The wealth while the wealthiest top 10 percent

 

The Internet was supposed to be a benevolent equaliser; a force for good
that would transmute humanity and bring about a technological renaissance at a
global scale.  A desiderata that allows
the poorest of children in the world to access to the exact same information as
the most privileged of their peers, a platform that creates a global marketplace
where buyer and seller is instantly connected, and a virtual place for
collaboration that could foster mutual understanding and help solve society’s
thorniest social problems.1 From text to transfers, education to
media, politics to public health, the promise of the Internet was the promise
of a more equal society in almost every way.

 

This essay will critically discuss
the role of the Internet in rising levels of inequality globally and aim to
draw learnings from it to inform a better strategy for managing similar effects
as unintended consequences of nascent Artificial Intelligence and related
technologies.

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Twenty years after the start of the Internet era, two realities have
come into sharper focus.  The scale,
reach and transformational ability of the Internet has left us in a reactive
position where research, policy and discourse is scrambling to keep up with the
social changes it brings about.   And
second, we now live in the most unequal society since the Gilded Age. We live
in what economist Thomas Piketty calls a ‘second Belle Époque’.2 

 

Data from Credit Suisse
reveals that the richest 1 percent of the world’s population have now
accumulated more wealth than the rest of the world put together.3
The latest available data from 2017 indicates that the bottom half collectively own less than 1 percent of the total
wealth while the wealthiest top 10 percent own 89 percent of all global assets.4

 

While inequality
intuitively sounds like a negative force within society, it is worthwhile
exploring some of its ill effects. Epidemiolists Wilkinson and Pickett applied
the logic and rigour of evidence-based medicine to research global inequality.

The meta-data they put forth indicate that unequal societies tend to be more
violent, have higher numbers of people in prison, experience greater levels of
mental illness and obesity, and have lower life expectancies and lower levels
of trust.5
The corollary, is that, after controlling for average incomes, more equal
societies have higher levels of child well-being, lower levels of stress and
drug use, and lower infant mortality.6
Other researchers have found that higher levels of inequality increase
segregation and reduce educational outcomes for children and young adults.7
While there is little empirical data available, many social scientists warn
that increased levels of inequality will lead to an increase in social unrest
as exemplified in the Occupy Wallstreet Movement (OWM) with the slogan “we are
the 99%”. The UN Human Development Report concluded that the world has become more economically polarized both
within and between countries8 largely thanks to the same
economic forces such as technology, globalistion and neoliberal policies.

 

Apologists of the status quo often cite the reduction in the number of
people living in extreme poverty as proof that inequality is not a major
problem9. This
ignores the social ills that come as a result in fewer people having a greater
influence on politics, legislation and macro economic actions. Yet others
believe that while inequality might be unjust, it doesn’t hamper growth and is
therefor a good thing. Economic growth is seen as the primary concern and they
erroneously assume that we can “outgrow” the ill-effects of inequality and that
because the current system is creating more wealth so as the tide rises, so
will all boats. However, A 2015 IMF report on
inequality concluded: “contrary to conventional wisdom, the benefits of higher
income are trickling up, not down”.10 To
compound this reverse flow of benefits, once the money has trickled up, an increasingly
intricate system of tax havens and a robust industry of wealth managers ensure
that it stays there as the recent Panama Papers11 scandal
revealed.  As a consequence the wealth remains
untaxed and therefore inaccessible to governments and of little value to ordinary
citizens. In 2014 it was estimated that $7.6 trillion of individual wealth –
more than the combined gross domestic product (GDP) of the UK and Germany – is
currently held offshore.12

 

The Internet was always going to bring with it a multitude of social challenges.

The Industrial Revolution caused massive air pollution and horrific exploitation
via child labour. With the Internet revolution, we are still coming to terms
with its modern equivalents. Rapid and accelerating digitisation brings social
and economic disruption, stemming from the fact that as computers get more
powerful, there will be a concentration of power and capital in the hands of
fewer organisations and individuals. In this new “Winner Takes All” (WTA)
economy, technological progress is going to leave behind some people, perhaps
even the vast majority of people as it races ahead13.  It won’t just leave people jobless, if
adoption of the internet and specific technologies such as Artificial
Intelligence grows at predicted rates we could see a stratification in society
like never before in human history with catastrophic social consequences. When looking at inequality and policies aimed at reducing it, a common
mistake governments make is assuming that a “more digital” economy will equal
economic growth that could counteract inequality. But digitalisation does not
necessarily translate into growth14
nor does it guarantee a more equitable distribution of the wealth across strata
in society.

