Abstract
Artificial intelligence allows to think and act humanely and rationally through hardware systems and software programs capable of providing performances that, to an ordinary observer, would seem to be the exclusive domain of natural (human) intelligence. The applications are more and more extensive, thanks also to the big data available today and the ability of self-learning (machine learning) or instead to the synergies with the natural intelligence, which for vision and flexibility remains irreplaceable. The examination of the business models of the companies that base their strategies on artificial intelligence or, more extensively, of the traditional companies using specific applications is preliminary to a framework of the legal problems (still pioneering) and of the profiles of economic evaluation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Selected References
Anzai, Y. (2012). Pattern recognition and machine learning. Amsterdam: Elsevier.
Ertel, W. (2018). Introduction to artificial intelligence. London: Springer.
Li, D., & Du, Y. (2017). Artificial intelligence with uncertainty. London: CRC Press.
Mariusz, F. (2016). Introduction to artificial intelligence. Cham: Springer.
Müller, V. C., & Bostrom, N. (2016). Future progress in artificial intelligence: A survey of expert opinion. In V. Müller (Eds.), Fundamental issues of artificial intelligence. Synthese Library (Studies in epistemology, logic, methodology, and philosophy of science, Vol. 376). Cham: Springer.
Nilsson, N. J. (1980). Principles of artificial intelligence. San Francisco: Morgan Kaufmann Publishers, Inc.
Parag, K., & Prachi, J. (2015). Artificial intelligence: Building intelligent systems. Delhi: PHI Learning.
Pedersen, M. (2016). Artificial intelligence for long-term investing. Available at SSRN: https://ssrn.com/abstract=2740218 or http://dx.doi.org/10.2139/ssrn.2740218.
Russel, S., & Norvig, P. (2016). Artificial intelligence: A modern approach. Pearson: Upper Saddle River.
Short, T., & Adams, T. (2017). Procedural generation in game design. New York: CRC Press.
Skansi, S. (2018). Introduction to deep learning: From logical calculus to artificial intelligence. Cham: Springer.
Stein, S. S. (2020). In Blockchain, artificial intelligence and financial services. Future of Business and Finance. Cham: Springer.
Stuart, R., & Norvig, P. (2016). Artificial intelligence: A modern approach (Global edition). Harlow: Pearson.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 The Author(s)
About this chapter
Cite this chapter
Moro Visconti, R. (2020). The Valuation of Artificial Intelligence. In: The Valuation of Digital Intangibles. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-36918-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-36918-7_8
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-030-36917-0
Online ISBN: 978-3-030-36918-7
eBook Packages: Economics and FinanceEconomics and Finance (R0)