To Shoot Or Not To Shoot

Why Haven’t We Got What We Want?

• The world is filled with insensitive SILLY people.

• Our publication rate is excessively modest.

• We really don’t have that much to say.

Automation Usage Decisions (AUDs)

AUDs- Choices in which a human operator has the option of relying upon manual control or one or more levels of automation (LOAs) to perform a task.

Optimal AUD-Operator relies upon the form of control that is most likely to result in a correct decision.

Some AUDs Are Commonplace

Checkbooks may be balanced with a calculator or by mental computation

Automobiles can be set to cruise control or the driver may operate the accelerator pedal

Stock purchases may be based on the output of software programs or investors may depend upon their subjective assessment of the market

Some AUDs Have Historic Consequences

Casey Jones Pearl Harbor

Some AUDs Have Historic Consequences

USS Greenville 2000 Election

Types of Suboptimal AUDs

Misuse is over reliance, operator employs automation when manual control or a relatively low LOA has a greater likelihood of success

Disuse is the under utilization of automation, operator manually performs a task that could best be done by a machine or a higher LOA.

Beck, Dzindolet, & Pierce (2002)

Appraisal Errors-Soldier misjudges the relative utilities of the automated (CID) and non-automated (e.g., view through gun site) options.

Intent Errors-Soldier disregards the utilities of the alternatives when making AUDs.

Intent Errors: Two Images of an Operator

An operator is a single-minded individual whose sole object is to maximize task performance

An operator‘s decision to rely on automation is based on a number of contingencies only one of which is to achieve a successful performance.

To Shoot Or Not To Shoot

Since 1900, 10% to 25% of US war fatalities in resulted from fratricide

John Henry Effect

John Henry Effect: Operators respond to automation as a challenger, competitor, or threat.

Increasing the operator’s personal involvement with the non-automated alternative augments the likelihood of a John Henry Effect.

John Henry Effect

Variables that increase the strength of a John Henry Effect augment operators‘ preference for the non-automated over the automated alternative

Heightened preference for the non-automated option should: 1) increase disuse and 2) decrease misuse

Design

2 (Operator: Self-reliant, Other-reliant) x 2 (Machine Performance: Inferior, Superior) x 14 (Trial Blocks) design

Dependent Variable: Suboptimal AUDs (Superior Machine: Basing credit point on the operator’s performance; Inferior Machine: Basing credit on the machine’s performance)

Credit Choice Screen

Sample Helicopter Photograph

Sample Helicopter Photograph

Operator Response Screen

CID Response Screen

Results Screen

Hypotheses

• Self-reliant operators will be less likely to base credit points on the CID than other-reliant operators

• Therefore– Disuse will be greater in the self-superior

than in the other-superior condition – Misuse will be higher among other-inferior

than self-inferior persons

Disuse

• Figure 1. Mean suboptimal automation usage decisions (AUDs) as a function of operator and trial block for persons working with the superior machine.

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Trial Blocks (20 Trials Per Trial Block)

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Misuse

• Figure 2. Mean suboptimal automation usage decisions (AUDs) as a function of operator and trial block for persons working with the inferior machine.

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Trial Blocks (20 Trials Per Trial Block)

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Conclusions

1) Self-reliant and other-reliant operators were yoked. Each had the same information. It seems reasonable to conclude that the difficulty in determining the optimal AUD was approximately equal in both conditions. Thus, the large differences in suboptimal AUDs were probably due to intent rather than appraisal errors.

2)Results support the hypotheses that factors which augment the degree of personal involvement or challenge from automated devices will increase the probability of disuse and decrease the likelihood of misuse

A Few Implications

1) Operator training programs should attempt to attenuate intent as well as appraisal errors.

2) At least on this task, intent errors were a significant source of suboptimal AUDs

3) Both appraisal and intent errors are sufficient to produce suboptimal AUDs

4) It will be a hollow achievement if advances in our knowledge of hardware and software is matched by an equally sophisticated comprehension of the causes and control of misuse and disuse.

That’s All Folks