[Paper Review] The Imperative for Grand Challenges in Computing
The paper argues that computing must define and pursue grand challenges of its own, offering a framework to identify, scale, and translate these challenges to science and society and calling the community to action.
Computing is an indispensable component of nearly all technologies and is ubiquitous for vast segments of society. It is also essential to discoveries and innovations in most disciplines. However, while past grand challenges in science have involved computing as one of the tools to address the challenge, these challenges have not been principally about computing. Why has the computing community not yet produced challenges at the scale of grandeur that we see in disciplines such as physics, astronomy, or engineering? How might we go about identifying similarly grand challenges? What are the grand challenges of computing that transcend our discipline's traditional boundaries and have the potential to dramatically improve our understanding of the world and positively shape the future of our society? There is a significant benefit in us, as a field, taking a more intentional approach to "grand challenges." We are seeking challenge problems that are sufficiently compelling as to both ignite the imagination of computer scientists and draw researchers from other disciplines to computational challenges. This paper emphasizes the importance, now more than ever, of defining and pursuing grand challenges in computing as a field, and being intentional about translation and realizing its impacts on science and society. Building on lessons from prior grand challenges, the paper explores the nature of a grand challenge today emphasizing both scale and impact, and how the community may tackle such a grand challenge, given a rapidly changing innovation ecosystem in computing. The paper concludes with a call to action for our community to come together to define grand challenges in computing for the next decade and beyond.
Motivation & Objective
- Motivate the need for grand challenges in computing as a proactive research direction.
- Explore why computing has not yet produced grand challenges at the scale of physics or astronomy.
- Propose a framework for identifying grand challenges that cross disciplinary boundaries and have societal impact.
- Emphasize translation and real-world impact as core components of grand challenges in computing.
- Issue a call to action for the community to define and pursue grand challenges for the next decade and beyond.
Proposed method
- Analyze historical lessons from past grand challenges in science and computing.
- Characterize the attributes of a grand challenge today, focusing on scale and impact.
- Discuss strategies for cross-disciplinary engagement and collaboration.
- Outline approaches to translation and realization of impacts on science and society.
- Provide a roadmap for how the computing community can identify and pursue future grand challenges.
Experimental results
Research questions
- RQ1What would constitute a grand challenge in computing today?
- RQ2Why have past grand challenges not been principally about computing, and how can this be changed?
- RQ3How can the computing community identify grand challenges that transcend traditional boundaries?
- RQ4What mechanisms are needed to translate computational advances into science and societal impact?
- RQ5What steps should the community take to define and pursue grand challenges over the next decade?
Key findings
- Grand challenges in computing are needed to ignite imagination and attract researchers from other disciplines.
- Grand challenges should be defined with both scale and impact in mind.
- Translation and realization of impacts on science and society require intentional strategies.
- The paper provides a framework for identifying and tackling grand challenges within a rapidly evolving innovation ecosystem.
- There is a call to action for the community to collaboratively define and pursue future grand challenges in computing.
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This review was created by AI and reviewed by human editors.