Advances in Artificial Intelligence Require Progress Across all of Computer Science
Authors: Gregory D. Hager, Randal Bryant, Eric Horvitz, Maja Mataric, Vasant Honavar
Abstract
Advances in Artificial Intelligence require progress across all of computer science.
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Papers around this one
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Closest papers
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Advances in Artificial IntelligenceAtefeh Farzindar, Vlado Keselj · 2010 · Lecture Notes in Computer Science · Not summarized yet
Advances in Artificial Intelligence is a broad AI topic, matching the paper’s general focus on progress in AI and computer science.
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Advances in Artificial IntelligenceOsmar R Zaiane, Sandra Zilles · 2012 · Lecture Notes in Computer Science · cited 37 times · Not summarized yet
Advances in Artificial Intelligence is a broad AI topic, matching the paper’s general focus on progress in AI and computer science.
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Advances in computational intelligenceM. Atencia, G. Joya, F. García-Lagos · 2019 · Neural computing & applications (Print) · cited 1 time · Not summarized yet
Advances in computational intelligence concerns advances in an AI-related area, while the paper calls for progress across computer science.
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Advances in Computing and Intelligent SystemsO. Hassan, Hazwani Hamdani, H. Hashim et al. · 2020 · Algorithms for Intelligent Systems · cited 9 times · Not summarized yet
Advances in Computing and Intelligent Systems spans computing and AI-related systems, matching the paper’s cross-computer-science focus.
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Ten Hard Problems in Artificial Intelligence We Must Get RightGavin Leech, Simson Garfinkel, Misha Yagudin et al. · 2024 · Artificial Intelligence · preprint, not peer reviewed · cited 5 times · AI summary available
Ten Hard Problems in Artificial Intelligence We Must Get Right identifies challenges in AI capabilities, assurance, applications, and governance.
Abstract
We explore the AI2050 "hard problems" that block the promise of AI and cause AI risks: (1) developing general capabilities of the systems; (2) assuring the performance of AI systems and their training processes; (3) aligning system goals with human goals; (4) enabling great applications of AI in real life; (5) addressing economic disruptions; (6) ensuring the participation of all; (7) at the same time ensuring socially responsible deployment; (8) addressing any geopolitical disruptions that AI causes; (9) promoting sound governance of the technology; and (10) managing the philosophical disruptions for humans living in the age of AI. For each problem, we outline the area, identify significant…
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Introduction to the Special Issue on Emerging Artificial Intelligence Technologies and ApplicationsWen-Feng Zheng, Chao Liu, L. Yin · 2025 · Computer Modeling in Engineering & Sciences · Not summarized yet
Introduction to the Special Issue on Emerging Artificial Intelligence Technologies and Applications surveys recent AI advances and applications.
Abstract
Artificial intelligence (AI) has evolved at an unprecedented pace in recent years. This rapid advancement includes algorithmic breakthroughs, cross-disciplinary integration
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From AGI to ASITim Genewein, Matija Franklin, Alexander Lerchner et al. · 2026 · Artificial Intelligence · preprint, not peer reviewed · cited 9 times · AI summary available
From AGI to ASI examines the future development of machine intelligence, whereas the paper calls for progress across computer science.
Abstract
Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI organisations. Achieving this goal would have profound and far-reaching impacts on human society, which raises many complex questions for the decade ahead. This report investigates how AI itself might continue to develop in a post-AGI world along the continuum of machine intelligence. The endpoint of this continuum, Universal AI, is theoretically well understood, which provides some formal grounding for the main focus of this report: the transition from human-level AGI to artificial general superintelligence, which…
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Progress in machine intelligenceDavid Sanders · 2008 · Industrial Robot-an International Journal · cited 40 times · Not summarized yet
Progress in machine intelligence shares the focus on advances in intelligent systems, though its title gives no further detail.
