Adopting robot lawyer? The extending artificial intelligence robot lawyer technology acceptance model for legal industry by an exploratory study

2019 ◽  
pp. 1-19 ◽  
Author(s):  
Ni Xu ◽  
Kung-Jeng Wang
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Exploratory Study ◽  
Two Dimensions ◽  
Legal Services ◽  
Legal Service ◽  
Human Beings ◽  
Semistructured Interviews ◽  
Acceptance Model

Abstract The development of artificial intelligence has created new opportunities and challenges in industries. The competition between robots and humans has elicited extensive attention among legal researchers. In this exploratory study, we addressed issues regarding the introduction of robots to the practice of legal service through a semistructured interviews with lawyers, judges, artificial intelligence experts, and potential clients. An extended robot lawyer technology acceptance model with five facets and 11 elements is proposed in this study. This model highlights two dimensions: ‘legal use’ and ‘perception of trust.’ In summary, this study provides new specific implications and exhibits three characteristics, namely, derivative, macroscopic, and instructive, in the legal services with artificial intelligence. In addition, artificial intelligence robot lawyers are being developed with some of the abilities necessary to substitute for human beings. Nevertheless, working with human lawyers is imperative to produce benefits from this type of reciprocity.

scholarly journals Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior

2021 ◽  
Author(s):  
Svenja Mohr ◽  
Rainer Kühl
Keyword(s):  
Artificial Intelligence ◽  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Perceived Behavioral Control ◽  
Labor Costs ◽  
Online Questionnaire ◽  
Acceptance Model

AbstractThe use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis (1989) and the theory of planned behavior (TPB) of Ajzen (1991) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.

scholarly journals Implementasi Technology Acceptance Model terhadap Adopsi Teknologi Artificial Intelligence pada Startup Digital

2021 ◽  
Vol 9 (2) ◽  
pp. 173-181
Author(s):  
Margo Purnomo ◽  
Erna Maulina ◽  
Aulia Rizki Wicaksono ◽  
Muhamad Rizal
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Simple Random Sampling ◽  
Sem Analysis ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Artificial Intelligence Technology ◽  
Acceptance Model

The purpose of this study is to describe and analyze the implementation of the technology acceptance model on the adoption of artificial intelligence technology in digital startups. By using simple random sampling, a sample of 109 out of 143 populations, which are startups in Greater Jakarta, was obtained. Based on an analysis using Structural Equation Modeling (SEM) analysis with the SmartPLS tool. The results show that the adoption of artificial intelligence in digital startups is influenced by attitudes, perceptions of convenience and perceptions of usefulness. Likewise, perceived convenience and perceived usefulness are significantly affected by external pressures.

scholarly journals Validation of a Short Questionnaire to Assess Healthcare Professionals’ Perceptions of Asynchronous Telemedicine Services: The Catalan Version of the Health Optimum Telemedicine Acceptance Questionnaire

2020 ◽  
Vol 17 (7) ◽  
pp. 2202 ◽  
Author(s):  
Josep Vidal-Alaball ◽  
Gemma Flores Mateo ◽  
Josep Lluís Garcia Domingo ◽  
Xavier Marín Gomez ◽  
Glòria Sauch Valmaña ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Healthcare Professionals ◽  
Two Dimensions ◽  
Psychometric Validation ◽  
Alpha Coefficient ◽  
Cronbach’S Alpha ◽  
Cronbach's Alpha ◽  
Validated Questionnaire ◽  
Acceptance Model

Telemedicine is both effective and able to provide efficient care at a lower cost. It also enjoys a high degree of acceptance among users. The Technology Acceptance Model proposed is based on the two main concepts of ease of use and perceived usefulness and is comprised of three dimensions: the individual context, the technological context and the implementation or organizational context. At present, no short, validated questionnaire exists in Catalonia to evaluate the acceptance of telemedicine services amongst healthcare professionals using a technology acceptance model. This article aims to statistically validate the Catalan version of the EU project Health Optimum telemedicine acceptance questionnaire. The study included the following phases: adaptation and translation of the questionnaire into Catalan and psychometric validation with construct (exploratory factor analysis), consistency (Cronbach’s alpha) and stability (test–retest) analysis. After deleting incomplete responses, calculations were made using 33 participants. The internal consistency measured with the Cronbach’s alpha coefficient was good with an alpha coefficient of 0.84 (95%, CI: 0.79–0.84). The intraclass correlation coefficient was 0.93 (95% CI: 0.852–0.964). The Kaiser–Meyer–Olkin test of sampling showed to be adequate (KMO = 0.818) and the Bartlett test of sphericity was significant (Chi-square 424.188; gl = 28; p < 0.001). The questionnaire had two dimensions which accounted for 61.2% of the total variance: quality and technical difficulties relating to telemedicine. The findings of this study suggest that the validated questionnaire has robust statistical features that make it a good predictive model of healthcare professional’s satisfaction with telemedicine programs.

