Artificial General Intelligence: Concept, State of the Art, and Future Prospects

By Ben Goertzel. Journal of Artificial General Intelligence, 2009

464 citations recorded by the source corpus.

Abstract In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/5c41252db73e543bc6a4935e5743f6a85055d191

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Citations in the corpus

Artificial Intelligence and Marketing: Pitfalls and Opportunities (2020, background): “…if one used the term “ artificial intelligence ” only when referring to “ artificial general intelligence ” (AGI), that is, the intelligence of a machine that can understand or learn any intellectual task that a human being can (Goertzel, 2015; Thórisson, Bieger, Schiffel, & Garrett, 2015).”
The alignment problem from a deep learning perspective (2022, background): “The rapid pace of these advances highlights the possibility that, within the coming decades, we may develop artificial general intelligence (AGI)—that is, AI which can apply domain-general cognitive skills (such as reasoning, memory, and planning) to perform at or above human level on a wide range o”
Towards artificial general intelligence via a multimodal foundation model (2021, background): “Despite not being precisely defined, AGI is broadly agreed to have several key features [1] including: (1) matching or exceeding human performance across a broad class of cognitive tasks (e.”
On Defining Artificial Intelligence (2019, background): “However, many AGI researchers share the belief that general-purpose systems and special-purpose systems have certain fundamental differences that are qualitative, not quantitative (Wang and Goertzel, 2007; Goertzel, 2014).”
Trustworthy artificial intelligence (2020, background): “artificial general intelligence, once it becomes a reality, behaves in a non-harmful a way (Goertzel 2014).”
Is ChatGPT a General-Purpose Natural Language Processing Task Solver? (2023, background): “The ability to perform new tasks based on instructions can be seen as an important step towards artificial general intelligence (Goertzel, 2014).”
A Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy (2017, methodology): “There have been several prior surveys of R&D on AGI and related technologies (Chong et al. 2007; Duch et al. 2008; Langley et al. 2008; de Garis et al. 2010; Goertzel et al. 2010; Samsonovich 2010; Taatgen and Anderson 2010; Thórisson and Helgasson 2012; Dong and Franklin 2014; Goertzel 2014; Kotser”
Position: Levels of AGI for Operationalizing Progress on the Path to AGI (2023, unknown): “Legg (Legg, 2008) and Goertzel (Goertzel, 2014) popularized the term AGI among computer scientists in 2001 (Legg, 2022), describing AGI as a machine that is able to do the cognitive tasks that people can typically do.”