Herbert Simon (1916-2001). The scientist of the artificial

With the disappearance of Herbert A. Simon, we have lost one of the most original thinkers of the 20th century. Highly influential in a number of scientific fields—some of which he actually helped create, such as artificial intelligence or information-processing psychology—Simon was a true polymath. His research started in management science and political science, later encompassed operations research, statistics and economics, and finally included computer science, artificial intelligence, psychology, education, philosophy of science, biology, and the sciences of design. His often controversial ideas earned him wide scientific recognition and essentially all the top awards of the fields in which he researched, including the Turing award from the Association of Computing Machinery, with Allen Newell, in 1975, the Nobel prize in economics, in 1978, and the Gold Medal Award for Psychological Science from the American Psychological Foundation, in 1988

Role of artificial intelligence in operations environment : a review and bibliometric analysis

Abstract: Purpose - ‘Technological Intelligence’ is the capacity to appreciate and adapt technological advancements, and ‘Artificial Intelligence’ is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave, and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its societal and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have we reached with respect to artificial intelligence research. Present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals, and citation statistics..

Implementing new interpretation oriented tools in KLASS to support decision making based on logistic regression

This project is part of an research line of combination of statistics methods and Artificial Intelligence for Knowledge Discovery in ill-structured real domains. At the end of this project KLASS contains the following functionalities: predictive models, dummies management and variables aggregation

Application of algorithms in newsrooms

Professional project report submitted in partial fulfillment of the requirements for the degree of Masters of Arts in Journalism from the School of Journalism, University of Missouri--Columbia.This research examines how early journalistic adopters of algorithms gained skills necessary to work with automation and artificial intelligence in newsrooms. The researcher conducted semi-structured interviews with eight journalists from medium to large news organizations. The research identified three key findings: Not every journalist needs to learn skills related to automation and artificial intelligence but having a basic understanding of what they are and their capabilities would be beneficial. It is more about learning those skills at conceptual levels without having to learn highly technical mathematics and statistics behind automation and artificial intelligence. Knowledge about common failures of automation and artificial intelligence or being able to see where things can go wrong is as equally important as technical and professional skills

The integration of AI on workforce performance for a South African banking institution

Abstract: Artificial Intelligence (AI) advanced technologies are growing and changing many industries. This paper will assess the relationship in which artificial intelligence impacts the performance of the workforce in a South African bank. The research explores the aspects that contribute to which a worker has improved productivity and performance through the adoption and use of artificial intelligence. The research considers the aspects of artificial intelligence toolset and their influence on the workforce performance. In addition, the paper assesses these aspect as to how they contribute towards the productivity with considerations to the integration of analytical and organized strategies that advance the workforces performance. The purpose is to improve the workforce’s quality performance in the banking institution of South Africa. The research has applied the descriptive statistics with the use of frequency distribution tables and graphical representations to analyze and present the information on the variables. The outcomes are evaluated with regards to the descriptive statistics and inferential statistics based on the variables which show that artificial intelligence has a relatively strong impact on workforce performance. Therefore, it is essential and recommended for banks to integrate them. The next frontier for shared services may be far more exciting, incorporating greater computing power and artificial intelligence into robotics, so that the lines between human judgment and automation become blurred

Building an Artificial Intelligence to Learn Go

This research aims to study the AlphaGo project series, a group of artificial intelligences for playing the game ‘Go’, and develop and train an artificial intelligence through reinforcement learning to play the game Go as well. Go is a 2-player board game where players take turns placing black and white pieces on a 19X19-tiled board in an adjacent tile to a similarly colored piece. Various statistics will be collected to determine its capability in comparison to the go-playing projects of AlphaGo and AlphaGo Zero (AGZ). Unlike the AlphaGo and AGZ projects, this research-developed artificial intelligence will attempt to play a much smaller board of size 9x9 due to the high level of complexity and the unavailability of the required computer power necessary to play at much higher board sizes. Although there are few graphical elements to this project, one element the user will have access to is the board state at each decision of the research-developed AI and its adversarial AI