CCC Quadrennial Papers
Every four years the Computing Research Association, through its subcommittees, publishes a series of white papers called Quadrennial Papers that explore areas and issues around computing research with potential to address national priorities. The white papers attempt to portray a comprehensive picture of the computing research field detailing potential research directions, challenges, and recommendations.
2024-2025 Quadrennial Papers
Setting a Course for Post-Moore Software Performance
Authors: William Gropp (University of Illinois Urbana-Champaign), Randal Burns (Johns Hopkins University), Brian LaMacchia (Farcaster Consulting Group), Charles E. Leiserson (MIT), and Michela Taufer (University of Tennessee, Knoxville)
With Moore’s Law having ended, the U.S. must pivot from relying on hardware improvements to investing heavily in software performance engineering (SPE) through research, education, and workforce development to maintain its technological edge, especially since few software engineers currently possess these critical skills.
The Post-Quantum Cryptography Transition: Making Progress, But Still a Long Road Ahead
Authors: Brian LaMacchia (Farcaster Consulting Group), Matt Campagna (Amazon Web Services), William Gropp (University of Illinois Urbana-Champaign)
The development of quantum computing threatens the security of our currently widely deployed cryptographic algorithms. While significant progress has been made in developing post-quantum cryptography (PQC) standards to protect against future quantum computing threats, the U.S. government’s estimated $7.1 billion transition cost for non-National Security Systems alone, coupled with an aggressive 2035 deadline, will require sustained funding, research, and international coordination to successfully upgrade existing cryptographic systems.
Lessons for Cybersecurity from the American Public Health System
Authors: Adam Shostack (University of Washington), L. Jean Camp (Indiana University), Yi Ting Chua (University of Tulsa), Josiah Dykstra (Trail of Bits), Brian LaMacchia (FARCASTER Consulting Group), Daniel Lopresti (Lehigh University)
The United States needs national institutions and frameworks to systematically collect cybersecurity data, measure outcomes, and coordinate responses across government and private sectors, similar to how public health systems track and address disease outbreaks.
Imperative for Educating the Next Generation Robotics Technology Workforce
Authors: Holly Yanco (University of Massachusetts Lowell), Odest Chadwicke Jenkins (University of Michigan), Weisong Shi (University of Delaware), William Regli (University of Maryland), and Monica Anderson Herzog (University of Alabama)
The United States must urgently develop comprehensive educational and career training pathways in robotics across all levels — from K-12 through professional development — to build a skilled workforce capable of leading technological innovation and maintaining the nation’s competitive edge in robotics and automation.
Prioritizing Computing Research to Empower and Protect Vulnerable Populations
Authors: Pamela Wisniewski (Vanderbilt University), Katie Siek (Indiana University Bloomington), Kevin Butler (University of Florida), Gabrielle Allen (University of Wyoming), Weisong Shi (University of Delaware), Manish Parashar (University of Utah)
Technology can pose significant risks to a wide array of vulnerable populations. However, by addressing the challenges and opportunities in technology design, research, and deployment, we can create systems that benefit everyone, fostering a society where even the most vulnerable are empowered and supported.
2020 Quadrennial Papers
Imagine All the People: Citizen Science, Artificial Intelligence, and Computational Research
Authors: Lea A. Shanley (University of Wisconsin-Madison; International Computer Science Institute, Berkeley, CA), Lucy Fortson (University of Minnesota), Tanya Berger-Wolf (The Ohio State University), Kevin Crowston (Syracuse University), Pietro Michelucci (Human Computation Institute)
Machine learning, artificial intelligence, and deep learning have advanced significantly over the past decade. Nonetheless, humans possess unique abilities such as creativity, intuition, context and abstraction, analytic problem solving, and detecting unusual events. To successfully tackle pressing scientific and societal challenges, we need the complementary capabilities of both humans and machines.
Taking Stock of the Present and Future of Smart Technologies for Older Adults and Caregivers
Authors: Christina N. Harrington (DePaul University), Ben Jelen (Indiana University), Amanda Lazar (University of Maryland), Aqueasha Martin-Hammond (Indiana University Purdue University – Indianapolis), Alisha Pradhan (University of Maryland), Blaine Reeder (University of Missouri), and Katie Siek (Indiana University)
Older adults should be involved in the design process of technology for them – from initial ideation to product development to deployment. This paper encourages federally funded researchers and industry to create compensated, diverse older adult advisory boards to address stereotypes about aging while ensuring their needs are considered.
