Classical definitions of Artificial Intelligence (AI) date back to the 1950s, all including the concept that AI can enable computers to accomplish intelligent tasks and activities, i.e., requiring human-level intelligence. Given the difficulties in defining human intelligence, a more operational definition refers to the abilities and capabilities AI aims to automatize: communication, in all forms and including all types of media (text, picture, audio); perception, which has attracted a considerable amount of attention with recent developments in new input/output devices (sensors, the Internet of Things); knowledge, making it storable, retrievable, and processable for a variety of applications; planning, as a backup for decision-making and responding (robotics, autonomous driving); and reasoning, simulating human thinking and learning processes. As all these are interconnected, so are the corresponding subfields of AI research: problem-solving, intelligent agents, natural language processing (NLP), speech recognition, computer vision, robotics, knowledge representation, and machine learning. Despite its ups and downs, the use of AI technologies and systems has become so widespread that discussions about their applications, performances, and impact are quotidian. As such, this chapter aims to discuss and explore why and how investing in AI and big data can be considerably beneficial for the tourism sector.

AI and Big Data in Tourism / Mich, Luisa. - ELETTRONICO. - (2022), pp. 3-15. [10.1007/978-3-030-88389-8_1]

AI and Big Data in Tourism

Mich, Luisa
2022-01-01

Abstract

Classical definitions of Artificial Intelligence (AI) date back to the 1950s, all including the concept that AI can enable computers to accomplish intelligent tasks and activities, i.e., requiring human-level intelligence. Given the difficulties in defining human intelligence, a more operational definition refers to the abilities and capabilities AI aims to automatize: communication, in all forms and including all types of media (text, picture, audio); perception, which has attracted a considerable amount of attention with recent developments in new input/output devices (sensors, the Internet of Things); knowledge, making it storable, retrievable, and processable for a variety of applications; planning, as a backup for decision-making and responding (robotics, autonomous driving); and reasoning, simulating human thinking and learning processes. As all these are interconnected, so are the corresponding subfields of AI research: problem-solving, intelligent agents, natural language processing (NLP), speech recognition, computer vision, robotics, knowledge representation, and machine learning. Despite its ups and downs, the use of AI technologies and systems has become so widespread that discussions about their applications, performances, and impact are quotidian. As such, this chapter aims to discuss and explore why and how investing in AI and big data can be considerably beneficial for the tourism sector.
2022
Applied Data Science in Tourism: Interdisciplinary Approaches, Methodologies, and Applications
Cham
Springer
978-3-030-88389-8
978-3-030-88388-1
Mich, Luisa
AI and Big Data in Tourism / Mich, Luisa. - ELETTRONICO. - (2022), pp. 3-15. [10.1007/978-3-030-88389-8_1]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/352984
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