Theories of Artificial Intelligence—Meta-Theoretical considerations

The paper has a review character, and the presented analysis is based on theoretical considerations referring to the works of other authors. The aim of the paper is to draw attention to the importance of human creativity in the context of technology development, with special emphasis on artificial intelligence. For the purpose of exploration, the study applies philosophical methods, especially methods typical of ethical reflections, also supported by the analysis of existing data derived from social sciences, especially contemporary sociology. The study is synthetic in nature and includes theoretical considerations concerning several issues. Positive and creative possibilities of using artificial intelligence in social and economic life were shown. Potential threats that may be associated with the inappropriate use of artificial intelligence – robots and information systems were also identified. Potential threats resulting from too much trust of people in algorithms were shown. Attention is focused on social and ethical aspects of the human-machine relationship, with special emphasis on the dimension of pragmatism, trust and fascination with new technologies, as well as the principles of robot ethics. A significant part of the considerations also refers to the effects of automation processes, including the functioning of the labour market, human creative abilities and appropriate competences. The third part of the study indicates still undeveloped research fields related to artificial intelligence. The conducted analysis may indicate the direction for further sociological and philosophical research that considers the specificity of the artificial intelligence functioning and seeks support in interdisciplinary research teams.

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An Aesthetics of Digital Virtual Environments

Advances in Social Networking and Online Communities - New Opportunities for Artistic Practice in Virtual Worlds ◽

10.4018/978-1-4666-8384-6.ch001 ◽

2015 ◽

pp. 1-22

Author(s):

Adam Nash

Keyword(s):

Artificial Intelligence ◽

Virtual Environments ◽

Virtual Environment ◽

Data Display ◽

Ontological Status ◽

Primary Qualities ◽

A Site ◽

Gilbert Simondon ◽

Theoretical Considerations ◽

Digital Sound

This chapter examines digital virtual environments as a site for art and proposes a formal aesthetics for art in digital virtual environments. The study arises from the author's decades-long practice producing art in virtual environments and the related theoretical considerations that have arisen from that practice. The technical, conceptual and ontological status of virtual environments is examined in order to establish a base of intrinsic qualities that identify virtual environments as a medium for art. The philosophy of Gilbert Simondon is used to achieve this. The elements and principles the artist must employ to work with this medium are identified as data, display and modulation. The specificities of virtual environments as a medium for art are examined in order to establish a formal aesthetics. In particular, digital colour, visual opacity, digital sound, code, artificial intelligence, emergence and agency are identified as the primary qualities that the artist manipulates to bring forth art in a virtual environment.

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Screen-Camera-Cars

Film Studies ◽

10.7227/fs.21.0005 ◽

2019 ◽

Vol 21 (1) ◽

pp. 53-64

Author(s):

Sonia Campanini

Keyword(s):

Artificial Intelligence ◽

Science Fiction ◽

The Self ◽

Human Interactions ◽

Cinematic Narratives ◽

Science Fiction Films ◽

Self Driving Cars ◽

Machine Interaction ◽

Theoretical Considerations ◽

Minority Report

Self-driving cars have long been depicted in cinematic narratives, across genres from science fiction films to fantasy films. In some cases, a self-driving car is personified as one of the main characters. This article examines cinematic representations and imaginaries in order to understand the development of the self-driving technology and its integration in contemporary societies, drawing on examples such as The Love Bug, Knight Rider, Minority Report and I, Robot. Conceptually and methodologically, the article combines close readings of films with technological concerns and theoretical considerations, in an attempt to grasp the entanglement of cinematographic imaginaries, audiovisual technologies, artificial intelligence and human interactions that characterise the introduction of self-driving cars in contemporary societies. The human–AI machine interaction is considered both on technological and theoretical levels. Issues of automation, agency and disengagement are traced in cinematic representations and tackled, calling into question the concepts of socio-technical assemblage.

