Ethnography and Engineering: How Qualitative … social life of cars. We found ... Questionnaires...
Transcript of Ethnography and Engineering: How Qualitative … social life of cars. We found ... Questionnaires...
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Ethnography and Engineering: How Qualitative Methods can Help Build the Car of
the Future Tyler Brickle , Stephen Gonzalez, Logan McLaughlin, and Heather S. Roth (University of North Texas)
Paper Presented at the Society for Applied Anthropology Annual Meeting
March 27, 2015
The central theme of this session is the role of qualitative data in the
“quantitative” world of business; however in this paper, we seek to challenge that
dichotomy because it is not always the most salient way to categorize research methods
in projects conducted within the high tech sector. Secondary to this theme is the value of
ethnography to the fields of engineering and technology. We intend to support these
theses based on our participation in an applied research project led by Dr. Christina
Wasson in partnership with the Nissan Research Center in Silicon Valley (NRC-SV), a
lab dedicated to developing autonomous vehicle technology (AV). Dr. Brigitte Jordan
consults at the NRC-SV and acted as lab liaison to the class during this project. The
research was conducted as part of a Design Anthropology course which took place
between August and December of 2014.
While other papers in this session describe situations in which the key
methodological contrast was the
use of qualitative versus
quantitative data, the contrast
between our class project and the
methodology used by the Lab was
ethnography versus experiment.
Our class undertook a decidedly
ethnographic approach to analyze
the social life of cars. We found
that in engineering research on
autonomous vehicles, there is a
heavy emphasis on experimental
methodologies, that is to say
various forms of testing. These
methods can be both quantitative
and qualitative. With regard to
qualitative methods, labs focus on
lean research because of the
perception that there is not
enough time to study the way
people behave over long periods.
They use market surveys and
bring people into the lab for qualitative evaluation and testing.
The idea of a self-driving car is not a new one; writers have been envisioning such
things since the early days of science fiction. By the 1950s it had even entered into the
public consciousness with fantastical advertisements for America’s Electric Light and
Power Companies, as shown in Figure 1. However it has only been within the last decade
that the technology for such a future may finally be in reach. The Defense Advanced
Figure 1: "Electricity May be the Driver, one day your car may speed along an electric super-highway, speed and steer controlled by electronic devices embedded in the road. Highways will be made safe - by electricity!” (Paleofuture.com) )2010).
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Research Projects Agency’s (DARPA) first driverless car challenge was issued in 2002.
Fifteen teams competed in the challenge but none of them were able to get their vehicles
to complete the seven mile course set in the Mojave Desert (DARPA 2014). One year
later they reconvened and several teams were able to complete the challenge. It was a
sign that driverless vehicles were possible. By 2009, Google hired many of these same
researchers to carry on their work. As a result of these initial autonomous vehicle
prototypes, AV research has now been kicked into high gear. This is an emerging and
rapidly developing field, so the academic literature on the topic is sparse. No doubt a lot
of research is hiding behind Non-Disclosure Agreements as companies battle to get the
first true AV experience on the road. Every major car manufacturer is entering the fray,
but what methods are they using to design these driverless cars? And how are
anthropologists and other social scientists contributing to the research and design of these
vehicles? (Or rather, how could they contribute?) The following sections explore the
existing literature and current landscape of the industry, specifically the methodologies
being used in the research and design of connected and autonomous vehicles, our own
project with Nissan Research Center in Silicon Valley (NRC-SV), and our
recommendations for the future of AV research.
Literature and Industry Review As previously mentioned, the academic literature on AV is still sparse, even
among various engineering and transportation journals (CAR 2012). This is especially
true for anthropology, but even if we explore cars more broadly, there has only been
some limited ethnography completed about various car cultures around the world (Miller
2001). In other disciplines, sociologists and psychologists have often assisted in market
research by exploring the personal and emotional aspects of car ownership. Sheller
(2004) speaks about car consumption as never being simply about rational economic
choices, but also about "aesthetic, emotional and sensory responses to driving." We
expected these types of responses in our own research, indeed the engineers and
researchers at NRC-SV expected it as well. However we found that the majority of our
participants were led by rational economic choices. Even the owner of a brand new 2014
red Mustang convertible viewed his car as primarily a vehicle for work, his previous
Jaguar ”dream” vehicle was ultimately unable to meet the functional needs he required.
