Managing and Adapting Library Information Services for Future Users

2021 ◽  
pp. 644-659
Author(s):  
Monicah Jemeli Chemulwo ◽  
Emily Chepkirui Sirorei
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Information Retrieval ◽  
Computer Science ◽  
Information Literacy ◽  
Information Services ◽  
Library Services ◽  
Human Interactions ◽  
Reference Information ◽  
Novel Technology

The advance of artificial intelligence (AI) as a field of computer science that can impact and improve all sciences and human interactions is changing the information sector. AI is reconfiguring many library tasks such as classification, indexing, cataloguing, information retrieval, reference, information literacy, and even learning. It is the greatest usable intelligence that has the capacity of assisting librarians in decision making and administration. AI can also be employed in various areas such as speech recognition, machine transformation, and librarian robots. The very disruptive nature of any novel technology can be perceived as a risk to many organizations, including libraries. However, the ultimate acceptance and integration of artificial intelligence into library services is indeed possible and beneficial.

Managing and Adapting Library Information Services for Future Users

2020 ◽  
pp. 145-164
Author(s):  
Monicah Jemeli Chemulwo ◽  
Emily Chepkirui Sirorei
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Information Retrieval ◽  
Computer Science ◽  
Information Literacy ◽  
Information Services ◽  
Library Services ◽  
Human Interactions ◽  
Reference Information ◽  
Novel Technology

The advance of artificial intelligence (AI) as a field of computer science that can impact and improve all sciences and human interactions is changing the information sector. AI is reconfiguring many library tasks such as classification, indexing, cataloguing, information retrieval, reference, information literacy, and even learning. It is the greatest usable intelligence that has the capacity of assisting librarians in decision making and administration. AI can also be employed in various areas such as speech recognition, machine transformation, and librarian robots. The very disruptive nature of any novel technology can be perceived as a risk to many organizations, including libraries. However, the ultimate acceptance and integration of artificial intelligence into library services is indeed possible and beneficial.

Quantum-Computing-Inspired Algorithms in Machine Learning

2018 ◽  
pp. 1-26
Author(s):  
Deeksha Kaul ◽  
Harika Raju ◽  
B. K. Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Quantum Computing ◽  
Computer Science ◽  
Real Time ◽  
Learning Algorithms ◽  
Machine Learning Algorithms

In this chapter, the authors discuss the use of quantum computing concepts to optimize the decision-making capability of classical machine learning algorithms. Machine learning, a subfield of artificial intelligence, implements various techniques to train a computer to learn and adapt to various real-time tasks. With the volume of data exponentially increasing, solving the same problems using classical algorithms becomes more tedious and time consuming. Quantum computing has varied applications in many areas of computer science. One such area which has been transformed a lot through the introduction of quantum computing is machine learning. Quantum computing, with its ability to perform tasks in logarithmic time, aids in overcoming the limitations of classical machine learning algorithms.

Artificial Intelligence in Marketing

2021 ◽  
pp. 342-365
Author(s):  
Özge Sığırcı
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Consumer Behavior ◽  
Literature Review ◽  
Ethical Decision ◽  
Ethical Decision Making ◽  
Previous Literature ◽  
Human Interactions ◽  
Consumer Vulnerability ◽  
Shed Light

The purpose of this chapter is to shed light on the consumer-AI interaction in the marketplace. By this aim, the chapter uses a literature review approach. The previous literature examining AI from a consumer behavior perspective is reviewed, and the findings are compiled in a meaningful flow. According to the review, we see that the traditional marketplace is shaped by AI from only human-to-human interactions to human-to-AI and AI-to-AI interactions. In this new marketplace, while consumers interact with AI, they gain new experiences and feel positive or negative because of these experiences. Also, they build different relationships with AI, such as servant, master, or partner. Besides these relationships, there are still concerns about AI that are related to privacy, algorithmic biases, consumer vulnerability, unemployment, and ethical decision making.

