scholarly journals Chatbots by business vis-à-vis consumers: A new form of power and information asymmetry

2021 ◽  
Vol 129 ◽  
pp. 05002
Author(s):  
Zanda Davida
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Information Asymmetry ◽  
Value Added ◽  
Legal Framework ◽  
Consumer Law ◽  
Study Results ◽  
The Sixties ◽  
Guidance Documents ◽  
New Form

Research background: The first notable early chatbots were created in the sixties, but the growing use of artificial intelligence (AI) has powered them significantly. Studies show that basically chatbots are created and used for purposes by government and business, mostly in consumer service and marketing. The new Proposal of the Artificial intelligence act aims to promote the uptake of AI and address the risks associated with certain uses of such technology. However, the act contains only minimum transparency obligation for some specific AL systems such as chatbots. Purpose of the article: In light of this issue, the article aims to discuss how existing European Union (EU) consumer law is equipped to deal with situations in which the use of chatbots can pose the risks of manipulation, aggressive commercial practices, intrusion into privacy, exploitation of a consumer’s vulnerabilities and algorithmic decision making based on biased or discriminatory results. Methods: The article will analyse the legal framework, compare guidance documents and countries’ experiences, study results of different consumer behavior researches and scientific articles. Findings & Value added: The article reveals several gaps in current EU consumer law and discusses the flaws of proposing legislation (particularly the Proposal for an Artificial intelligence act) regarding relations between business and consumers.

scholarly journals Liability issues for the use of artificial intelligence in health care in Canada: AI and medical decision-making

2020 ◽  
Vol 46 (2) ◽  
Author(s):  
Mélanie Bourassa Forcier ◽  
Lara Khoury ◽  
Nathalie Vézina
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Decision Making ◽  
Medical Decision Making ◽  
Legal Framework ◽  
Medical Decision

This paper explores Canadian liability concerns flowing from the integration of artificial intelligence (AI) as a tool assisting physicians in their medical decision-making. It argues that the current Canadian legal framework is sufficient, in most cases, to allow developers and users of AI technology to assess each stakeholder's responsibility should the technology cause harm.

Expert Systems and Adaptive Procedures of the Computer Educational System Adept

2016 ◽  
Vol 5 (1) ◽  
pp. 14-31
Author(s):  
Zdeňka Krišová ◽  
Miroslav Pokorný
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Educational System ◽  
Teaching Methods ◽  
Study Materials ◽  
Adaptive Procedures ◽  
Learning Procedure ◽  
Study Results ◽  
Pedagogical Research ◽  
Unconventional Methods

Abstract Current pedagogical research has striven to create an adaptive computer educational system which would come closest to each student’s needs and skills, and would ensure the quickest and the most effective way of acquiring the necessary knowledge in the field concerned. Modern informational technologies are fundamental which make use of unconventional methods of artificial intelligence to mechanically and abstractedly formalize mental models of experienced educators, which leads to mechanical representation of their sophisticated teaching methods and procedures. The structure of the adaptive educational system includes fuzzy expert modules which formalize mental decision-making functions of an experienced educator. Two adaptive loops execute the processes of the adjustment of study materials according to the continuous study results shown and of learning the system according to the information about the student’s modified learning procedure.

Blockchain in Supply Chain: Case Study of Lottemart Ciputat

2019 ◽  
Vol 5 (1) ◽  
pp. 38-49 ◽  
Author(s):  
B. K. Handoyo ◽  
M. R. Mashudi ◽  
H. P. Ipung
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Information Asymmetry ◽  
New Technology ◽  
Business Case ◽  
Analysis Method ◽  
Chain Management ◽  
Production Processes

Current supply chain methods are having difficulties in resolving problems arising from the lack of trust in supply chains. The root reason lies in two challenges brought to the traditional mechanism: self-interests of supply chain members and information asymmetry in production processes. Blockchain is a promising technology to address these problems. The key objective of this paper is to present qualitative analysis for blockchain in supply chain as the decision-making framework to implement this new technology. The analysis method used Val IT business case framework, validated by the expert judgements. The further study needs to be elaborated by either the existing organization that use blockchain or assessment by the organization that will use blockchain to improve their supply chain management.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

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