A Narrative Analysis of Artificial Intelligence, A Modern Approach

2021 ◽  
Vol 41 ◽  
pp. 7-29
Author(s):  
Jahyon Ku
Keyword(s):  
Artificial Intelligence ◽  
Narrative Analysis ◽  
Modern Approach

scholarly journals Erosión ética en el trato con la inteligencia artificial

2020 ◽  
pp. 43-58
Author(s):  
Desireé Torres Lozano
Keyword(s):  
Artificial Intelligence ◽  
San Francisco ◽  
Mirror Neurons ◽  
Machine Intelligence ◽  
Publishing Company ◽  
Frankfurt Am Main ◽  
Modern Approach ◽  
Oxford University ◽  
Computing Machinery ◽  
West Bohemia

ResumenEl presente artículo tiene como finalidad definir la IA y poner en discusión su injerencia social, así como las consecuencias éticas que esto conlleva, ya que la construcción del hombre contemporáneo debe tener en cuenta el trato con estos sistemas. Definiremos qué es la inteligencia, cómo es que se le ha llamado inteligencia a los procesos de las máquinas y podremos establecer un diálogo entre la influencia ética que conlleva el trato con las mismas. Palabras clave Inteligencia artificial; Ética; Sistemas; Tecnología; Hombre Referencias Aristóteles, De Anima, Madrid: Gredos, 2000. ___, Ética a Nicómaco, Madrid: Gredos, 2000. ___, Política, Madrid, Gredos, 2003. Aspe, V. Nuevos sentidos mimesis en la Poética de Aristóteles, en Tópicos, Revista de filosofía, México: Tópicos, 2005. Bellman, Richard, An Introduction To Artificial Intelligence, San Francisco: Boyd and Fraser Publishing Company, 1978. Büchner et al, Discovering Internet Marketing Intelligence through Web Log Mining, Antrin, Mine it, Newtownabbey: University of Ulster Shore Road, 1998. Corominas, Pascual, Diccionario Crítico Etimológico Castellano e Hispánico, Madrid, Gredos, 2002. Descartes, Meditaciones Metafísicas, Gredos, Madrid, 2000. Elaine Rich, Kevin Knight, Artificial Intelligence, New Delhi: McGraw-Hill, 1991. Bude, Gesellschaft der Angst, Hamburgo: Hamburger Edition HIS, 2014. Heidegger, Platon: Sophistes, Frankfurt: Vittorio Klostermann, 1992. ___, Über den Humanismus, Frankfurt: Vittorio Klostermann, 1949. ___, Was heisst denken?, Frankfurt Am Main: Vittorio Klostermann, 2002. Hickock, Gregory, The Myth of Mirror Neurons. The Real Neuroscience of communication and cognition, Nueva York: W. W. Norton & ­Company, 2014. J. Haugeland, Artificial Intelligence: The very idea, Cambridge: MIT Press, 1985. Kirk, G.S. y Raven, J. E., Los filósofos presocráticos, Madrid: Gredos, 1970. Kurzweil Raymond, The Age of Intelligent Machines, Cambridge: MIT Press, 1990. Mariarosaria Taddeo, Luciano Floridi, How AI can be a force for good, en Science, Vol. 361, Issue 6404, Oxford: Oxford University, 2018. Nils Johan Nilsson, Artificial Intelligence: A new synthesis, USA: Morgan Kaufmann, 1998. Platón, Cratilo, Madrid, Gredos, 2004. Poole David et al, Computational Intelligence, a Logical Approach, Oxford: Oxford University, 1998. Press, Gill, A Very Short History Of Artificial Intelligence (AI), USA: Forbes, 2016. Russell, Norvig, Artificial Intelligence, A Modern Approach, New Jersey, Pearson, 2010. Armstrong, S., & K. Sotala, ​How we​’re predicting AI​ or failing to,​ Beyond Artificial Intelligence, Machine Intelligence Research Institute, Pilsen: University of West Bohemia,2015. Turing Alan, MIND, Computing Machinery and Intelligence, Cambridge: A Quarterly Review of Psychology and Philosophy, 1950. Winston Patrick Henry, Artificial intelligence, USA: Addison Wesley, Publishing Company, 1992.

