Develop Knowledge and Information Processing Capabilities through Classical Chinese Education Using Artificial Intelligence

How much do anthropomorphisms influence the perception of users about whether they are conversing with a human or an algorithm in a chatbot environment? We develop a cognitive model using the constructs of anthropomorphism and explainability to explain user experiences with conversational journalism (CJ) in the context of chatbot news. We examine how users perceive anthropomorphic and explanatory cues, and how these stimuli influence user perception of and attitudes toward CJ. Anthropomorphic explanations of why and how certain items are recommended afford users a sense of humanness, which then affects trust and emotional assurance. Perceived humanness triggers a two-step flow of interaction by defining the baseline to make a judgment about the qualities of CJ and by affording the capacity to interact with chatbots concerning their intention to interact with chatbots. We develop practical implications relevant to chatbots and ascertain the significance of humanness as a social cue in CJ. We offer a theoretical lens through which to characterize humanness as a key mechanism of human–artificial intelligence (AI) interaction, of which the eventual goal is humans perceive AI as human beings. Our results help to better understand human–chatbot interaction in CJ by illustrating how humans interact with chatbots and explaining why humans accept the way of CJ.

Download Full-text

The 6C model for accurately capturing the patient’s medical history

Diagnosis ◽

10.1515/dx-2020-0126 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Taro Shimizu

Keyword(s):

Artificial Intelligence ◽

Differential Diagnosis ◽

Patient Safety ◽

Information Processing ◽

Safety Concern ◽

Data Gathering ◽

Diagnostic Errors ◽

Accurate Diagnosis ◽

History Taking ◽

Novel Approach

Abstract Diagnostic errors are an internationally recognized patient safety concern, and leading causes are faulty data gathering and faulty information processing. Obtaining a full and accurate history from the patient is the foundation for timely and accurate diagnosis. A key concept underlying ideal history acquisition is “history clarification,” meaning that the history is clarified to be depicted as clearly as a video, with the chronology being accurately reproduced. A novel approach is presented to improve history-taking, involving six dimensions: Courtesy, Control, Compassion, Curiosity, Clear mind, and Concentration, the ‘6 C’s’. We report a case that illustrates how the 6C approach can improve diagnosis, especially in relation to artificial intelligence tools that assist with differential diagnosis.

Download Full-text

AI technologies and their impact on supply chain resilience during COVID-19

International Journal of Physical Distribution & Logistics Management ◽

10.1108/ijpdlm-12-2020-0434 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Sachin Modgil ◽

Shivam Gupta ◽

Rébecca Stekelorum ◽

Issam Laguir

Keyword(s):

Artificial Intelligence ◽

Supply Chain ◽

Information Processing ◽

Supply Chains ◽

Failure Modes ◽

Stress Test ◽

Weak Links ◽

Content Type ◽

Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

Download Full-text

Construction Research of Exercise Prescription Expert System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.718-720.2422 ◽

2013 ◽

Vol 718-720 ◽

pp. 2422-2426

Author(s):

Ming Gou ◽

Jing Yang

Keyword(s):

Artificial Intelligence ◽

Information Processing ◽

Expert System ◽

Exercise Prescription ◽

Scientific Model ◽

Test Database

The test database of students' health is being analyzed with the information processing tool of artificial intelligence Expert System in order to create a scientific model of students Exercise Prescription in the end. It aims at starting with studying every student to realize an optimized development for the quality potential of every student.

Download Full-text

Information Technology in the Search for Employment

Information Technology Trends for a Global and Interdisciplinary Research Community - Advances in Human and Social Aspects of Technology ◽

10.4018/978-1-7998-4156-2.ch012 ◽

2021 ◽

pp. 252-267

Author(s):

Pablo Chamoso ◽

Alfonso González-Briones ◽

Fancisco José García-Peñalvo

Keyword(s):

Artificial Intelligence ◽

Information Technology ◽

Information Processing ◽

State Of The Art ◽

Developed Countries ◽

Search Results ◽

Technological Advances ◽

Career Opportunities ◽

Job Opportunities

Employability is one of the main concerns of the citizens of developed countries. Over the last 10 years, it has become popular to use technology to find employment and better career opportunities. Currently, there are many technology-powered tools available which offer their users (candidates and companies) the possibility of finding the best job opportunities/employees. However, technology is becoming increasingly advanced and current employment-oriented websites must keep up with those standards. Thanks to the computing and information processing capabilities provided by artificial intelligence, today's websites are not mere directories of jobs and candidates; instead, they make it possible to automatically filter search results according to the characteristics of candidates and jobs. This chapter presents a review of state-of-the-art technologies aimed at improving employability and analyzes the technological advances in this sector.

Download Full-text

Neuroglial Behaviour in Computer Science

Artificial Neural Networks in Real-Life Applications ◽

10.4018/978-1-59140-902-1.ch001 ◽

2006 ◽

pp. 1-21 ◽

Cited By ~ 1

Author(s):

Ana B. Porto ◽

Alejandro Pazos

Keyword(s):

Artificial Intelligence ◽

Information Processing ◽

Computer Science ◽

Glial Cells ◽

Computational Models ◽

Brain Circuits

This chapter presents a study that incorporates into the connectionist systems new elements that emulate cells of the glial system. More concretely, we have considered a determined category of glial cells known as astrocytes, which are believed to be directly implicated in the brain’s information processing. Computational models have helped to provide a better understanding of the causes and factors that are involved in the specific functioning of particular brain circuits. The present work will use these new insights to progress in the field of computing sciences and artificial intelligence. The proposed connectionist systems are called artificial neuroglial networks (ANGN).

Download Full-text