Three Layers Framework Concept for Adjustable Artificial Intelligence

2015 ◽  
Vol 19 (6) ◽  
pp. 867-879
Author(s):  
Benoît Vallade ◽  
◽  
Alexandre David ◽  
Tomoharu Nakashima
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Video Games ◽  
Computer Science ◽  
Source Code

This paper proposes a concept of layered framework for adjustable artificial intelligence. Artificial intelligences are used in various areas of computer science for decision making tasks. Traditionally artificial intelligences are developed in order to be used for a specific purpose within a particular software. However, this paper stands as the first step of a research in progress whose final objective is to design an artificial intelligence adjustable to every types of problems without any modification in its source code. The present work focuses on a framework of such an artificial intelligence and is conducted in the context of video games. This framework, composed of three layers, would be re-usable for all types of game.

scholarly journals Trust does not need to be human: it is possible to trust medical AI

2020 ◽  
pp. medethics-2020-106922
Author(s):  
Andrea Ferrario ◽  
Michele Loi ◽  
Eleonora Viganò
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Recent Article ◽  
Interpersonal Trust ◽  
Monitoring And Control ◽  
Human Interactions ◽  
And Control ◽  
Do So

In his recent article ‘Limits of trust in medical AI,’ Hatherley argues that, if we believe that the motivations that are usually recognised as relevant for interpersonal trust have to be applied to interactions between humans and medical artificial intelligence, then these systems do not appear to be the appropriate objects of trust. In this response, we argue that it is possible to discuss trust in medical artificial intelligence (AI), if one refrains from simply assuming that trust describes human–human interactions. To do so, we consider an account of trust that distinguishes trust from reliance in a way that is compatible with trusting non-human agents. In this account, to trust a medical AI is to rely on it with little monitoring and control of the elements that make it trustworthy. This attitude does not imply specific properties in the AI system that in fact only humans can have. This account of trust is applicable, in particular, to all cases where a physician relies on the medical AI predictions to support his or her decision making.

Quantum-Computing-Inspired Algorithms in Machine Learning

2021 ◽  
pp. 429-448
Author(s):  
Deeksha Kaul ◽  
Harika Raju ◽  
B. K. Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Quantum Computing ◽  
Computer Science ◽  
Real Time ◽  
Learning Algorithms ◽  
Machine Learning Algorithms

In this chapter, the authors discuss the use of quantum computing concepts to optimize the decision-making capability of classical machine learning algorithms. Machine learning, a subfield of artificial intelligence, implements various techniques to train a computer to learn and adapt to various real-time tasks. With the volume of data exponentially increasing, solving the same problems using classical algorithms becomes more tedious and time consuming. Quantum computing has varied applications in many areas of computer science. One such area which has been transformed a lot through the introduction of quantum computing is machine learning. Quantum computing, with its ability to perform tasks in logarithmic time, aids in overcoming the limitations of classical machine learning algorithms.

scholarly journals The Information Literacy of the Students Studying Mathematics and Computer Science Programs at University

Pedagogika ◽  
2014 ◽  
Vol 115 (3) ◽  
pp. 39-51
Author(s):  
Palmira Pečiuliauskienė ◽  
Loreta Damauskienė
Keyword(s):  
Information Retrieval ◽  
Computer Science ◽  
Information Literacy ◽  
Information Science ◽  
Information Selection ◽  
Information Strategies ◽  
Significant Difference ◽  
Ability Groups ◽  
Processing Abilities ◽  
Information Skills

The paper examines the information literacy of the students studying mathematics and computer science programs considering the following components of the theoretical model of information literacy: 1) understanding the purpose and the need for the information; 2) determining the strategy for the information retrieval and obtaining the information; 3) selection and processing the information, 4) use of the information for the intended objective; 5) ethical and legal use of the information. This paper compares the components of students’ information literacy and explains the differences between them as well as the factors causing these differences. It has been revealed that the strategic and ethical abilities of mathematics and information science students are mostly developed, in particular ethical and legal use of information (average of correctly completed tasks is 56.35 %), and research purpose and need of understanding (average of correctly completed tasks average is 50.46 %). The information selection and processing abilities are weakest (average of correctly completed tasks is 38.08 %) and the abilities of determining information strategies and search of information also are weak (average of correctly completed tasks is 40.99 %). ANOVA (analysis of variance) identified statistical significant difference between five groups of information skills. Turkey test has revealed the homogeneity of two ability groups (3 – Selection and management of information and 2 – information retrieval and information strategy for the achievement).

Medical Diagnosis from a Clinician’s Point of View

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Computer Science ◽  
Medical Diagnosis ◽  
Information Science ◽  
Point Of View ◽  
Joint Research ◽  
The World

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.

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