• Title/Summary/Keyword: Human-AI collaboration

Search Result 22, Processing Time 0.022 seconds

A Study on Human-AI Collaboration Process to Support Evidence-Based National Innovation Monitoring: Case Study on Ministry of Oceans and Fisheries (Human-AI 협력 프로세스 기반의 증거기반 국가혁신 모니터링 연구: 해양수산부 사례)

  • Jung Sun Lim;Seoung Hun Bae;Kil-Ho Ryu;Sang-Gook Kim
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.46 no.2
    • /
    • pp.22-31
    • /
    • 2023
  • Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.

A Study on the Impact of Artificial Intelligence on Decision Making : Focusing on Human-AI Collaboration and Decision-Maker's Personality Trait (인공지능이 의사결정에 미치는 영향에 관한 연구 : 인간과 인공지능의 협업 및 의사결정자의 성격 특성을 중심으로)

  • Lee, JeongSeon;Suh, Bomil;Kwon, YoungOk
    • Journal of Intelligence and Information Systems
    • /
    • v.27 no.3
    • /
    • pp.231-252
    • /
    • 2021
  • Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

ETRI AI Strategy #1: Proactively Securing AI Core Technologies (ETRI AI 실행전략 1: 인공지능 핵심기술 선제적 확보)

  • Kim, S.M.;Yeon, S.J.
    • Electronics and Telecommunications Trends
    • /
    • v.35 no.7
    • /
    • pp.3-12
    • /
    • 2020
  • In this paper, we introduce ETRI AI Strategy #1, "Proactively Securing AI Core Technologies." The first goal of this strategy is to innovate artificial intelligence (AI) service technology to overcome the current limitations of AI technologies. Even though we saw a big jump in AI technology development recently due to the rise of deep learning (DL), DL still has technical limitations and problems. This paper introduces the four major parts of the advanced AI technologies that ETRI will secure to overcome the problems of DL and harmonize AI with the human world: post DL technology, human-AI collaboration technology, intelligence for autonomous things, and big data platform technology.

A Case Study of Human-AI Co-creation(HAIC) in Fashion Design (패션 디자인에서의 인간-AI 공동창조(HAIC) 사례 연구)

  • Kyunghee Chung;Misuk Lee
    • Journal of Fashion Business
    • /
    • v.27 no.4
    • /
    • pp.141-162
    • /
    • 2023
  • With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

Perception of Fashion Designer's Capability and Product Quality -Human vs. Human+AI vs. AI- (패션 디자인 주체에 따른 패션디자이너 역량 및 제품 품질 지각 -Human vs. Human+AI vs. AI-)

  • Ju-ri Jung;Seyoon Jang;Yuri Lee
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.47 no.4
    • /
    • pp.743-759
    • /
    • 2023
  • Collaboration between AI and fashion designers is becoming essential. Thus, this study explored (1) 321 consumer responses to fashion designers, comparing their capabilities and product quality across different designer types, (2) the relationship between designer capabilities and perceived product quality, and (3) the moderating role of AI knowledge in the effect of capabilities on perceived product quality. Data were analyzed using EFA, ANOVA, regression, and moderation analysis. The results indicated that subjects perceived human designers as having higher capabilities and perceived product quality than AI designers. All subjects' perceived creativity and empathy significantly impacted the perceived functionality, aesthetics, and symbolism-sociality of clothing. Additionally, the perceived creativity of AI and human+AI designers, and the perceived empathy of human and human+AI designers, significantly influenced the perceived functionality and symbolism-sociality, but the perceived creativity of human designers and empathy of AI designers did not directly impact perceived functionality and symbolism-sociality. Moreover, perceptions of the designers' capabilities significantly aesthetics in all subjects. Furthermore, low levels of perceived consumer AI knowledge enhanced the positive impact of perceived human+AI designers' creativity and empathy on perceived functionality and aesthetics. The study suggests that fashion companies should refrain from revealing AI designers at this time.

