Human Factors in Automated and Robotic Space Systems Proceedings of a Symposium (1987) / Chapter Skim
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Sharing Cognitive Tasks Between People and Computers in Space Systems
Sharing Cognitive Tasks Between People and Computers in Space Systems
Pages 418-443
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From page 418... ...
. Mutation is have been accelerating nearly 25 percent yearly, the cost of logic haggle has been draping Dally rapidly, and the Elation work dorm Lath each unit of ~v has An rising thirty percent per am.
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From page 419... ...
_` _~_ __. People can Berate with imprecise ark somewhat in~lete plans, and they can extrapolate Bed pat experiences to navel situations while Agonizing that they are indeed Operating outside ache limits of their direct experience (A11en, 1982; Dreyfus and l~reyfus, 1986; Mbray, 1986; Reason, 1986; Winograd and Flores, 1986~.
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From page 420... ...
For exa=le, experimental studies of people who Ale being paid law haIrly wages for making repel ted choice between two cleanly defined, attract synods that have no implications for later events probably say lithe abed he an behavior In Pro-life settings where actions may have per~;istent arm Dismally significant I= arm Me actors may no even perceive ~chenselves as having choices. Tersely, broad generalizations about the by riors of May people ~ diver~;e si - lotion probably say little about the behaviors of carefully Ale people who are performing Unusual tasks in Dish they have great experience.
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From page 421... ...
Creating Useful Workloads 3. Anticipating Human Errors 4.
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From page 422... ...
422 investigate Ire alternatives or to take a~mt of more contingencies than people consider. Computers may also adroit sew of the apical errors to with people typically fall prey, arm thus may draw same infer that pec$'le wed miss (Bcibrocr et al., 1986~.
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From page 423... ...
Outer pr~ra~i~ efforts that have begun by imitating human behavior have often ended up unwire techniques that made no pretense of imitatir~ human behaviors; arx! erasers and scientists have Reprised, without imitating human expertise, many techniques that enable computers to exceed ~ best of human capable ities.
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From page 424... ...
In what way should a decision-support sysbem's know' edge and logical rules fit each user individually? Given cpportNnities to tailor int~fa~= to their p~;onal preferences, inexperier~ users may design illterfa~= poorly (I=nais arx]
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From page 425... ...
Cnea~cing Useful Workloads A=oma~cic~n Is to malce chum; responsible for Rhine, -say Dams arm ~ leave the Tonne, difficult tasks for people. Cone ran for this may be me Option that r~onr~tine harks are interesting ark ballerina, arm Is worthy of hogan attention, w~P~as routme tacks appear -my awl ~int~ting, arxi so ante to people.
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From page 426... ...
426 r tend to work Isis ly when they are performing ~e kits of activities Mat card be automated. De Geyser also t however, potted cut that serious eminencies call for as not automation as possible because they produce extreme time pries, ~r~ly complex problems, and extreme dangers all of which greatly Engram the capabilities of human Repairs.
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From page 427... ...
So human~tcr systems Should also try to predict human errors ~ order to make serious errors unlikely in advance (Schneider et al., 1980; 5hneid~man, 19861. and more errecclve Bean cure, and rcs~rch on error pr~entlon But usefully cc~ler~nt the current projects.
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From page 428... ...
428 ABLE ~ Scam Error Categories arrt Prescriptions Forming the Wrong Intentions Made errors: misclassifications of systems' Awes Ascription errors: a~bigua~s statements of intentions Misdiagncees: Eliminate ~es. Give better indications of medic.
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From page 429... ...
observed: "I was startled to see how quickly arm hat very deeply people conversing with tF~TZA-1 be Optionally involved With the Muter arm how unequivocally they anthr~r~ihized it." Weizenbamn's Ore colorful examples concerned people who did not have close acq~In~cance with Muters. Nearly all of Of resorb on h~nan~ter interaction has face on people who laid thorough training and who had little experience winch is.
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From page 430... ...
