[Themaintainers] Data & Society AI in Context Report: The Labor of Integrating New Technologies

[Lee Vinsel]

Dear Madeleine,

Thank you so much for sharing this report with the list. Just a few days
ago, I got up on a soap box to preach to a grad student about how we needed
to see many more studies of adoption - or integration as you are putting it
- in science and technology studies, broadly construed. It's not totally
surprising but totally fascinating nonetheless that when we get into the
guts of integration, maintenance and repair come to the fore. It reminds me
a bit of Orr's book about Xerox repair people, Talking about Machines

I'm also really interested in how you've found that the use of these
technologies often goes hand in hand with the economics of precarious and
stressful work!

Anyway, great work. I'll definitely be using your report in my classes.

Best,

Lee



On Mon, Feb 4, 2019 at 7:03 PM Madeleine Clare Elish <mce2102 at columbia.edu>
wrote:

> Hello Maintainers community!
>
> I'm a long-time reader and fan, first time poster. I wanted to share with
> you all a Data & Society <http://datasociety.net> research report my
> colleague Alexandra Mateescu and I published last week, AI in Context:
> The Labor of Integrating New Technologies
> <https://datasociety.net/output/ai-in-context/>. The report argues
> through brief case studies (in retail and farming) that moving automated
> and "AI" systems into existing work environments requires significant —and
> often unacknowledged — human labor (of course, we’re preaching to the choir
> here on this list!) One intervention we propose is to use the language of
> “integration” rather than “deployment” when talking about introducing new
> technologies in order to force attention to the social contexts at stake,
> and we use the paper to explore the implications of that difference for
> workers.
>
> This is a public audience report (hopefully good for students, too!),
> though we draw deeply on literatures around labor and digital technologies
> (including many scholars on this list!).
>
> In particular, I think folks might be interested in the section that
> discusses self-check out machines and workers experiences in a southern
> California grocery store (pp 34-49). Below I've included some excerpts to
> pique your interest.
>
> If you have questions or would like to discuss further, please do be in
> touch!
>
> Thanks,
> Madeleine
>
> Some particularly relevant passages:
>
> "As this section has shown, the impact of these retail technologies has
> generally not been one of replacing human labor. Rather, they facilitate
> cost-cutting measures such as relying more heavily  on  part-time
> employees,  understaffing,  and  intensifying  work  activities. In this
> context, employers can place greater pressures on  frontline  workers  to
> absorb  the  consequences  of  these  business  decisions.  In  other
> words,  the  “success”  of  technologies  like  self- checkout machines is
> in large part produced by the human effort  necessary to maintain them."
> (44)
>
> "Filling  the  gap  between  shoppers  and  checkout  machines requires a
> different skill set than that of simply operating a  check  stand,  more
> akin  to  that  of  a  traffic  officer  coordinating   vehicles  at  a
> convoluted  intersection.  As  one  sales  manager  said,  'Usually, we
> want our most experienced cashiers on these robots. '" (46)
>
> "Workers monitoring self-checkout need competencies including diagnosing
> a  shopper’s source of confusion, being able to spot potential theft, and
> dealing with the fatigue of maintaining attention, multitasking, and
> standing  for  long  stretches  of  time.  In  some  cases,  frontline
> employees  had  also  taught  themselves  to  do  basic  mechanical  and
> software  repairs,  since  the  machines  often  broke  down  and
> managers  were  reluctant  to  call  in  a technician.  Luis,  a
> cashier  in  his 50s, described how he was often called upon to fix
> mechanical issues, such as unjamming the cash dispensers. Although this was
> not  a  part  of  his  official  job  description,  he  gained  a
> reputation  among staff as being “mechanically inclined” because of his
> previous work experience repairing Bell and Howell equipment in the 1990s."
> (47)
>
> "While  retailers  experiment  with  new  ways  of  reconfiguring
> shopping practices through technology, frontline employees struggle to
> compensate  for  these  new  systems’  shortcomings." (48)
>
>
> --
> Madeleine Clare Elish
>
> Research Lead | AI on the Ground Initiative
> <https://datasociety.net/research/ai-on-the-ground/>
> Data & Society Institute <http://www.datasociety.net/>
> 36 West 20th Street, 11th Floor
> New York, NY 10011
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>


-- 
Assistant Professor
Department of Science, Technology, and Society
Virginia Tech
leevinsel.com
Twitter: @STS_News
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