And so the question of whether society at large is ready to ‘give up’ driving may not be
as problematic as one might think. Evidence shows that fewer and fewer teenagers are
acquiring their driver's license, with only 49% of 17 year olds getting theirs in 2008
compared to 75% in 1978 (KPMG and CAR 2012).
The world of automated driving is a veritable alphabet soup, so it is important to
establish some terminology first. Although our project was aimed at exploring current
driver behavior in order to better inform NRC-SV's design of AV technology, and indeed
the current research zeitgeist gripping the industry is directed towards fully autonomous
vehicles, even the most optimistic scenarios don't envision a fully automated world for at
least two decades (Lin et al 2013). In the interim, vehicle-to-vehicle (V2V) and vehicle-
to-infrastructure (V2I) communication technologies are being tested in pilot programs
around the country (Narla 2013). Known collectively as V2X in the U.S. and Car2X in
Europe, such technologies will be instrumental in an AV world. From an infrastructure
standpoint, another umbrella term is intelligent transportation systems (ITS). ITS refers to
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the myriad of telecommunications and traffic management systems being developed to
handle all the data that V2X technologies will create (Narla 2013).
Historically, automotive research has taken place in an experimental paradigm,
usually in the form of driving simulations or usability testing of new prototype
technologies. However, recent technological advances have led to a more “quasi-
ethnographic” method that seeks to observe driver behavior unobtrusively for long
periods of time (Nes et al 2013). This methodology is termed ‘naturalistic driving studies’
or NDS for short. One of the primary means of data collection used by NDS researchers
is the use of low-instrumented cars (LICs) and highly instrumented cars (HICs). These
vehicles contain different kinds of data acquisition systems, ranging from GPS loggers to
eye-tracking equipment, interior and exterior video cameras, and speed, acceleration, and
steering sensors (Valero-Mora et al 2013). Some examples of NDS studies include cell
phone usage in the car (Fitch 2014), holistic sensing and active displays (Trivedi and
Cheng 2007), and right-turn behavior when in the presence of bicyclists (Nes et al 2013).
Valero-Mora et al (2013) looked at three NDS research programs in the UK, Greece, and
Spain, comparing and contrasting the pros and cons of each. One of their conclusions was
that for all the massive amounts of information that can be collected, analyzing hundreds
of hours of video and sensor data is simply not feasible (Valero-Mora et al 2013). These
NDS studies are actually quite similar to our own project in terms of their goal to observe
driving behavior. Yet where NDS projects focus on collecting massive amounts of data
and video with participants driving test cars in test situations, our study relied on
ethnographic fieldwork with individuals driving their own cars in everyday life.
Although NDS studies put an emphasis on observing the behavior of driving, our
project sought to make the act of driving visible, understanding more of its intricacies
than just the behavior itself. There has been little exploration about what people actually
do while they drive in everyday life. Certainly, the naturalistic driving studies described
above attempt just that, but only in response to very narrow research questions. The
broader ethnography of cars is curiously lacking when you consider that driving has been
a ubiquitous activity for a large segment of human society for the past century.
Questionnaires and surveys have been used to explore consumer attitudes towards
the coming shift to connected vehicle and AV technology. Of note to us is a survey of
public opinion on AV technology conducted in the U.S., U.K., and Australia (Schoettle
and Sivak 2014). A similar study by Payre et al (2014) used a mixed methods approach,
first conducting limited interviews about AV technology and then building a
questionnaire out of those results. A previous study by the Center for Automotive
Research conducted focus groups for Michigan’s Department of Transportation (CAR
2012). These studies all seem to suggest the same thing, that people are cautiously
optimistic about AV technology.
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In terms of coming technology developments, Google has aggressively pioneered
the AV landscape, and they want their driverless cars on the road by 2017 (Newcomb
2014). Nissan has announced that their Autonomous Drive technology will be available
to consumers by 2020 (Newcomb 2014). Mercedes-Benz, whose current vehicles already
contain some of the most advanced driver assistance technology on the market, officially
unveiled their luxurious F 015 autonomous concept earlier this year at the Consumer
Electronic Show (Wilson 2015). Their vision is decidedly more futuristic, with a chromed
out body, swivel chairs, and more LEDs and touchscreens than you can count. In
contrast, Toyota has stated
unequivocally that they are
not making a driverless car
but that hasn’t stopped them
from developing an
Advanced Safety Research
Lexus, capable of steering
itself in certain driving
conditions (Newcomb 2014).
