Human-in-the-loop
| Part of a series on |
| Machine learning and data mining |
|---|
Human-in-the-loop (HITL) is used in multiple contexts. It can be defined as a model requiring human interaction.[1][2] HITL is associated with modeling and simulation (M&S) in the live, virtual, and constructive taxonomy. HITL along with the related human-on-the-loop are also used in relation to lethal autonomous weapons.[3] Further, HITL is used in the context of machine learning.[4]
Machine learning
In machine learning, HITL is used in the sense of humans aiding the computer in making the correct decisions in building a model.[4] HITL improves machine learning over random sampling by selecting the most critical data needed to refine the model.[5]
Simulation
In simulation, HITL models may conform to human factors requirements as in the case of a mockup. In this type of simulation a human is always part of the simulation and consequently influences the outcome in such a way that is difficult if not impossible to reproduce exactly. HITL also readily allows for the identification of problems and requirements that may not be easily identified by other means of simulation.
HITL is often referred to as interactive simulation, which is a special kind of physical simulation in which physical simulations include human operators, such as in a flight or a driving simulator.
Benefits
Human-in-the-loop allows the user to change the outcome of an event or process. The immersion effectively contributes to a positive transfer of acquired skills into the real world. This can be demonstrated by trainees utilizing flight simulators in preparation to become pilots.
HITL also allows for the acquisition of knowledge regarding how a new process may affect a particular event. Utilizing HITL allows participants to interact with realistic models and attempt to perform as they would in an actual scenario. HITL simulations bring to the surface issues that would not otherwise be apparent until after a new process has been deployed. A real-world example of HITL simulation as an evaluation tool is its usage by the Federal Aviation Administration (FAA) to allow air traffic controllers to test new automation procedures by directing the activities of simulated air traffic while monitoring the effect of the newly implemented procedures.[6]
As with most processes, there is always the possibility of human error, which can only be reproduced using HITL simulation. Although much can be done to automate systems, humans typically still need to take the information provided by a system to determine the next course of action based on their judgment and experience. Intelligent systems can only go so far in certain circumstances to automate a process; only humans in the simulation can accurately judge the final design. Tabletop simulation may be useful in the very early stages of project development for the purpose of collecting data to set broad parameters, but the important decisions require human-in-the-loop simulation.[7]
Within virtual simulation taxonomy
Virtual simulations inject HITL in a central role by exercising motor control skills (e.g. flying an airplane), decision making skills (e.g. committing fire control resources to action), or communication skills (e.g. as members of a C4I team).
Examples
- Flight simulators
- Driving simulators
- Marine simulators
- Video games
- Supply chain management simulators[8]
- Digital puppetry
Misconceptions
Although human-in-the-loop simulation can include a computer simulation in the form of a synthetic environment, computer simulation is not necessarily a form of human-in-the-loop simulation, and is often considered as human-out-of-the loop simulation. In this particular case, a computer model’s behavior is modified according to a set of initial parameters. The results of the model differ from the results stemming from a true human-in-the-loop simulation because the results can easily be replicated time and time again, by simply providing identical parameters.
Weapons
Three classifications of the degree of human control of autonomous weapon systems were laid out by Bonnie Docherty in a 2012 Human Rights Watch report.[3]
- human-in-the-loop: a human must instigate the action of the weapon (in other words not fully autonomous)
- human-on-the-loop: a human may abort an action
- human-out-of-the-loop: no human action is involved
See also
- Humanistic intelligence, which is intelligence that arises by having the human in the feedback loop of the computational process[9]
- Reinforcement learning from human feedback
- MIM-104 Patriot - Examples of a human-on-the-loop lethal autonomous weapon system posing a threat to friendly forces.
References
- ^ "DoD Modeling and Simulation (M&S) Glossary", DoD 5000.59-M, DoD, January 1998 "Directives Division" (PDF). Archived from the original (PDF) on 2007-07-10. Retrieved 2009-04-22.
- ^ Karwowski, Waldemar, International encyclopedia of ergonomics and human factors, ISBN 0-415-30430-X, 9780415304306, CRC Press, 2006
- ^ a b Amitai Etzioni; Oren Etzioni (June 2017). "Pros and Cons of Autonomous Weapons Systems". army.mil.
- ^ a b Vikram Singh Bisen (May 20, 2020). "What is Human in the Loop Machine Learning: Why & How Used in AI?". medium.com.
- ^ Chelsea Chandler; Peter W Foltz; Brita Elvevåg (26 May 2022). "Improving the Applicability of AI for Psychiatric Applications through Human-in-the-loop Methodologies". Schizophrenia Bulletin. 48 (5): 949–956. doi:10.1093/schbul/sbac038. PMC 9434423. PMID 35639561.
- ^ Sollenberger, R. (2005). Human-in-the-Loop Simulation Evaluating the Collocation of the User Request Evaluation Tool. U.S. Department of Transportation Federal Aviation Administration, 1. Retrieved July 19, 2010, from http://hf.tc.faa.gov/technotes/dot-faa-ct-tn04-28.pdf Archived 2010-06-09 at the Wayback Machine
- ^ Human-in-the-loop simulation: (2007, Spring). Port Technology International, 32, 1-2. Retrieved July 19, 2010, from http://www.marinesafety.com/research/documents/HumanintheloopSimulationasPublishedinPortTechnologyInternationalIssue32.pdf Archived 2011-07-14 at the Wayback Machine
- ^ Pinto R, Mettler T, Taisch M (2013), Managing supplier delivery reliability risk under limited information: Foundations for a human-in-the-loop DSS, Decision Support Systems, 54:2, 1076–1084
- ^ [Minsky, Kurzweil, Mann, IEEE ISTAS 2013].
Notes
This article is a direct transclusion of the Wikipedia article and therefore may not meet the same editing standards as LIMSwiki.
