Content uploaded by Michele Loi
Author content
All content in this area was uploaded by Michele Loi on Aug 19, 2015
Content may be subject to copyright.
Technological unemployment and human
disenhancement
“It is questionable if all the mechanical inventions yet made have lightened the day’s
toil of any human being.”
(John Stuart Mill, Principles of Political Economy, IV.6.9)
Introduction
In the debate on human enhancement, little attention has been spent on the threat that
ICT technologies, while greatly expanding the capacities and welfare of a minority,
may reduce those of the majority of the population. Borrowing a term from bioethics,
I refer to this possibility as human disenhancement. Here I will argue that ICT
technologies can be disenhancement technologies on account of how they influence
the creation and elimination of human jobs: they may disenhance more humans than
they enhance.
To support this claim, I provide the example of innovation in machine
intelligence, which substitutes human skills characteristic of middle-class jobs,
1
This is an excerpt of “Technological unemployment and human
disenhancement”, forthcoming in Ethics and Information Technology.
The published paper is available at
http://link.springer.com/article/10.1007/s10676-015-9375-8?
wt_mc=email.event.1.SEM.ArticleAuthorOnlineFirst
You can email me loimichele@gmail.com for a pre-publication draft of
the paper.
making these jobs redundant. As an effect, more people may be forced to find jobs
that are less amenable to automation, but which, paradoxically, may turn out to be less
desirable than the jobs most humans could find in the past. This undermines one of
the arguments supporting machine use, namely that machines substitute men in hard
physical tasks, then release man from the burden of heavy workloads, hazardous work
environments, boring and repetitive tasks, and close supervision by other humans. I
will argue that, given the tendency of job polarization we already observe, the
opposite may turn out to be the case. By eliminating predominantly middle-skills,
middle-class jobs, ICT technologies may “disenhance” more individuals than they
enhance.
The conclusions I reach are not immediately translatable into policy advice.
My purpose here is only to argue that current innovation in ICT has a morally
problematic aspect. There is no doubt that ICT innovation is puzzling and difficult to
assess from a moral point of view. There are at least three different reasons for this:
first, the relation between economic data and theory is uncertain; second, statistical
data may be hard to interpret; third, different technologies can have significantly
different effects, so sweeping generalizations are difficult to sustain. However, moral
theory can be applied to real world issues only if we rely on the best available
evidence, which is sometimes uncertain. We rely on the evidence we have in order to
specify what are the possible, and not entirely unlikely, scenarios we face. Any
argument of this kind has to rely on uncertain empirical premises and will support
possible, not apodictic conclusions. But this is no reason to refuse to engage with
moral arguments, as these possibilities are really important.
Indeed, it is surprising how little attention recent developments in ICT
technology have received within normative applied philosophy, in spite of the wealth
2
of relevant data and attention in the media (Autor and Dorn 2013b; Krugman 2012;
Stajic et al. 2015). While economists have investigated the relation between computer
innovation, wages and employments, normative political and moral philosophy has
been mostly silent on this issue.
I conjecture that the silence of moral and political philosophy, in striking
contrast to the attention paid to the possibility of genetic human enhancement, rests on
a common optimistic preconception, which I will refer to as the humanistic fallacy.
The humanistic fallacy
The tendency to assume that the substitution of human work by
machines will leave (most) humans with better jobs, than those
humans have now.
Why “humanistic”? Because the fallacy may rest on the belief of an a priori
connection between what humans can do relatively better and what is really
worthwhile for them to do.
This paper has two specific goals: one is to expose the fallacy in the argument
above. The second is to present empirical evidence, mostly from economics, of
machines leaving humans with worse jobs than the ones they had before these
technologies were introduced. In the last century, technological innovations have
generally improved the conditions of human work, by replacing humans in positions
that were repetitive, uncomfortable, and physically exhausting. Yet, as I shall show,
this has not always been the case and it need not be the case in the future.
