industrial revolutions and development: exploring the
TRANSCRIPT
Industrial Revolutions and Development: Exploring the Potential Impacts of the 4IR
Rasigan Maharajh, PhD
4th Industrial Revolution Summit for Economic Development, Moses Kotane Institute
25th March 2018, e’Thekwini.
Outline
• Introduction
• Evolutionary and Revolutionary History of Global Development
• Contemporary Conjuncture
• Impacts of Technological Change
• Conclusion
• AI Glossary
• References
pre-Introduction: World Mercator Projection and True Sizes
Introduction
• Our Contemporary Conjuncture is defined by Contradictions and Crisis's originating in the hegemonic mode of production: Globalised Neoliberal Capitalism, which shapes World Systems and produces Combined and Uneven, yet Common characteristics (Maharajh, 2015)
• The Anatomy of South African society is discernible through analysing:• the development of productive forces, and • the structure of the relations of ownership (Maharajh,
2011)
• Persistence of Prior Accumulation Strategies-
Minerals-Energy Complex (Fine & Rustomjee, 1996)
• Poverty• Underdevelopment • Unemployment• Inequality• Increased ecological constraints, climate
change, and environmental degradation
Global Timeline of Human Transformation of the Terrestrial Biosphere
Source: Ellis, et al., 2017
2018: Global Distribution of the People
Changing Regional Contributions to World GDP
1 1000 1500 1600 1700 1820 1870 1913 1950 1973 2003
Africa 7.618451263 11.49286836 7.80172674 7.079520572 6.939702984 4.501308671 4.071646724 2.9079907 3.809880884 3.432545993 3.231428714
USA 0.258059619 0.431969031 0.322002858 0.18096163 0.141884834 1.806512544 8.854935996 18.92842705 27.30684404 22.07231306 20.60636434
Asia 72.80222387 70.50316085 64.93066876 65.4746322 61.83459513 59.38355711 38.31294089 24.9065895 18.59437038 24.11897281 40.4637587
Europe 15.54904082 11.23534836 20.47897925 22.58732907 24.93242297 26.5991264 37.59202701 37.93869461 29.65478669 29.00550762 21.12707407
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% o
f W
orl
d G
DP
Source: Angus Maddison
Forecasting 2017 & 2030
Global Wealth Inequality (2019)
Source: Davies et al, 2018 Source: Oxfam, 2019
World Wealth (2018)
Africa: Wealth & Poverty
Africa:Growth
Contemporary World Systems: Combined, Uneven, and Common
Source: Various, 2019
Materialist Conception of Human Social History
Source: Carter, 2017
Co-evolution of Labour Processes & Technology
Source: Keller et al, 2018
Kondratieff Waves of Capitalist Expansion
Source: Saskatchewan Research Council, 2014
Planetary Impacts
Understanding ‘Techno-Economic Paradigms’
Source: Perez, 2009.
Technological Surges
Source: Perez, 2009.
Waves of Techno-Economic Transformation
Source: Hargroves & Smith, 2005.
Contextualising Economic History of south Africa~1 - 1400 1400 -
1600
1600 -
1700
1700 – 1800 1800 - 1900 1900 - 2000 2000 - …
Industrial Revolutions (WEF)
Euro
pean
Glo
bal Exp
ansio
n (C
on
qu
est, Expro
priatio
n, &
Inco
rpo
ration
)
1784- “shift from reliance on
animals, human effort and
biomass as primary sources of
energy to the use of fossil
fuels and the mechanical
power”
1870- “electricity distribution, both wireless and
wired communication, the synthesis of ammonia
and new forms of power generation”
1969-“development of
digital systems,
communication and
rapid advances in
computing power”
2016- “advent of ‘cyber-
physical systems’
involving entirely new
capabilities for people
and machines”
Technological
Economic Waves
~1771- Industrial
Revolution: Iron,
Water Power,
Mechanisation,
Textiles, Commerce
~1829-
Industrial
Production:
Steam
Power,
Railroads,
Steel,
Cotton
~1875-
Scientific
Revolution:
Electricity,
Chemicals,
Internal
Combustion
Engines
~1908- Scientific-Technical
Revolution: Automobile, Mass
Production, Petro-chemical
Industries, Aviation, Electronics,
Space
~1971- ICT Revolution:
Microcomputers,
Information &
Communications
Technologies, Software,
Digital Networks
~2010- Sustainability,
Radical Resource
Productivity, Whole-System
Design, Biomimicry, Green
Chemistry, Industrial
Ecology, Renewable
Energy, Green
Nanotechnology, …
south Africa
~1030 –
1290-
Mapungub
we Kingdom
1652-
Corpora
te
Capture
of the
Cape
~1770s - Wars of
Dispossession
(Frontier Wars)
* 1798- Cape
Colony Post Office
1809- Proclamation regulates
the use of Khoi, San and
coloured labour for white
farmers
1834- Slavery Abolished
1860- first steam train
(Durban and the Point)
1867- Diamonds ‘Discovered’
1882- Electric streetlights
(Kimberley)
1886- Gold fields Proclaimed
1910- Union of South Africa
1912- African National Congress
formed
1913 - Land Act
1923- Electricity Supply Commission
1934- Status of the Union Act (a
‘sovereign’ independent state)
1948– Apartheid regime installed
1952- ‘electric tabulator’ (IBM-
South Africa)
1961– Republic Proclaimed &
uMkhonto weSizwe Launches
1963- Arms Embargo
1977- Mandatory
Sanctions
1990- National Liberation
Movements Unbanned
1994- Democratic
Breakthrough
1994-1996-
Reconstruction and
Development
1996-2005- Growth,
Employment and
Redistribution
2006-2014- Accelerated
and Shared Growth
Initiative for South Africa
2015-2018- New
Development Plan
2019- New Dawn …
Source: Various
Emerging and Disruptive Trends in AI
Emergent Socio-Techno-Economic Change
Emergent Socio-Techno-Economic Change
Emergent Technology Growth (2018-2028)
Source: Moffet, 2018.