Artificial intelligence in personnel management: the development of APM model

2020 ◽  
Vol 33 (4) ◽  
pp. 377-388
Author(s):  
Kirk Chang
Keyword(s):  
Artificial Intelligence ◽  
Organizational Performance ◽  
Personnel Management ◽  
Narrative Analysis ◽  
Well Being ◽  
Content Type ◽  
Managerial Practices ◽  
Management Literature ◽  
Job Levels

Purpose Managers have mixed views of how artificial intelligence (AI) affects personnel management (PM). The purpose of this paper is to identify potential knowledge gap and bring new insights to the AI-personnel-management literature. Design/methodology/approach Both applicability and theoretical perspectives are adopted to critically discuss the constraint and opportunity of AI in PM. Tables and narrative analysis are used to clarify the role of AI in managerial practices. Findings Research findings have helped to develop a new model titled AI in Personnel Management (APM). The APM model unfolds itself in three levels, followed by potential outcome. The three levels comprise “organizational, managerial and individual job levels,” and the outcome comprises “organizational performance, employees’ well-being and staff turnover rate”. Research limitations/implications The APM model helps managers to understand the implication of AI in their workplace. With better understanding of AI’s implication, managers are more likely to develop appropriate AI-driven managerial policies, which in turn benefit employees and their organizations. The APM model acts as a reference guide, helping managers to evaluate the AI’s constraint and opportunity in their managerial practices. Originality/value The APM model is valuable and informative to the academic researchers, as it has first responded to Malik et al. (2019)’s call (re: the absence of AI and management literature), and, more importantly, it has advanced the knowledge of AI–management relationship, supporting scholars to further understand the role of AI in PM.

Artificial Intelligence: A Modern Approach

1995 ◽  
Vol 9 (2) ◽  
pp. 215-218 ◽  
Author(s):  
Antoni Ligeza
Keyword(s):  
Artificial Intelligence ◽  
Modern Approach

A modern approach to design and integrate conceptual methods in video games with artificial intelligence

2017 ◽  
Vol 4 (8) ◽  
pp. 9100-9106
Author(s):  
Tata A.S.K. Ishwarya ◽  
R.China Appala Naidu ◽  
K. Meghana ◽  
G. Prabhakar Reddy
Keyword(s):  
Artificial Intelligence ◽  
Video Games ◽  
Modern Approach

scholarly journals Artificial intelligence: A modern approach

1996 ◽  
Vol 82 (1-2) ◽  
pp. 369-380 ◽  
Author(s):  
Nils J. Nilsson
Keyword(s):  
Artificial Intelligence ◽  
Modern Approach

scholarly journals On the Task Approach in Artificial Intelligence and Cognitive Sciences

2020 ◽  
Vol 18 (2) ◽  
pp. 5-29
Author(s):  
Evgeny E. Vityaev ◽  
Sergey S. Goncharov ◽  
Dmitry I. Sviridenko
Keyword(s):  
Artificial Intelligence ◽  
Systems Theory ◽  
Cognitive Processes ◽  
Cognitive Functions ◽  
Cognitive Sciences ◽  
Modern Approach ◽  
Agent Based ◽  
Functional Systems ◽  
Purposeful Behavior ◽  
Satisfaction Of Needs

This work continues a series of publications on the task approach in artificial intelligence. As noted earlier, the agent-based approach described in the monograph by Stuart Russell and Pieter Norwig “Artificial Intelligence. The Modern Approach", may be more argumentatively presented within the framework of the task approach. This paper will show that not only the problems of the bases of mathematics and artificial intelligence, but also many cognitive functions performed by humans and analyzed in cognitive sciences, can also be described and studied within the framework of the task approach. In particular, this paper shows that the analogue of the concept of task in cognitive sciences is the concept of goal and that the Functional Systems Theory (FST), which describes purposeful behavior, can be presented as the brain's solution of tasks to achieve goals and satisfaction of needs. It gives the chance to compare directly the tasks of artificial intellect with natural cognitive processes and, thereby, to reveal the list of those tasks of "natural" intellect and schemes of their solution which can be successfully used for the solution of artificial intelligence tasks.

Sign in / Sign up

Export Citation Format

Share Document