Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status

Frank Emmert-Streib; Olli Yli-Harja; Matthias Dehmer

doi:10.3389/frai.2020.524339

Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status

Frank Emmert-Streib^*
, Olli Yli-Harja
, Matthias Dehmer

^*Corresponding author for this work

Tampere University
Institute of Biosciences and Medical Technology
Institute for Systems Biology
Private University for Health Sciences, Medical Informatics and Technology
Swiss Distance University of Applied Sciences
Nankai University

Research output: Contribution to journal › Article › peer-review

58 Citations (Scopus)

Abstract

The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the “intelligence” nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.

Original language	English
Article number	524339
Journal	Frontiers in Artificial Intelligence
Volume	3
DOIs	https://doi.org/10.3389/frai.2020.524339
Publication status	Published - 23 Dec 2020
Externally published	Yes

Keywords

artificial general intelligence
artificial intelligence
data mining
data science
deep neural networks
machine learning
pattern recognition
statistics

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10.3389/frai.2020.524339

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AB - The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the “intelligence” nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.

KW - artificial general intelligence

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KW - data mining

KW - data science

KW - deep neural networks

KW - machine learning

KW - pattern recognition

KW - statistics

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JO - Frontiers in Artificial Intelligence

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M1 - 524339

ER -

Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status

Abstract

Keywords

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