 

During the Industrial Revolution, it took considerable social and
political pressure in combination with democratic government and technological
progress to to abolish child slavery and contain sulfur dioxide pollution. Unlike
the industrial revolution, we don’t have decades to fix these problems – our
window is much narrower and the stakes at play much larger. It is argued that
challenges of the digital revolution and AI technology can also be met, but
first we have to be clear on what they are and the actors involved.

 

This essay argues that inequality is one of the biggest challenges that
the Internet and emergent technologies like AI will need to mitigate. It is
clear from the last 20 years worth of economic data that there is no “invisible
hand” that will solve this problem. There is a second machine age unfolding currently
– an important inflection point in the history of our economies and societies15.  While it is tempting to hope that a
yet-to-be-discovered technology will solve all our social ills, we will need to
actively shape the agenda and tackle problems collectively and proactively.

 

One of the key actors to persuade to join the cause is technology
entrepreneurs. On the pessimistic side, inequality, in the broadest sense, is
precisely, and perhaps paradoxically, what technology enabled entrepreneurship or
‘tech startups’ is all about.16 Entrepreneurs
use their intellect and creativity to rapidly scale across new markets and
generate extraordinary wealth, sometimes very quickly, more often over a decade
or two17. As
a consequence, entrepreneurship in the era of AI rewards risk-tolerant
investors with impressive above-market (some say ‘unequal’) financial returns. Looking
broader at technology companies in general
the four most influential companies in the word, or what Scott Galloway refers
to as the four horses of
the economic apocalypse (Apple,
Google, Amazon and Facebook) – their scale and market dominance make them virtually
unbeatable18.

 

Two world wars, the
Depression and high taxes pushed down the return on wealth in the 20th century,
while rapid productivity and population rises pushed up growth19
Add to this, the fact that a unit of wealth is created today with much fewer
workers compared to 10 or 15 years ago is possible because digital businesses
have marginal costs that tend towards zero20
– especially nascent technologies such as AI. In the digital age, many new
businesses provide “information goods” with storage, transportation and
replication costs that are virtually nil which means most disruptive tech
companies require little capital to prosper.21  Layer on top on this the “winner takes all”
(WTA) economics that pervades the technology sector and we have a milieu in
which AI could enrich very few. This essay argues that the absence of countervailing
factors such as high taxation combined with the marginal cost of business in
the internet age, higher returns on capital will only serve to further
concentrate wealth.

 

This already extreme example of income
inequality, if not properly planned for could destabilise the current political
and social system when AI technology comes into its own. In addition to the
obvious economic benefits that would accrue to whoever designs advanced AI
first, those who profit from AI will also likely have: access to better health
care, happier and longer lives, more opportunities for their children, various
forms of intelligence enhancement, and so on.22

 

From the above
analysis,  it is evident that allowing
pure market forces to define ethics has not worked with the internet age which
arguably is of a smaller order of magnitude compared to the potential of AI.  The Internet has failed to become the ‘Great Democratizer’, over half of the world is still offline, and primarily those already well-off and
well-educated have taken disproportionate advantage
of the internet to achieve greater success23.

The major challenges of social research around AI will be how AI
technologies should benefit and empower as many people as possible and how to
share the economic prosperity created by AI broadly, to benefit all of humanity.24

 

It
is argued that the stakes are even higher this time since we are fashioning a
world where algorithms will comprehend and anticipate what we want to do – and
in the future, they’ll do it for us. The velocity at which AI is permeating every industry and every organization simultaneously is
something we did not experience in the internet era.25 Those
without access to AI from the very beginning will have little to no chance to
catch up later, especially while income inequality continues to
widen. While often sensationalised, there is very
little short term basis for the public concerns over possibly losing control of
AI, especially since many of the firms and individuals who are on the creating bleeding
edge AI research do not yet really understand how it works.26

 

The
real worry is not that machines will be malevolent; it is that they will be
competent.  A superintelligent AI is by
definition going to be extremely competent at attaining goals, whatever they
may be, so we need to ensure that its goals are aligned with ours.27 Which
raises the questions how broad these goals will be and how we will agree upon
them. Will these goals reflect western centric neo-liberalism or a more
egalitarian viewpoint that puts equality at the centre? Two of the most serious lessons to learn from internet era were
lack of inclusion and the lack of impartiality. Both of which will be vital to address
before the age of AI dawns.

