scholarly journals Peacekeeping Conditions for an Artificial Intelligence Society

2019 ◽  
Vol 3 (2) ◽  
pp. 34
Author(s):  
Hiroshi Yamakawa
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Human Society ◽  
Common Value ◽  
Goal Management ◽  
Computer Based ◽  
Common Goals ◽  
Near Future ◽  
Advanced System ◽  
Local Value

In a human society with emergent technology, the destructive actions of some pose a danger to the survival of all of humankind, increasing the need to maintain peace by overcoming universal conflicts. However, human society has not yet achieved complete global peacekeeping. Fortunately, a new possibility for peacekeeping among human societies using the appropriate interventions of an advanced system will be available in the near future. To achieve this goal, an artificial intelligence (AI) system must operate continuously and stably (condition 1) and have an intervention method for maintaining peace among human societies based on a common value (condition 2). However, as a premise, it is necessary to have a minimum common value upon which all of human society can agree (condition 3). In this study, an AI system to achieve condition 1 was investigated. This system was designed as a group of distributed intelligent agents (IAs) to ensure robust and rapid operation. Even if common goals are shared among all IAs, each autonomous IA acts on each local value to adapt quickly to each environment that it faces. Thus, conflicts between IAs are inevitable, and this situation sometimes interferes with the achievement of commonly shared goals. Even so, they can maintain peace within their own societies if all the dispersed IAs think that all other IAs aim for socially acceptable goals. However, communication channel problems, comprehension problems, and computational complexity problems are barriers to realization. This problem can be overcome by introducing an appropriate goal-management system in the case of computer-based IAs. Then, an IA society could achieve its goals peacefully, efficiently, and consistently. Therefore, condition 1 will be achievable. In contrast, humans are restricted by their biological nature and tend to interact with others similar to themselves, so the eradication of conflicts is more difficult.

scholarly journals The students' and graduates' perception of the potential usefulness of Artificial Intelligence (AI) in the academic curricula of Finance and Accounting Courses

e-mentor ◽  
2021 ◽  
Vol 92 (5) ◽  
pp. 16-25
Author(s):  
Barbara Grabińska ◽  
◽  
Mariusz Andrzejewski ◽  
Konrad Grabiński
Keyword(s):  
Artificial Intelligence ◽  
Technological Change ◽  
New Technologies ◽  
New Technology ◽  
University Education ◽  
Academic Education ◽  
Accounting Courses ◽  
One Step ◽  
Computer Based ◽  
Near Future

The application of computer-based technologies in academic education has at least three decades of history and experience. In some study fields, it has been present since the very beginning, while in others it has become a necessity only in recent years. The ongoing technological revolution is disrupting the traditional professions with fundamental changes and – in some cases – even with the threat of disappearance of jobs. The finance and accounting professions are expected to undergo a technological change in the near future. While the changes are visible at the corporate level, university education seems to lag one step behind. We conducted a study among the students and graduates of the finance and accounting line of studies at the Cracow University of Economics. Using regression analysis, we investigate the perception of the usefulness of courses providing knowledge on new technologies like Artificial Intelligence (AI). We use a unique Polish setting, which is a leader in terms of outsourcing services. Our findings show that both students and graduates are aware of the importance of technological change. The courses teaching basic subjects are essential, but the current expectations are much higher in terms of the application of new technology based on AI in finance and accounting.

scholarly journals Artificial Intelligence: The Attitude of the Public and Representatives of Various Industries

2021 ◽  
Vol 14 (8) ◽  
pp. 339
Author(s):  
Tatjana Vasiljeva ◽  
Ilmars Kreituss ◽  
Ilze Lulle
Keyword(s):  
Artificial Intelligence ◽  
Primary Data ◽  
Structured Interviews ◽  
The Public ◽  
Qualitative And Quantitative ◽  
Public Survey ◽  
Significant Difference ◽  
Main Factors ◽  
Negative Factors ◽  
Near Future

