THE FOURTH INDUSTRIAL REVOLUTION AND SOCIETY Professor Tshilidzi - - PowerPoint PPT Presentation

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THE FOURTH INDUSTRIAL REVOLUTION AND SOCIETY Professor Tshilidzi - - PowerPoint PPT Presentation

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South African Film Summit 4 February 2019 THE FOURTH INDUSTRIAL REVOLUTION AND SOCIETY Professor Tshilidzi Marwala Vice Chancellor and Principal, University of Johannesburg, Republic of South Africa Contents Industrial revolutions

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Professor Tshilidzi Marwala

Vice Chancellor and Principal, University of Johannesburg, Republic of South Africa

South African Film Summit 4 February 2019

THE FOURTH INDUSTRIAL REVOLUTION AND SOCIETY

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Contents

  • Industrial revolutions
  • Key technologies that are driving the fourth industrial revolution
  • Fourth Industrial Revolution and Economics
  • Fourth Industrial Revolution and Politics
  • Fourth Industrial and Psychology
  • Fourth Industrial Revolution and Medical Sciences
  • Fourth Industrial Revolution and Engineering

Contents

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Professor Tshilidzi Marwala l University of Johannesburg

History of the Future: Past Futures

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DNA: Newton and James Watt steam mechanization, etc.

1st Industrial Revolution: knowledge formulation 2nd Industrial Revolution: knowledge evolution

DNA: Electro-Magnetism by Faraday, Maxwell and Hans Christian Ørsted electrification, mass production, etc.

03

DNA: Transistors based on Semi-Conductors by Bardeen, Brattain and Shockley computerization, Internetization, etc.

3rd Industrial Revolution: knowledge distribution

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DNA: Artificial Intelligence by Turing cyber-physical systemization, artificial cognization, robotization, etc.

4th Industrial Revolution: knowledge mutation

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Professor Tshilidzi Marwala l University of Johannesburg

Technologies for the fourth industrial revolution

  • Cyber:
  • Artificial Intelligence, IoT, Blockchain, Quantum
  • Physical:
  • 3-D Printing; Robotics; New Materials: graphene
  • Biological:
  • Biomedical Engineering; Biotechnology
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Professor Tshilidzi Marwala l University of Johannesburg

Artificial Intelligence, Machine Learning and Deep Learning

Soft Computing

Compu

  • mputa

tati tion

  • nal

al Inte ntell llig igen ence ce

Deep Learning

Machine Learning Artificial Intelligence

Big Data = Using AI to analyze large amount of data

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Professor Tshilidzi Marwala l University of Johannesburg

Soft Computing: Bluff and Detect Bluffing (Fraud detection)

Fuzzy Logic, Multi-Agent System, Mechanism Design

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Computational Intelligence: Ant Colony Optimization

Professor Tshilidzi Marwala l University of Johannesburg

  • Eugene Marais - Die Siel van die Mier; Ant movement deposits a trail of pheromones; The path

with the strongest pheromones then is the shortest path between one point to another; Particle swarm optimization has found use in applications such as scheduling

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Professor Tshilidzi Marwala l University of Johannesburg

Machine Learning: Statistical Approach to AI

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π’Œ=𝟏 𝑡

π’™π’π’Œπ’ˆπ’Šπ’‹π’†π’†π’‡π’

𝒋=𝟏 𝑢

π’™π’‹π’Œπ’šπ’‹

Citation: http://news.unchealthcare.org/images/science- images/neuron-illustration-1/image_view_fullscreen Citation: https://en.wikipedia.org/wiki/Artificial_intelligence

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Professor Tshilidzi Marwala l University of Johannesburg

Deep Learning

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Professor Tshilidzi Marwala l University of Johannesburg

Citation: https://www.youtube.com/watch?v=TZxdao4s6rg

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Professor Tshilidzi Marwala l University of Johannesburg

KAIST Robot

  • Learns
  • Senses
  • Reacts
  • Drives
  • Walks
  • Almost human.
  • It is artificially intelligent.
  • Does it fall in love?
  • Is it conscious?
  • Can it be recruited by COSATU?
  • Can it respond to the call: β€œRobots of the world unite, you have nothing to lose but

chains”?

