• Educational Technology International
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• v.8 no.1
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• pp.1-16
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• 2007

The general aim of this article is to explicate what can be researched in our field based on the new understanding on the ability of human visual intelligence. To follow this aim, three key discussions were followed. The first is to explain why the human visual intelligence research is so important in our field and how it was neglected. The basic orientations of the research questions used in its framing and in answering are reviewed. After reviewing traditional research orientations, as the second discussion, alternative, more useful perspective for thinking about human visual intelligence is suggested. And the possibility of contribution for the future research in general is discussed. In doing so, human visual intelligence was defined in rather practically oriented ways rather than theoretically oriented ones. More practical perspectives were suggested. The third discussion is to show how to use the alternative perspectives of human visual intelligence in the areas of educational technology research. It was hoped that the article lays out conceptual groundwork for generation of educational technology research frameworks which can be used for the research conduct, reproduction and sharing by adopting practically oriented views on human visual intelligence as a new territory of educational technology research.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.652-655
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• 1997

An exploration for an intelligence paradigm has been delineated. Artificial intelligence and artificial life paradigms seem to fail to show the whole picture of human intelligence. We may understand the human intelligence better by adding the emotional part of human intelligence to the intellectual part of human intelligence. Emotional intelligence is investigated in terms of composing machine as a modern abstract art. Various algorithmic composition and performance concepts are currently being investigated and implemented. Intelligent mapping algorithms restructure the traditional predetermined composition algorithms. Music based on fractals and neural networks is being composed. Also, emotional intelligence and aesthetic aspects of Korean traditional music are investigated in terms of fractal relationship. As a result, this exploration will greatly broaden the potentials of the intelligence research. The exploration of art in the view of intelligence, information and structure will restore the balanced sense, of art and science which seeks happiness in life. The investigations of emotional intelligence will establish the foundations of intelligence, information and control technologies.

• Journal of Korean Philosophical Society
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• v.143
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• pp.141-164
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• 2017

Artificial intelligence may be said like a human being. What is different thing between artificial intelligence and human intelligence? The people think that the artificial intelligence understands the meaning of the word to see artificial intelligence saying. However, it is different that artificial intelligence is identified as understanding a human being. We apply Wittgenstein's philosophy to this problem whether the artificial intelligence understands a meaning of language. We think that the artificial intelligence does not understand a live meaning of human life.

• Cartoon and Animation Studies
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• s.50
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• pp.423-452
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• 2018

The possibility of future industrialization of artificial intelligence was studied through aspects of artificial intelligence art and movie. The field of artificial intelligence is developing by imitating humans through past and present, so it can be inferred that it is important to grasp the future image presented in movie and artificial intelligence art. Human values are represented differently in artificial intelligence films and arts. Artificial intelligence film and art are concerned with the external and internal aspects of human values, respectively. The AI movie looks at similar external aspects in human and AI shape and function, but artificial intelligence art deals with human alienation and lack of communication due to artificial intelligence technology development. Artificial intelligence in movies is a direction to visualize the imagination for artificial intelligence technology, and artificial intelligence art is expressed in the way of making and implementing works using technology. The future of artificial intelligence, which we have shown in imagination in movies today, is being realized technologically. Artificial intelligence art reflects the problems of artificial intelligence technology that can be appeared through current technology, and human problems that may arise from artificial intelligence technology development. Movies and artificial intelligence art reflect the current problems, and through them we can see the future of artificial intelligence. The future of artificial intelligence in movies is an artificial intelligence service that provides human convenience, cyborg artificial intelligence industry, industry that uses exoskeleton robot and exoskeleton suit, and artificial intelligence secretary. If we look at the future of artificial intelligence through the artificial intelligence art in terms of the problems of artificial intelligence technology and the problem of human value, there are artificial intelligence to learn from trial and error or mistakes, self-expression and communication by lifelogging, recovery of miscommunications by a reflective thinking, and an expansion of the area of artificial intelligence artist through human uncertainty. The future industrialization potential of artificial intelligence as study through aspects of artificial intelligence art and movie is an industry that extends the five senses, an industry that improves the insufficient physical ability of the human, an industry that enhances the physical ability of the human being, and an industry that maintains psychological and mental well-being.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2328-2344
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• 2022

2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

• Korean Medical Education Review
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• v.18 no.2
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• pp.47-50
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• 2016

Development of artificial intelligence is expected to revolutionize today's medicine. In fact, medicine was one of the areas to which advances in artificial intelligence technology were first applied. Recently, state-of-the-art artificial intelligence, especially deep learning technology, has been actively utilized to treat cancer patients and analyze medical image data. Application of artificial intelligence has the potential to fundamentally change various aspects of medicine, including the role of human doctors, the clinical decision-making process, and even overall healthcare systems. Facing such fundamental changes is unavoidable, and we need to prepare to effectively integrate artificial intelligence into our medical system. We should re-define the role of human doctors, and accordingly, medical education should also be altered. In this article, we will discuss the current status of artificial intelligence in medicine and how we can prepare for such changes.

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

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 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.

• Korean Security Journal
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• no.17
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• pp.317-336
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• 2008

The purpose of this study is to progress foreign secret service's human intelligence(HUMINT) activity through case study. This study presents confrontation way of our country analyzing characteristic of foreign secret service's human intelligence(HUMINT) activity and examples concretely. The examples that is used this study is foreign secret service's human intelligence(HUMINT) in USA and Japan. The following was the result of the study. First, we need importance awareness of persons security that correspond in foreign secret service's human intelligence activity. Second, we must secure administrative means for persons security means to correspond in foreign secret service's human intelligence (HUMINT) activity. Third, we must raise anti-espionage ability that correspond in foreign secret service's human intelligence(HUMINT) activity.

• Journal of Korean Elementary Science Education
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• v.37 no.2
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• pp.126-146
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• 2018

The current study explores students' views about artificial intelligence (AI) through analyses of their drawings and perceptions. The data were gathered from a total of 177 elementary school students. The constant comparative analysis was used as the data analysis method. Based on the result, the current study found that students' views about artificial intelligence were constructed into two distinct dimensions: form and relationship. The form dimension, students' views about artificial intelligence were categorized into human, household goods, machine, smart computer, electronic chip/algorithm, or the hybridized form related to the game of go such as AlphaGo. On the relationship dimension, students' views about artificial intelligence were categorized into servants, friends or enemy. Given the combination of two dimensions, the current study found two noted patterns. The first, students who viewed artificial intelligence as human form perceived artificial intelligence as a friend or an enemy. However, those who viewed artificial intelligence as non-human form perceived artificial intelligence as a servant or an enemy. Based on these results, educational implications related to the preparation of artificial intelligence era for elementary science education are discussed.