Sources of Risk and Design Principles of Trustworthy Artificial Intelligence

被引:3
|
作者
Steimers, Andre [1 ]
Boemer, Thomas [1 ]
机构
[1] German Social Accid Insurance, Inst Occupat Safety & Hlth, Alte Heerstr 111, D-53757 St Augustin, Germany
关键词
Trustworthy artificial intelligence; Safety; Risk; Machine learning;
D O I
10.1007/978-3-030-77820-0_18
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The importance of artificial intelligence is constantly increasing due to ongoing research successes and the implementation of new applications based on it. It is already described as one of the core technologies of the future. This technology is also increasingly being applied in the field of safety-related applications, which enables the implementation of innovative concepts for novel protection and assistance systems. However, for this to lead to a benefit for human safety and health, a safe or trustworthy artificial intelligence is required. However, the increasing number of accidents related to this technology shows that classical design principles of safe systems still need to be adapted to the new artificial intelligence methods. On the one hand, this requires a basic understanding of the components of trustworthy artificial intelligence, but on the other hand, it also requires an understanding of AI-specific sources of risk. These new sources of risk should be considered in the overall risk assessment of a system based on AI technologies, examined for their criticality, and managed accordingly at an early stage to prevent later failure of the system.
引用
收藏
页码:239 / 251
页数:13
相关论文
共 50 条
  • [21] Trustworthy Artificial Intelligence for Cyber Threat Analysis
    Wang, Shuangbao Paul
    Mullin, Paul A.
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, 2023, 542 : 493 - 504
  • [22] Trustworthy Artificial Intelligence for Securing Transportation Systems
    Thuraisingham, Bhavani
    PROCEEDINGS OF THE 29TH ACM SYMPOSIUM ON ACCESS CONTROL MODELS AND TECHNOLOGIES, SACMAT 2024, 2024, : 5 - 6
  • [23] How to achieve trustworthy artificial intelligence for health
    Baeroe, Kristine
    Miyata-Sturm, Ainar
    Henden, Edmund
    BULLETIN OF THE WORLD HEALTH ORGANIZATION, 2020, 98 (04) : 257 - 262
  • [24] Cyber Threat Analysis and Trustworthy Artificial Intelligence
    Wang, Shuangbao Paul
    Arafin, Md Tanvir
    Osuagwu, Onyema
    Wandji, Ketchiozo
    2022 6TH INTERNATIONAL CONFERENCE ON CRYPTOGRAPHY, SECURITY AND PRIVACY, CSP 2022, 2022, : 86 - 90
  • [25] Cultivating Trustworthy Artificial Intelligence in Digital Government
    Harrison, Teresa M.
    Luna-Reyes, Luis Felipe
    SOCIAL SCIENCE COMPUTER REVIEW, 2022, 40 (02) : 494 - 511
  • [26] Wasabi: A Conceptual Model for Trustworthy Artificial Intelligence
    Singh, Amika M.
    Singh, Munindar P.
    COMPUTER, 2023, 56 (02) : 20 - 28
  • [27] Impact of Explanations for Trustworthy and Transparent Artificial Intelligence
    Manresa-Yee, Cristina
    Ramis, Silvia
    Gaya-Morey, F. Xavier
    Buades, Jose M.
    PROCEEDINGS OF THE XXIII INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION, INTERACCION 2023, 2023,
  • [28] An Overview for Trustworthy and Explainable Artificial Intelligence in Healthcare
    Arslanoglu, Kubra (karslanoglu@firat.edu.tr), 1600, Institute of Electrical and Electronics Engineers Inc.
  • [29] Introduction for the Special Issue on Trustworthy Artificial Intelligence
    Fan, Wenqi
    Zhao, Shu
    Tang, Jiliang
    ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA, 2025, 19 (02)
  • [30] Ethics and governance of trustworthy medical artificial intelligence
    Jie Zhang
    Zong-ming Zhang
    BMC Medical Informatics and Decision Making, 23