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Still Think Robots Can't Do Your Job? Essays on Automation and Technological Unemployment



Is Artificial Intelligence qualitatively different from other means of economizing the use of labor? Are we on the edge of a jobless society? If yes, are we ready for it? These are a few of the questions discussed in this collection of academic works. This book traces a brief history of the concept of technological unemployment; proposes a short-term scenario analysis concerning the relations between automation, education, and unemployment; analyzes the most recent literature on social robotics; examines the possible futures generated by the development of intelligent machines; shows the relation between automation and unemployment in an Italian case study; considers the impact if machines become effective pursuers of knowledge or even conscious; and addresses the role of serendipity in the development of science and technology.
Riccardo Campa
Libreria di Neoantropologia
A series edited by Riccardo Campa
Scientific Committee
Campa, Riccardo – Still Think Robots Can’t Do Your Job?
Essays on Automation and Technological Unemployment
ISBN: 9788894830200
Copyright D Editore © 2018. All right reserved.”
D Editore, Rome
Contacts: +39 320 8036613
This ebook is made with StreetLib Write editor”
Chapter 1. Technological Unemployment:
A Brief History of an Idea
Chapter 2. Automation, Education, Unemployment:
A Scenario Analysis
Chapter 3. The Rise of Social Robots:
A Review of the Recent Literature
Chapter 4. Technological Growth and Unemployment:
A Global Scenario Analysis
Chapter 5. Workers and Automata:
A Sociological Analysis of the Italian Case
Chapter 6. Pure Science and the Posthuman Future
Chapter 7. Making Science by Serendipity:
A review of Robert K. Merton and Elinor Bar-
ber’s The Travels and Adventures of Serendipity
The first industrial revolution ex-
tended the reach of our bodies, and
the second is extending the reach
of our minds. As I mentioned, em-
ployment in factories and farms
has gone from 60 percent to 6 per-
cent in the United States in the past
century. Over the next couple of
decades, virtually all routine phys-
ical and mental work will be auto-
Ray Kurzweil
This is one of those books that one writes hoping to be
wrong. The question with which I begin the book has recently
been asked quite often. I ask it also to myself: Do I still think
robots cannot do my job? My personal answer is simply “no”.
Sooner or later, there will be robots that can teach and do sci-
In spite of the fact that this is a collection of academic works,
I ask my readers to allow me the indulgence of introducing the
topic by offering a personal story.
I have always been fascinated by technologies, old and new,
and especially by Artificial Intelligence and robotics. Not by
chance, therefore, before turning into a social scientist I studied
electronics. Still, I could never turn my back to the unwanted
collateral effects of technological development.
When I was a teenager, I worked in a factory in summertime
as a manual worker in order to pay for my studies. It was the
1980s, when the first wave of robotization was hitting Italian
industries. I remember that every week a new machine was
“hired” by my company, and a few fellow workers fired. Being
seasonal workers we were not protected by long term contracts.
One day a computerized scale was introduced in my depart-
ment. It was pretty obvious that it was there to do the job of my
own team. I was at once fascinated and scared by that machine.
On the one hand I was curious to see how it worked, on the oth-
er I knew it might lead to my firing. When the meal break start-
ed, by getting close to the machinery, I heard the boss saying
that the hiring manager was looking but they had not yet found a
worker who could supervise its functioning. So instead of join-
ing my colleagues at the canteen, I started reading the instruc-
tion manual.
When the bell rang to signal the end of the meal break, I went
to the boss and told him that I was a student of electronics and I
knew how the scale worked. He was quite happy to have the
machinery immediately in function, and I was happy to leave the
physical work and turn into a supervisor. Even though I had to
wait until late that evening to eat, I did not even feel hungry. I
was proud of myself, and I thought my parents would be proud
of me also, if they just could see me. I was just sixteen years old
and it was only a modest seasonal job, but to me that “career ad-
vancement” meant a lot.
Still, what I predicted would happen, happened. My friends
and colleagues were fired. I knew it was not their “fault”. Even
if all of them did what I did—give up eating and study the in-
struction manual—only one supervisor was needed. The ma-
chine would have done the rest. I also know that some of those
friends did not find a new job for long time.
This happened almost thirty-five years ago. It was my first
experience with technological unemployment. By resorting to
sociological jargon, I can say that my first knowledge in the so-
ciology of work came from “participant observation.”
This probably explains why, once I became a professional
sociologist, I focused so much on technology and future of
work. I wrote much on these topics in both Italian and English.
In this volume I present several of my works written in the Eng-
lish language. As often happens in a collection of essays pub-
lished at different times, a few concepts and quotes are repeated.
However, I wanted to leave the writings in their original form,
as they were published by scientific journals. Here is a short de-
scription of the chapters.
The first chapter traces a brief history of the concept of tech-
nological unemployment. The historical narration covers four
centuries, since the beginning of the industrial revolution up to
the present. As a consequence, it is highly selective, mainly
based on sources in the English language and referring to only a
few of the many social scientists involved in the debate. The
scopes of the inquiry are essentially two. The first is to show
that focusing on technological unemployment as an idea and
not simply as a phenomenon is appropriate, because of the
high level of controversy that still characterizing the debate. The
second is to provide an understanding of critical societal chang-
es occurring in the twenty-first century.
