The concept of reliability is widely recognized across various academic disciplines. However, the conventional understanding of reliability varies by discipline, does not adequately address the intricate and ever-changing environments, and fails to account for the dynamic interactions between humans and artificial intelligence (AI) systems. To address these gaps, a new framework is proposed for considering reliability that accounts for performance on both supraordinate and subordinate objectives. By framing reliability in such a manner, the evaluation of systems can become more precise and research involving human-machine interactions can gain greater clarity. This is crucial for product designers and evaluators working to develop systems that meet end-use goals and comply with regulations. Researchers and practitioners alike need to rethink reliability in the context of AI systems, and this article proposes a new framework for understanding reliability.
Army Regulation 70-1 Research, Development, and Acquisition Army Acquisition Policy. (2018). Army.
2.
BahnerJ. E.ElepfandtM. F.ManzeyD. (2008). Misuse of diagnostic aids in process control: The effects of automation misses on complacency and automation bias. Proceedings of the Human Factors and Ergonomics Society, 2, 1330–1334. https://doi.org/10.1177/154193120805201906
3.
BaileyN. R.ScerboM. W. (2007). Automation-induced complacency for monitoring highly reliable systems: The role of task complexity, system experience, and operator trust. Theoretical Issues in Ergonomics Science, 8(4), 321–348. https://doi.org/10.1080/14639220500535301
4.
BowdenV. K.GriffithsN.StricklandL.LoftS. (2021). Detecting a Single Automation Failure: The Impact of Expected (But Not Experienced) Automation Reliability. Human Factors. https://doi.org/10.1177/00187208211037188
5.
BrownR. D.GalsterS. M. (2004). Effects of Reliable and Unreliable Automation on Subjective Measures of Mental Workload, Situation Awareness, Trust and Confidence in a Dynamic Flight Task. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 147–151. https://doi.org/10.1177/154193120404800132
6.
ChavaillazA.WastellD.SauerJ. (2016). System reliability, performance and trust in adaptable automation. Applied Ergonomics, 52, 333–342. https://doi.org/10.1016/j.apergo.2015.07.012
7.
de VisserE. J.BeattyP. J.EsteppJ. R.KohnS.AbubshaitA.FedotaJ. R.McDonaldC. G. (2018). Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents. Frontiers in Human Neuroscience, 12(309), 1–15. https://doi.org/10.3389/fnhum.2018.00309
8.
de VisserE. J.ParasuramanR. (2011). Adaptive Aiding of Human-Robot Teaming: Effects of Imperfect Automation on Performance, Trust, and Workload. Journal of Cognitive Engineering and Decision Making, 5(2), 209–231. https://doi.org/10.1177/1555343411410160
DuN.HuangK. Y.YangX. J. (2019). Not All Information Is Equal: Effects of Disclosing Different Types of Likelihood Information on Trust, Compliance and Reliance, and Task Performance in Human-Automation Teaming. Human Factors, 1–15. https://doi.org/10.1177/0018720819862916
11.
DuiH.ZhangC.BaiG.ChenL. (2021). Mission reliability modeling of UAV swarm and its structure optimization based on importance measure. Reliability Engineering & System Safety, 215, 107879. https://doi.org/10.1016/j.ress.2021.107879
12.
DzindoletM. T.PetersonS. A.PomrankyR. A.PierceL. G.BeckH. P. (2003). The role of trust in automation reliance. International Journal of Human Computer Studies, 58(6), 697–718. https://doi.org/10.1016/S1071-5819(03)00038-7
13.
ForoughiC. K.DevlinS.PakR.BrownN. L.SibleyC.CoyneJ. T. (2021). Near-Perfect Automation: Investigating Performance, Trust, and Visual Attention Allocation. Human Factors: The Journal of the Human Factors and Ergonomics Society, 001872082110328. https://doi.org/10.1177/00187208211032889
HuegliD.MerksS.SchwaningerA. (2020). Automation reliability, human–machine system performance, and operator compliance: A study with airport security screeners supported by automated explosives detection systems for cabin baggage screening. Applied Ergonomics, 86(April), 2–3. https://doi.org/10.1016/j.apergo.2020.103094
16.