This paper looks at public and business attitudes towards artificial intelligence, examining the main factors that influence them. The conceptual model is based on the technology–organization–environment (TOE) framework and was tested through analysis of qualitative and quantitative data. Primary data were collected by a public survey with a questionnaire specially developed for the study and by semi-structured interviews with experts in the artificial intelligence field and management representatives from various companies. This study aims to evaluate the current attitudes of the public and employees of various industries towards AI and investigate the factors that affect them. It was discovered that attitude towards AI differs significantly among industries. There is a significant difference in attitude towards AI between employees at organizations with already implemented AI solutions and employees at organizations with no intention to implement them in the near future. The three main factors which have an impact on AI adoption in an organization are top management’s attitude, competition and regulations. After determining the main factors that influence the attitudes of society and companies towards artificial intelligence, recommendations are provided for reducing various negative factors. The authors develop a proposition that justifies the activities needed for successful adoption of innovative technologies.

scholarly journals A Survey on Bias and Fairness in Machine Learning

2021 ◽  
Vol 54 (6) ◽  
pp. 1-35
Author(s):  
Ninareh Mehrabi ◽  
Fred Morstatter ◽  
Nripsuta Saxena ◽  
Kristina Lerman ◽  
Aram Galstyan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Real World ◽  
State Of The Art ◽  
Future Directions ◽  
Discriminatory Behavior ◽  
Real World Applications ◽  
Near Future ◽  
Different Sources

With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.

Instrumented Interface Construction Evaluator

1996 ◽  
Vol 40 (17) ◽  
pp. 863-863
Author(s):  
James H. Hicinbothom
Keyword(s):  
Intelligent Agents ◽  
Cognitive Task ◽  
Human Factors Engineering ◽  
User Models ◽  
Engineering Research ◽  
Window System ◽  
Development Tools ◽  
System User ◽  
Computer Based ◽  
User Actions

Human factors engineering research into human-computer interaction (HCI) needs means to easily and objectively study HCI. The Instrumented Interface Construction (IICON) Evaluator, and its associated IICON Data Taps, provide such means. Any X Window system user interface built using development tools for which appropriate IICON Data Taps exist (e.g., IICON Data Taps/TAE+5.2) can be automatically instrumented. Instrumented interfaces can then be used by subjects, recording a complete transcript of user actions. Once an operator's session has been recorded, it can be replayed on-screen as needed for further observation and analysis. These capabilities are extremely helpful for developing cognitive task models (i.e., user models) for analytic purposes, or for construction of Intelligent Agents to be embedded in the operator's computer-based workstation. Furthermore, with a complete objective record of all operator actions, IICON Evaluator supports a wide variety of research investigations of HCI.

APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN MS. PAC-MAN GAME: A REVIEW

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Tse Guan Tan ◽  
Jason Teo
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Video Games ◽  
Analysis Method ◽  
Engineering Economics ◽  
Game Ai ◽  
Content Analysis Method ◽  
Wide Range ◽  
Computer Based ◽  
Future Direction

