From the New York Review of Books, May 24:
Self-Tracking 
by Gina Neff and Dawn Nafus
MIT University Press, 248 pp., $15.95 (paper)
Sociometric Badges: State of the Art and Future Applications
by Daniel Olguín Olguín and Alex (Sandy) Pentland
IEEE 11th International Symposium on Wearable Computers, Boston, October 2007, available at vismod.media.mit.edu/tech-reports/TR-614.pdf
Machine, Platform, Crowd: Harnessing Our Digital Future
by Andrew McAfee and Erik Brynjolfsson
Norton, 402 pp, $29.95
In her seminal work The Managed Heart: Commercialization of Human Feeling (1983),
the sociologist Arlie Russell Hochschild described a workplace practice
known as “emotional labor management.” Hochschild was studying the
extreme kinds of “emotional labor” that airline stewardesses, bill
collectors, and shop assistants, among others, had to perform in their
daily routines. They were obliged, in her words, “to induce or suppress
feeling in order to sustain the outward countenance that produces the
proper state of mind in others.” In the case of airline stewardesses,
the managers and human resources staff of the airline companies relied
on reports from passengers or management spies to make sure that
stewardesses kept up their cheerful greetings and radiant smiles no
matter what.
The stewardesses Hochschild studied were working
under a regime of “scientific management,” a workplace control system
conceived in the 1880s and 1890s by the engineer Frederick Winslow
Taylor. Workers subject to such regimes follow precise, standardized
routines drawn up by managers and undergo rigorous monitoring to ensure
that these routines are followed to the letter. Taylor’s practice is
often associated with such factory workplaces as the early Ford Motor
plants or today’s Amazon “fulfillment centers,” where workers must
perform their prescribed tasks on a strict schedule.
Hochschild
showed that regimes of scientific management could be applied virtually
anywhere. Her airline company managers aspired to control every aspect
of their employees’ emotional conduct. What kept them from doing so was
that they weren’t actually present in plane cabins during flights and so
had to rely on haphazard reporting to confirm that the stewardesses
were always behaving as they should. But in the twenty-first century,
new technologies have emerged that enable companies as varied as Amazon,
the British supermarket chain Tesco, Bank of America, Hitachi, and the
management consultants Deloitte to achieve what Hochschild’s managers
could only imagine: continuous oversight of their workers’ behavior.
These technologies are known as “ubiquitous computing.” They yield
data less about how employees perform when working with computers and
software systems than about how they behave away from the computer,
whether in the workplace, the home, or in transit between the two. Many
of the technologies are “wearables,” small devices worn on the body.
Consumer wearables, from iPhones to smart watches to activity trackers
like Fitbit, have become a familiar part of daily life; people can use
them to track their heart rate when they exercise, monitor their insulin
levels, or regulate their food consumption.
The new ubiquity of
these devices has “raised concerns,” as the social scientists Gina Neff
and Dawn Nafus write in their recent book Self-Tracking—easily
the best book I’ve come across on the subject—“about the tremendous
power given to already powerful corporations when people allow companies
to peer into their lives through data.” But the more troubling sorts of
wearables are those used by companies to monitor their workers
directly. This application of ubiquitous computing belongs to a field
called “people analytics,” or PA, a name made popular by Alex “Sandy” Pentland and his colleagues at MIT’s Media Lab.
Pentland has given PA
a theoretical foundation and has packaged it in corporate-friendly
forms. His wearables rely on many of the same technologies that appear
in Self-Tracking, but also on the sociometric badge, which does
not. Worn around the neck and attached to microphones and sensors, the
badges record their subjects’ frequency of speaking, tone of voice,
facial expressions, and body language. In Sociometric Badges: State of the Art and Future Applications
(2007), Pentland and his colleague Daniel Olguín Olguín explained that
the badges “automatically measure individual and collective patterns of
behavior, predict human behavior from unconscious social signals,
identify social affinity among individuals…and enhance social
interactions by providing feedback.”