HusseinA.ElsawahS.AbbassH. A. (2020a). The Reliability and Transparency Bases of Trust in Human-Swarm Interaction: Principles and Implications. Ergonomics, 1–20.
17.
HusseinA.ElsawahS.AbbassH. A. (2020b). Trust Mediating Reliability–Reliance Relationship in Supervisory Control of Human–Swarm Interactions. Human Factors, 62(8), 1237–1248. https://doi.org/10.1177/0018720819879273
18.
JohnO. (2012). Measurement:Reliability, construct validation, and scale construction Multiple Cultural Self-Identifications and Personal Social Networks View project Personality Measurement View project. https://www.researchgate.net/publication/232498571
19.
JohnsonJ. D. (2004). Type of Automation Failure: The Effects on Trust and Reliance in Automation. Georgia Institute of Technology.
20.
KaltenbachE.DolgovI. (2017). On the dual nature of transparency and reliability: Rethinking factors that shape trust in automation. Proceedings of the Human Factors and Ergonomics Society, 308–312. https://doi.org/10.1177/1541931213601558
21.
KatreinS. P. (2015). The Effect of Stages and Levels of Automation and Reliability on Workload and Performance for Remotely Piloted Aircraft Operations. Air Force Institute of Technology.
22.
KellerD.RiceS. (2009). System-wide versus component-specific trust using multiple aids. Journal of General Psychology, 137(1), 114–128. https://doi.org/10.1080/00221300903266713
23.
KöhlerT.CortinaJ. M.KurtessisJ. N.GölzM. (2015). Are We Correcting Correctly?: Interdependence of Reliabilities in Meta-Analysis. Organizational Research Methods, 18(3), 355–428. https://doi.org/10.1177/1094428114563617
24.
LittlewoodB.StriginiL. (2000). Software Reliability and Dependability: A Roadmap. Proceedings of the Conference on the Future of Software Engineering.
25.
LyonsJ. B.VoT.WynneK. T.MahoneyS.NamC. S.GallimoreD. (2020). Trusting Autonomous Security Robots: The Role of Reliability and Stated Social Intent. Human Factors, 1–16. https://doi.org/10.1177/0018720820901629
26.
MartinK. (2020). Cryptography: The Key to Digital Security, How It Works, and Why It Matters. WW Norton & Company.
27.
Masalonisa. J.ParasuramanR. (2003). Effects of Situation-Specific Reliability on Trust and Usage of Automated Air Traffic Control Decision Aids. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 47(3), 533–537. https://doi.org/10.1177/154193120304700359
28.
MetzgerU.ParasuramanR. (2005). Automation in future air traffic management: Effects of decision aid reliability on controller performance and mental workload. Human Factors, 47(1), 35–49. https://doi.org/10.1518/0018720053653802
29.
ModarresM.KaminskiyM. P.KrivtsovV. (2009). Reliability Engineering and Risk Analysis. In Reliability Engineering and Risk Analysis. CRC Press. https://doi.org/10.1201/9781420008944
30.
MorganD. E.TaylorD. J.CusteauG. (1977). A Survey of Methods for Improving Computer Network Reliability and Availability. Computer, 10(11), 42–50. https://doi.org/10.1109/C-M.1977.217563
31.
National Aeronautics and Space Administration. (2017). NASA-STD-8729.1A: NASA reliability and maintainability (R&M) standard for spaceflight and support systems. 1–52.
32.
NavarroJ.AllaliS.CabrignacN.CegarraJ. (2021). Impact of Pilot’s Expertise on Selection, Use, Trust, and Acceptance of Automation. IEEE Transactions on Human-Machine Systems, 1–10. https://doi.org/10.1109/thms.2021.3090199
33.
NiuJ.GengH.ZhangY.DuX. (2018). Relationship between automation trust and operator performance for the novice and expert in spacecraft rendezvous and docking (RVD). Applied Ergonomics, 71. https://doi.org/10.1016/j.apergo.2018.03.014
34.
