• Title/Summary/Keyword: AI Certification

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Roadmap Toward Certificate Program for Trustworthy Artificial Intelligence

  • Han, Min-gyu;Kang, Dae-Ki
    • International journal of advanced smart convergence
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    • v.10 no.3
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    • pp.59-65
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    • 2021
  • In this paper, we propose the AI certification standardization activities for systematic research and planning for the standardization of trustworthy artificial intelligence (AI). The activities will be in two-fold. In the stage 1, we investigate the scope and possibility of standardization through AI reliability technology research targeting international standards organizations. And we establish the AI reliability technology standard and AI reliability verification for the feasibility of the AI reliability technology/certification standards. In the stage 2, based on the standard technical specifications established in the previous stage, we establish AI reliability certification program for verification of products, systems and services. Along with the establishment of the AI reliability certification system, a global InterOp (Interoperability test) event, an AI reliability certification international standard meetings and seminars are to be held for the spread of AI reliability certification. Finally, TAIPP (Trustworthy AI Partnership Project) will be established through the participation of relevant standards organizations and industries to overall maintain and develop standards and certification programs to ensure the governance of AI reliability certification standards.

Trends of Artificial Intelligence Product Certification Programs

  • Yejin SHIN;Joon Ho KWAK;KyoungWoo CHO;JaeYoung HWANG;Sung-Min WOO
    • Korean Journal of Artificial Intelligence
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    • v.11 no.3
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    • pp.1-5
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    • 2023
  • With recent advancements in artificial intelligence (AI) technology, more products based on AI are being launched and used. However, using AI safely requires an awareness of the potential risks it can pose. These concerns must be evaluated by experts and users must be informed of the results. In response to this need, many countries have implemented certification programs for products based on AI. In this study, we analyze several trends and differences in AI product certification programs across several countries and emphasize the importance of such programs in ensuring the safety and trustworthiness of products that include AI. To this end, we examine four international AI product certification programs and suggest methods for improving and promoting these programs. The certification programs target AI products produced for specific purposes such as autonomous intelligence systems and facial recognition technology, or extend a conventional software quality certification based on the ISO/IEC 25000 standard. The results of our analysis show that companies aim to strategically differentiate their products in the market by ensuring the quality and trustworthiness of AI technologies. Additionally, we propose methods to improve and promote the certification programs based on the results. These findings provide new knowledge and insights that contribute to the development of AI-based product certification programs.

Certification Framework for Aviation Software with AI Based on Machine Learning (머신러닝 기반 AI가 적용된 항공 소프트웨어 인증체계)

  • Dong-hwan Bae;Hyo-jung Yoon
    • Journal of Advanced Navigation Technology
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    • v.28 no.4
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    • pp.466-471
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    • 2024
  • Recently, the Machine Learning based Artificial Intelligence has introduced in aviation field. In most cases, safety assurance of aviation software is achieved by applying RTCA DO-178C or DO-278A or similar standards. These standards were developed for and are well-suited to software that has inherent deterministic properties and explainability. Considering the characteristics of AI software based on ML, it is not feasible to assure the integrity of those new aviation systems using traditional software assurance standards mentioned above. In this paper, we research the certification framework that is newly suggested by EASA to deal with the aviation system including ML AI functions, and discuss what should the Korean authority and related industries prepare to cope with this issue.

A Methodology for Using ChatGPT to Improve BIM-based Design Data Evaluation System (BIM기반 설계데이터 평가 시스템 개선을 위한 ChatGPT활용 방법론)

  • Yu, Eun-Sang;Kim, Gu-Taek;Ahn, Yong-Han;Choi, Jung-Sik
    • Journal of KIBIM
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    • v.14 no.2
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    • pp.25-34
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    • 2024
  • This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.

Cybersecurity Development Status and AI-Based Ship Network Security Device Configuration for MASS

  • Yunja Yoo;Kyoung-Kuk Yoon;David Kwak;Jong-Woo Ahn;Sangwon Park
    • Journal of Navigation and Port Research
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    • v.47 no.2
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    • pp.57-65
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    • 2023
  • In 2017, the International Maritime Organization (IMO) adopted MSC.428 (98), which recommends establishing a cyber-risk management system in Ship Safety Management Systems (SMSs) from January 2021. The 27th International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) also discussed prioritizing cyber-security (cyber-risk management) in developing systems to support Maritime Autonomous Surface Ship (MASS) operations (IALA guideline on developments in maritime autonomous surface ships). In response to these international discussions, Korea initiated the Korea Autonomous Surface Ship technology development project (KASS project) in 2020. Korea has been carrying out detailed tasks for cybersecurity technology development since 2021. This paper outlines the basic concept of ship network security equipment for supporting MASS ship operation in detailed task of cybersecurity technology development and defines ship network security equipment interface for MASS ship applications.

