• Title/Summary/Keyword: strong AI

Search Result 106, Processing Time 0.019 seconds

User Experience (UX) in the Early Days of Generative AI : The benefits and concerns of employees in their 30s and 40s through the Q-methodology (생성형 인공지능 초기 단계의 사용자경험(UX): Q-방법론을 통해 살펴본 30-40대 직장인의 편의와 우려)

  • Yi, Eunju;Yun, Ji-Chan;Lee, Junsik;Park, Do-Hyung
    • The Journal of Information Systems
    • /
    • v.33 no.1
    • /
    • pp.1-30
    • /
    • 2024
  • Purpose The purpose of this study is to examine the customer experience of generative AI among office workers aged 30 to 40, investigating usability, usefulness, and affect, and understanding concerns and expectations. Design/Methodology/Approach This research used Q methodology to assess the customer experience of generative AI. Users are engaged in a problem-solving journey, and data is collected by having participants rank 36 statements based on usability, usefulness, and affect, referred to as the three goals of User Experience. Participants use a forced distribution table with a scale from -5 to +5 to indicate the subjective importance of each statement. The results identified four groups, reflecting different perspectives and attitudes toward generative AI. Findings Participants express overall comfort with generative AI, perceive AI as more knowledgeable in unfamiliar domains, but harbor doubts about AI's understanding. Disagreements emerge on AI replacing humans, the value of unique human roles, data confidentiality, fears of AI advancement, and emotional impacts. Identified four groups: Users who treat AI as a soulless assistant and are active in business use, Uncle users who want to use new technologies properly and are not afraid of technology, users who recognize the limits of AI despite its efficiency, and users who require strong verification in the future. It has the potential to guide future guidelines, ethical codes, and regulations for the appropriate use of AI. In addition, this approach lays the groundwork for future empirical analyses of generative AI.

A Study on the Intention of Financial Consumers to Accept AI Services Using UTAUT Model (통합기술수용이론을 이용한 금융소비자들의 인공지능 서비스 수용의도 연구)

  • Kim, Sun Mi;Son, Young Doo
    • Journal of Korean Society for Quality Management
    • /
    • v.50 no.1
    • /
    • pp.43-61
    • /
    • 2022
  • Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

A Study on the Militarization of Artificial Intelligence Technology in North Korea and the Development Direction of Corresponding Weapon System in South Korea (북한 인공지능 기술의 군사화와 우리 군의 대응 무기체계 발전방향 연구)

  • Kim, Min-Hyuk
    • Journal of Information Technology Services
    • /
    • v.20 no.1
    • /
    • pp.29-40
    • /
    • 2021
  • North Korea's science and technology policies are being pursued under strong leadership and control by the central government. In particular, a large part of the research and development of science and technology related to the Fourth Industrial Revolution in North Korea is controlled and absorbed by the defense organizations under the national defense-oriented policy framework, among which North Korea is making national efforts to develop advanced technologies in artificial intelligence and actively utilize them in the military affairs. The future weapon system based on AI will have superior performance and destructive power that is different from modern weapons systems, which is likely to change the paradigm of the future battlefield, so a thorough analysis and prediction of the level of AI militarization technology, the direction of development, and AI-based weapons system in North Korea is needed. In addition, research and development of South Korea's corresponding weapon systems and military science and technology are strongly required as soon as possible. Therefore, in this paper, we will analyze the level of AI technology, the direction of AI militarization, and the AI-based weapons system in North Korea, and discuss the AI military technology and corresponding weapon systems that South Korea military must research and develop to counter the North Korea's. The next study will discuss the analysis of AI militarization technologies not only in North Korea but also in neighboring countries in Northeast Asia such as China and Russia, as well as AI weapon systems by battlefield function, detailed core technologies, and research and development measures.

