The risks associated with Artificial General Intelligence: A systematic review

被引:41
|
作者
McLean, Scott [1 ]
Read, Gemma J. M. [1 ]
Thompson, Jason [1 ,2 ]
Baber, Chris [3 ]
Stanton, Neville A. [1 ]
Salmon, Paul M. [1 ]
机构
[1] Univ Sunshine Coast, Ctr Human Factors & Sociotech Syst, Sippy Downs, Qld, Australia
[2] Univ Melbourne, Melbourne Sch Design, Transport Hlth & Urban Design Thud Res Lab, Parkville, Vic, Australia
[3] Univ Birmingham, Sch Comp Sci, Birmingham, England
基金
澳大利亚研究理事会;
关键词
Artificial General Intelligence; artificial intelligence; risk; existential threat; safety; SOCIOTECHNICAL SYSTEMS;
D O I
10.1080/0952813X.2021.1964003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Artificial General intelligence (AGI) offers enormous benefits for humanity, yet it also poses great risk. The aim of this systematic review was to summarise the peer reviewed literature on the risks associated with AGI. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Sixteen articles were deemed eligible for inclusion. Article types included in the review were classified as philosophical discussions, applications of modelling techniques, and assessment of current frameworks and processes in relation to AGI. The review identified a range of risks associated with AGI, including AGI removing itself from the control of human owners/managers, being given or developing unsafe goals, development of unsafe AGI, AGIs with poor ethics, morals and values; inadequate management of AGI, and existential risks. Several limitations of the AGI literature base were also identified, including a limited number of peer reviewed articles and modelling techniques focused on AGI risk, a lack of specific risk research in which domains that AGI may be implemented, a lack of specific definitions of the AGI functionality, and a lack of standardised AGI terminology. Recommendations to address the identified issues with AGI risk research are required to guide AGI design, implementation, and management.
引用
收藏
页码:649 / 663
页数:15
相关论文
共 50 条
  • [41] USING ARTIFICIAL INTELLIGENCE METHODS FOR SYSTEMATIC REVIEW IN HEALTH SCIENCES: A SYSTEMATIC REVIEW
    Blaizot, A.
    Veettil, S. K.
    Saidoung, P.
    Moreno-Garcia, C. F.
    Wiratunga, N.
    Aceves-Martins, M.
    Lai, N. M.
    Chaiyakunapruk, N.
    VALUE IN HEALTH, 2022, 25 (07) : S517 - S517
  • [42] Using artificial intelligence methods for systematic review in health sciences: A systematic review
    Blaizot, Aymeric
    Veettil, Sajesh K.
    Saidoung, Pantakarn
    Moreno-Garcia, Carlos Francisco
    Wiratunga, Nirmalie
    Aceves-Martins, Magaly
    Lai, Nai Ming
    Chaiyakunapruk, Nathorn
    RESEARCH SYNTHESIS METHODS, 2022, 13 (03) : 353 - 362
  • [43] Artificial general intelligence for the upstream geoenergy industry: A review
    Li, Jimmy Xuekai
    Zhang, Tiancheng
    Zhu, Yiran
    Chen, Zhongwei
    Gas Science and Engineering, 2024, 131
  • [44] ASSUMING THE RISKS OF ARTIFICIAL INTELLIGENCE
    Stein, Amy L.
    BOSTON UNIVERSITY LAW REVIEW, 2022, 102 (03) : 979 - 1035
  • [45] A Systematic Literature Review on Artificial Intelligence and Explainable Artificial Intelligence for Visual Quality Assurance in Manufacturing
    Hoffmann, Rudolf
    Reich, Christoph
    ELECTRONICS, 2023, 12 (22)
  • [46] Artificial Intelligence to Improve Antibiotic Prescribing: A Systematic Review
    Amin, Doaa
    Garzon-Orjuela, Nathaly
    Pereira, Agustin Garcia
    Parveen, Sana
    Vornhagen, Heike
    Vellinga, Akke
    ANTIBIOTICS-BASEL, 2023, 12 (08):
  • [47] Artificial Intelligence Techniques in Medical Imaging: A Systematic Review
    Azizi, Abdellah
    Azizi, Mostafa
    Nasri, Mbarek
    INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING, 2023, 19 (17) : 66 - 97
  • [48] Using artificial intelligence for systematic review: the example of elicit
    Nathan Bernard
    Yoshimasa Sagawa Jr
    Nathalie Bier
    Thomas Lihoreau
    Lionel Pazart
    Thomas Tannou
    BMC Medical Research Methodology, 25 (1)
  • [49] Artificial Intelligence in Tourism Environments : A Systematic Literature Review
    Harahap, Eka Purnama
    Sediyono, Eko
    Hasibuan, Zainal Arifin
    Rahardja, Untung
    Hikam, Ihsan Nuril
    2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022, 2022,
  • [50] Artificial intelligence in urban forestry-A systematic review
    de Lima Araujo, Henrique Cesar
    Martins, Fellipe Silva
    Philippi Cortese, Tatiana Tucunduva
    Locosselli, Giuliano Maselli
    URBAN FORESTRY & URBAN GREENING, 2021, 66