I do not intend here to argue against human progress. Clearly we all derive the
benefits of the sacrifices of human workers in past generations. I concede that distant
generations, looking backwards, may easily be able to say the same about current
3
developments. But the benefit present generations derive from the sacrifices of the
working class during the first industrial revolution does not justify the exploitation of
those workers. More generally, the mere fact that one generation gains from sacrifices
made by another is not tantamount to a justification in terms of inter-generational
justice (Gosseries 2005; Rawls 1999, pp. 251–259; 263–264).
The paper has the following structure. After an introductory section clarifying the
definitions of enhancement (1), section (2) provides a short summary of relevant
findings and theories in the history of technology and economics. The humanistic
fallacy is rejected in section (3), while section (4) confronts the empirical evidence for
the new trends. Section (5) analyses and rejects an important objection, and section
(6) provides an ethical assessment of the threat of human disenhancement raised by
ICT innovation.
Conclusions
ICT innovation under current socio-economical institutions is associated with a
significant risk of human (welfarist) disenhancement. In theory, human workers
should be entitled to strict ethical oversight of technological innovation in their
workplace. They should be entitled to protection by “ethics committees”, analogous to
bioethics committees in biomedical research, with a mandate to protect the present
and long-term interests of human workers threatened by technological substitution.
Under conditions of global competition, adopting this policy in a single society will
cause more harm to workers, than it prevents, since it would impose a competitive
handicap on the first nation to adopt it. If, as it seems plausible, the required global
coordination to adopt this ethics committee at the global level is unlikely to be
4
achieved, other institutional solutions to protect the future interests of future human
workers must be sought.
One way to avert the undesirable implications of technological progress in
ICT is through institutional reforms only indirectly targeted at technological
innovation. For example, non conditional welfare systems (such as the basic income
proposal) provide greater incentives for private enterprises to develop and use
automation to replace human work in jobs that humans have less reasons to desire
(section 5). Alternatively, the state may directly invest in the creation of technology
that is more suitable to replace human work necessary for the least attractive jobs.
As already pointed out, the difference between past and future technological
unemployment is that the latter may affect middle-skill jobs to a greater extent than
low-skill ones. This is expected to exacerbate the competition for jobs at either ends
of the economic and social spectrum. Recent advances in natural language processing
(Hirschberg and Manning 2015), economic reasoning (Parkes and Wellman 2015),
and more broadly, machine learning and rationality (Jordan and Mitchell 2015;
Gershman et al. 2015), suggest that this cannot be considered any longer a scenario
“better left to science fiction than to science” (Stajic et al. 2015).
In the most optimistic scenario, advancements in education will significantly
raise the level of skill of the median worker. In theory, this could drive up the
productivity of human work: the median worker would acquire skills that are
complementary to machine intelligence, comparable to those well paid high-skill
workers have today. A large supply of well-trained workers will drive down the
wages associated with high-skills and make them a resource most companies can
afford to employ. In this way, better education may enable the “resurrection” of a
large number of jobs that will be “middle-class” (in economic and social terms), while
5
requiring higher skills than current middle-class jobs. In a less optimistic scenario,
demand for goods and services will support but a limited number of high-skill jobs. In
this case, the morally important function of education will be enabling more equal
opportunities to the relatively scarce good jobs at the top (Rawls 1999, p. 73). An
effective strategy to improve educational outcomes may require additional investment
in early education (Heckman 2008), or, more radically, the introduction of genetic,
pharmacological or public health approaches to intelligence enhancement (Bostrom
and Roache 2011; Sandberg and Savulescu 2011; Outram and Racine 2011). In other
words, biomedical enhancement may become a necessity to merely counterbalance
human disenhancement due to increased competition with machine intelligence.
Genetic enhancement may contribute to equality of opportunity as well, by mitigating
natural inequalities in IQ.
What about software creators? My provisional, defeasible, conclusion is that
they are not subjects of special obligations. Technological disenhancement is a
systemic risk, not an individual responsibility. Well-intentioned attempts by
individuals to prevent harmful future social outcomes are rarely successful. If only
because of significant coordination problems, they require institutional, not
individual, solutions (Rawls 1996; Williams 1998). In conclusion, a moral view
requiring software creators, as individuals, to voluntarily refrain from making
progress in software creation would be unreasonably demanding.