The Challenges of AI Ethics and Human Identity Reproduced by Global Content: Focusing on Narrative Analysis of Netflix Documentary (글로벌 콘텐츠가 재현하는 AI 윤리와 인간 정체성의 과제: 넷플릭스 다큐 <소셜딜레마>의 서사 분석을 중심으로)

  • Choi, Jong-Hwan;Lee, Hyun-Ju
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.7
    • /
    • pp.548-562
    • /
    • 2022
  • This study was conducted to diagnose the issues of AI ethics in global content and to discuss what kind of discourse is needed to strengthen human identity. To this end, the study selected Netflix original content "The Social Dilemma" for analysis and adopted narrative analysis as the research method. The analysis results confirmed that "Social Dilemma" showed the structure of a traditional current affairs documentary and mainly used experts and statistical data to develop the story. It also reinforced core content claims by enumerating domestic and foreign cases such as the 2021 Myanmar massacre and the spread of fake news. In addition, the relationship between the characters clearly revealed the binary opposition between developers and media companies as well as users and advertisers. For the solution to the problem, strong regulations on businesses and the suspension of social media use were reached. However, "The Social Dilemma" merely pointed out the misuse of AI technology and had a narrative that ignored human identity and social relationships. Such results raise the need for creating contents that emphasize the importance of human sociality, relationships, and learning ability in the age of AI.

Deep Learning-Based, Real-Time, False-Pick Filter for an Onsite Earthquake Early Warning (EEW) System (온사이트 지진조기경보를 위한 딥러닝 기반 실시간 오탐지 제거)

  • Seo, JeongBeom;Lee, JinKoo;Lee, Woodong;Lee, SeokTae;Lee, HoJun;Jeon, Inchan;Park, NamRyoul
    • Journal of the Earthquake Engineering Society of Korea
    • /
    • v.25 no.2
    • /
    • pp.71-81
    • /
    • 2021
  • This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

Investigating the Restructuring of Artificial Intelligence Curriculum in Specialized High Schools Following AI Department Reorganization (특성화고 인공지능학과 개편에 따른 인공지능 교육과정 개편 방안 연구)

  • EunHee Goo
    • Journal of Practical Engineering Education
    • /
    • v.16 no.1_spc
    • /
    • pp.41-49
    • /
    • 2024
  • The advancement of artificial intelligence on a global scale is significantly transforming life. In the field of education, there is a strong emphasis on actively utilizing AI and fostering creatively integrated talents with diverse knowledge. In alignment with this trend, there is a paradigm shift in AI education across primary, middle, high school, as well as university and graduate education. Leading AI schools and specialized high schools are dedicated to enhancing students' AI capabilities, while universities integrate AI into software courses or establish new AI departments to nurture talent. In AI-integrated education graduate programs, national efforts are underway to educate instructors from various disciplines on applying AI technology to the curriculum. In this context, specialized high schools are also restructuring their departments to cultivate technological talent in AI, tailored to students' characteristics and career paths. While the current education focuses primarily on the fundamental concepts and technologies of AI, there is a need to address the aspect of developing practical problem-solving skills. Therefore, this research aims to compare and analyze essential educational courses in AI-leading schools, AI-integrated high schools, AI high schools, university AI departments, and AI-integrated education graduate programs. The goal is to propose the necessary educational courses for AI education in specialized high schools, with the expectation that a more advanced curriculum in AI education can be established in specialized high schools through this effort.

