• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.13-21
• /
• 2021

In this paper, we developed an artificial intelligence literacy education program to strengthen the AI convergence education capacity and cultivate literacy of in-service elementary and secondary teachers, and verify the effect on the degree of interest in artificial intelligence convergence education by applying it. As a test tool, the level of interest questionnaire scale developed by George, Hall & Stiegelbauer(2006) was used based on the center of interest acceptance model of Hall et al.(1979). As a result of analyzing the degree of interest in artificial intelligence convergence education before and after the application of the artificial intelligence literacy education program, the types of non-users were found both before and after the application of the program, but the overall degree of interest increased compared to before application. As a result of analyzing the satisfaction result of the artificial intelligence literacy education program, a response that was satisfied in most areas was derived, but there was a tendency to be somewhat less satisfied with the case of convergence and application of artificial intelligence and industry.

• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.269-275
• /
• 2022

As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.

• Journal of Internet of Things and Convergence
• /
• v.9 no.1
• /
• pp.49-55
• /
• 2023

The evolution of new digital technologies is progressing rapidly. In particular, many changes in software and artificial intelligence are progressing rapidly in the field of education. The Ministry of Education is planning an educational program by linking software and artificial intelligence regular curriculum. Before applying it to regular subjects, various software and artificial intelligence related experience camps are being promoted. This study aims to construct an educational model for software and artificial intelligence education programs for high school students based on new digital technology. By expanding and distributing software and artificial intelligence education, we aim to enhance the basic capabilities of software and artificial intelligence for high school students. I would like to define the concept of software and artificial intelligence in high school and propose a model that links software and artificial intelligence learning factors to the regular curriculum.

• Journal of Internet of Things and Convergence
• /
• v.9 no.4
• /
• pp.71-75
• /
• 2023

Changes in modern society are resulting in the emergence of various service models that apply software and artificial intelligence, and all fields are rapidly changing based on software and artificial intelligence. Education on software and artificial intelligence is emerging as a major influencing factor that determines national competitiveness. Following these social changes, interest in the use of software and artificial intelligence is quite high. Starting in 2025, software and artificial intelligence-related curricula are scheduled to be introduced into public education in elementary, middle, and high schools, so many educational activities are becoming active. In this study, based on the content of operating the software and artificial intelligence experience activity program, we would like to propose the efficiency of future learning programs and operating methods for software and artificial intelligence.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.227-235
• /
• 2024

In the era of the information revolution, the need for artificial intelligence convergence education is emerging in the trend of global change. Therefore, in this paper, a physical computing programming education method that combines artificial intelligence was developed and applied. The control group was provided with physical computing programming education that did not converge with artificial intelligence, and the experimental group developed and applied a physical computing programming education method that fused artificial intelligence to analyze the impact on elementary school students' computing thinking ability. As a result, it was confirmed that physical computing programming education fused with artificial intelligence had a more positive effect on enhancing elementary school students' computational thinking skills compared to physical computing programming education without artificial intelligence.

• Electronics and Telecommunications Trends
• /
• v.35 no.3
• /
• pp.1-8
• /
• 2020

Artificial-intelligence (AI) technology is used in a variety of fields, from robot cleaner motion control to call center counselors, AI speakers, and Mars exploration. Because the technology levels of all applications and services that utilize AI vary widely, it is not possible to view all applications using AI technology at the same level. Nevertheless, there have been no cases in which the level of AI technology was defined. Therefore, the Electronics and Telecommunications Research Institute (ETRI) Artificial Intelligence Research Laboratory has defined the levels of the main technical elements of AI from steps 1 to 6. In this report, the Artificial Intelligence Technology Level 1.0 (ATL 1.0) is presented. It was established by comprehensively referring to the AI technology prospects and technology roadmaps of major countries. It is hoped that it can be used as a measure for determining the levels of AI applications or services or as an indicator for establishing a technology roadmap.

• Journal of Wellbeing Management and Applied Psychology
• /
• v.2 no.1
• /
• pp.1-8
• /
• 2019

"In the future, 80% of doctors will be replaced by advanced technology." It has been talked about for a long time. When I first heard this story, people said it was ridiculous. But now that AlphaGo has won the Go match against Lee Se-dol, and many global companies have come up with a variety of services and products based on artificial intelligence, the story has become no more than ridiculous. In other words, it is beginning to come true. Artificial intelligence technology is already widely used in manufacturing and service industries. This spread of artificial intelligence is sure to usher in an era of great change in our future. And it is safe to say that it is the "medical world" where the biggest changes will be made. So how on earth does artificial intelligence replace medical personnel? If replaced, where would you stand out? In order to understand this, we must first be familiar with deep learning, which is the basis of medical artificial intelligence. And as the fourth industrial revolution gradually approaches reality, various occupational groups are becoming meaningless, as in the preceding industrial revolution, and in this paper we will learn about the impact of this situation on the medical community.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.2
• /
• pp.177-182
• /
• 2019

As progress of technology, Artificial Intelligence is applied in various fields of industry such as finance, production, medical treatment, service, art by changing the way they look continuously. As AI is progressive area, We have to know what kind of changing is merged in human society by AI. In this paper, through the investigations of Artificial Intelligence's concept and the way Artificial Intelligence's technology is implemented in modern industry, we studied positive effect and negative effect of AI. By this study, In conclusion, by realizing how close Artificial Intelligence had come to our life, we can prepare to seek a foothold to deal with this Artificial Intelligence.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1630-1648
• /
• 2021

Owing to the unprecedented COVID-19 pandemic, the pharmaceutical industry has attracted considerable attention, spurred by the widespread expectation of vaccine development. In this study, we collect relevant topics from news articles related to COVID-19 and explore their links with two South Korean pharmaceutical indices, the Drug and Medicine index of the Korea Composite Stock Price Index (KOSPI) and the Korean Securities Dealers Automated Quotations (KOSDAQ) Pharmaceutical index. We use generalized Dirichlet-multinomial regression (g-DMR) to reveal the dynamic topic distributions over metadata of index values. The results of our analysis, obtained using g-DMR, reveal that a greater focus on specific news topics has a significant relationship with fluctuations in the indices. We also provide practical and theoretical implications based on this analysis.

• ETRI Journal
• /
• v.44 no.3
• /
• pp.426-437
• /
• 2022

To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.