scholarly journals Autoencoder-Based Semantic Novelty Detection: Towards Dependable AI-Based Systems

2021 ◽  
Vol 11 (21) ◽  
pp. 9881
Author(s):  
Andreas Rausch ◽  
Azarmidokht Motamedi Sedeh ◽  
Meng Zhang
Keyword(s):  
Artificial Intelligence ◽  
System Development ◽  
Novelty Detection ◽  
Autonomous Systems ◽  
Training Data ◽  
Safety Measure ◽  
False Negatives ◽  
Safety Critical ◽  
Error Calculation

Many autonomous systems, such as driverless taxis, perform safety-critical functions. Autonomous systems employ artificial intelligence (AI) techniques, specifically for environmental perception. Engineers cannot completely test or formally verify AI-based autonomous systems. The accuracy of AI-based systems depends on the quality of training data. Thus, novelty detection, that is, identifying data that differ in some respect from the data used for training, becomes a safety measure for system development and operation. In this study, we propose a new architecture for autoencoder-based semantic novelty detection with two innovations: architectural guidelines for a semantic autoencoder topology and a semantic error calculation as novelty criteria. We demonstrate that such a semantic novelty detection outperforms autoencoder-based novelty detection approaches known from the literature by minimizing false negatives.

Strong Artificial Intelligence and Consciousness

2020 ◽  
Vol 07 (01) ◽  
pp. 63-72 ◽  
Author(s):  
Gee Wah Ng ◽  
Wang Chi Leung
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Human Life ◽  
Autonomous Systems ◽  
Holistic Approach ◽  
Future Research ◽  
Strong Ai ◽  
Strong Artificial Intelligence ◽  
Future Research Directions

In the last 10 years, Artificial Intelligence (AI) has seen successes in fields such as natural language processing, computer vision, speech recognition, robotics and autonomous systems. However, these advances are still considered as Narrow AI, i.e. AI built for very specific or constrained applications. These applications have its usefulness in improving the quality of human life; but it is not good enough to do highly general tasks like what the human can do. The holy grail of AI research is to develop Strong AI or Artificial General Intelligence (AGI), which produces human-level intelligence, i.e. the ability to sense, understand, reason, learn and act in dynamic environments. Strong AI is more than just a composition of Narrow AI technologies. We proposed that it has to be a holistic approach towards understanding and reacting to the operating environment and decision-making process. The Strong AI must be able to demonstrate sentience, emotional intelligence, imagination, effective command of other machines or robots, and self-referring and self-reflecting qualities. This paper will give an overview of current Narrow AI capabilities, present the technical gaps, and highlight future research directions for Strong AI. Could Strong AI become conscious? We provide some discussion pointers.

scholarly journals ARTIFICIAL INTELLIGENCE BASED AUTOGATE SYSTEM DEVELOPMENT CONCEPT IN IMMIGRATION EXAMINATION FOR INDONESIAN CITIZENS AT IMMIGRATION EXAMINATION IN SOEKARNO-HATTA INTERNATIONAL AIRPORT

2019 ◽  
Vol 1 (1) ◽  
pp. 69-80
Author(s):  
Ary Rezqy Hakim
Keyword(s):  
Artificial Intelligence ◽  
Control Function ◽  
System Development ◽  
Immigration Control ◽  
Use Of Technology ◽  
Strategic Role ◽  
Directorate General ◽  
The Times

Immigration checks are one part of the immigration control function which has a strategic role in maintaining security and upholding the country's sovereignty. Along with the times, the implementation of immigration checks has experienced several increasingly complex obstacles and challenges. The use of technology is seen as one of the solutions that can overcome these obstacles and challenges. The Directorate General of Immigration has currently implemented an innovation in the form of autogate which is considered to have provided various benefits, although from the beginning of its implementation, until now autogate has not been able to fully replace the role of immigration officers. This is because immigration checks using autogate are unable to carry out profiling, and interviews with prospective passers at the Immigration Checkpoint, but currently with the discovery of technology in the form of Artificial Intelligence, it is expected to be able to improve the quality of immigration checks with autogate.

scholarly journals Ultrasound Image-Based Diagnosis of Malignant Thyroid Nodule Using Artificial Intelligence

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1822 ◽  
Author(s):  
Dat Tien Nguyen ◽  
Jin Kyu Kang ◽  
Tuyen Danh Pham ◽  
Ganbayar Batchuluun ◽  
Kang Ryoung Park
Keyword(s):  
Artificial Intelligence ◽  
Thyroid Nodule ◽  
State Of The Art ◽  
Ultrasound Image ◽  
The State ◽  
Training Data ◽  
Deep Convolutional Neural Networks ◽  
Training Samples ◽  
Frequency Domains

Computer-aided diagnosis systems have been developed to assist doctors in diagnosing thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly based on the experiences of doctors. Therefore, the performance of such systems plays an important role in enhancing the quality of a diagnosing task. Although there have been the state-of-the art studies regarding this problem, which are based on handcrafted features, deep features, or the combination of the two, their performances are still limited. To overcome these problems, we propose an ultrasound image-based diagnosis of the malignant thyroid nodule method using artificial intelligence based on the analysis in both spatial and frequency domains. Additionally, we propose the use of weighted binary cross-entropy loss function for the training of deep convolutional neural networks to reduce the effects of unbalanced training samples of the target classes in the training data. Through our experiments with a popular open dataset, namely the thyroid digital image database (TDID), we confirm the superiority of our method compared to the state-of-the-art methods.

scholarly journals Implementation of artificial intelligence technologies in human resources management in Russian companies