A study on legal service of AI

  • Park, Jong-Ryeol;Noe, Sang-Ouk
    • Journal of the Korea Society of Computer and Information
    • /
    • v.23 no.7
    • /
    • pp.105-111
    • /
    • 2018
  • Last March, the world Go competition between AlphaGo, AI Go program developed by Google Deep Mind and professional Go player Lee Sedol has shown us that the 4th industrial revolution using AI has come close. Especially, there ar many system combined with AI hae been developing including program for researching legal information, system for expecting jurisdiction, and processing big data, there is saying that even AI legal person is ready for its appearance. As legal field is mostly based on text-based document, such characteristic makes it easier to adopt artificial intelligence technology. When a legal person receives a case, the first thing to do is searching for legal information and judical precedent, which is the one of the strength of AI. It is very difficult for a human being to utilize a flow of legal knowledge and figures by analyzing them but for AI, this is nothing but a simple job. The ability of AI searching for regulation, precedent, and literature related to legal issue is way over our expectation. AI is evaluated to be able to review 1 billion pages of legal document per second and many people agree that lot of legal job will be replaced by AI. Along with development of AI service, legal service is becoming more advanced and if it devotes to ethical solving of legal issues, which is the final goal, not only the legal field but also it will help to gain nation's trust. If nations start to trust the legal service, it would never be completely replaced by AI. What is more, if it keeps offering advanced, ethical, and quick legal service, value of law devoting to the society will increase and finally, will make contribution to the nation. In this time where we have to compete with AI, we should try hard to increase value of traditional legal service provided by human. In the future, priority of good legal person will be his/her ability to use AI. The only field left to human will be understanding and recovering emotion of human caused by legal problem, which cannot be done by AI's controlling function. Then, what would be the attitude of legal people in this period? It would be to learn the new technology and applying in the field rather than going against it, this will be the way to survive in this new AI period.

A Case Study on Artificial Intelligence Education for Non-Computer Programming Students in Universities (대학에서 비전공자 대상 인공지능 교육의 사례 연구)

  • Lee, Youngseok
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.2
    • /
    • pp.157-162
    • /
    • 2022
  • In a society full of knowledge and information, digital literacy and artificial intelligence (AI) education that can utilize AI technology is needed to solve numerous everyday problems based on computational thinking. In this study, data-centered AI education was conducted while teaching computer programming to non-computer programming students at universities, and the correlation between major factors related to academic performance was analyzed in addition to student satisfaction surveys. The results indicated that there was a strong correlation between grades and problem-solving ability-based tasks, and learning satisfaction. Multiple regression analysis also showed a significant effect on grades (F=225.859, p<0.001), and student satisfaction was high. The non-computer programming students were also able to understand the importance of data and the concept of AI models, focusing on specific examples of project types, and confirmed that they could use AI smoothly in their fields of interest. If further cases of AI education are explored and students' AI education is activated, it will be possible to suggest its direction that can collaborate with experts through interest in AI technology.

A Study on the Factors Affecting Continuous Use of AI Speaker Using SNA (SNA를 이용한 AI 스피커 지속적 사용에 영향을 미치는 요인 분석 연구: 아마존 에코 리뷰 중심으로)

  • Kim, Young Bum;Cha, Kyung Jin
    • The Journal of Society for e-Business Studies
    • /
    • v.26 no.4
    • /
    • pp.95-118
    • /
    • 2021
  • As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

Categorization of Interaction Factors through Analysis of AI Agent Using Scenarios (인공지능 에이전트의 사용 시나리오 분석을 통한 인터랙션 속성 유형화)

  • Cheon, Soo-Gyeong;Yeoun, Myeong-Heum
    • Journal of the Korea Convergence Society
    • /
    • v.11 no.11
    • /
    • pp.63-74
    • /
    • 2020
  • AI products are used 'AI assistants' as embedded in smart phones, speakers, appliances as agents. Studies on anthropomorphism, such as personality, voice with a weak AI are being conducted. Role and function of AI agents will expand from development of AI technology. Various attributes related to the agent, such as user type, usage environment, appearance of the agent will need to be considered. This study intends to categorize interaction factors related to agents from the user's perspective through analysis of concept videos which agents with strong AI. Framework for analysis was built on the basis of theoretical considerations for agents. Concept videos were collected from YouTube. They are analyzed according to perspectives on environment, user, agent. It was categorized into 8 attributes: viewpoint, space, shape, agent behavior, interlocking device, agent interface, usage status, and user interface. It can be used as reference when developing, predicting agents to be commercialized in the future.