• Broadcasting and Media Magazine
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• v.28 no.2
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• pp.53-59
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• 2023

(주)문화방송(MBC)은 콘텐츠 제작 및 유통 워크플로우에 인공지능(Artificial Intelligence, AI) 기술을 적용한 미디어AI 서비스를 운영하고 있다. 영상아카이브에 보관되어 있는 수십만 개의 아날로그와 SD급 콘텐츠를 대상으로 HD급 수준의 영상화질로 품질을 향상시키기 위해서 AI영상화질개선시스템을 2020년에 개발 구축해서 여러 목적에 활용하고 있으며, HD급 콘텐츠를 대상으로 4K 초고화질급으로 변환하는 기술로 고도화해서 실서비스 적용을 눈앞에 두고 있다. 그리고 2년의 STT(Speech-To-Text, 음성문자변환) 베타서비스를 통해 얻어진 사용성 검증과 운영 경험을 바탕으로 STT HUB 서비스를 개발 구축해서 2022년부터 보도와 시사교양 프로그램의 제작 워크플로우에 적용하고 있다. 이들 서비스의 주요 기능들과 기술적 요소들의 구현, 미디어AI 서비스 운영의 경험을 나누고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2241-2258
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• 2023

This study developed digital literacy instruments and tested their effectiveness on college students' perceptions of AI technologies. In creating a new digital literacy test tool, we reviewed the concept and scale of digital literacy based on previous studies that identified the characteristics and measurement of AI literacy. We developed 23 preliminary questions for our research instrument and used a quantitative approach to survey 318 undergraduates. After conducting exploratory and confirmatory factor analysis, we found that digital literacy in the age of AI had four ability sub-factors: critical understanding, artificial intelligence social impact recognition, artificial intelligence technology utilization, and ethical behavior. Then we tested the sub-factors' predictive powers on the perception of AI's usefulness and ease of use. The regression result shows that the most common powerful predictor of the usefulness and ease of use of AI technology was the ability to use AI technology. This finding implies that for college students, the ability to use various tools based on AI technology is an essential competency in the AI era.

• Smart Media Journal
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• v.12 no.9
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• pp.172-172
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• 2023

• Human Ecology Research
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• v.59 no.1
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• pp.23-43
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• 2021

This study looked through the text mining analysis to check the status of the virtual assistant service, and explore the needs of consumers, and present consumer-oriented directions. Trendup 4.0 was used to analyze the keywords of AI services in Online News and social media from 2016 to 2020. The R program was used to collect consumer comment data and implement Topic Modeling analysis. According to the analysis, the number of mentions of AI services in mass media and social media has steadily increased. The Sentimental Analysis showed consumers were feeling positive about AI services in terms of useful and convenient functional and emotional aspects such as pleasure and interest. However, consumers were also experiencing complexity and difficulty with AI services and had concerns and fears about the use of AI services in the early stages of their introduction. The results of the consumer review analysis showed that there were topics(Technical Requirements) related to technology and the access process for the AI services to be provided, and topics (Consumer Request) expressed negative feelings about AI services, and topics(Consumer Life Support Area) about specific functions in the use of AI services. Text mining analysis enable this study to confirm consumer expectations or concerns about AI service, and to examine areas of service support that consumers experienced. The review data on each platform also revealed that the potential needs of consumers could be met by expanding the scope of support services and applying platform-specific strengths to provide differentiated services.

• Broadcasting and Media Magazine
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• v.25 no.2
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• pp.36-43
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• 2020

AI 시스템은 우리 생활 전반에서 다양한 예측을 도와주는 장치로써 그 중요성이 크다. AI 시스템의 활용도는 AI 장치가 얼마나 우리 생활 전반에 다각도로 이용되어야 하는지에 달려있다. 현재 AI 시스템은 높은 정확도를 위해 학습과 추론에 고성능 컴퓨팅 장비를 필요로 한다. 고성능 장치를 우리 생활 저변에서 쉽게 설치하고 사용할 수 없기 때문에, AI 시스템을 우리 생활에 사용하기 위해서 크게 두 가지의 접근법을 사용하고 있다. 첫째, 고성능 네트워크와 고성능 컴퓨팅 서버를 사용하여 end-user 장치의 계산 복잡도를 최소화하는 시스템을 설계할 수 있다. 둘째, AI 시스템의 학습 및 추론 효율성을 높여, 서버와 네트워크 없이도 end-user 장치에서 최선의 성능을 내는 시스템을 설계할 수 있다. 첫번째 접근법은 고성능 네트워크의 발전을 수반하고, 네트워크의 항상성을 전제로 하기 때문에, 실현하는데 많은 시간과 자원이 요구된다. 두번째 접근법은 비용-효율적이긴 하나 첫번째 접근법에 비해 AI 시스템의 성능이 다소 떨어질 수 있다. 이 글에서는 두번째 접근법의 AI 시스템, 특히 시각 인식 시스템을 응용으로 하는 기술들을 살펴보도록 하겠다.

• The Journal of Information Systems
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• v.31 no.1
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• pp.175-195
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• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.77-85
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• 2022

Unlike previous studies that focused on the diversity of YouTube content, this study tried to identify factors affecting users' satisfaction with the YouTube recommendation system. Specifically, by adding content preference suitability and privacy concerns to the technology acceptance model, we empirically analyzed how these variables affect user's satisfaction of the YouTube AI recommendation system. For this purpose, asurvey was conducted on college students in their 20s and 30s, and the main research results are as follows. First, in the respondents of this study, playfulness and usefulness, which are major variables of the technology acceptance model, appeared as significant factors affecting the satisfaction of the YouTube AI recommendation system, whereas the effect of ease to use was not found. Second, content preference suitability was found to affect the satisfaction with AI recommendation system, but privacy concerns did not affect the satisfaction with YouTube AI recommendation system. Based on these research results, the implications of the study and the directions for future studies were suggested.

• Smart Media Journal
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• v.13 no.1
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• pp.67-75
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• 2024

The purpose of this research is to investigate consumer responses to production recommendations by AI. In order to test hypotheses of this study, we conducted experimental study that was a 2(Brand reputation: high vs. low) X 2(Social comparison: high vs. low). The results of this study showed the interaction effects of brand reputation and social comparison on brand attitude. Based on the results, we provide theoretical implications to extent the existing research regarding product recommendations. Moreover, the results of this study provide some practical implications and a new aspect about AI recommendations.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.101-108
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• 2017

This study explores how Artificial Intelligence (AI), which is tremendously developed these days, applies to the game and advances. It analyzes the reality of AI and provides reasonable suggestion in Poker, one of the most popular games. Specifically, this study focuses on Texas Hold'em, the most favored kind in the world among various kinds of Poker games and deals with two AIs, Libratus and DeepStack that have applied to the game. Several news media report the growth of AI, but this study will multi-dimensionally discusses how and why AI works in Poker, the real problems of AI, and suggestions for advancement.