Toyota stated at the 2014
ITS World Congress that
they see driving as a,
“collaboration between the
driver and technology”
(Newcomb 2014). Similarly,
GM has announced that
certain 2017 Cadillac models
will have Super Cruise
Technology, providing
hands-off (and feet-off)
braking, speed control, and
lane following (Newcomb
2014). Perhaps the hope for
some manufacturers is that
all this driver assistance will
just slowly turn into true AV
before consumers notice.
Google doesn’t seem
interested in being subtle
though; their prototypes have
already ditched the steering
wheel and look less like cars
and more like the driverless pods that are already operating at the Heathrow Airport in
London, as shown in Figure 2.
Figure 2: (Top) - London Heathrow PRT Pod (Sharpe 2011). (Bottom)- Google self-driving car (Google self-driving car project 2014).
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So how are all these cars and systems actually being designed? Again, it is
difficult to know exactly what’s going on behind closed doors at these companies, and to
what extent they may be using ethnography or other qualitative methods in their research
and design. One high-profile, public testing ground that is currently under construction,
and expected to be open later this year, is the M City facility at the University of
Michigan in Ann Arbor. Under the newly established Mobility Transformation Center,
the M City facility will be a one of a kind testing ground for connected and autonomous
vehicles. It is being supported by both
U.S. and Michigan Departments of
Transportation as well as a number of
corporate sponsors, including car
manufacturers Ford Motor Company,
GM, Honda, Nissan, Toyota, and other
businesses like Delphi Automotive, State
Farm, Verizon, and Xerox (Mobility
Transformation Center 2015). The
Mobility Transformation Center is also
collaborating across multiple university
departments, so the research to be
conducted will hopefully be varied in
discipline, theory, and methodology, see
Figure 3.
Sophisticated testing facilities
will be complementary to sophisticated
infrastructure and connected networks. As
Zafiroglu (2013) mentions in response to Healy’s glorious vision of an automated
wonderland (2013), smart cars are useless without smart roads. The Institute of
Transportation Engineers echoed Zafiroglu’s sentiments in a recent survey where
respondents felt “they are on the sidelines in the creation of these technologies" (Lin et al
2013). Anthropologists are often called upon to be the cultural negotiators in such
instances. We can continue to do so even in the realm of advanced technologies like AV
cars, bridging the gap between designers, engineers, traffic management, and consumers
(Zafiroglu 2013).
Our Project So, where do the realms of anthropology and engineering overlap when it comes
to the design of AV technologies? A close examination of our project will reveal how it
served as a supplement to the qualitative, quantitative, and experimental work the lab had
already done. This serves as a basis for a discussion about research methodologies and
how ethnography can contribute to the future of AV. Our project was exploratory and
ethnographic in the sense that we employed an array of qualitative research methods that
added a contextual richness that is so often overlooked in the engineering world at the
fuzzy front end. Most notably we wanted to answer: what is the social life of the car?
And how can our understanding of driving impact self-driving cars?
A total of 18 student researchers were paired in teams of two, one design student
and one anthropologist, for a total of nine teams. Each of these teams then recruited a
Figure 3: University Partners (Mobility Transformation Center 2015)
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study participant from the Dallas/Fort Worth metroplex. The study participants consisted
of friends, friends of friends and family members in a convenience sample of the
population. Although not truly representative, student researchers attempted to gather a
sample population of varying demographics with an age range from early twenties to
mid-sixties with an even balance of genders to better understand the views of the truly
massive possible user base for AV.
Our investigation was divided into three sections: a pre-driving interview, a
driving observation, and finally a post-driving interview. To understand driving habits
and behaviors among participants, we conducted in-depth, open-ended interviews. During
the pre-driving interview participants were asked to give the researchers a walk-through
of the car and unpack its contents and discuss what objects they carry in their car. The
researchers also employed participant observation to understand and make visible the
natural act of driving. During the driving observation, participants were accompanied on
a variety of different activities such as commuting to work, taking children to gym class,
and purchasing items from a gas station. The post-driving interview allowed the
researchers to reflect on the experience of driving to derive a richer understanding of the
ethnographic process.
Since each section was video recorded, we did not have to rely solely on memory
to find meaning in the micro-interactions between drivers and their cars. Each pair of
student researchers wrote a set of field notes, which correlated to the video recordings via
precise timestamps. This resulted in 27 total sets of field notes that were then analyzed
and coded using online qualitative analysis software known as Dedoose. This process
allowed the researchers to link participants’ behaviors and attitudes together, creating
patterns that offered insight into how people act and what they do when they drive. The
findings generated by this process allowed researchers to make design recommendations
for the Lab.
