• Journal of Engineering Education Research
• /
• v.25 no.6
• /
• pp.81-92
• /
• 2022

The purpose of this paper was to develop an instructional design model and checklist for AI education. Literature review was conducted to derive the structure of the instructional design model. And delphi survey was conducted twice to revise and improve the elements & items of the instructional design model and checklist and to confirm the content validity of both instructional design model and the checklist. As a result, an instructional design model consisting of three main steps(Analysis - Design & Development - Implementation & Evaluation) was suggested with a detail checklist which explained what teachers need to do in each step of this instructional development model when they prepare AI education using this instructional design model. Limitations and suggestions for further studies were presented at the end of this paper.

• Journal of Internet of Things and Convergence
• /
• v.10 no.3
• /
• pp.7-12
• /
• 2024

The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase. This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions. The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.

• Journal of Internet of Things and Convergence
• /
• v.10 no.3
• /
• pp.49-55
• /
• 2024

This study was conducted with the purpose of developing a checklist of questions to measure middle school students' AI capabilities. To achieve the goal of the study, literature analysis and question development Delphi survey were used. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements are understanding of artificial intelligence (5 elements), artificial intelligence thinking (5 elements), utilization of artificial intelligence (4 elements), artificial intelligence ethics (6 elements), and artificial intelligence social-emotion (6 elements). elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 31 questions were developed. The developed questions were verified through the first Delphi survey, and 10 questions were revised according to the revision opinions. The validity of 31 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the level of reliability of measurement results increases.

• Journal of Information Technology Services
• /
• v.22 no.2
• /
• pp.23-40
• /
• 2023

Despite the growing interest and normative discussions on AI ethics, there is a lack of discussion on policy instruments that are necessary for companies to develop AI-based services in compliance with ethical principles. Thus, the purpose of this study is to explore policy instruments that can encourage companies to voluntarily comply with and adopt AI ethical standards and self-checklists. The study reviews previous research and similar cases on AI ethics, conducts interviews with AI-related companies, and analyzes the data using AHP to derive action plans. In terms of desirability and feasibility, Research findings show that policy instruments that induce companies to ethically develop AI-based services should be prioritized, while regulatory instruments require a cautious approach. It was also found that a consulting support policy consisting of experts in various fields who can support the use of AI ethics, and support for the development of solutions that adhere to AI ethical standards are necessary as incentive policies. Additionally, the participation and agreement of various stakeholders in the process of establishing AI ethical standards are crucial, and policy instruments need to be continuously supplemented through implementation and feedback. This study is significant as it presents the necessary policy instruments for companies to develop ethical AI-based services through an analytical methodology, moving beyond discursive discussions on AI ethical principles. Further analysis on the effectiveness of policy instruments linked to AI ethical principles is necessary for establishing ethical AI-based service development.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.6
• /
• pp.1523-1537
• /
• 2018

The AI speaker is a simple operation that provides users with useful functions such as music playback, online search, and so the AI speaker market is growing at a very fast pace. However, AI speakers always wait for the user's voice, which can cause serious problems such as eavesdropping and personal information exposure if exposed to security threats. Therefore, in order to provide overall improved security of all AI speakers, it is necessary to identify potential security threats and analyze them systematically. In this paper, security threat modeling is performed by selecting four products with high market share. Data Flow Diagram, STRIDE and LINDDUN Threat modeling was used to derive a systematic and objective checklist for vulnerability checks. Finally, we proposed a method to improve the security of AI speaker by comparing the vulnerability analysis results and the vulnerability of each product.

• Journal of Intelligence and Information Systems
• /
• v.28 no.3
• /
• pp.259-278
• /
• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Imaging Science in Dentistry
• /
• v.53 no.3
• /
• pp.193-198
• /
• 2023

Purpose: Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. Materials and Methods: A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type of AI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Results: Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was 91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. Conclusion: AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.