The badges
and their associated software are being marketed by Humanyze, a Boston
company cofounded by Pentland, Olguín Olguín, and Ben Waber among others
(Waber was formerly one of Pentland’s researchers at MIT and is now the
company’s CEO). Under its original name, Sociometric Solutions, the
company got early commissions from the US Army and Bank of America. By
2016 Humanyze had among its clients a dozen Fortune 500 companies and
Deloitte. In November 2017 it announced a partnership with HID Global, a
leading provider of wearable identity badges, which allows HID to
incorporate Humanyze’s technologies into its own products and so expands
the use of such badges by US businesses.
The main tool in Humanyze’s version of PA
is a digital diagram in which people wearing sociometric badges are
represented by small circles arrayed around the circumference of a
sphere, rather like the table settings for diners at a banquet. Each
participant is linked to every other one by a straight line, the
thickness of which depends on what the system considers the “quality” of
their relationship based on the data their badges collect.
In a 2012 essay for the Harvard Business Review, Pentland described how this method was used to evaluate the performance of employees at a business meeting in Japan.1 The PA
diagram for Day One showed that the lines emanating from two members of
an eight-person team, both of whom happened to be Japanese, were
looking decidedly thin. But by Day Seven, the diagrams were showing that
the “Day 1 dominators” had “distributed their energy better” and that
the two Japanese members were “contributing more to energy and
engagement.” Evidently some determined managerial nudging had taken
place between Days One and Seven. In a June 2016 interview with MEL
Magazine, Waber claimed that little escapes the gaze of the sociometric
badge and its associated technologies: “Even when you’re by yourself,
you’re generating a lot of interesting data. Looking at your posture is
indicative of the kind of work and the kind of conversation you’re
having.”2
In a 2008 article Pentland commended his PA systems for being more rational and dependable than their human counterparts.3 But the “intelligence” of his and Waber’s PA
systems is not that of disembodied artificial intelligence—whatever
that may look like—but of corporate managers with certain ideas about
how their subordinates should behave. The managers instruct their
programmers to create algorithms that in turn embed these managerial
preferences in the operations of the PA systems. Pentland and Waber’s PA
regime is in fact a late variant of scientific management and descends
directly from the “emotional labor management” Hochschild discussed in The Managed Heart.
But these twenty-first-century systems have powers of surveillance and
control that the HR managers of the airline companies thirty years ago
could only dream of.
Not all PA systems depend on wearable devices. Some target landlines and cell phones. Behavox, a PA
company financed by Citigroup, specializes in the surveillance of
employees in financial services. “Emotion recognition and mapping in
phone calls is increasingly something that banks really want from us,”
Erkin Adylov, the company’s CEO, told a reporter in 2016.4
Behavox’s website advertises that its systems give “real-time and
automatic tracking” of aspects of employee conversation like the
“variability in the timing of replies, frequency in communications, use
of emoticons, slang, sentiment and banter.” The company, in the words of
a recent Bloomberg report,
scans petabytes
of data, flagging anything that deviated from the norm for further
investigation. That could be something as seemingly innocuous as
shouting on a phone call, accessing a work computer in the middle of the
night, or visiting the restroom more than colleagues.5
“If you don’t know what your employees are doing,” Adylov told another reporter in 2017, “then you’re vulnerable.”
Most
PA
software providers rely on combinations of wearables and computer-based
technologies to monitor and control workplace behavior. These companies
boast that their systems can find out virtually everything there is to
know about employees, both in the workplace and outside it. “Thanks to
modern technology,” in the words of Hubstaff, a
PA company based in Indianapolis, “companies can monitor almost 100 percent of employee activity and communication.”
6
Max
Simkoff, the cofounder of San Francisco’s Evolv Corporation (now taken
over by Cornerstone, another Humanyze competitor), has said that his PA
systems can analyze more than half a billion employee data points
across seventeen countries and that “every week we figure out more
things to track.” Kronos Incorporated, a management software firm based
in Lowell, Massachusetts, claims that its workforce management systems
are used daily by “more than 40 million people” and offer “immediate
insight into…productivity metrics at massive scale.”7
Microsoft entered the PA
market when it acquired the Seattle-based company Volometrix in 2015.