An Exploratory Study on the User Adoption of Central Cyber Government Office of the Hong Kong Government

2010 ◽  
pp. 603-614
Author(s):  
Kevin K.W. Ho ◽  
Calvin Chun Yu ◽  
Michael C.L. Lai
Keyword(s):  
Hong Kong ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Exploratory Study ◽  
Civil Servants ◽  
Survey Study ◽  
Factors Affecting ◽  
User Adoption ◽  
Intranet Portal ◽  
Acceptance Model

This chapter investigates those factors affecting the user adoption of the Intranet Portal of the Hong Kong Government, a.k.a., Central Cyber Government Office (CCGO). The authors conducted a survey study in 2004 and they interviewed some of the users to collect their feedbacks on the user adoption of CCGO based on the premises of the Technology Acceptance Model (TAM). Based on the results of their survey and interviews, the authors noted that civil servants of Hong Kong demonstrated strong reluctance to adopt CCGO.

Artificial Intelligence in Aircraft Docking: The Fear of Reducing Ground Marshalling Jobs to Robots and Way-Out

2018 ◽  
Vol 1 (2) ◽  
pp. 25-32
Author(s):  
Adeniran, Adetayo Olaniyi ◽  
Kanyio, Olufunto Adedotun
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Industrial Revolution ◽  
Air Transportation ◽  
Attitude Theory ◽  
Acceptance Model ◽  
The Impact

This study gaudily examines the impact of Artificial Intelligence on aircraft docking, and technophobia that may arise on the part of ground marshallers. Ground marshallers are ground personnel that signal or communicate visually to pilots when docking the aircraft in an airport. Artificial Intelligence is an expert system which can be incorporated in different areas, such as finance, transportation, aviation, and tele-communications. Attitude theory and Technology Acceptance Model (TAM) were used to establish the acceptance of Artificial Intelligence. It should be noted that expert systems make decisions which requires human level of expertise. In order to reduce the fear that technology will replace the jobs of human in the field of air transportation particularly with aircraft docking, it is crucial for airport personnel to embrace the upcoming revolution by developing themselves as regard Artificial Intelligence; Universities should prepare the transport students to face the upcoming reality. Also various organizations should put in place necessary resources needed to be part of this revolution which will be fully achieved in the fourth indus-trial revolution and the fifth industrial revolution.

scholarly journals Analysis of Students' Ability to Accept M-Learning Technology: An Exploratory Study from High Schools in Vietnam

2021 ◽  
Vol 15 (12) ◽  
pp. 86
Author(s):  
Le Thi Tuyet Trinh ◽  
Trinh Thi Phuong Thao ◽  
Thu Thi Nguyen Hang ◽  
Nguyen Chi Thanh ◽  
Tran Trung
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Exploratory Study ◽  
Industry 4.0 ◽  
The Internet ◽  
Learning Technology ◽  
Factors Affecting ◽  
Efficiency Increase ◽  
Acceptance Model ◽  
Survey Questionnaires

<p class="0abstract">With the availability of mobile devices capable of accessing the Internet in the Industry 4.0 era, M-learning methodology has been established. Based on the Technology Acceptance Model on technology adoption, this article analyses factors affecting the decision to use M-learning in Vietnam. The study used survey questionnaires with 238 students. The analysis shows to encourage students to choose to use M-learning is that educators need to pay attention to the design of appropriate courses to save time, improve learning efficiency, increase the mobility of learners and necessary introduce the convenience of courses to learners through many different channels.</p>

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