AbstrakTeknik Kecerdasan Buatan (AI) berjaya digunakan dan diaplikasikan dalam pelbagai bidang, termasukpembuatan, kejuruteraan, ekonomi, perubatan dan ketenteraan. Kebelakangan ini, terdapat minat yangsemakin meningkat dalam Permainan Kecerdasan Buatan atau permainan AI. Permainan AI merujukkepada teknik yang diaplikasikan dalam permainan komputer dan video seperti pembelajaran, pathfinding,perancangan, dan lain-lain bagi mewujudkan tingkah laku pintar dan autonomi kepada karakter dalampermainan. Objektif utama kajian ini adalah untuk mengemukakan beberapa teknik yang biasa digunakandalam merekabentuk dan mengawal karakter berasaskan komputer untuk permainan Ms Pac-Man antaratahun 2005-2012. Ms Pac-Man adalah salah satu permainan yang digunakan dalam siri pertandinganpermainan diperingkat antarabangsa sebagai penanda aras untuk perbandingan pengawal autonomi.Kaedah analisis kandungan yang menyeluruh dijalankan secara ulasan dan sorotan literatur secara kritikal.Dapatan kajian menunjukkan bahawa, walaupun terdapat berbagai teknik, limitasi utama dalam kajianterdahulu untuk mewujudkan karakter permaianan Pac Man adalah kekurangan Generalization Capabilitydalam kepelbagaian karakter permainan. Hasil kajian ini akan dapat digunakan oleh penyelidik untukmeningkatkan keupayaan Generalization AI karakter permainan dalam Pasaran Permainan KecerdasanBuatan. Abstract Artificial Intelligence (AI) techniques are successfully used and applied in a wide range of areas, includingmanufacturing, engineering, economics, medicine and military. In recent years, there has been anincreasing interest in Game Artificial Intelligence or Game AI. Game AI refers to techniques applied incomputer and video games such as learning, pathfinding, planning, and many others for creating intelligentand autonomous behaviour to the characters in games. The main objective of this paper is to highlightseveral most common of the AI techniques for designing and controlling the computer-based charactersto play Ms. Pac-Man game between years 2005-2012. The Ms. Pac-Man is one of the games that used asbenchmark for comparison of autonomous controllers in a series of international Game AI competitions.An extensive content analysis method was conducted through critical review on previous literature relatedto the field. Findings highlight, although there was various and unique techniques available, the majorlimitation of previous studies for creating the Ms. Pac-Man game characters is a lack of generalizationcapability across different game characters. The findings could provide the future direction for researchersto improve the Generalization A.I capability of game characters in the Game Artificial Intelligence market.

Real time computer based communication with conducting polymers: an artificial intelligence approach

1995 ◽  
Vol 32 (10) ◽  
pp. 405 ◽  
Author(s):  
Afshad Talaie ◽  
Nasser Esmaili ◽  
Farhad Talaie
Keyword(s):  
Artificial Intelligence ◽  
Conducting Polymers ◽  
Real Time ◽  
Computer Based ◽  
Intelligence Approach ◽  
Artificial Intelligence Approach

scholarly journals Challenges and Approaches to Scaling the Global Commons

2021 ◽  
Vol 4 ◽  
Author(s):  
Felix Fritsch ◽  
Jeff Emmett ◽  
Emaline Friedman ◽  
Rok Kranjc ◽  
Sarah Manski ◽  
...  
Keyword(s):  
Large Scale ◽  
Sharing Economy ◽  
Natural Habitats ◽  
Common Value ◽  
Exchange Value ◽  
Space Agency ◽  
The Commons ◽  
Common Goals ◽  
Distribution Of Power ◽  
New Generation

The re-emergence of commoning over the last decades is not incidental, but rather indicative of a large-scale transition to a more “generative” organization of society that is oriented toward the planet’s global carrying capacity. Digital commons governance frameworks are of particular importance for a new global paradigm of cooperation, one that can scale the organization of communities around common goals and resources to unprecedented levels of size, complexity and granularity. Distributed Ledger Technologies (DLTs) such as blockchain have lately given new impetus to the emergence of a new generation of authentic “sharing economy,” protected from capture by thorough distribution of power over infrastructure, that spans not only digital but also physical production of common value. The exploration of the frontiers of DLT-based commoning at the heart of this article considers three exemplary cases for this new generation of commons-oriented community frameworks: the Commons Stack, Holochain and the Commons Engine, and the Economic Space Agency. While these projects differ in their scope as well as in their relation to physical common-pool resources (CPRs), they all share the task of redefining markets so as to be more conducive to the production and sustainment of common value(s). After introducing each of them with regards to their specificities and commonalities, we analyze their capacity to foster commons-oriented economies and “money for the commons” that limit speculation, emphasize use-value over exchange-value, favor equity in human relations, and promote responsibility for the preservation of natural habitats. Our findings highlight the strengths of DLTs for a federated scaling of CPR governance frameworks that accommodates rather than obliterates cultural differences and creates webs of fractal belonging among nested communities.

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