• Korean Journal of Clinical Pharmacy
• /
• v.30 no.1
• /
• pp.1-10
• /
• 2020

Objective: The aim of the study was to perform a meta-analysis of randomized clinical trials to compare the clinical efficacy and safety between combination of cyclin-dependent kinase (CDK) 4/6 inhibitors with aromatase inhibitors (AIs) and AIs alone in patients with hormone receptor+/human epidermal growth factor receptor type2-(HR+/HER2-) advanced breast cancer. Methods: Published clinical studies were identified through electronic database searches until February 2019. Literature qualities were assessed by the Scottish Intercollegiate Guidelines Network Checklist. Key endpoints of efficacy were progression-free survival (PFS), objective response rate (ORR), and clinical benefit (CB). Endpoints of safety were adverse events (AEs) (neutropenia, leukopenia, any grade 3/4 AEs, and serious AEs) and on-treatment death. Meta-analysis was performed using the RevMan 5.3 software. Results: The selected five studies were evaluated as "good" in quality assessment. Compared to AIs alone, the combination therapy significantly improved PFS (pooled hazard ratio=0.55; 95% confidence interval (CI) 0.49-0.62), ORR (odds ratio=1.78; 95% CI=1.49-2.13), and CB (odds ratio=1.86; 95% CI=1.51-2.28). The prevalence of AEs was significantly higher in the combination group than in the AIs alone group. On-treatment death was greater in the combination group than in the AIs alone group, although insignificant. Conclusion: The combination therapy of CDK4/6 inhibitors with AIs was more effective for the treatment of HR+/HER2- advanced breast cancer, but less safe than AIs alone. The combination therapy should be effectively managed through patient monitoring, and further studies are needed to reduce AEs in the combination therapy of CDK4/6 inhibitors with AIs.

• Korean Journal of Radiology
• /
• v.24 no.12
• /
• pp.1179-1189
• /
• 2023

Objective: We aimed to evaluate the reporting quality of research articles that applied deep learning to medical imaging. Using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) guidelines and a journal with prominence in Asia as a sample, we intended to provide an insight into reporting quality in the Asian region and establish a journal-specific audit. Materials and Methods: A total of 38 articles published in the Korean Journal of Radiology between June 2018 and January 2023 were analyzed. The analysis included calculating the percentage of studies that adhered to each CLAIM item and identifying items that were met by ≤ 50% of the studies. The article review was initially conducted independently by two reviewers, and the consensus results were used for the final analysis. We also compared adherence rates to CLAIM before and after December 2020. Results: Of the 42 items in the CLAIM guidelines, 12 items (29%) were satisfied by ≤ 50% of the included articles. None of the studies reported handling missing data (item #13). Only one study respectively presented the use of de-identification methods (#12), intended sample size (#19), robustness or sensitivity analysis (#30), and full study protocol (#41). Of the studies, 35% reported the selection of data subsets (#10), 40% reported registration information (#40), and 50% measured inter and intrarater variability (#18). No significant changes were observed in the rates of adherence to these 12 items before and after December 2020. Conclusion: The reporting quality of artificial intelligence studies according to CLAIM guidelines, in our study sample, showed room for improvement. We recommend that the authors and reviewers have a solid understanding of the relevant reporting guidelines and ensure that the essential elements are adequately reported when writing and reviewing the manuscripts for publication.

• Journal of Nutrition and Health
• /
• v.41 no.1
• /
• pp.65-76
• /
• 2008

This study was performed to identify association between nutritional status and health risks of the elderly. This was a cross-sectional study involving low income elderly women in Gwangju, Korea (${\geq}$65y, n = 92). Socio-demographics, life style characteristics, health conditions, dietary intakes based on 24h-recall method, anthropometric measures, and clinical biochemistry parameters were examined. Anthropometric and clinical parameters included wt, ht, waist, hip, body protein, body fat, abdominal fat, total cholesterol, HDL-cholesterol, triglyceride, total protein, albumin, hemoglobin, hematocrit, fasting blood glucose, ferritin, IL-2, IL-6, TNF-${\alpha}$, CRP, TAS, TBARS, systolic blood pressure, and diastolic blood pressure. The subjects were divided into three groups based on age (65-74y, 75-84y, 85y${\leq}$) and were divided into two groups according to the sum of the Nutrition Screening Initiative (NSI) checklist score (adequate nutritional status, NSI score ${\leq}$3; at risk of malnutrition, NSI score >3). Mean and frequency of variables were estimated. Analysis of Variance, Tukey test, Chi-square test, and Multiple linear regression analyses were performed. Mean BMI and body fat were 25.1 $kg/m^2$ and 40.0%, respectively. However, for over 80% of subjects, the intakes of energy, fiber, thiamin, riboflavin, niacin, folate, Ca, K, and Zn were less than the Korean DRI (EAR or AI). The subjects who had lower NSI score tended to have better health status, eat meals frequently, have less depression, and exercise regularly. The subjects who had higher NSI score tended to have tooth problems, to eat alone most of time, and to be physically unable to cook or feed. Serum IL-6 and TNF-${\alpha}$ were significantly related with nutritional status which suggested higher tendency of inflammatory response. Serum IL-2, TAS, and glucose were significantly correlated with body fat (%) or abdominal fat (%). These results suggest that improving the nutritional status, increasing regular exercise, maintaining normal weight are beneficial to health care of low income elderly women.