Название: Handbook of Research on Artificial Intelligence, Innovation and Entrepreneurship
Автор: Elias G. Carayannis, Evangelos Grigoroudis
Издательство: Edward Elgar Publishing
Серия: Research Handbooks in Business and Management series
Год: 2023
Страниц: 474
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The Handbook of Research on Artificial Intelligence, Innovation and Entrepreneurship focuses on theories, policies, practices, and politics of technology innovation and entrepreneurship based on Artificial Intelligence (AI). It examines when, where, how, and why AI triggers, catalyzes, and accelerates the development, exploration, exploitation, and invention feeding into entrepreneurial actions that result in innovation success.

Individual chapters explore the factors that shape and drive innovation and entrepreneurship, including modalities (such as the Internet of Things (IoT)), challenges (such as privacy and safety concerns), and opportunities (such as augmenting the efficacy frontier of technological solutions enabled by AI).

Today we experience the era of Deep Learning. Deep Learning involves the use of artificial neural networks (ANNs) to perform multilevel learning. It is part of machine learning processes based on how the data is presented using highly sophisticated algorithms. Deep Learning is leading a revolution in analytics and enabling practical applications of Artificial Intelligence (AI). This Handbook provides comprehensive coverage of AI, technology, and innovation and entrepreneurship for academics, policy makers, practitioners, and students.

Artificial Intelligence refers to machine intelligence and describes the ability of a machine to replicate the cognitive functions of a human. It is the ability to learn and solve problems. In Computer Science, these machines are aptly called “smart agents” or bots. Still, not all AI terms are the same. Artificial Intelligence has enhanced the way we deal with several aspects of decision-making processes.

Blockchain technology has been one of the main technological advancements of Computer Science in recent years. It has successfully been used to substantially change how information systems are built in domains where multiple nodes need to interact with each other in non-trusted environments. Distributed ledger technology has been one of the hottest sub-domains of computer security during the last years. It offers an alternative approach to the traditional client-server model, that has served the explosion of the internet and digital systems during the last decades. The client-server model has evident shortcomings, such as privacy concerns, single points of failure, and requires highly powerful nodes that control everything, including data integrity. In contrast, blockchain technology enables decentralized systems, where such powerful nodes do not exist and all nodes are equal. The cryptographic protocols ensure the integrity of the data stored on such systems along with the integrity of the processes of the systems. Blockchain technology is mainly used when the preservation of data integrity is critical, but its guarantee does not come for free, as current implementations suffer in terms of performance, privacy, or ease of use.

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