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Weak artificial intelligence (weak AI) is artificial intelligence that implements a limited part of the mind, or, as narrow AI,[1][2][3] is focused on one narrow task.

Weak AI is contrasted with strong AI, which can be interpreted in various ways:

Narrow AI can be classified as being "limited to a single, narrowly defined task. Most modern AI systems would be classified in this category."[4] Artificial general intelligence is conversely the opposite.

Applications and risks

Some examples of narrow AI are AlphaGo,[5] self-driving cars, robot systems used in the medical field, and diagnostic doctors. Narrow AI systems are sometimes dangerous if unreliable. And the behavior that it follows can become inconsistent.[6] It could be difficult for the AI to grasp complex patterns and get to a solution that works reliably in various environments. This "brittleness" can cause it to fail in unpredictable ways.[7]

Narrow AI failures can sometimes have significant consequences. It could for example cause disruptions in the electric grid, damage nuclear power plants, cause global economic problems, and misdirect autonomous vehicles.[1] Medicines could be incorrectly sorted and distributed. Also, medical diagnoses can ultimately have serious and sometimes deadly consequences if the AI is faulty or biased.[8]

Simple AI programs have already worked their way into our society unnoticed. Autocorrection for typing, speech recognition for speech-to-text programs, and vast expansions in the data science fields are examples.[9] As much as narrow and relatively general AI is slowly starting to help out societies, they are also starting to hurt them as well. AI had already unfairly put people in jail, discriminated against women in the workplace for hiring, taught some problematic ideas to millions, and even killed people with automatic cars.[10] AI might be a powerful tool that can be used for improving lives, but it could also be a dangerous technology with the potential for misuse.

Despite being "narrow" AI, recommender systems are efficient at predicting user reactions based their posts, patterns, or trends.[11] For instance, TikTok's "For You" algorithm can determine user's interests or preferences in less than an hour.[12] Some other social media AI systems are used to detect bots that may be involved in biased propaganda or other potentially malicious activities.[13]

Weak AI versus strong AI

John Searle contests the possibility of strong AI (by which he means conscious AI). He further believes that the Turing test (created by Alan Turing and originally called the "imitation game", used to assess whether a machine can converse indistinguishably from a human) is not accurate or appropriate for testing whether an AI is "strong".[14]

Scholars such as 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"[15] (as, on the other hand, implied by the strong AI assumption).

See also

References

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