Empirical Research on the Interaction between Visual Art Creation and Artificial Intelligence Collaboration (시각예술 창작과 인공지능 협업의 상호작용에 관한 실증연구)

  • Hyeonjin Kim;Yeongjo Kim;Donghyeon Yun;Hanjin Lee
    • The Journal of the Convergence on Culture Technology
    • /
    • v.10 no.1
    • /
    • pp.517-524
    • /
    • 2024
  • Generative AI, exemplified by models like ChatGPT, has revolutionized human-machine interactions in the 21st century. As these advancements permeate various sectors, their intersection with the arts is both promising and challenging. Despite the arts' historical resistance to AI replacement, recent developments have sparked active research in AI's role in artistry. This study delves into the potential of AI in visual arts education, highlighting the necessity of swift adaptation amidst the Fourth Industrial Revolution. This research, conducted at a 4-year global higher education institution located in Gyeongbuk, involved 70 participants who took part in a creative convergence module course project. The study aimed to examine the influence of AI collaboration in visual arts, analyzing distinctions across majors, grades, and genders. The results indicate that creative activities with AI positively influence students' creativity and digital media literacy. Based on these findings, there is a need to further develop effective educational strategies and directions that incorporate AI.

Coexistence Direction of AI and Webtoon Artist

  • Bo-Ra Han
    • Journal of the Korea Society of Computer and Information
    • /
    • v.29 no.2
    • /
    • pp.87-99
    • /
    • 2024
  • This study aims to identify the competencies required for webtoon artists to survive in the future era of AI commercialization. It explores the current and future use of AI in webtoons, and predicts the role of artists in the future webtoon industry. The study finds that AI will replace human workers in some areas, but human empathy-related fields can be sustained. Artist roles like story projectors, Visual directors, and AI editors were identified as potential models for the changing role of artists. To address terminology ambiguity, a three-step AI categorization mechanical type AI, humanoid type AI, and transcendent type AI was proposed for a more realistic separation of AI capabilities. The researcher suggested these findings as guidelines for developing skills in emerging artists or re-skilling existing ones, emphasizing collaboration with AI for mutual growth rather than a negative acceptance of new technology.

'Knowing' with AI in construction - An empirical insight

  • Ramalingham, Shobha;Mossman, Alan
    • International conference on construction engineering and project management
    • /
    • 2022.06a
    • /
    • pp.686-693
    • /
    • 2022
  • Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

  • PDF

A Study on the System for Controlling Factory Safety based on Unity 3D (Unity 3D 기반 깊이 영상을 활용한 공장 안전 제어 시스템에 대한 연구)

  • Jo, Seonghyeon;Jung, Inho;Ko, Dongbeom;Park, Jeongmin
    • Journal of Korea Game Society
    • /
    • v.20 no.3
    • /
    • pp.85-94
    • /
    • 2020
  • AI-based smart factory technologies are only increase short-term productivity. To solve this problem, collaborative intelligence combines human teamwork, creativity, AI speed, and accuracy to actively compensate for each other's shortcomings. However, current automation equipmens require high safety measures due to the high disaster intensity in the event of an accident. In this paper, we design and implement a factory safety control system that uses a depth camera to implement workers and facilities in the virtual world and to determine the safety of workers through simulation.

The Role and Collaboration Model of Human and Artificial Intelligence Considering Human Factor in Financial Security (금융 보안에서 휴먼팩터를 고려한 인간과 인공지능의 역할 및 협업 모델)

  • Lee, Bo-Ra;Kim, In-Seok
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.28 no.6
    • /
    • pp.1563-1583
    • /
    • 2018
  • With the deregulation of electronic finance, FinTech has been revitalized. The discussion on artificial intelligence is active in the financial industry. However, there is a problem of increasing security threats behind new technologies. Security vulnerabilities have increased because we are more connected than before, and the channels and entities of the financial industry have diversified. Although there are technical and policy discussions on security, the essence of all discussions is human. Fundamentals of finance are trust and security, and attention to human factors is important. This study presents the role of human and artificial intelligence for financial security, respectively. Furthermore, this derives a collaborative model in which human and artificial intelligence complement each other's limitations. To support this, it first discusses the development of finance and IT, AI, human factors, and financial security threats. This study suggests that the security threats will intensify in the era of new technology, but it can overcome them by using machinery and technology.