 

The lack of impartiality has meant that the internet is not the decentralised
utopia of information sharing that many had thought it would be since platforms
such as Google and Facebook control much of what we see and do on the web and
fundamentally transformed the way online industries from media and marketing to
political campaigning works.28 The implication for AI is
evident, if these big firms crack AI first, oversight, regulation and
egalitarianism is unlikely to follow. By which levers would anyone be able to
persuade technology firms to spread the benefit of AI to as many people as
possible? Firms such as Google have founded projects such as PAIR
(People + AI Research) to study the social effects of AI and “ensure
inclusion so that everyone can benefit from breakthroughs in AI” 29. However, the current
team at PAIR consists of only 12 individuals30 which is a lacklustre
effort given the scale and significance of the challenge and the resources available
to them.

The
second problem was that as a global society, we didn’t get enough people access
quickly enough and did not ensure that internet-based technologies and
solutions were unbiased. Once again, how do we avoid this with AI?Critically,
what is the AI equivalent of “getting everyone online? With technology
revolutions, Moore’s law typically means that something that was previously
very expensive gets much cheaper and therefore becomes ubiquitous. If
“connecting and communicating” became cheap with the Internet (which for many
it didn’t), it is argued that “analyzing and predicting” will become cheap with
AI31. Organisations
with unique access to data will benefit most strategically from this which is
convenient since the top five global AI vendors – Google, Facebook, Amazon,
Microsoft and Baidu – all have substantial proprietary data sets32. While
these firms and firms like them utilise open source AI algorithms and models
that they have developed, they guard the data closely.

No one has proposed any credible policy
intervention to deal with rising inequality that will make everyone, including
those at the very top, better off – especially in light of AI.33
This essay has argued that with the rise in AI, this needs to be an ethical
imperative with firm public and private policy implications. If we don’t get it right, AI will go from
being potentially the greatest problem solver in human history to the greatest expediter
of inequality. And worse still, unlike our sci-fi horror fantasies, it
will be humans and not robots that destroy us.

 

1 R. Klain, ‘Inequality
and the Internet’, 2015, Democracy: A Journal of Ideas, http://democracyjournal.org/magazine/37/inequality-and-the-internet/ (accessed on 12 October
2016).

2 T. Piketty, Capital in
the Twenty-First Century, Cambridge Massachusetts, The Belknap Press of Harvard
University, 2014

3
Credit
Suisse, ‘Global Wealth Databook 2017’, 2017, http://publications.credit-suisse.com/tasks/render/file/index.cfm?fileid=C26E3824-E868-56E0-CCA04D4BB9B9ADD5 (accessed on 11 October
2016)

4
Oxfam Briefing Paper ‘An Economy for the 1%: How Privilege and Power in the
Economy Drive Inequality and How it can be Stopped’, 2016, http://policy-practice.oxfam.org.uk/publications/an-economy-for-the-1-how-privilege-and-power-in-the-economy-drive-extreme-inequ-592643

(accessed on 11 October 2016)

5 R.G. Wilkinson and K. Pickett, ‘The Spirit
Level: Why Greater Equality Makes Societies Stronger’, 2010, Bloomsbury’s
Press: New York

6 Ibid

7 S.F. Reardon and K. Bischoff, ‘More
Unequal and More Separate: Growth in the Residential Segregation of Families by
Income, 1970-2009’, 2011, US 2010 Project, 
https://s4.ad.brown.edu/projects/diversity/Projects/Reports.htm
(accessed 25 October 2016). 