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An Aesthetics of Digital Virtual Environments

Mobile Computing and Wireless Networks ◽

10.4018/978-1-4666-8751-6.ch007 ◽

2016 ◽

pp. 128-149

Author(s):

Adam Nash

Keyword(s):

Artificial Intelligence ◽

Virtual Environments ◽

Virtual Environment ◽

Data Display ◽

Ontological Status ◽

Primary Qualities ◽

A Site ◽

Gilbert Simondon ◽

Theoretical Considerations ◽

Digital Sound

This chapter examines digital virtual environments as a site for art and proposes a formal aesthetics for art in digital virtual environments. The study arises from the author's decades-long practice producing art in virtual environments and the related theoretical considerations that have arisen from that practice. The technical, conceptual and ontological status of virtual environments is examined in order to establish a base of intrinsic qualities that identify virtual environments as a medium for art. The philosophy of Gilbert Simondon is used to achieve this. The elements and principles the artist must employ to work with this medium are identified as data, display and modulation. The specificities of virtual environments as a medium for art are examined in order to establish a formal aesthetics. In particular, digital colour, visual opacity, digital sound, code, artificial intelligence, emergence and agency are identified as the primary qualities that the artist manipulates to bring forth art in a virtual environment.

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Machine Knowledge: Information Studies and Artificial Intelligence in Dialogue

Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI ◽

10.29173/cais971 ◽

2018 ◽

Author(s):

Julia Bullard ◽

Muhammad Abdul-Mageed

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Data Science ◽

Knowledge Organization ◽

Information Studies ◽

Nous Examinons ◽

Theoretical Considerations

In this piece, we examine the parallels and contrasts between knowledge organization and data science with a focus on the subfields of AI and machine learning in particular. Our analysis aims to both highlight and aid making connections between information studies and artificial intelligence through the discussion of shared practical and theoretical considerations and concerns around simplification and transparency.Dans cet article, nous examinons les parallèles et les contrastes entre l'organisation des connaissances et la science des données en mettant l'accent sur les sous-domaines de l'IA et de l'apprentissage machine en particulier. Notre analyse vise à mettre en évidence et à aider à établir des liens entre les études sur l'information et l'intelligence artificielle par la discussion de considérations pratiques et théoriques partagées et de préoccupations concernant la simplification et la transparence.

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Effective Automatic Method Selection for Nonlinear Regression Modeling

International Journal of Neural Systems ◽

10.1142/s0129065721500209 ◽

2021 ◽

pp. 2150020

Author(s):

Jan Kalina ◽

Aleš Neoral ◽

Petra Vidnerová

Keyword(s):

Artificial Intelligence ◽

Nonlinear Regression ◽

Nonlinear Least Squares ◽

Regression Modeling ◽

Automatic Method ◽

Method Selection ◽

Selection For ◽

Theoretical Considerations ◽

Original Approach ◽

Selection Of

Metalearning, an important part of artificial intelligence, represents a promising approach for the task of automatic selection of appropriate methods or algorithms. This paper is interested in recommending a suitable estimator for nonlinear regression modeling, particularly in recommending either the standard nonlinear least squares estimator or one of such available alternative estimators, which is highly robust with respect to the presence of outliers in the data. The authors hold the opinion that theoretical considerations will never be able to formulate such recommendations for the nonlinear regression context. Instead, metalearning is explored here as an original approach suitable for this task. In this paper, four different approaches for automatic method selection for nonlinear regression are proposed and computations over a training database of 643 real publicly available datasets are performed. Particularly, while the metalearning results may be harmed by the imbalanced number of groups, an effective approach yields much improved results, performing a novel combination of supervised feature selection by random forest and oversampling by synthetic minority oversampling technique (SMOTE). As a by-product, the computations bring arguments in favor of the very recent nonlinear least weighted squares estimator, which turns out to outperform other (and much more renowned) estimators in a quite large percentage of datasets.

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