The second chapter proposes a short-term scenario analysis
concerning the possible relations between automation, educa-
tion, and unemployment. In my view, the scenario analysis elab-
orated by the McKinsey Global Institute in 2013 underestimates
the problem of technological unemployment and proposes an
education model which is inadequate for handling the challenges
of twenty-first century disruptive technologies. New technologi-
cal advances – such as the automation of knowledge work – will
also affect the jobs of highly educated workers. Therefore, poli-
cy makers will not avert massive unemployment only by extend-
ing the study of math, science, and engineering. A better solu-
tion could be the establishment of a universal basic income, and
the elaboration of an education model capable of stimulating
creativity and the sense of belonging to a community.
In the third chapter I explore the most recent literature on so-
cial robotics and argue that the field of robotics is evolving in a
direction that will soon require a systematic collaboration be-
tween engineers and sociologists. After discussing several prob-
lems relating to social robotics, I emphasize that two key con-
cepts in this research area are scenario and persona. These are
already popular as design tools in Human-Computer Interaction
(HCI), and an approach based on them is now being adopted in
Human-Robot Interaction (HRI). As robots become more and
more sophisticated, engineers will need the help of trained soci-
ologists and psychologists in order to create personas and sce-
narios and to “teach” humanoids how to behave in various cir-
The aim of the fourth chapter is to explore the possible fu-
tures generated by the development of artificial intelligence. The
focus is on the social consequences of automation and robotiza-
tion, with special attention on the problem of unemployment. To
start, I make clear that the relation between technology and
structural unemployment is still hypothetical and, therefore, con-
troversial. Secondly, as proper scenario analysis requires, I do
not limit myself to predicting a unique future; instead I extrapo-
late from present data four different possible scenarios: 1) un-
planned end of work; 2) planned end of robots; 3) unplanned
end of robots; and 4) planned end of work. Finally, I relate these
possible developments not just to observed trends but also to
social and industrial policies presently at work in our society
which may change the course of these trends.
The aim of chapter five is to determine if there is a relation
between automation and unemployment within the Italian socio-
economic system. Italy is second in Europe and fourth in the
world in terms of robot density, and among the G7 it is the na-
tion with the highest rate of youth unemployment. Establishing
the ultimate causes of unemployment is a very difficult task, and
– as we said – the notion itself of ‘technological unemployment’
is controversial. Mainstream economics tends to correlate the
high rate of unemployment in Italy with the low flexibility of the
labor market and the high cost of manpower. Little attention is
paid to the impact of artificial intelligence and robots on the lev-
el of employment. With reference to statistical data, we will
show that automation can be seen at least as a contributory cause
of unemployment in Italy. In addition, we will argue that both
Luddism and anti-Luddism are two faces of the same coin both
focusing on technology itself (the means of production) instead
of on the system (the mode of production). Banning robots or
ignoring the problems of robotization are not effective solutions.
A better approach would consist in combining growing automa-
tion with a more rational redistribution of income.
The sixth chapter explores a more remote scenario, namely
the hypothesis that machines could sooner or later “wake up”,
become conscious, and have a role also in the pursuit of
knowledge. It is a scenario analysis that often goes under the
label of “transhumanism” and predicts the advent of the Singu-
larity. Since the industrial revolution, humans have tended to
reduce science to the ancillary role of an engine of technology.
But the quest for knowledge using rational, scientific methods
started at least two and a half millennia ago with the aim of set-
ting humans free from ignorance. The first scientists and philos-
ophers (at least that we know about because they wrote things
down) saw knowledge as the goal, not as the means. The main
goal was to understand the nature of matter, life, conscience,
intelligence, our origin, and our destiny, not only to solve practi-
cal problems. Being skeptical of myths and religions, they gave
themselves the goal to reach The Answer via rational and empir-
ical inquiry. Transhumanism is a unique philosophy of technol-
ogy because one of its goals is the creation of a posthuman intel-
ligence. Several scientists share this hope: Making technology
an ancillary of science, and not vice versa. By evolving and
reaching the Singularity, the hope is that posthumans can
achieve one the greatest dreams of sentient beings: finding The
In the seventh and last chapter I address the role of serendipi-
ty in the development of science and technology. It is a review
of Robert K. Merton and Elinor Barber’s book The Travels and
Adventures of Serendipity. A Study in Sociological Semantics
and the Sociology of Science. Although this book does not treat
the issue of technological unemployment directly, it critically
discusses the orthodox Marxist theory on automation. According
to this theory, scientific and technological discoveries are prod-
ucts of necessity. Industrial automation could not be developed
in ancient times, because of the slavery mode of production. The
cost of manpower was very low, so there was no need to pro-
duce machines. In the capitalistic mode of production character-
istic of modern times, however, slaves are not available, so ma-
chines can fit the bill. While there is truth in this narrative, it is
an oversimplification, because – as Merton and Barber convinc-
ingly argue – many scientific discoveries and technical inven-
tions depend on chance and serendipity. Indeed, the fact that
Heron and other Alexandrine engineers already projected and
built automatons in ancient times does not fit Marxist theory.