Artificial Intelligence at the Edge
Authors: Sujata Banerjee (VMware Research) and Elisa Bertino (Purdue University)
Could AI better support societal needs if it were deployed at the edge of the network, close to application end-points, as opposed to in a centralized cloud? This white paper examines those potential uses and identifies requirements and areas of research that need to be explored before implementation of AI systems at the edge can be realized.
Artificial Intelligence and Cooperation
Authors: Elisa Bertino (Purdue University), Finale Doshi-Velez (Harvard University), Maria Gini (University of Minnesota), Daniel Lopresti (Lehigh University), and David Parkes (Harvard University)
This paper argues for further research in AI and human cooperation in order to understand the ways in which systems of AIs and people, working together, can engender cooperative behavior. Through a set of illustrative examples, a broad research agenda for this goal is laid out incorporating aspects of AI architectures, collaborative human-AI systems, economic viewpoints, and human preferences and control.
Interdisciplinary Approaches to Understanding Artificial Intelligence’s Impact on Society
Authors: Suresh Venkatasubramanian (University of Utah), Nadya Bliss (Arizona State University), Helen Nissenbaum (Cornell University), and Melanie Moses (University of New Mexico)
Among the convenience and opportunities that AI brings to the table, these systems also produce a multitude of problems including seemingly racial or gender-biased algorithms, infringements on citizens’ privacy or freedom or deepening inequalities among different groups. This paper calls for an interdisciplinary approach that incorporates the expertise from a broad set of disciplines and application domains to gain a deeper understanding of how technology and society interact in order to avoid these negative impacts from AI technologies.
The Rise of AI-Driven Simulators: Building a New Crystal Ball
Authors: Ian Foster (University of Chicago), David Parkes (Harvard University), and Stephan Zheng (Salesforce AI Research)
Simulations are now pervasive throughout human society and the economy, providing decision makers with a remarkable crystal ball—not just for next week’s weather but also for the spread of a disease through a population. This paper lays out the importance of AI-driven simulators, describing challenges, accomplishments, and a potential research agenda in order to realize the full potential of simulation predictions.
Next Wave Artificial Intelligence: Robust, Explainable, Adaptable, Ethical, and Accountable
Authors: Odest Chadwicke Jenkins (University of Michigan), Daniel Lopresti (Lehigh University), and Melanie Mitchell (Portland State University)
This paper describes the history and limitations of today’s AI systems, such as brittleness, weakness against adversarial attacks, and the difficulties of system training. It names a series of recommendations and focus areas for research necessary to catalyze this new wave of AI.
An Agenda for Disinformation Research
Authors: Nadya Bliss (Arizona State University), Elizabeth Bradley (University of Colorado, Boulder), Joshua Garland (Santa Fe Institute), Filippo Menczer (Indiana University), Scott W. Ruston (Arizona State University), Kate Starbird (University of Washington), and Chris Wiggins (Columbia University)
This paper describes a multi-disciplinary research agenda incorporating disinformation detection, education, measurements of impact, and a new common research infrastructure to combat disinformation and its effects upon the US and the world.
Modernizing Data Control: Making Personal Digital Data Mutually Beneficial for Citizens and Industry
Authors: Sujata Banerjee (VMware Research), Yiling Chen (Harvard University), Kobbi Nissim (Georgetown University), David Parkes (Harvard University), Katie Siek (Indiana University Bloomington), and Lauren Wilcox (Georgia Institute of Technology)
Via the Internet and IoT systems, there is an increasing amount of data being collected on individuals every day. This paper dives into the big questions related to this phenomenon, such as who owns the data, the implications for using, controlling, and quantifying the data, and, most importantly, how to best protect citizens’ privacy.
A National Research Agenda for Intelligent Infrastructure: 2021 Update
Authors: Daniel Lopresti (Lehigh University) and Shashi Shekhar (University of Minnesota)
In 2017, the CCC produced a series of intelligent infrastructure whitepapers, and in 2020 CCC issued a set of companion whitepapers on closely related topics. This paper briefly surveys those earlier works and then highlight four themes of rising national prominence where intelligent infrastructure can also play an enabling role, driven by experiences with the COVID-19 pandemic and the social justice movement.
Pandemic Informatics: Preparation, Robustness and Resilience *
Authors: Elizabeth Bradley (University of Colorado Boulder), Madhav Marathe (University of Virginia), Melanie Moses (University of New Mexico), William Gropp (University of Illinois at Urbana–Champaign), and Daniel Lopresti (Lehigh University)
In light of the recent pandemic, this paper outlines an effective strategy to reduce the impact of global pandemics stressing early detection, predicting the public’s reaction and developing effective policies. These aims require research and technological advancements in a number of areas, particularly in how informatics infrastructure can be used to assist in global outbreaks and better prepare for the next health crisis.
