In his new book Shop Class as Soul­craft, Michael Craw­ford shares a num­ber of fas­ci­nat­ing insights about the nature of work, its eco­nomic his­tory, and its role in the main­te­nance of our indi­vid­ual moral char­ac­ter. I found it a cap­ti­vat­ing read, encour­ag­ing me to think about the dis­tant forces of tenure and rep­u­ta­tion that impact my judg­ments as a teacher and researcher and to recon­sider to what extent I let them intrude upon what I know my work demands.

Buried through­out his enlight­en­ing dis­course, how­ever, is a strike at the heart of computing—and in par­tic­u­lar, automation—as a tool for human good.

His argu­ment is as follows:

“Rep­re­sent­ing states of the world in a merely for­mal way, as “infor­ma­tion” of the sort that can be coded, allows them to be entered into a log­i­cal syl­lo­gism of the sort that com­put­er­ized diag­nos­tics can solve. But this is to treat states of the world in iso­la­tion from the con­text in which their mean­ing arises, so such rep­re­sen­ta­tions are espe­cially liable to nonsense.“

This non­sense often gives machine, rather than man, the authority:

“Con­sider the angry feel­ing that bub­bles up in this per­son when, in a pub­lic bath­room, he finds him­self wav­ing his hands under the faucet, try­ing to elicit a few sec­onds of water from it in a futile rain dance of guessed-at mudras. This man would like to know: Why should there not be a han­dle? Instead he is asked to sup­pli­cate invis­i­ble pow­ers. It’s true, some peo­ple fail to turn off a man­ual faucet. With its blan­ket pre­sump­tion of irre­spon­si­bil­ity, the infrared faucet doesn’t merely respond to this fact, it installs it, giv­ing it the sta­tus of nor­malcy. There is a kind of infan­tiliza­tion at work, and it offends the spir­ited personality.“

It’s not just a lack of accu­rate con­tex­tual infor­ma­tion, how­ever, that is miss­ing from the infrared faucet, thiev­ing our con­trol to save water. Craw­ford argues that there is some­thing unique that we do as human beings that is crit­i­cal to sound judg­ment, but inim­itable in machines:

”… in the real world, prob­lems don’t present them­selves in this predi­gested way; usu­ally there is too much infor­ma­tion, and it is dif­fi­cult to know what is per­ti­nent and what isn’t. Know­ing what kind of prob­lem you have on hand means know­ing what fea­tures of the sit­u­a­tion can be ignored. Even the bound­aries of what counts as “the sit­u­a­tion” can be ambigu­ous; mak­ing dis­crim­i­na­tions of per­ti­nence can­not be achieved by the appli­ca­tion of rules, and requires the kind of judg­ment that comes with experience.“

Craw­ford goes on to assert that this human expe­ri­ence, and more specif­i­cally, human exper­tise, is some­thing that must be acquired through sit­u­ated engage­ment in work. He describes his work as a motor­cy­cle mechanic, artic­u­lat­ing the role of men­tor­ship and fail­ure in acquir­ing this sit­u­ated expe­ri­ence, and argues that “the degra­da­tion of work is often based on efforts to replace the intu­itive judg­ments of prac­ti­tion­ers with rule fol­low­ing, and cod­ify knowl­edge into abstract sys­tems of sym­bols that then stand in for sit­u­ated knowledge.”

The point I found most damn­ing was the designer’s role in all of this:

“Those who belong to a cer­tain order of society—people who make big deci­sions that affect all of us—don’t seem to have much sense of their own fal­li­bil­ity. Being unac­quainted with fail­ure, the kind that can’t be inter­preted away, may have some­thing to do with the lack of cau­tion that busi­ness and polit­i­cal lead­ers often dis­play in the actions they under­take on behalf of other people.“

Or soft­ware design­ers, per­haps. Because design­ers and pol­icy mak­ers are so far removed from the con­texts in which their deci­sions will man­i­fest, it is often impos­si­ble to know when soft­ware might fail, or even what fail­ure might mean to the idio­syn­cratic con­cerns of the indi­vid­u­als who use it.

Crawford’s claim that soft­ware degrades human agency is dif­fi­cult to con­test, and yet at odds with many core endeav­ors in HCI. As with the faucet, defi­cient mod­els of the world are often at the root of usabil­ity prob­lems and yet we per­sist in believ­ing we can rid of them with the right tools and meth­ods. Context-aware com­put­ing, as much as we try, is still in its infancy in try­ing to cre­ate sys­tems that come remotely close in mak­ing fac­sim­i­les of human judg­ments. Our efforts to bring machine learn­ing to the fold may help us rea­son about prob­lems that were before unrea­son­able, but in doing so, will we inad­ver­tently com­pel peo­ple, as Craw­ford puts it, “to be that of a cog … rather than a think­ing per­son”? Even infor­ma­tion sys­tems, with their focus on rep­re­sen­ta­tion, rather than rea­son­ing, frame and fix data in ways that we never intended (as in Facebook’s recent release of phone num­bers to mar­keters).

As HCI researchers, we also have some role to play in Crawford’s para­dox about tech­nol­ogy and consumerism:

“There seems to be an ide­ol­ogy of free­dom at the heart of con­sumerist mate­r­ial cul­ture; a promise to dis­bur­den us of men­tal and bod­ily involve­ment with our own stuff so we can pur­sue ends we have freely cho­sen. Yet this dis­bur­den­ing gives us fewer occa­sions for the expe­ri­ence of direct respon­si­bil­ity… It points to a para­dox in our expe­ri­ence of agency: to be mas­ter of your own stuff entails also being mas­tered by it.“

Are there types of soft­ware tech­nol­ogy that enhance human agency, rather than degrade it? And to what extent are we, as HCI researchers, fur­ther­ing or fight­ing this trend by try­ing to make com­put­ing more acces­si­ble, ubiq­ui­tous, and context-aware? These are moral ques­tions that we should all con­sider, as they are at the core of our community’s val­ues and our impact on society.