8 United Nations, ‘UN Human Development
Report: 1996’, 1996

9 M. Lawson, ‘It’s time to demolish
the myth of trickle-down economics’, World Economic Forum, 2016, https://www.weforum.org/agenda/2016/07/it-s-time-to-demolish-the-myth-of-trickle-down-economics/
(accessed on 14 December 2017)

10 International Monetary Fund, ‘Causes and
Consequences of Income Inequality: A Global Perspective’, 2015, https://www.imf.org/en/News/Articles/2015/09/28/04/53/sonew061715a
(accessed 16 January 2016)

11 International Consortium of Investigative
Journalists. https://www.icij.org/investigations/paradise-papers/
(accessed 16 January 2018)

12 G. Zucman, ‘Taxing Across Borders:
Tracking Personal Wealth and Corporate Profits’, Journal of

Economic
Perspectives. 2014,  http://gabriel-zucman.eu/files/Zucman2014JEP.pdf
(accessed 25 October)

13 A. Bernstein and
A. Raman, ‘The Great Decoupling: An Interview with Erik
Brynjolfsson and Andrew McAfee’, Harvard Business Review, 2015, https://hbr.org/2015/06/the-great-decoupling
(accessed 2 January 2018)

14 J.P.V. Sampere, ‘Why
Estonia is Letting Entrepreneurs Become “E-Residents”, Harvard Business Review,
2016, https://hbr.org/2016/03/why-estonia-is-letting-entrepreneurs-become-e-residents (accessed 4 October
2016)

15 E. Brynjolfsson and A. McAfee, ‘The Second
Machine Age: Work, Progress, and Prosperity in a Time of Brilliant
Technologies’, 2014, W.W. Norton & Company, New York.

16 D.

Isenberg, ‘Entrepreneurship Always Leads to Inequality’, Harvard Business
Review, 2014, https://hbr.org/2014/03/entrepreneurship-always-leads-to-inequality (accessed 3 October
2016)

17 Ibid

18 S. Galloway, “The
Four: The Hidden DNA of Amazon, Apple, Facebook and Google”, London, Penguin
Random House, 2017

19 T. Piketty, ‘Capital in
the Twenty-First Century’, Cambridge Massachusetts, The Belknap Press of
Harvard University, 2014

20 K. Schwab, ‘The Fourth Industrial
Revolution: What it Means, How to Respond’, World Economic Forum

21 Ibid

22 A. Conn, ‘AI Should Provide Benefit for as
Many People as Possible’, 2018, Future of Life Institute,
https://futureoflife.org/2018/01/10/shared-benefit-principle/ (accessed on 16
January 2018)

23 World Development Report
2016: Digital Dividends, 2016, http://www.worldbank.org/en/publication/wdr2016
(accessed 16 January 2018)

24 Asilomar AI Principles, Future of Life
Institute, 2017, https://futureoflife.org/ai-principles/
(accessed on 13 December 2017)

25 PWC, ‘Bot.me: How artificial intelligence is pushing man
and machine closer together’, 2017, https://www.pwc.com/us/en/industry/entertainment-media/publications/consumer-intelligence-series/assets/pwc-botme-booklet.pdf
(accessed on 12 January 2018)

26 W. Knight, ‘The
Dark Secret at the Heart of AI’, 2017, MIT Technology Review, https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/
(accessed on 14 January 2018)

27 M. Tegmark, ‘Life 3.0’, 2017,  Penguin Random House

28 Wired, ‘The web’s greatest minds explain how we can fix
the internet’, 2017, http://www.wired.co.uk/article/the-webs-greatest-minds-on-how-to-fix-it
(accessed 23 December 2017)

29 Google PAIR https://ai.google/pair/
(accessed 16 January 2018)

30 Google PAIR https://ai.google/pair/
(accessed 16 January 2018)

31 S. Venkatachalam, ‘AI and equality: Let’s
Get it Right This Time”, 2017, https://www.forbes.com/sites/forbestechcouncil/2017/07/28/ai-and-equality-lets-get-it-right-this-time/2/#21595fe08be4
(accessed 14 December 2017)

32 Ibid

33 N.G. Mankiw, ‘Defending the One Percent’,
Journal of Economic Perspectives, vol 27, no 3, 2017