OnnaschL. (2015). Crossing the boundaries of automation—Function allocation and reliability. International Journal of Human-Computer Studies, 76, 12–21. https://doi.org/10.1016/j.ijhcs.2014.12.004
35.
ParasuramanR.SheridanT. B.WickensC. D. (2008). Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs. Journal of Cognitive Engineering and Decision Making, 2(2), 140–160. https://doi.org/10.1518/155534308X284417
36.
PetritoliE.LecceseF.CianiL. (2018). Reliability and Maintenance Analysis of Unmanned Aerial Vehicles. Sensors, 18(9), 3171. https://doi.org/10.3390/s18093171
37.
RoshandelR. (2004). Calculating architectural reliability via modeling and analysis. Proceedings. 26th International Conference on Software Engineering, 69–71. https://doi.org/10.1109/ICSE.2004.1317426
38.
RossJ. M.SzalmaJ. L.HancockP. A.BarnettJ. S.TaylorG. (2008). The effect of automation reliability on user automation trust and reliance in a search-and-rescue scenario. In Proceedings of the Human Factors and Ergonomics Society (pp. 1340–1344). https://doi.org/10.1177/154193120805201908
39.
RossiA.DautenhahnK.KoayK. L.WalterM. L.WaltersM. L. (2017). How the Timing and Magnitude of Robot Errors Influence Peoples’ Trust of Robots in an Emergency Scenario. International Conference on Social Robotics, 526–535. https://doi.org/10.1007/978-3-319-70022-9
40.
RuijtersE.StoelingaM. (2015). Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools. Computer Science Review, 15–16, 29–62. https://doi.org/10.1016/j.cosrev.2015.03.001
41.
RyanM. (2020). In AI We Trust: Ethics, Artificial Intelligence, and Reliability. Science and Engineering Ethics, 26(5), 2749–2767. https://doi.org/10.1007/s11948-020-00228-y
42.
SalemM.LakatosG.AmirabdollahianF.DautenhahnK. (2015). Would You Trust a (Faulty) Robot?: Effects of Error, Task Type and Personality on Human-Robot Cooperation and Trust. ACM/IEEE International Conference on Human-Robot Interaction, 2015-March, 141–148. https://doi.org/10.1145/2696454.2696497
43.
SchraagenJ. M.ElsasserP.FrickeH.HofM.RagalmutoF. (2020). Trusting the X in XAI: Effects of different types of explanations by a self-driving car on trust, explanation satisfaction and mental models. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 339–343. https://doi.org/10.1177/1071181320641077
44.
SchwarzC.GasparJ.BrownT. (2019). The effect of reliability on drivers’ trust and behavior in conditional automation. Cognition, Technology and Work, 21(1), 41–54. https://doi.org/10.1007/s10111-018-0522-y
45.
SebokA.WickensC. D. (2017). Implementing Lumberjacks and Black Swans into Model-Based Tools to Support Human-Automation Interaction. Human Factors, 59(2), 189–203. https://doi.org/10.1177/0018720816665201
TenhundfeldN. L.BarrH. M.O’HearE. H.WegerK. (2022). Is My Siri the Same as Your Siri? An Exploration of Users’ Mental Model of Virtual Personal Assistants, Implications for Trust. IEEE Transactions on Human Machine Systems, 52(3), 512–521.
48.
TenhundfeldN. L.DavisJ. R.HublerM. (2022). Success by Undesirable Means: Differences in Trust Following Successful (Yet Deviant) Flight Path Adherence. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 66(1), 142–146. https://doi.org/10.1177/1071181322661097
49.
UdayP.MaraisK. (2015). Designing Resilient Systems-of-Systems: A Survey of Metrics, Methods, and Challenges: RESILIENT SoS DESIGN. Systems Engineering, 18(5), 491–510. https://doi.org/10.1002/sys.21325
50.
WiegmannD. A.WoodL. J.CohenT. N.ShappellS. A. (2022). Understanding the “Swiss Cheese Model” and Its Application to Patient Safety. Journal of Patient Safety, 18(2), 119–123. https://doi.org/10.1097/PTS.0000000000000810