2021 ◽  
pp. 97-121
Author(s):  
Yuri Petrunin ◽  
◽  
Anna Pugacheva ◽  
Keyword(s):  
Artificial Intelligence ◽  
Personnel Management ◽  
Personnel Selection ◽  
Human Resources Management ◽  
Training Data ◽  
Data Set ◽  
Management Processes ◽  
Efficiency And Effectiveness ◽  
Selection Of

The article examines the problems and prospects of the introduction of artificial intelligence technologies in the selection of personnel in commercial companies in Russia. In recent years, both the number of applications and the number of scientific articles on the use of artificial intelligence technologies in personnel management processes both in our country and abroad have been growing. However, at present, there is a certain gap in the issues of evaluating the effectiveness of the use of these technologies, identifying the most promising areas for the use of artificial intelligence in the selection of personnel, and determining the factors that affect the results of such implementations in relation to Russian conditions. The survey of experts and practitioners in the field of working with artificial intelligence technologies in the field of personnel management of leading Russian companies allowed us to partially answer the relevant questions. The analysis of the respondents ' responses showed that these technologies favorably affect the selection of employees, improve the quality of selection, increase its speed, unload employees, save money resources and help eliminate bias towards candidates. The factors that increase the efficiency and effectiveness of the implementation of artificial intelligence technologies in the selection of personnel were identified: the category of selected employees, the scale of selection, and the possibility of integration with existing software. The difficulties of using artificial intelligence technologies in the selection of personnel include the presence of atypical positions for selection, the dependence of the results on the quality and volume of the training data set, and the possible reluctance of candidates to communicate with the robot. According to the results of the study, we can make a reasonable conclusion that artificial intelligence in the field of personnel selection, despite the presence of certain problems, has many advantages, as well as great prospects for development.

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

Development and Application of Quality Control System for Highway Subgrade Construction

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Tong Wang
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Detection Method ◽  
System Development ◽  
Effective Control ◽  
Construction Process ◽  
Development Mode ◽  
The Road ◽  
Whole Process

The compaction quality of the subgrade is directly related to the service life of the road. Effective control of the subgrade construction process is the key to ensuring the compaction quality of the subgrade. Therefore, real-time, comprehensive, rapid and accurate prediction of construction compaction quality through informatization detection method is an important guarantee for speeding up construction progress and ensuring subgrade compaction quality. Based on the function of the system, this paper puts forward the principle of system development and the development mode used in system development, and displays the development system in real-time to achieve the whole process control of subgrade construction quality.

Pemanfaatan Sistem Informasi Terhadap Kinerja Pelayanan, Sirkulasi Buku Dan Pengolahan Arsip

2018 ◽  
Vol 4 (1) ◽  
pp. 87-96
Author(s):  
Yanni Suherman
Keyword(s):  
Information System ◽  
Data Processing ◽  
System Development ◽  
Processing System ◽  
Data Processing System ◽  
Data Archiving ◽  
Data Archives ◽  
Development Life Cycle ◽  
Search Data

Research conducted at the Office of Archives and Library of Padang Pariaman Regency aims to find out the data processing system library and data archiving. All data processing is done is still very manual by using the document in writing and there is also a stacking of archives on the service. By utilizing library information systems and archives that will be applied to the Office of Archives and Library of Padang Pariaman Regency can improve the quality of service that has not been optimal. This research was made by using System Development Life Cycle (SDLC) which is better known as waterfall method. The first step taken on this method is to go directly to the field by conducting interviews and discussions. This information system will be able to assist the work of officers in terms of data processing libraries and facilitate in search data archives by presenting reports more accurate, effective and efficient.

A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

AI Magazine ◽  
2012 ◽  
Vol 34 (1) ◽  
pp. 10 ◽  
Author(s):  
Steve Kelling ◽  
Jeff Gerbracht ◽  
Daniel Fink ◽  
Carl Lagoze ◽  
Weng-Keen Wong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Feedback Loop ◽  
Human Computation ◽  
Computational Power ◽  
Learning Networks ◽  
Learning Network ◽  
Computer Learning ◽  
The Individual ◽  
Citizen Science Project

In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both, and thereby continually improves the effectiveness of the network as a whole. In this paper we explore how Human-Computer Learning Networks can leverage the contributions of a broad recruitment of human observers and processes their contributed data with Artificial Intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts.

scholarly journals The fourth industrial revolution and labour market regulation in Singapore

2020 ◽  
Vol 31 (3) ◽  
pp. 347-363
Author(s):  
Peter Waring ◽  
Azad Bali ◽  
Chris Vas
Keyword(s):  
Artificial Intelligence ◽  
Labour Market ◽  
Industrial Revolution ◽  
Autonomous Systems ◽  
Market Regulation ◽  
Jel Codes ◽  
Fourth Industrial Revolution ◽  
Labour Market Regulation ◽  
Social Safety Nets ◽  
Large Survey

The race to develop and implement autonomous systems and artificial intelligence has challenged the responsiveness of governments in many areas and none more so than in the domain of labour market policy. This article draws upon a large survey of Singaporean employees and managers (N = 332) conducted in 2019 to examine the extent and ways in which artificial intelligence and autonomous technologies have begun impacting workplaces in Singapore. Our conclusions reiterate the need for government intervention to facilitate broad-based participation in the productivity benefits of fourth industrial revolution technologies while also offering re-designed social safety nets and employment protections. JEL Codes: J88, K31, O38, M53

Sign in / Sign up

Export Citation Format

Share Document