Implementation of an Autostereoscopic Virtual 3D Button in Non-contact Manner Using Simple Deep Learning Network

  • You, Sang-Hee;Hwang, Min;Kim, Ki-Hoon;Cho, Chang-Suk
    • Journal of Information Processing Systems
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    • v.17 no.3
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    • pp.505-517
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    • 2021
  • This research presented an implementation of autostereoscopic virtual three-dimensional (3D) button device as non-contact style. The proposed device has several characteristics about visible feature, non-contact use and artificial intelligence (AI) engine. The device was designed to be contactless to prevent virus contamination and consists of 3D buttons in a virtual stereoscopic view. To specify the button pressed virtually by fingertip pointing, a simple deep learning network having two stages without convolution filters was designed. As confirmed in the experiment, if the input data composition is clearly designed, the deep learning network does not need to be configured so complexly. As the results of testing and evaluation by the certification institute, the proposed button device shows high reliability and stability.

Intelligent Security Solution Using Image Processing AI Technology and QR Certification (영상처리 AI기술과 QR인증을 이용한 지능형 방범 솔루션)

  • Song, Keun Yong;Kim, Seong Ho;Kim, Yoon Ho;Lee, Choong Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.394-396
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    • 2022
  • After COVID-19, hybrid stores operated as unmanned stores at specific times have spread, and theft crimes against these stores have also increased. In this paper, we propose an intelligent crime prevention system that fully utilizes existing shop devices to identify and respond to crimes occurring during the late night hours of unmanned shops in real time.

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Research on institutional improvement measures to strengthen artificial intelligence ethics (인공지능 윤리 강화를 위한 제도적 개선방안 연구)

  • Gun-Sang Cha
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.63-70
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    • 2024
  • With the development of artificial intelligence technology, our lives are changing in innovative ways, but at the same time, new ethical issues are emerging. In particular, issues of discrimination due to algorithm and data bias, deep fakes, and personal information leakage issues are judged to be social priorities that must be resolved as artificial intelligence services expand. To this end, this paper examines the concept of artificial intelligence and ethical issues from the perspective of artificial intelligence ethics, and includes each country's ethical guidelines, laws, artificial intelligence impact assessment system, artificial intelligence certification system, and the current status of technologies related to artificial intelligence algorithm transparency to prevent this. We would like to examine and suggest institutional improvement measures to strengthen artificial intelligence ethics.

Discussion on Establishing UAM Operating Concept from the Pilot's Perspective (조종사 관점에서 UAM 운영개념 수립에 대한 고찰)

  • Hi-seok Yoon;Keun-young Lee;Kyu-wang Kim
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.32 no.1
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    • pp.39-48
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    • 2024
  • Aviation industry is moving towards the third innovative era of AAM with electric power and AI after the JET-powered era following the Wright brothers' first flights. Research on UAM, eVTOL development, certification, and operations is competitively progressing, primarily in aviation-leading countries, aiming to resolve urban traffic saturation and foster the future aviation industries. This study introduces the concept of the pilot's role transition in operational safety as AI autonomous flight advances, comparing K-UAM operational concept with research from FAA, NASA, and EASA. It is to identify and propose solutions for challenges from the pilot's perspective in developing UAM and its safe operation system. To succeed in Advanced Air Mobility National Project, we suggest the collaboration among industry, academia, and institutions, along with the cooperation between civilians, governments, military, and the need for Urban Air Mobility integrated policies.

Development of Measurement Indicators by Type of Risk of AI Robots (인공지능 로봇의 위험성 유형별 측정지표 개발)

  • Hyun-kyoung Song
    • Journal of Internet Computing and Services
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    • v.25 no.4
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    • pp.97-108
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    • 2024
  • Ethical and technical problems are becoming serious as the industrialization of artificial intelligence robots becomes active, research on risk is insufficient. In this situation, the researcher developed 52 verified indicators that can measure the body, rights, property, and social risk of artificial intelligence robots. In order to develop measurement indicators for each type of risk of artificial intelligence robots, 11 experts were interviewed in-depth after IRB deliberation. IIn addition, 328 workers in various fields where artificial intelligence robots can be introduced were surveyed to verify their fieldwork, and statistical verification such as exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression analysis was verifyed to measure validity and reliability. It is expected that the measurement indicators presented in this paper will be widely used in the development, certification, education, and policies of standardized artificial intelligence robots, and become the cornerstone of the industrialization of artificial intelligence robots that are socially sympathetic and safe.