Papers that cite it
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A detailed survey of Artificial Intelligence and Spftware Engineering: Emergent IssuesZainab Alkashri, Nur Siyam, Omar Alqaryouti · 2020 · International Conference on Information Security and Cryptology · cited 7 times · Not summarized yet
A detailed survey of Artificial Intelligence and Software Engineering discusses AI advances and software-engineering issues, and cites the paper.
Abstract
Recently, Artificial Intelligence (AI) has become a trend and part of our typical mainstream albeit its existence ages ago. AI is at the top of the list of trending technologies and one of the hottest topics. In the coming decades, the world is going in the direction of increasing automation and cognitive technologies. This study attempts to explore and discuss the tipping points and evolution of AI. Further, it envisions the future impact that the advances of AI would have on occupations in various sectors such as technological unemployment. The study also tackles on the ethical and policy concerns involved in this upcoming AI evolution. Organizations should be able to manage both humans an…
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A Review on New Challenges in AI and Software EngineeringI. V. Dwaraka Srihith, R. Varaprasad, Y. Mohan et al. · 2022 · International Journal of Advanced Research in Science, Communication and Technology · cited 3 times · Not summarized yet
A Review on New Challenges in AI and Software Engineering discusses AI development issues and cites the paper.
Abstract
Artificial Intelligence (AI) has been around for a long time, but it's only recently become a mainstream concern. When it comes to cutting-edge research and development, At the moment, AI is at the top of the list. Over the next few decades, we will see a rise in the use of automated and cognitive technology. To be sure, this will occur. This study and related discourse focuses on identifying and discussing potential AI development inflection points. It also considers issues like technological unemployment, which could arise as a result of AI development in the future and affect job prospects in a wide range of industries. This paper also looks at the ethical and policy issues that might com…
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New Trends in Second Language Learning and Teaching through the lens of ICT, Networked Learning, and Artificial IntelligenceJaya Kannan, P. Munday · 2018 · CIRCULO de linguistica aplicada a la comunicacion · cited 101 times · Not summarized yet
New Trends in Second Language Learning and Teaching through the lens of ICT, Networked Learning, and Artificial Intelligence studies AI among technologies for language learning.
Abstract
In the last few decades, Information and Communications Technology (ICT) applications have been shaping the field of Computer Assisted Language Learning (CALL). Mobile Assisted Language Learning (MALL) paved the way for ubiquitous learning. The advent of new technologies in the early 21st century also added a social dimension to ICT that allowed for Networked Learning (NL). Given that language learning is fundamentally a socio-cultural experience, networked learning capabilities have provided the potential for language learning in community settings. This has revitalized the earlier frameworks provided by CALL. NL has empowered language learners today to connect globally, to access Open Educ…
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The Increasing Risks of Risk Assessment: On the Rise of Artificial Intelligence and Non-Determinism in Safety-Critical SystemsChris W. Johnson · 2018 · Evolution of System Safety · cited 23 times · Not summarized yet
The Increasing Risks of Risk Assessment examines how AI in autonomous safety-critical systems challenges traditional risk assessment.
Abstract
Risk assessment plays a key role in Safety Management Systems. For more than forty years, likelihood and consequence have been used to guide the allocation of finite resources. Standards, such as IEC61508 and the DO-178 series, extended these concepts to support the development of software related systems. Human reliability analysis developed risk assessment techniques to represent and reason about operator ‘error’ and management failure. However, new challenges raise questions about the utility of traditional approaches to the development of safety-critical systems. The introduction of artificial intelligence within autonomous systems makes it hard to reason about the probability and conseq…
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Explainability is not Enough : Requirements for Human-AI-Partnership in Complex Socio-Technical SystemsT. Waefler, Ute Schmid · 2020 · cited 17 times · Not summarized yet
Explainability is not Enough : Requirements for Human-AI-Partnership in Complex Socio-Technical Systems focuses on human-AI partnership requirements in complex systems.
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Updated on 5 November 2026.