*The ever-changing dynamics of the pandemic and the continuing conversations of the Pandemic Informatics: Preparation, Robustness, and Resilience authors has spurred a monthly pandemic addendum series. “Each phase of the pandemic has had lessons to teach, and it seems prudent to do our best to document them as they arise so that we can learn from them.”
Infrastructure for Artificial Intelligence, Quantum and High Performance Computing
Authors: Sujata Banerjee (VMware Research), William Gropp (University of Illinois at Urbana–Champaign), and Ian Foster (University of Chicago)
This paper breaks down the barriers separating AI, Quantum, and High Performance Computing (HPC). It calls for combining resources to support these critical areas, and highlights synergies between them. The goal is to bridge current gaps between these three areas and use the infrastructure from one discipline to catalyze progress in another.
Robotics Enabling the Workforce
Authors: Henrik Christensen (UC San Diego), Maria Gini (University of Minnesota), Odest Chadwicke Jenkins (University of Michigan), and Holly Yanco (University of Massachusetts, Lowell)
This paper portrays how robotics can aid and leverage the workforce by increasing automation and providing new opportunities for workers. It outlines necessary investments in research, technology development, education, training and policy, but most critically, we need research to understand how future robot technologies can compliment our workforce to get the best of both human and automated labor.
A Research Ecosystem for Secure Computing
Authors: Nadya Bliss (Arizona State University), Lawrence A. Gordon (University of Maryland), Daniel Lopresti (Lehigh University), Suresh Venkatasubramanian (University of Utah), and Fred Schneider (Cornell University)
In today’s world tech developers are more focused on the capabilities of the technology rather than the security. This paper stresses the importance of prioritizing security in the design phase and identifies specific focus areas for research and funding that touch on transition and adoption, training/education, and incentive structures for better security.
Post Quantum Cryptography: Readiness Challenges and the Approaching Storm
Authors: Matt Campagna (Amazon), Brian LaMacchia (Microsoft Research), and David Ott (VMware Research)
Few people are aware that each advancement we make in quantum computing brings us closer to a complete breakdown of our digital security and privacy. As quantum-driven advancements in cryptographic analysis and computing technology are achieved, the cryptographic algorithms that protect our private online information and data is threatened. This paper identifies issues that need to be addressed before the quantum transition, particularly in identifying a replacement for current cryptography algorithms and ensuring a safe transition of uses.
Theoretical Computer Science: Foundations for an Algorithmic World
Authors: Shuchi Chawla (University of Wisconsin-Madison), Jelani Nelson (UC Berkeley), Chris Umans (California Institute of Technology), and David Woodruff (Carnegie Mellon University)
This paper presents the case for robust support of research and foundational work in Theoretical Computer Science (TCS), highlighting three major areas of current interest in the field. Work in this discipline benefits the entire field of computer science by offering insights to the possibilities and limitations of computation, identifying key issues in new areas and discerning computation and algorithms in settings beyond computer science.
Computing Research Challenges in Next Generation Wireless Networking
Authors: Elisa Bertino (Purdue University), Daniel Bliss (Arizona State University), Daniel Lopresti (Lehigh University), Larry Peterson (Princeton University), and Henning Schulzrinne (Columbia University)
Wireless networking has seen explosive growth over the past decade and continues to evolve rapidly. Cellular technology is now progressing from 4G and its potential for broadband speeds to mobile devices, to 5G which will further enhance transmission speeds, cell capacity, and latency through the use of different radio technologies. 6G is already envisioned to employ virtualization across all layers and the pervasive deployment of AI. On the hardware side, new classes of highly flexible application specific processors (ASICs) are being developed, driving further progress. In addition, deep programmability will open up enormous opportunities to manage the complexity and harness the power of the new network infrastructure. This paper explores these key technologies and outlines a research agenda to make them a reality.
Advancing Computing’s Foundation of US Industry & Society
Authors: Thomas Conte (Georgia Institute of Technology), Ian Foster (University of Chicago), William Gropp (University of Illinois at Urbana–Champaign), and Mark Hill (University of Wisconsin-Madison)
As the 55-year reign of Moore’s Law comes to an end, new computing techniques will be required in order to continue the improvement of computer speed and performance. This paper outlines a number of techniques that will lead to advancements in the computing field and benefits society as a whole.
