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Human-Automation Interaction

Foundational literature

11 volumes · 13 lab cases Every source: bibliography checked ✓

What is here

This shelf holds eleven foundational papers published between 1948 and 2010. They answer one question: once work is handed to a machine, what happens on the human side? Each node opens from one of four angles: a common belief put to the test, an experiment or incident, a design tradeoff, or two ideas that are usually run together. The research literature then answers it, and each page records how far its sources were checked.

Reading order

The order follows the argument rather than the publication dates. It runs in three groups, listed with their internal order in the node sequence below; every node carries its original year.

How to read across

Carry one question as you read: is the mechanism in this node another face of the previous one, or an independent second source? These papers cite each other: Bainbridge's argument that sustained monitoring must fail rests on Mackworth's vigilance work. Read them against each other and the eleven nodes close into one interlocking structure.

Content layers

The theory layer is fully open and may be reproduced, with attribution and a link back to the original page. The Lab case layer is a case-reading library. It is paid content under Trigpoint Pass and is not licensed for reproduction, though some cases are open to preview.

Node sequence

Suggested reading order · from the language of task allocation to the way out by design

1 · Task allocation and its paradoxOrder within the group: the original allocation proposal → the structural irony → the scale language that replaces it

Function allocation

Fitts list (MABA-MABA) · Fitts (1951)

The 1951 Fitts list splits system functions into "humans are better at" and "machines are better at", which later readers took to mean assigning each function to whichever side is stronger. It is where the study of human-machine division of labour begins. Its fatal assumption is that humans and machines are interchangeable containers, so allocating work means moving it across a line. Half a century later that assumption was refuted directly. Automation changes the character of the work it leaves behind.

Ironies of automation

Bainbridge (1983)

Automation set out to replace an unreliable human and ended up handing the hardest, most critical residual work to a human whose skills are decaying. The more successful the automation, the harder the human's role becomes.

Levels of automation

Sheridan & Verplank (1978) · Parasuraman, Sheridan & Wickens (2000)

Level of automation is a continuous scale, running from the human doing everything to the computer doing everything and not telling the human. The scale is also set stage by stage: information acquisition, information analysis, decision selection, and action execution can each sit at a different point. The idea that automation is a single switch is where most automation design errors begin.

Lab cases ×2

2 · The cost on the human sideOrder within the group: physiological limit → attention mechanism → performance consequence → awareness framework → measurement tool

Vigilance decrement

Mackworth (1948)

When a person watches a signal source that rarely changes, detection rate declines over time; in Mackworth's experiment it had dropped measurably within about thirty minutes (an order of magnitude, reported secondhand). So when the only safeguard is having someone watch the automation, the risk of a miss grows with time on watch, and the timing and size need calibrating to your own situation. This is not a discipline problem. It is a limit of human attention, and the fix belongs in the design, not in trying harder.

Lab cases ×3

Automation complacency and bias

Parasuraman & Manzey (2010)

Complacency and bias are two overlapping phenomena with attention at their core. Attention withdraws from the automation's output: on the monitoring side silent failures go unseen (complacency), on the decision side the system's recommendation is accepted without challenge (bias). It comes from how attention is allocated under multitask load, and long practice does not remove it.

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Out-of-the-loop performance problem

Endsley & Kiris (1995)

Automation turns the operator into a bystander, and situation awareness and hands-on feel drain away together. While everything is running normally the loss is invisible and costs nothing. Then the system fails and someone has to take over: comprehension has dropped and decisions after the failure come slower. That is the out-of-the-loop performance problem.

Situation awareness

Endsley (1995)

Situation awareness has three levels: perception (what is happening), comprehension (so what), and projection (what happens next). The levels ascend, and they are not strictly linear stages. It is the input to a decision, so when the picture is unclear, good judgement has nothing to work on.

Lab cases ×2

Mental workload (NASA-TLX)

Hart & Staveland (1988)

NASA-TLX takes mental workload, which cannot be measured directly, and breaks it into six ratable dimensions: mental demand, physical demand, temporal demand, own performance, effort, and frustration. Respondents then set the weights themselves through pairwise comparison, and the scores are combined into a weighted mean. What it measures is perceived workload. It is a self-report instrument and not an objective reading, and using it well starts with admitting that.

Lab cases ×1

3 · The way out by designOrder within the group: calibrating trust → classifying mismatch → dynamic allocation as intervention

Trust in automation

Lee & See (2004)

People decide whether to use automation on the basis of trust, and trust can be mismatched. Too much and they keep relying on a system that has stopped working; too little and a usable tool sits idle. The design goal was never to push trust higher. It is to calibrate trust against what the system can actually do.

Use, misuse, disuse, abuse

Parasuraman & Riley (1997)

The relationship between people and automation splits into four categories: appropriate use, and three ways it goes wrong: misuse (over-reliance), disuse (distrusted and left idle), and abuse (pushed through on the design side with no regard for human factors). Each of the three failure modes has its own causes and they feed each other. The most common managerial illusion is treating misuse and disuse as two ends of one dial.

Lab cases ×1

Adaptive automation

Scerbo (1996)

The division of labour does not have to be fixed at design time. It can move up and down during operation with load, state and performance. That is adaptive automation: the machine takes over when load peaks and hands back when it drops. The real governance question is who decides to shift, the system or the person.

Lab cases ×2

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