References
Arneson, R. J. (1999). Human Flourishing versus Desire Satisfaction. Social
Philosophy and Policy, 16(1), 113–142.
Autor, D. H. (2010). The Polarization of Job Opportunities in the U.S. Labor Market:
Implications for Employment and Earnings. Jointly released by The Center for
6
American Progress and The Hamilton Project.
http://cdn.americanprogress.org/wp-
content/uploads/issues/2010/04/job_polarization_report.html
Autor, D. H. (2014, August 21). Polanyi’s Paradox and the Shape of Employment
Growth. prepared for the Federal Reserve Bank of Kansas City’s economic
policy symposium on “Re- Evaluating Labor Market Dynamics,” Jackson
Hole, Wyoming. http://economics.mit.edu/files/9835
Autor, D. H., & Dorn, D. (2013a). The growth of low-skill service jobs and the
polarization of the US labor market. The American Economic Review, 103(5),
1553–1597.
Autor, D. H., & Dorn, D. (2013b, August 24). How Technology Wrecks the Middle
Class. New York Times, pp. 24–27.
Autor, D. H., Levy, F., & Murnane, R. J. (2003). The Skill Content of Recent
Technological Change: An Empirical Exploration. The Quarterly Journal of
Economics, 118(4), 1279–1333.
Bostrom, N., & Roache, R. (2011). Smart Policy: Cognitive Enhancement and the
Public Interest. In G. Kahane, J. Savulescu, & R. Ter Meulen (Eds.),
Enhancing Human Capacities (pp. 138–49). Oxford: Wiley & Blackwell.
Brynjolfsson, E., & McAfee, A. (2011). Race Against The Machine: How the Digital
Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly
Transforming Employment and the Economy. Digital Frontier Press.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: work, progress,
and prosperity in a time of brilliant technologies.
Buchanan, A., Cole, T., & Keohane, R. O. (2011). Justice in the Diffusion of
Innovation. Journal of Political Philosophy, 19(3), 306–332.
7
doi:10.1111/j.1467-9760.2009.00348.x
Buchanan, A. E. (2008). Enhancement and the Ethics of Development. Kennedy
Institute of Ethics Journal, 18(1), pp. 1–34.
Buchanan, A. E. (2011). Beyond Humanity?: The Ethics of Biomedical Enhancement.
Oxford University Press.
Buchanan, A. E., Brock, D. W., Daniels, N., & Wikler, D. (2000). From Chance to
Choice. Cambridge, UK: Cambridge University Press.
Chatterjee, A. (2004). Cosmetic neurology: The controversy over enhancing
movement, mentation, and mood. Neurology, 63(6), 968–974.
Cowen, T. (2011). The Great Stagnation: How America Ate All the Low-Hanging
Fruit of Modern History, Got Sick, and Will(Eventually) Feel Better. Dutton
Adult.
Cowen, T. (2013). Average is over: powering America beyond the age of the great
stagnation.
Craig Smith. (n.d.). 100+ Amazing Instagram Statistics (December 2014).
http://expandedramblings.com/index.php/important-instagram-stats/. Accessed
14 December 2014
Douglas, T. (2008). Moral Enhancement. Journal of Applied Philosophy, 25(3), 228–
245. doi:10.1111/j.1468-5930.2008.00412.x
Eurofound. (2014). United Kingdom: Trends in skills requirements and work-related
issues. Eurofound.
http://www.eurofound.europa.eu/observatories/eurwork/articles/working-
conditions/united-kingdom-trends-in-skills-requirements-and-work-related-
issues. Accessed 17 May 2015
Finnis, J. (2011). Natural Law and Natural Rights. Oxford University Press.
8
Ford, M. (2009). The Lights in the Tunnel: Automation, Accelerating Technology and
the Economy of the Future. Acculant Publishing.