Discussion: challenging the assumptions of the session
Going into this project the class was aware that the NRC-SV had already
collected a vast amount of technical knowledge on the subject of cars, yet their
conclusions were derived from an experimental research framework. Thus our class
sought to address the gaps in knowledge formed from qualitative research conducted
experimentally in a lab versus qualitative research conducted ethnographically in a
natural setting. Not only would we answer questions about cars and driving through
ethnographic context, but we would also develop a more complex vision for future
research by demonstrating the usefulness of ethnography to an experimental framework.
In our specific case it was not a clash between the cold science of quantitative
methods and the rich personal nature of qualitative methods, but rather an entirely new
methodological framework. This is because we cannot label our methods wholly
qualitative and those of the lab wholly quantitative. In our case it was unavoidable to
quantify the data in order to understand the importance and frequency of certain patterns
of behavior. Such that, when we communicated our data to the Lab, we often phrased
patterns in terms of “x out of nine participants demonstrated behavior y.” For example
seven out of nine participants sang in their cars. We recognized the importance of
including client needs. As young scholar-practitioners, our goal was to adapt to the
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research culture of the Lab and complement their methods with ours, not clash with them.
This exercise realistically integrated anthropology in the high tech sector.
The research methods we used allowed us to gain a fresher, more nuanced
perspective of how people actually drive and understand their cars by redefining the
interactions between researcher and study participant that are not typically seen in an
experimental approach. For instance the necessity of building rapport was paramount to
obtaining a genuine level of social interaction between student researcher and study
participant. We met drivers in their homes, at cafes, and outside of their workplace,
flipping the logic of laboratory-experimental settings and disbanding the anonymity of
market survey research. Researchers carefully guided the pre and post interviews by
asking open-ended questions, allowing participants to digress on themes most important
to them. Student researchers also sat in the cars of study participants, observing them in
their natural setting while driving. The presence of a researcher is something that was
truly innovative in our study. Finally, and most importantly, we studied participants
driving their very own cars. Naturalistic driving studies often neglect this crucial detail,
instead mounting sensors and cameras in test vehicles to objectively record the driver’s
interactions (Valero-Mora et al 2013). We argue that much is lost in this process. The
subtleties of ethnographic fieldwork generate a compelling set of rich, contextual data
previously untapped by experimental methodologies that employed similar methods.
The utilitarian relationship drivers had with their cars is just one example of a
finding our ethnographic methodology uncovered in direct contrast to market research
studies investigating the same phenomenon. Student researchers found that drivers had
utilitarian relationships with their cars rather than an emotional attachment. This finding
was revealed through a series of discoveries researchers stumbled upon after gently
prompting participants to answer open-ended questions about the exterior of their own
car. For example one participant mentioned a broken door handle that may have gone
unnoticed from mounted cameras and sensors. In addition, the participant explained
further that the broken door handle had been in that condition for quite some time without
being fixed. Other participants experienced obnoxiously loud engines and dents in the
exterior as trivial annoyances to the functionality of the vehicle. The car’s ability to travel
was the important thing, and this logic was used to put off repairs because they were too
expensive or deemed unnecessary. These findings may challenge current market-studies
that label the car as a significant portion of the American identity. Furthermore, instead of
mounting sensors and video cameras on the car, student researchers actively explored the
exterior and interior of the vehicle themselves, driving along, and empirically
investigating what naturalistic driving studies could not possibly do.
Thus the traditional dichotomy of quantitative versus qualitative did not actually
exist in our research. Instead our study aimed to add substance, focusing on people’s
natural driving habits that could not be reproduced in a lab. This allowed us to add to the
complexity of the Lab’s wealth of experimental data, rendering a more complete picture
of the driving experience. The goal of our project was to include context and social
interaction during research and present the Lab with findings that could not come from
their own methods of data collection. This speaks to the value of ethnography in the high
tech sector and to a greater shift in the business sector for practicing anthropologists. Our
class learned to respond to client needs, preparing the next generation of scholar-
practitioners as adaptable superheroes in the corporate sector and beyond. Research
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cultures will differ for every startup, business, and organization in the field, rendering the
quantitative-qualitative dichotomy one way to describe the difference in methodological
styles, but not necessarily the only way. We as students are already learning how to seek
creative avenues that combine various research methodologies and adapt to different
contexts by extending ethnographic richness to whatever industry in which we may find
ourselves.
