Engineering:Weak AI
Weak artificial intelligence (weak AI) is artificial intelligence that implements a limited part of mind, or, as narrow AI,[1][2][3] is focused on one narrow task. In John Searle's terms it “would be useful for testing hypotheses about minds, but would not actually be minds”.[4]
It is contrasted with Strong AI, which is defined variously as:
- Artificial general intelligence: a machine with the ability to apply intelligence to any problem, rather than just one specific problem.
- Human-level intelligence: a machine with a similar intelligence to an average human being.
- Superintelligence: a machine with a vastly superior intelligence to the average human being.
- Artificial consciousness: a machine that has consciousness, sentience and mind.
Scholars like Antonio Lieto have argued that the current research on both AI and cognitive modelling are perfectly aligned with the weak-AI hypothesis (that should not be confused with the "general" vs "narrow" AI distinction) and that the popular assumption that cognitively inspired AI systems espouse the strong AI hypothesis is ill-posed and problematic since "artificial models of brain and mind can be used to understand mental phenomena without pretending that that they are the real phenomena that they are modelling" [5] (p. 85) (as, on the other hand, implied by the strong AI assumption).
Terminology
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“Weak AI” is sometimes called “narrow AI”, but the latter is usually interpreted as subfields within the former.[by whom?] Hypothesis testing about minds or part of minds are typically not part of narrow AI, but rather implementation of some superficial lookalike feature. Many currently existing systems that claim to use “artificial intelligence” are likely operating as a narrow AI focused on a specific problem, and are not weak AI in the traditional sense.
Siri, Cortana, and Google Assistant are all examples of narrow AI, but they are not good examples of a weak AI[citation needed][discuss], as they operate within a limited pre-defined range of functions. They do not implement parts of minds, they use natural language processing together with predefined rules. They are in particular not examples of strong AI as there are no genuine intelligence nor self-awareness. AI researcher Ben Goertzel, on his blog in 2010, stated Siri was "VERY narrow and brittle" evidenced by annoying results if you ask questions outside the limits of the application.[6]
Impact
Some commentators[who?] think weak AI could be dangerous because of this "brittleness" and fail in unpredictable ways. Weak AI could cause disruptions in the electric grid, damage nuclear power plants, cause global economic problems, and misdirect autonomous vehicles.[1]
See also
- Artificial intelligence
- A.I. Rising
- Deep learning
- Expert system
- History of artificial intelligence
- Intelligent personal assistant
- Machine learning
- Philosophy of artificial intelligence
- Strong artificial intelligence
- Hardware for artificial intelligence
- Synthetic intelligence
References
- ↑ 1.0 1.1 Dvorsky, George (April 1, 2013). "How Much Longer Before Our First AI Catastrophe?". https://gizmodo.com/how-much-longer-before-our-first-ai-catastrophe-464043243.
- ↑ Muehlhauser, Luke (October 18, 2013). "Ben Goertzel on AGI as a Field". https://intelligence.org/2013/10/18/ben-goertzel/.
- ↑ Chalfen, Mike (October 15, 2015). "The Challenges Of Building AI Apps". https://techcrunch.com/2015/10/15/machine-learning-its-the-hard-problems-that-are-valuable/.
- ↑ The Cambridge handbook of artificial intelligence. Frankish, Keith., Ramsey, William M., 1960-. Cambridge, UK. 12 June 2014. pp. 342. ISBN 978-0-521-87142-6. OCLC 865297798.
- ↑ Lieto, Antonio (2021). Cognitive Design for Artificial Minds. London, UK: Routledge, Taylor & Francis. ISBN 9781138207929.
- ↑ Goertzel, Ben (February 6, 2010). "Siri, the new iPhone "AI personal assistant": Some useful niche applications, not so much AI". http://multiverseaccordingtoben.blogspot.com/2010/02/siri-new-iphone-personal-assistant-some.html.
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