It inherited Volometrix’s “Network Efficiency Index” (NEI), which
measures how efficiently employees build and maintain their “internal
networks.” The index is calculated by dividing “the total number of
hours spent emailing and meeting with other employees” by the number of
“network connections” an employee manages to secure. The NEI’s
recognition of an employee’s network connection depends on whether
encounters with coworkers have met both a “frequency of interaction
threshold” and “an intimacy of interaction threshold,” the latter of
which is satisfied when there are “2 or more interactions per month
which include 5 or fewer people total.”8
When
workers fail to meet these thresholds, other workplace technologies can
be enlisted to give them a nudge. One Humanyze client created a robotic
coffee machine that responded to data collected from sociometric badges
worn by nearby employees. By connecting to Humanyze’s Application
Programming Interface (API), the coffee machine could assess when a
given group of workers needed to interact more; it would then wheel
itself to wherever it could best encourage that group to mingle by
dispensing lattes and cappuccinos.9
When American managers want to install PA
surveillance systems, employees rarely manage to stop them. In Britain,
an exception to this trend occurred in January 2016, when journalists
at the London office of the Daily Telegraph came to work one
Monday and found that management had affixed small black boxes on the
undersides of their desks that used heat and motion sensors to track
whether or not they were busy at any given time. Seamus Dooley of the UK
National Union of Journalists told The Guardian that “the NUJ will resist Big Brother–style surveillance in the newsroom.” The boxes were removed.10
The Telegraph’s journalists were right to act as they did. A 2017 paper by the National Workrights Institute in Washington, D.C.,11
cites a wealth of academic research on the physical and psychological
costs that intrusive workplace monitoring can have on employees. A study
by the Department of Industrial Engineering at the University of
Wisconsin has shown that the introduction of intense employee monitoring
at seven AT&T-owned companies led to a 27 percent increase in
occurrences of pain or stiffness in the shoulders, a 23 percent increase
in occurrences of neck pressure, and a 21 percent increase in back
pain. Other research has suggested that the psychological effects of
these technologies can be equally severe. Many of Bell Canada’s
long-distance and directory assistance employees have to meet
preestablished average work times (AWTs). Seventy percent of the workers
surveyed in one study reported that they had “difficulty in serving a
customer well” while “still keeping call-time down,” which they said
contributed to their feelings of stress to “a large or very large
extent.”
How have the corporate
information-technology community and its academic allies justified these
practices and the violations of human dignity and autonomy they entail?
Among economists, Erik Brynjolfsson at MIT is perhaps the leading
counsel for the defense. With Andrew McAfee, also of MIT, he has
published two books to this end, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (2014) and Machine, Platform, Crowd: Harnessing Our Digital Future (2017), the latter clearly written with a corporate audience in mind.
In the opening chapter of Machine, Platform, Crowd,
they write that “our goal for this book is to help you.” The “you” in
question is a corporate CEO, CIO, or senior executive who might be
saddled with obsolete technologies—in Brynjolfsson and McAfee’s words,
“the early-twenty-first-century equivalent of steam engines.” Each
subsequent chapter ends with a series of questions aimed at such
readers: “Are you systematically and rigorously tracking the performance
over time of your decisions?”
Although the use of information
technology in the workplace is a dominant theme of Brynjolfsson and
McAfee’s two books, the authors say nothing about the surveillance
powers of People Analytics or its predecessors, whose existence cannot
easily be reconciled with the glowing vision they describe in the
opening chapters of The Second Machine Age. There are, for instance, eighteen references to Amazon in The Second Machine Age and Machine, Platform, Crowd.
All of them are to technological breakthroughs like the company’s
“recommendation engine,” which reduces search costs so that “with a few
checks over two million books can be found and purchased.”...MUCH MORE