If we ask common people if we need conscious computers
and robots, the answer would probably be mixed, with – I guess
a majority against the idea. Personally, I am not prejudicially
against the idea, but I think we should also take into account the
possibility that conscious Artificial Intelligence may emerge
from a serendipitous discovery, in an unplanned way and regard-
less of its social necessity.
In fact, as the development of Artificial Intelligence pro-
gresses, we may ask whether serendipity – intended as the capa-
bility of making fortuitous discoveries, or the ability to find
something while we are looking for something else will be a
virtue we share with our mechanical children, or whether it will
be a factor – maybe THE factor – that continues to differentiate
humans from intelligent machines. In any case, we should con-
sider the role of serendipity when we reflect and speculate about
the future of work.
I am particularly indebted to Alan Sparks for his editorial con-
tributions to various parts of this book. Besides being an award-
winning non-fiction writer, Alan is also an accomplished com-
puter scientist and astute social observer, and discussions with
him have been very stimulating also with regard to content.
I am grateful also to Catarina Lamm for having translated
from Italian into English chapters four and five of this book1,
and to Matt Hammond and Lucas Mazur for having proofread
other fragments of the book. It goes without saying that any re-
maining inaccuracies in the facts or in the style are my own.
With regard to the title of this book, I have to credit Nikhil
Sonnad, who published a press article in digital magazine
Quartz entitled “Robot all too robot. Still think robots can’t do
your job? This video may change your mind” (2014). After
struggling to find a title, and after realizing that all the titles I
was thinking of were already used for other books, I decided to
borrow and reuse a fragment of that article title.
I also thank the readers of La società degli automi, a book
written in my native language, partly covering the same topic
but still more focused on Italian issues, that rapidly became a
bestseller in Italy. Without the positive feedback of the public,
my Italian publisher would have probably hesitated to print a
second book on automation and technological unemployment in
English. It will be a challenge also to D Editore to cross the bor-
ders and promote this book worldwide. So, the last thanks goes
to Emmanuele Pilia for accepting the challenge.
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... The prospect of integrated automation of work has been called the 'fourth industrial revolution' (Schwab, 2017), or the 'second machine age' (Brynjolfsson and McAfee, 2014). Several articles, books, and reports have pointed out that disruptive innovationssuch as advanced robotics, mobile connections, the Internet of things, the automation of cognitive work, Cloud technology, autonomous or semi-autonomous vehicles, nano-materials and nano-structures, energy storage techniques, 3D printers, to name but a fewcould lead to massive unemployment for workers engaged in routine tasks (Brynjolfsson and McAfee, 2011;Campa, 2018;Ford, 2015;Manyika et al., 2013;WEF, 2016). ...
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The aim of this article is to explore the possible futures generated by the development of artificial intelligence. Our focus will be on the social consequences of automation and robotisation, with special attention being paid to the problem of unemployment. In spite of the fact that this investigation is mainly speculative in character, we will try to develop our analysis in a methodologically sound way. To start, we will make clear that the relation between technology and structural unemployment is still controversial. Therefore, the hypothetical character of this relation must be fully recognized. Secondly, as proper scenario analysis requires, we will not limit ourselves to predict a unique future, but we will extrapolate from present data at least four different possible developments: 1) unplanned end of work scenario; 2) planned end of robots scenario; 3) unplanned end of robots scenario, and 4) planned end of work scenario. Finally, we will relate the possible developments not just to observed trends but also to social and industrial policies presently at work in our society which may change the course of these trends.
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In this article I explore the most recent literature on social robotics and argue that the field of robotics is evolving in a direction that will soon require a systematic collaboration between engineers and sociologists. After discussing several problems relating to social robotics, I emphasize that two key concepts in this research area are scenario and persona. These are already popular as design tools in Human-Computer Interaction (HCI), and an approach based on them is now being adopted in Human-Robot Interaction (HRI). As robots become more and more sophisticated, engineers will need the help of trained sociologists and psychologists in order to create personas and scenarios and to " teach " humanoids how to behave in various circumstances.
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The aim of this investigation is to determine if there is a relation between automation and unemployment within the Italian socioeconomic system. Italy is Europe's second nation and the fourth in the world in terms of robot density, and among the G7 it is the nation with the highest rate of youth unemployment. Establishing the ultimate causes of unemployment is a very difficult task, and the notion itself of 'technological unemployment' is controversial. Mainstream economics tends to relate the high rate of unemployment that characterises Italian society with the low flexibility of the labour market and the high cost of manpower. Little attention is paid to the impact of artificial intelligence on the level of employment. With reference to statistical data, we will try to show that automation can be seen at least as a contributory cause of unemployment. In addition, we will argue that both Luddism and anti-Luddism are two faces of the same coin. In both cases attention is focused on technology itself (the means of production) instead of on the system (the mode of production). Banning robots or denying the problems of robotisation are not effective solutions. A better approach would consist in combining growing automation with a more rational redistribution of income.