Human Factors Considerations for Teaming between Construction Workersand Voice-based Intelligent Virtual Agent (VIVA)

2021 ◽  
Vol 65 (1) ◽  
pp. 72-76
Author(s):  
Maryam Rahimi Movassagh ◽  
Nazila Roofigari-Esfahan ◽  
Sang Won Lee ◽  
Carlos Evia ◽  
David Hicks ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Research Agenda ◽  
Task Environment ◽  
Virtual Agent ◽  
Work Processes ◽  
Construction Sites

Construction sites experience low productivity due to particular characteristics such as unique designs in each project, sporadic arrival of projects, and complexity of the process. Another contributing factor to low productivity is poor communication among workers, supervisors, and a site’s centralized knowledge hub. Research shows that introducing advanced artificial intelligence (AI) technology in construction can tackle these problems. In this paper, we analyzed human factors considerations–user, task, environment, and technology and identified their characteristics and challenges to design an interactive AI system to facilitate communication between workers and other stakeholders. Based on the analysis, we propose a voice-based intelligent virtual agent (VIVA) as a multi-purpose AI system on construction sites with a further research agenda. We hope that this effort can guide the design of construction-specific AI systems and that this worker-AI teaming can improve overall work processes, enhance productivity, and promote safety in construction.

scholarly journals Artificial intelligence in human factors and ergonomics: an overview of the current state of research

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Deborah Petrat
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Work Processes ◽  
Research Gaps ◽  
Corporate Education ◽  
Current State ◽  
Human Factors And Ergonomics ◽  
Literature Reviews ◽  
State Of Research ◽  
Efficient Work

AbstractThe development of artificial intelligence (AI) technologies continues to advance. To fully exploit the potential, it is important to deal with the topics of human factors and ergonomics, so that a smooth implementation of AI applications can be realized. In order to map the current state of research in this area, three systematic literature reviews with different focuses were conducted. The seven observation levels of work processes according to Luczak and Volpert (1987) served as a basis. Overall n = 237 sources were found and analyzed. It can be seen that the research critically deals with human-centered, effective as well as efficient work in relation to AI. Research gaps, for example in the areas of corporate education concepts and participation and voice, identify further needs in research. The author postulates not to miss the transition between forecasts and verifiable facts.

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

How and where is artificial intelligence in the public sector going? A literature review and research agenda

2019 ◽  
Vol 36 (4) ◽  
pp. 101392 ◽  
Author(s):  
Weslei Gomes de Sousa ◽  
Elis Regina Pereira de Melo ◽  
Paulo Henrique De Souza Bermejo ◽  
Rafael Araújo Sousa Farias ◽  
Adalmir Oliveira Gomes
Keyword(s):  
Artificial Intelligence ◽  
Public Sector ◽  
Literature Review ◽  
Research Agenda ◽  
The Public

Framework kognitive Produktionsarbeit 4.0/Framework for Cognitive Production Work 4.0 – Conceptualization and Model Approach for the Production System of the Future within the Future Work Lab

2020 ◽  
Vol 110 (03) ◽  
pp. 108-112
Author(s):  
Simon Schumacher ◽  
Bastian Pokorni
Keyword(s):  
Artificial Intelligence ◽  
Production System ◽  
Research Agenda ◽  
Reference Model ◽  
Work Organisation ◽  
Research Topics ◽  
Interdisciplinary Project ◽  
The Future ◽  
Future Work ◽  
Model Approach

Das Future Work Lab ist ein Innovationslabor für Arbeit, Mensch und Technik am Standort Stuttgart mit Fokus auf Künstlicher Intelligenz (KI) und vernetzter Arbeitsorganisation. Ein zentraler Bestandteil ist das Framework kognitive Produktionsarbeit 4.0, das als Referenzmodell für das Themenfeld Produktionsarbeit 4.0 dienen soll. Ein entsprechendes Konzept wurde in einem interdisziplinären Projektteam entwickelt. In diesem Beitrag wird das Grobmodell vorgestellt und die weitere Forschungsagenda präsentiert.   The Future Work Lab is an innovation lab for work, people and technology in Stuttgart, Germany with a focus on artificial intelligence and interconnected work organisation. A key component consists of the framework for cognitive production work 4.0, which will serve as a reference model for the research topics. A corresponding concept was developed in an interdisciplinary project team. In this article the raw model is introduced and the further research agenda is presented.

