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

[Madeleine Clare Elish]

 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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