430 T ~ 2 How Experienced Programmers' Performances Vary with Different Languages First experiment: answer questions about program specifications Normal F1 ~ t Program-design English Symbols language Time needed to answer: Forwar5-tracing questions 45.9 37.6 35.1 Backward-tracing questions 46.8 37.6 35.8 Input-output questions 42.9 39.4 41.0 Percent of programmers preferring 14 33 53 Second experiment: write and debug pro grams Normal Flowchart Program-design English Symbols Language T.ime needed ~ write and debug programs 29.7 23.9 20.5 Factor transactions before solution 37 39 32 Attempts before solution 3.0 2.7 2.2 Semantic errors 2.4 1.4 .8 % of programmers preferring 6 35 59 Third experiment: correct faulty programs T;~- needed to Normal Flowchart- Prrgra=-design English Symbols Language correct faulty prim 18.7 14.2 14.5 Attempts before solution I.9 2.2 1.9 Percent of programmers p ~ fearing 33 34 33 Fours experiment: edify and debug pr~rmns Normal Abbrexriated Program~esign E~glidlh English Iar~uage Tine no to n~ifir arxt dog 28.1 26.6 25.0 Semantic errors .9 1.
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From page 431... ...
Sedans can mat statements that nean aft anti - , or nathi~. Even a z,3stricted natural language, probably because it Isles unrestricted natural lar~uagel may Bake users pertain fat Ire Eve legitimate arm fitful to the catheter system (Jarke et al., 1985: shneiderman.
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From page 432... ...
Thus, interface languages that approximate natural languages ~ ght turn out to be more vane An space systems than in the situations that have been Died. Us mg Pe#ningfu1 interface Metaphors One very significant contribution to human-cc mputer interaction was Xerox's star interface, thin derived from many years of rest tsy many regear&hers.
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From page 433... ...
"me following main goals were ~r';ued In designing the Star user interface: firm; 1 far user ~ s conceptual Yodel arming are pointing versus ruing ark typing Hat you see is what you get universal cuds consistent y simplicity model- interaction user tai loran 1 its "...We decided ~ create electronic count~rts ~ the physical Objects in an office: paper, folders, file cabinets, mail boxes, ark so on an electronic metaphor for the office. We hoped this Acid make the electronic 'world' seen more familiar, less alien, and ~ less crainir~....
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From page 434... ...
Under stress, people tend to rearers fit - it specific, learned, complex models bac3` to generic, cc~mnon sense, simple models: Which of the equations that users have unleaded through tray d~= stress reawaken? Does stress, for instance,
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From page 435... ...
People play central roles in Locational activities because they serve as identifiable portals of referee In setting; that wood otherwise seem mechanistic, rate, and alien. Another of the apace
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From page 436... ...
Anticipating Human Errors Research on error prevention might tunefully complement the current projects on error detection and error tolerance. For many tasks, it would be feasible to explicate fairly accurate models Of people that would enable human-cecputer systems to predict and adapt to human errors.
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From page 437... ...
The people ^o Ate Space systems first receive thoralgh training, so gear deficits of ~e~ri~ce sand be small. Nearly all of the reseat ~ cat human ~ uter interaction has foals ~ on people who lacked thorough training and who had little experience with computers, so most of these findings may not extrapolate to the well-trained and experienced operators of space systems.
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From page 438... ...
Becalms= early decision off constrz`m later m~ifica~cions, astronauts and controllers should participate freon the Baird of any rear project. AC~=I~1~ mis report has beer improved by constructive suggestions Fran Michael Burlm, Janet l~kerich, Kenneth Inudon, Henry Incas, yes Milliken, Jon Larry, Carte Webster, faith Weigelt, and Hazily W~lbers.
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From page 439... ...
. an ave~iew ~ P~h and Practice Canfield Smith, D., Any, C., Shell, R., V=plar~c, B., arm Harslem, B
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From page 440... ...
M., armful whiten, W B., II 1985 Augmenting generic reseat with prototype evaluation: experience in applying generic research to Specific pros.
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From page 441... ...
Unwon: Academic E=ss. 1986 Recurrent errors in process environments: some implications for the design of ~nt=1ligent decision support systems.
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From page 442... ...
A 1984 Software ergonomics: effects of Inter application design parameters on Orator task perforate arm heals.
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From page 443... ...
D Woods, "c., Intelligent Decision Support In less Er~viroTments.
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