In this way anthropological methods have the potential to leave a huge impact on
AV technology and it is precisely the relationship between ethnographic and
experimental methodologies that can catalyze the process. The project we did is only the
first step into a new type of hybridized ethnographic perspective on design, one that
builds on the experiments and methods that engineers have already built. The division
between quantitative and qualitative is an epistemological artifact of an age before
applied anthropology and an age before mixed methods became commonplace. Much like
the engineers setting their sights on a future of automated vehicles, we too must set our
sights on a future of integrating ethnography, not solely qualitative methods into design
research.
The future of AV research The future of AV is not a distant one, in a sense we are no longer designing “the
car of the future” in some science fiction sense; we are designing the car of today. We’ve
already painted a picture of the AV landscape and, in short, AV technology extends far
beyond this research with NRC-SV. So where does that situate applied research, not only
within the scope of AV but of the technology sector as well? How do we need to adapt
ethnography to supplement the experimental paradigm the tech sector has come to rely
on? One of the things we found seemingly most important in our research was easing the
transition into AV technology for people. Not only were we concerned with the
affordances of AV and how they can meet the basic performance requirements of the user
base, but looking into how to make people comfortable with the idea of a car without a
driver.
Exploratory user research can offer quite a bit to both designers and engineers
when it comes to proper prototyping and testing of new products or technologies. AV is a
technology that will fundamentally change the lives of millions of people, so there are
important questions to ask about accessibility and safety. These grey areas have obvious
anthropological considerations because cars are embedded within cultures, which
significantly impacts their use around the world. We really have to ask the question if AV
technology can meet the needs of all of its users within our very own culture. Other
important stakeholders we have to consider are both the internal and external consumers
of AV technology, as end users and as intermediaries, the car companies themselves, and
the industries related to cars that will be influenced by the advancement of AV
technology.
These are all issues we can tackle with applied anthropology, not only
understanding the initial implications of AV, but how the technology itself will impact
society. This initial research opens doors into projects looking at commuters who use
public transit so we can better understand what people may do with the time they would
otherwise spend driving. We can determine the implications AV will have for long haul
freight services and how factories will need to innovate to produce these new vehicles.
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We can look at how cities will have to change the urban landscape to accommodate the
transition to autonomous vehicles. There are many other implications to the existence of
AV technology, much like the introduction of the home computer or the smart phone,
which could fundamentally change the way we live our day-to-day lives. The way people
drive their cars and the overall user experience is critical to understand, but these are by
no means the only aspects of AV that we as anthropologists can or even should take on
with ethnographic study.
Conclusion Mixed methods approaches are the cornerstone of industry research, so much so
that the traditional dichotomy of quantitative and qualitative methods is one that needs to
be expanded upon. While the quantitative-qualitative dichotomy is a reliable, traditional
starting place, research cultures of various industries may demonstrate new dichotomies,
much like the one we identified during our project. In the fluid and innovative high tech
sector, it is a set of interdisciplinary methods that should become the focus of how
anthropology can have an impact on the world of engineering and business. Therefore we
should endeavor to bring ethnography, in as full a sense as we can, into the
varied research cultures applied practitioners find themselves in.
Ethnography is our lens of choice to examine the messy present and explore
issues beyond the fuzzy front-end. Understanding that human behavior is often chaotic in
all of its varying contexts, we need to consider these contexts that extend into our very
own workplaces and research. The project conducted by our design class adapted and
integrated an ethnographic approach to the Lab’s experimental research model. For that
reason we were able to innovate, reinforce, and add valuable, rich information to NRC-
SV’s understanding of the human factors of AV. They had already used surveys
conducted by other groups and tested mockups of dashboard prototypes with people.
What we did differently was what came naturally to us as anthropologists, we went into
our own lab of the real world, and conducted research in the way that we knew how,
ethnographically. All of these experiences have led us to conclude that in order to treat
“Anthropology as a Profession” we must adapt to the myriad of professional worlds, their
distinct research cultures, and aggressively demonstrate the value of ethnographic context
for innovative technological projects.
Acknowledgements
Special thanks to Dr. Christina Wasson and Dr. Brigitte Jordan for making this project
possible and to the entire Design Anthropology Class for working on the project: Cate
Ferman, Chris Ferrell, Marwah Halwani, Hira Hasan, Austin Hartt, Alexandra Hickling,
Jung Kim, Luis Machado, Andy Pottkotter, Molly Shade, Tricia Smith, Amanda
Whatley.
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