Trends in the Development of Electronic Document Management: Prospects, Problems, Opportunities

2021 ◽  
Vol 27 (12) ◽  
pp. 963-970
Author(s):  
S. A. Zhutyaeva ◽  
T. A. Lysova
Keyword(s):  
Artificial Intelligence ◽  
Legal Status ◽  
Business Processes ◽  
Document Management ◽  
Electronic Document ◽  
Work Processes ◽  
Blockchain Technology ◽  
Electronic Document Management ◽  
Corporate System ◽  
The Impact

Aim. The presented study aims to determine the role and place of electronic document management in the corporate system of Russian enterprises, outlining the prospects for its development.Tasks. The authors examine the legislative acts of the Russian Federation on the prospects for the implementation of electronic document management; assess the impact of the pandemic on the digitalization of document management; analyze the business costs of paper document management; identify the advantages of using electronic document management and promising technologies in document processing.Methods. This study uses theoretical and empirical research methods. The dialectic method is used to determine the role, significance, and legal status of electronic document management. Through a logical approach, the essence of such concepts as 'electronic document' and 'electronic document management' is identified.Results. The study presents directions for the development of electronic document management using blockchain technology, which will improve workflows by processing, sorting, exchanging data and documents protected from unauthorized access, and artificial intelligence, which can help organizations process documents faster by simplifying operational procedures. Obstacles that prevent companies from actively using electronic document management are identified. These include additional investment, time costs, and reorganization of management. The volume of innovative services is analyzed by the type of economic activity, and the costs of creating, storing, and processing paper documents are considered.Conclusions. Recent trends in legislation indicate the government's firm commitment to the speedy introduction of electronic document management in Russia. Its use frees up a lot of resources, including time, labor, and finances. The 2020 pandemic has emphasized the importance of digitalizing business processes to ensure their continuity in unforeseen situations. Integrated into the automation of work processes, blockchain technology will ensure the protection of information from unauthorized tampering. Artificial intelligence will open up new opportunities for processing electronic documents.

Engineering AI Systems

2021 ◽  
pp. 1-19 ◽  
Author(s):  
Jan Bosch ◽  
Helena Holmström Olsson ◽  
Ivica Crnkovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Quality ◽  
Case Studies ◽  
Research Agenda ◽  
Production Quality ◽  
Research Community ◽  
Design Methods ◽  
Engineering Approach ◽  
Quality Design

Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in industry. However, based on well over a dozen case studies, we have learned that deploying industry-strength, production quality ML models in systems proves to be challenging. Companies experience challenges related to data quality, design methods and processes, performance of models as well as deployment and compliance. We learned that a new, structured engineering approach is required to construct and evolve systems that contain ML/DL components. In this chapter, the authors provide a conceptualization of the typical evolution patterns that companies experience when employing ML as well as an overview of the key problems experienced by the companies that they have studied. The main contribution of the chapter is a research agenda for AI engineering that provides an overview of the key engineering challenges surrounding ML solutions and an overview of open items that need to be addressed by the research community at large.

scholarly journals How artificial intelligence will change the future of marketing

2019 ◽  
Vol 48 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Thomas Davenport ◽  
Abhijit Guha ◽  
Dhruv Grewal ◽  
Timna Bressgott
Keyword(s):  
Artificial Intelligence ◽  
Research Agenda ◽  
Marketing Strategies ◽  
Important Policy ◽  
The Future ◽  
Task Types ◽  
The Impact ◽  
Future Of Marketing

Abstract In the future, artificial intelligence (AI) is likely to substantially change both marketing strategies and customer behaviors. Building from not only extant research but also extensive interactions with practice, the authors propose a multidimensional framework for understanding the impact of AI involving intelligence levels, task types, and whether AI is embedded in a robot. Prior research typically addresses a subset of these dimensions; this paper integrates all three into a single framework. Next, the authors propose a research agenda that addresses not only how marketing strategies and customer behaviors will change in the future, but also highlights important policy questions relating to privacy, bias and ethics. Finally, the authors suggest AI will be more effective if it augments (rather than replaces) human managers.

Sign in / Sign up

Export Citation Format

Share Document