Frank, R. H., & Cook, P. J. (1995). The Winner-Take-All Society: How More and
More Americans Compete for Ever Fewer and Bigger Prizes, Encouraging
Economic Waste, Income Inequality, and an Impoverished Cultural Life. New
York: Free Press.
Frey, C. B., & Osborne, M. A. (2013). The Future of Employment: How Susceptible
are Jobs to Computerisation. Oxford, UK: Oxford Martin Programme on the
Impacts of Future Tecnology.
Gershman, S. J., Horvitz, E. J., & Tenenbaum, J. B. (2015). Computational
rationality: A converging paradigm for intelligence in brains, minds, and
machines. Science, 349(6245), 273–278. doi:10.1126/science.aac6076
Goldin, C. D., & Katz, L. F. (2008). The Race Between Education and Technology.
Cambridge, Mass.: Belknap Press of Harvard University Press.
Goos, M., & Manning, A. (2007). Lousy and lovely jobs: The rising polarization of
work in Britain. The Review of Economics and Statistics, 89(1), 118–133.
Gosseries, A. (2005). Intergenerational Justice. In H. LaFollette (Ed.), The Oxford
Handbook of Practical Ethics. Oxford University Press.
http://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199284238.00
1.0001/oxfordhb-9780199284238-e-19. Accessed 15 November 2013
Greely, H., Sahakian, B., Harris, J., Kessler, R. C., Gazzaniga, M., Campbell, P., &
Farah, M. J. (2008). Towards responsible use of cognitive-enhancing drugs by
the healthy. Nature, 456(7223), 702–705. doi:10.1038/456702a
Griffin, J. (1986). Well-Being: Its Meaning, Measurement, and Moral Importance.
Oxford: Claredon Press.
9
Harris, J. (1992). Wonderwoman and Superman: the ethics of human biotechnology.
Oxford University Press.
Heckman, J. J. (2008, June). Schools, Skills, and Synapses. Working Paper 14064
National Bureau of Economic Research, Cambridge MA.
http://www.nber.org/papers/w14064
Heller, J., & Peterson, C. (2009). Human Enhancement and Nanotechnology: A
Foresight Nanotech Institute Policy Issues Brief. The Forsesight Institute.
http://www.foresight.org/policy/brief2.html. Accessed 28 November 2009
Henschke, A. (2012). Making Sense of Animal Disenhancement. NanoEthics, 6(1),
55–64. doi:10.1007/s11569-012-0140-8
Hernandez, D., & Kaiser Health News. (2014, June 2). Artificial Intelligence Is Now
Telling Doctors How to Treat You. WIRED.
http://www.wired.com/2014/06/ai-healthcare/. Accessed 19 July 2015
Hirschberg, J., & Manning, C. D. (2015). Advances in natural language processing.
Science, 349(6245), 261–266. doi:10.1126/science.aaa8685
Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and
prospects. Science, 349(6245), 255–260. doi:10.1126/science.aaa8415
Krugman, P. (2012, December 8). Rise of the Robots. Paul Krugman Blog.
http://krugman.blogs.nytimes.com/2012/12/08/rise-of-the-robots/. Accessed
21 April 2015
Lemieux, T. (2006). Post-Secondary Education and Increasing Wage Inequality
(NBER Working Paper No. 12077). National Bureau of Economic Research,
Inc. https://ideas.repec.org/p/nbr/nberwo/12077.html. Accessed 22 January
2015
Levy, F., & Murnane, R. J. (2004). The New Division of Labor: How Computers Are
10
Creating the Next Job Market. New York; Princeton, N.J.: Russell Sage
Foundation ; Princeton University Press.
Marmot, M. G., Siegrist, J., & Theorell, T. (2006). Health and the Psychosocial
Environment at Work. In R. G. Wilkinson & M. G. Marmot (Eds.), Social
Determinants of Health (2nd ed., pp. 97–130). New York: Oxford University
Press.
