By involving individuals and communities in carbon capture and storage, this idea promises another important benefit to society – greater awareness of increasing carbon levels and its consequences. This understanding alone could result in fewer new carbon emissions, leaving less to extract. In practice, Public Carbon Capture and Sequestration also raises exciting new questions for social and behavioral scientists, presenting a unique opportunity to study how to motivate people to make small-scale changes that could lead to global impact. This may offer insight into other collaborations, inspiring a model for widespread change through mass participation.
The idea of Public Carbon Capture and Sequestration leverages the millions of Americans concerned about global warming and enlists them in the solution. It puts to new use an infrastructure already in place to engage the public in climate control. And it applies emerging and existing technologies to address a global urgency. By adding new allies and cutting-edge tools to our carbon-reducing strategy, we could come closer to reversing the damage of climate change and creating a model for other solutions, made lighter by many hands.
Meritorious prize winners
Reinventing Scientific Talent
Jason Williams – Assistant Director, External Collaborations - DNA Learning Center, Cold Spring Harbor Laboratory
In these times of unprecedented, accelerating discovery, there is a need for new thinking about scientific talent. Will today's graduates in science, technology, engineering and math (STEM) keep pace with discoveries over the next decade? "Reinventing Scientific Talent" asks the urgent question: How will scientists, educators, and other STEM workforce professionals continue to learn throughout their careers? NSF has invested heavily in developing a large, diverse pool of STEM talent. This winning idea asks how to maximize that investment by combining the expertise acquired through a degree with novel approaches to training and learning. The goal is to empower STEM professionals to adapt and grow as discovery changes industries and academia. It envisions truly life-long, enduring STEM careers so that today's — yesterday's and tomorrow's — STEM graduates will remain full-fledged participants in the future STEM workforce.
Theory of Conscious Experience
Vincent Conitzer – Kimberly J. Jenkins University Professor of New Technologies, Department of Computer Science, Duke University
"I think, therefore I am," René Descartes wrote nearly 350 years ago. Today, understanding of how consciousness arises remains elusive. Historically, scientific research about conscious experience has been grounded, to significant extent, in neuroscientific understanding. Are there complementary approaches that might enhance progress on understanding consciousness? "Theory of Conscious Experience" imagines going beyond neuroscientific approaches by converging research on cognition, philosophical concepts, theoretical computer science, artificial intelligence, computational modeling, and virtual and augmented reality to study the subjective experience of consciousness. Such a new approach could offer insight into conscious experience. It could even offer a paradigm for answering the hard problems of consciousness, such as, "If I am, does that mean I think?"
Unlocking the Future of Infrastructure
Juan Pablo Gevaudan – Graduate Student, Civil, Environmental and Architectural Engineering, University of Colorado at Boulder
Chelsea Heveran – Assistant Professor, Mechanical and Industrial Engineering, Montana State University
Urban growth can't rely on the fixed and aging infrastructure built in past centuries. "Unlocking the Future of Infrastructure" imagines converging approaches from materials science, robotics, computer science, civil engineering, architectural engineering, and mechanical engineering to enable the development of new building materials and automated construction systems. These new materials could exhibit properties such as self-repairing, self-healing, recycling and repurposing, in order to be able to respond to localized environmental conditions, meet globalized low-carbon demands, and interface with intelligent robotic construction. Fully automate construction systems would be self-sensing, self-localized, and self-powering, in order to operate at hazardous construction sites. Ultimately, the winning contestants envision development of next-generation infrastructure materials and construction systems that could lead to better infrastructure on Earth and in distant planets in the future.
To further develop the themes that emerged from the top group of Idea Machine entries, NSF issued a Dear Colleague Letter to invite proposal submissions for conferences and EArly-concept Grants for Exploratory Research (EAGER).
NSF INCLUDES
An enabling Big Idea
The NSF INCLUDES Big Idea focused on transforming STEM education and career pathways at the national scale, making them more fully and widely inclusive.
NSF INCLUDES, renamed in the "CHIPS and Science Act of 2022" as the NSF Eddie Bernice Johnson INCLUDES Initiative, continues to advance efforts that broaden participation in STEM at scale by providing research, sustainable activities and infrastructure for collaborative systems change.
Visit the links below to learn more.
Quantum Leap
A research Big Idea
The Quantum Leap Big Idea focused on exploiting quantum mechanics to observe, manipulate and control the behavior of particles and energy at atomic and subatomic scales, resulting in next-generation technologies for sensing, computing, modeling and communicating.
NSF's investments in quantum information science continue across many programs. Visit the links below to learn more.
Understanding the Rules of Life
A research Big Idea
The universally recognized biggest gap in biological knowledge is researchers' inability to predict an organism's observable characteristics — its phenotype — from what is known about its genetics and environment. Many factors influence the traits in an organism, making this prediction extremely complex.
The Understanding the Rules of Life Big Idea focused on:
- Elucidating the set of rules that predict organisms' phenotypes.
- Developing research tools and infrastructure to further this research.
- Training the next generation of researchers to elucidate the rules of life.
- Fostering collaboration and convergent research to address key questions in the life sciences.
NSF's investments in this area continue through a number of programs. Visit the links below to learn more.
Windows on the Universe
A research Big Idea
For decades, researchers have been making observations across the known electromagnetic spectrum — from radio waves to gamma rays — to explore the universe.
The Windows on the Universe Big Idea focused on using powerful new techniques to observe cosmic waves, gravitational waves and particles like neutrinos to expand humanity's insights into the nature and behavior of matter and energy.
NSF's investments in this area continue through a number of programs. Visit the links below to learn more.