Emulation of artificial intuition using random choice and logic

Srdanov, Aleksa; Kovacevic, Nada Ratkovic; Vasić, Selena; Мilоvаnоvić, Drаgаn

doi:10.1109/neurel.2016.7800114

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…At the core of algorithms is decidability and thus indecisiveness is ruled out. This is going to be changed very soon (see [9] ), and indecisiveness will be given its real value.…”

Section: Indecisivenessmentioning

confidence: 99%

An Indecisiveness in Problems of Machine Learning and Artificial Intelligence

Srdanov¹

2020

J Autonom Intell

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The problem of indecisiveness is integral part in each scientific research. However, it is still not a certainty whether this problem has an objective nature. In this paper we will extend the analysis of the sources and causes of indecisiveness and define the new categories that are a stumbling block in writing high quality software. Based on a sample, we will propose several ways to classify indecisiveness. Specifically, we will investigate indecisiveness related to a human, machine and environment. In some cases, it is possible to distinguish between remediable and unavoidable indecisiveness depending on the cause.

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“…At the core of algorithms is decidability and thus indecisiveness is ruled out. This is going to be changed very soon (see [9] ), and indecisiveness will be given its real value.…”

Section: Indecisivenessmentioning

confidence: 99%

An Indecisiveness in Problems of Machine Learning and Artificial Intelligence

Srdanov¹

2020

J Autonom Intell

View full text Add to dashboard Cite

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Towards a Computational Model of Artificial Intuition and Decision Making

Johnny

Trovati

Ray

2019

Advances in Intelligent Networking and Collaborative Systems

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Artificial Intuition in Tech Journalism on AI: Imagining the Human Subject

Johanssen

Wang

2021

HMC

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Artificial intuition (AI acting intuitively) is one trend in artificial intelligence. This article analyzes how it is discussed by technology journalism on the internet. The journalistic narratives that were analyzed claim that intuition can make AI more efficient, autonomous, and human. Some commentators also write that intuitive AI could execute tasks better than humans themselves ever could (e.g., in digital games); therefore, it could ultimately surpass human intuition. Such views do not pay enough attention to biases as well as transparency and explainability of AI. We contrast the journalistic narratives with philosophical understandings of intuition and a psychoanalytic view of the human. Those perspectives allow for a more complex view that goes beyond the focus on rationality and computational perspectives of tech journalism.

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Emulation of artificial intuition using random choice and logic

Cited by 3 publications

References 5 publications

An Indecisiveness in Problems of Machine Learning and Artificial Intelligence

An Indecisiveness in Problems of Machine Learning and Artificial Intelligence

Towards a Computational Model of Artificial Intuition and Decision Making

Artificial Intuition in Tech Journalism on AI: Imagining the Human Subject

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