Marx, K. (1887). In S. Moore (Ed.), Capital Volume One: The Process of Production
of Capital (First English edition of 1887 (4th German edition changes
included as indicated). On-line HTML edition by www.marxists.org., Vols. 1-
3, Vol. 1). Moscow, USSR: Progress Publishers.
http://www.marxists.org/archive/marx/works/1867-c1/
Mehlman, M. J. (2000). The Law of Above Averages: Leveling the New Genetic
Enhancement Playing Field. Iowa Law Review, 85(2), 517–93.
Moravec’ s paradox. (n.d.). In ʹWikipedia, the free encyclopedia.
http://en.wikipedia.org/wiki/Moravec%27%CA%B9s_paradox. Accessed 3
October 2014
Outram, S. M., & Racine, E. (2011). Developing Public Health Approaches to
Cognitive Enhancement: An Analysis of Current Reports. Public Health
Ethics, 4(1), 93 –105. doi:10.1093/phe/phr006
Parfit, D. (1984). Reasons and persons. Oxford: Clarendon Press.
Parkes, D. C., & Wellman, M. P. (2015). Economic reasoning and artificial
intelligence. Science, 349(6245), 267–272. doi:10.1126/science.aaa8403
Pierce, B. (2001). Compensation inequality. Quarterly Journal of Economics, 1493–
1525.
Pierce, B. (2010). Recent Trends in Compensation Inequality. In Labor in the New
11
Economy (pp. 63–98). University of Chicago Press.
http://www.nber.org/chapters/c10814.pdf. Accessed 22 January 2015
Piketty, T., & Saez, E. (2014). Inequality in the long run. Science, 344(6186), 838–
843. doi:10.1126/science.1251936
Rawls, J. (1971). A Theory of Justice (1st ed.). Cambridge, MA: Harvard University
Press.
Rawls, J. (1996). The Basic Structure as Subject. In Political Liberalism (pp. 257–
288). New York: Columbia University Press.
Rawls, J. (1999). A Theory of Justice (2nd ed.). Cambridge, MA: Harvard University
Press.
Rochester Business Journal. (2012, January 19). Kodak’s growth and decline: a
timeline | Rochester Business Journal New York business news and
information. Rochester Business Journal. http://www.rbj.net/article.asp?
aID=190078. Accessed 14 December 2014
Sandberg, A., & Savulescu, J. (2011). The Social and Economic Impacts of Cognitive
Enhancements. In G. Kahane, J. Savulescu, & R. Ter Meulen (Eds.),
Enhancing Human Capacities (pp. 92–112). Oxford: Wiley & Blackwell.
Sandoe, P., Nielsen, B. L., Christensen, L. G., & Sorensen, P. (1999). Staying good
while playing god--the ethics of breeding farm animals. Animal welfare, 8(4),
313–28.
Savulescu, J., & Kahane, G. (2009). The Moral Obligation to Create Children with the
Best Chance of the Best Life. Bioethics, 23(5), 274–290.
Savulescu, J., Meulen, R. ter, & Kahane, G. (2011). Enhancing Human Capacities.
John Wiley & Sons.
Savulescu, J., Sandberg, A., & Kahane, G. (2011). Well-Being and Enhancement. In
12
G. Kahane, J. Savulescu, & R. Ter Meulen (Eds.), Enhancing Human
Capacities (pp. 1–18). Oxford: Blackwell.
Stajic, J., Stone, R., Chin, G., & Wible, B. (2015). Rise of the Machines. Science,
349(6245), 248–249. doi:10.1126/science.349.6245.248
Stone, B., & Vance, A. (2012, October 4). Facebook’s “Next Billion”: A Q&A With
Mark Zuckerberg. BusinessWeek: technology.
http://www.businessweek.com/articles/2012-10-04/facebooks-next-billion-a-
q-and-a-with-mark-zuckerberg. Accessed 14 December 2014
Sumner, L. W. (1996). Welfare, Happiness, and Ethics. Oxford; New York:
Clarendon Press ; Oxford University Press.
Veen, R. J. V. D., & Van Parijs, P. (1986). A capitalist road to communism. Theory
and Society, 15(5), 635–655.
Williams, A. (1998). Incentives, Inequality, and Publicity. Philosophy and Public
Affairs, 27(3), 225–247.
13