Conclusions: 21st Century Transformational Challenges
• Economic Expansion to absorb under-Employment & improve Productive Forces
• Ecological Resilience & Sustainability
• Inclusion & Redress against Inequality
• Redistribution through High-quality Public Infrastructures & Institutions
Source: CBI Insights, 2017
AI Glossary
• ALGORITHM A set of step-by-step instructions. Computer algorithms can be simple (if it's 3 p.m., send a reminder) or complex (identify pedestrians).
• BACKPROPAGATION The way many neural nets learn. They find the difference between their output and the desired output, then adjust the calculations in reverse order of execution.
• BLACK BOX A description of some deep learning systems. They take an input and provide an output, but the calculations that occur in between are not easy for humans to interpret.
• DEEP LEARNING How a neural network with multiple layers becomes sensitive to progressively more abstract patterns. In parsing a photo, layers might respond first to edges, then paws, then dogs.
• EXPERT SYSTEM A form of AI that attempts to replicate a human's expertise in an area, such as medical diagnosis. It combines a knowledge base with a set of hand-coded rules for applying that knowledge. Machine-learning techniques are increasingly replacing hand coding.
• GENERATIVE ADVERSARIAL NETWORKS A pair of jointly trained neural networks that generates realistic new data and improves through competition. One net creates new examples (fake Picassos, say) as the other tries to detect the fakes.
• MACHINE LEARNING The use of algorithms that find patterns in data without explicit instruction. A system might learn how to associate features of inputs such as images with outputs such as labels.
• NATURAL LANGUAGE PROCESSING A computer's attempt to “understand” spoken or written language. It must parse vocabulary, grammar, and intent, and allow for variation in language use. The process often involves machine learning.
• NEURAL NETWORK A highly abstracted and simplified model of the human brain used in machine learning. A set of units receives pieces of an input (pixels in a photo, say), performs simple computations on them, and passes them on to the next layer of units. The final layer represents the answer.
• NEUROMORPHIC CHIP A computer chip designed to act as a neural network. It can be analogue, digital, or a combination.
• PERCEPTRON An early type of neural network, developed in the 1950s. It received great hype but was then shown to have limitations, suppressing interest in neural nets for years.
• REINFORCEMENT LEARNING A type of machine learning in which the algorithm learns by acting toward an abstract goal, such as “earn a high video game score” or “manage a factory efficiently.” During training, each effort is evaluated based on its contribution toward the goal.
• STRONG AI AI that is as smart and well-rounded as a human. Some say it's impossible. Current AI is weak, or narrow. It can play chess or drive but not both, and lacks common sense.
• SUPERVISED LEARNING A type of machine learning in which the algorithm compares its outputs with the correct outputs during training. In unsupervised learning, the algorithm merely looks for patterns in a set of data.
• TENSORFLOW A collection of software tools developed by Google for use in deep learning. It is open source, meaning anyone can use or improve it. Similar projects include Torch and Theano.
• TRANSFER LEARNING A technique in machine learning in which an algorithm learns to perform one task, such as recognizing cars, and builds on that knowledge when learning a different but related task, such as recognizing cats.
• TURING TEST A test of AI's ability to pass as human. In Alan Turing's original conception, an AI would be judged by its ability to converse through written text.
Source: Hutson, 2017
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DankieThank you
NgiyathokozaEnkosi
NgiyabongaKe a lebogaKe a lebohaKe a lebogaSiyabonga
Ndo livhuwa/ Ro livhuwaInkomu
www.ieri.org.zaFaculty of Economics & Finance,
Tshwane University of Technology,
159 Nana Sita Street,
Pretoria CBD, 0002
City of Tshwane
Province of Gauteng
Republic of South Africa
AbstractWhilst our contemporary conjuncture remains characterised by combined and uneven development, our common future is imperilled by threats of catastrophic climate change, environmental degradation, and the persistent militarised hegemony of the advanced and mature capitalist economies.
Science, Technology, and Innovation are deeply embedded social constructions that have co-evolved with humankind’s development.
This presentation provides an overview of the long-run of historical development which affirms evolutionary progress of humankind and the revolutionary accelerations which afforded various societies of the world the possibility of providing a better life for their citizenry.
Notwithstanding the miss-numbering, we are today poised on the brink of another revolutionary transition within the mode of production.
The current industrial revolution, which would be variously enumerated in the respective historical contexts of different country experiences, holds a range of radical potentials for effecting creative destruction (innovation) and expanding economic capabilities and capacities.
Thus, it is in the contested terrain of unfair international trade, geopolitical inequalities, and an international division of labour that privileges the global North over the vast majority of the world’s peoples located in the global South.
The presentation concludes with tentative recommendations for the Province of KwaZulu in the Republic of South Africa to advantage itself and its people through deeper engagements with knowledge-intensive institutions, enabling productive Black economic empowerment, and enabling a better life for all.