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Professor Tshilidzi Marwala l University of Johannesburg

Economics

  • Demand and Supply
  • Rational

Expectations and Rational Choice

  • Bounded Rationality and

Behavioral Economics

  • Game

Theory and Mechanism Design

  • Causality

and Counterfactuals

  • Pricing

and Portfolio Theory

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Professor Tshilidzi Marwala l University of Johannesburg

Decision Making with Incomplete/Imperfect Information: Prediction of HIV Risk

Tshilidzi Marwala, Rendani Mbuvha. (South African Provisional Patent 2018/06344) A system and method for imputing missing data in a dataset, a method and system for determining a health condition of a person, and a method and system of calculating an insurance premium.

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Professor Tshilidzi Marwala l University of Johannesburg

Political Science: Interstate conflict

马瓦拉

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Professor Tshilidzi Marwala l University of Johannesburg

Psychology Human-Robots Interaction

  • Impact on behavior of people resulting in

interaction with machines

  • Cognitive development and technology
  • 4IR and absent parents (e.g. fathers)
  • 4IR and Job Insecurity
  • 4IR and Spending Habits
  • AI and Behavioral Economics
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Professor Tshilidzi Marwala l University of Johannesburg

Medical Application: Detection of epilepsy

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Professor Tshilidzi Marwala l University of Johannesburg

Medical Application: Artificial larynx

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Professor Tshilidzi Marwala l University of Johannesburg

Medical Application: Pulmonary embolism

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Professor Tshilidzi Marwala l University of Johannesburg

Medical Application: Prioritize patients (triage)

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Professor Tshilidzi Marwala l University of Johannesburg

Monitoring the condition of structures

Citation: https://city-press.news24.com/Business/whos-to-blame-for- grayston-bridge-collapse-20160710

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Professor Tshilidzi Marwala l University of Johannesburg

Finite Element Model

SzΕ±cs et. al. Finite Element Analysis of the Human Mandible to Assess the Effect

  • f Removing an Impacted Third Molar. J Can Dent Assoc 2010;76:a72

E.F Morgan & M.L Bouxsein Use of finite element analysis to assess bone strength (2005) 2, 8–19 (2005) doi:10.1138/20050187

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Monitoring and predicting dam levels

Tshilidzi Marwala, Dipanjan Paul and Satyakama Paul. (South African Provisional Patent 2018/03463) System and method for real time prediction of water level and hazard level of a dam.

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Professor Tshilidzi Marwala l University of Johannesburg

Regulations and Ethics

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  • Post-work era (due to advanced means of production)
  • Irrelevance in the 4thIR versus exploitation of 1stIR
  • Increase inequality
  • Bounded freedom (we are being watched)
  • Bounded decision making by humans
  • Bounded nationalism
  • Bounded democracy – (democracy in peril)
  • Laws and ethics to regulate automation
  • New economic theories
  • Human-Robot interaction will create new psychology in people

Consequences of the 4thIR

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  • Produce skills for the 4thIR (WEF): Cognitive Abilities; Systems; Complex

Problem Solving; Content; Process; Social; Resource Management; Technical; Physical

  • Regulation of ownership of data
  • Understand the relationship between automation and people
  • Understand automation and the future of work: β€œThe jobs of the future will

be those that make people happy or at ease” Khathutshelo Marwala

  • Adapt to the fast changing world: flipped and blended classrooms
  • Redefining infrastructure: Wearables, Soft-labs, Simulation
  • We can achieve these through multi-disciplinary education where human

and social sciences understand science and technology and vice versa

Looking forward

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Professor Tshilidzi Marwala l University of Johannesburg

AI of University of Johannesburg on CNN Marketplace Africa

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Thank you… …

Ngiyabonga…