Universal Basic Income and the Threat to Democracy as We Know It

Peter Nelson

• Publisher: Business Expert Press
• Year: 2018
• Print ISBN: 9781948198646
• eBook ISBN: 9781948198653
• Topic: Economics
• Subtopic: Economic Theory
• Index: Economics

Some of the greatest minds of the century have predicted that computers or artificial intelligence will replace 80 percent, if not more, of the world's workforce. The only uncertainty is the time frame, with the average prediction at about 30 years, although many believe it will be sooner. No matter the exact period, the impact on our planet will eventually be enormous because governments will still need to find a way to provide the unemployed with money on which to live and a Universal Basic Income (UBI), or something similar, is proposed to be paid to everyone without means test. That solution might appear well in theory, but the large numbers of unemployed will not want to be marginalized and will demand over time that the UBI be increased. Following human nature, under a democratic system as we know it, supposedly based on one person one vote, people will vote for whoever gives them more, and more, until the economic system breaks down, unable to afford the payments. The question is whether democracy will survive the challenge or whether we finish with a benign group of bureaucrats at the top who decide what is in the best interests of the majority and the rest of the global population simply accepts it.

CHAPTER 1

Introduction

Some of the greatest minds of the century have predicted that up to at least 80 percent, if not more, of the world’s workforce will be replaced by computers, robots, or artificial intelligence lumped together as AI, the only uncertainty being the time frame. The average prediction appears to be about 30 years for most jobs to be replaced, but many believe it will be sooner. This covers with a broad and daily expanding brush, the way new technology is replacing jobs as are currently defined and looks at the period over which this will likely occur. It looks at what AI might contribute toward formulation of new jobs even in the face of the changing climate. The focus is not so much about listing which jobs are on the way out, but providing an illustration that suggest that most of them are, while at the same time, pointing out that any new AI-based jobs are unlikely to replace what is lost. The analysis is more on trying to draw attention to the problem of how this will impact democracy and to bring focus on its importance, where to date, no government appears to have taken the long-term probability seriously.

No matter the exact period of total job losses, the impact on our planet will be enormous because governments will still need to find a way to provide the unemployed with money on which to live and a ­Universal Basic Income, a UBI or something like it, is proposed to be paid to ­everyone without means test. Models of UBI have been instigated on a limited scale, but no one has looked at an overall impact on government structure.

The study of the future requires analysis of the benefits of a UBI along with its shortcomings, and because the subject deals with humans and humanity, it looks at the role which gender might ultimately play in elimination of jobs and the eventual possible world domination by either women or computers. Along with those possibilities is the need to look at what will have to change as jobs disappear and if a UBI or overall flat-line social welfare system is to be introduced can this be funded and on what legal framework.

Hypothesizing that a UBI is eventually introduced, this raises important issues not only regarding what people do with 100 ­percent leisure time, which might appear attractive in theory, but with low levels of ­payment, that high percentage of unemployed will not want to be ­marginalized and will demand over time that their UBI be increased.

The likely stages of introduction will be important to individuals in a specific country, but facing a global economy, ­geopolitical structures will see a rollout of the system across the globe. As ­history has demonstrated, large disaffected numbers of a society can rebel against the established order and military intervention is always a possibility.

As human nature will have it, under a democratic system, supposedly based on one person one vote, people will vote for whoever gives them more, and more, until the economic system would break down unable to afford the UBI payments. The question is whether democracy will ­survive the challenge or whether the world finishes with a benign group of bureaucrats at the top of a global government who decide what is in the best interests of the majority and the rest of the population must just accept the consequences.

If this is not a world people want, and democracies are to survive, planning for the eventualities outlined need to be considered seriously at individual and global government level. Logic suggests there being a trigger point in job loss numbers from which a UBI will be introduced, after which it will be too late to turn back and democracy as it is currently recognized will be finished.

CHAPTER 2

The Future of Employment

According to most of the great minds of the century, including Stephen Hawking, Elon Musk, Google’s Chief Ray Kurzweil, or as outlined in the recent study of the McKinsey Global Institute,¹ robotics or artificial intelligence (AI) in one form or another will replace most jobs.² Hawking predicts machines will have replaced humans in 100 years. According to a survey of a broad section of AI experts, AI will probably take over most jobs in the next 50 years.³ The World Bank estimates 57 percent of jobs could be automated within the next 20 years. There seems to be little dispute about the event, only differences of opinion on the timeframe. The question then becomes, what is to be done about it? No one seems to know how to move forward because of so many unknown factors.⁴ Even if they do, no one has yet looked seriously at how this will affect the politics of the world as understood today.

The question of job losses is nothing new. John Maynard Keynes predicted widespread technological unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.”⁵ This was an extension on governments having to pay people to dig holes and then filling them in again. This system only works while governments still can generate enough money from other sources to be able to pay the ditch diggers. Unfortunately, there is a tendency to create money by printing more of it when the supply runs out, creating a further problem because its purchasing power is reduced.

Future predicted losses in the work force occur on a daily basis as reported in the press and on various websites. Starting the new year of 2018, Futurism’s Claudia Geib⁶ featured the hype of what the future would bring viewed from 100 years back. Many of the predictions from that time have been realized in one form or another, even when the technology that would bring in the ultimate invention had yet to be conceived. This as with predictions for TV type images which could be projected at home through telephone connections, well before TV had been invented. A common feature in projections was that new technology would reduce the need for workers, not increase their numbers.

From a recent Oxford and Yale University study, surveying 1,600 academics, the researchers were able to put likely timeframes on jobs that will be replaced, from, as an example, truck drivers gone within six years and off the road completely in 20. This study established a base line for repetitive job loss and for those that still require human to AI interface, such as where drivers are still required by law to be present in driverless vehicles. On an advanced level were predictions of AI’s ability to write a best seller for the New York Times best seller list within 26 years and a top pop song written by a machine in 12 years. More worrying for humanity has been the prediction that, within 50 years, AI will be developing itself and then replacing humans in 80 years, or in Hawking’s estimates, not even requiring humans in 100 years.

Where the period is the main issue in dispute, even with current guesses, care needs to be taken that the predictions might just be conservative when looking for example at how quickly Uber caught everyone, especially the taxi industry by surprise. Driven by an app, with Uber, there is almost no human interface and the next step is to replace even the driver.

The experts predicted in 2015 that AI machines would not be sufficiently advanced to beat the world Go⁷ champion, Ke Jie, and yet, this was accomplished by a robot in 2017.⁸ In a new paper, Google researchers detail how their latest AI evolution, AlphaZero, developed superhuman performance in chess, after being programmed with the rules it took just four hours to learn. It then obliterated the world champion chess program, Stockfish,⁹ which had already defeated humans.

What can be seen is that AI will initially replace some jobs completely. Others will be partially replaced, and in the first instance, AI will simply assist in supporting various professions. Quoted have been examples of databases allowing paralegals to download every reference to any law on a legal question and then to further refine these to specifics for a particular case.¹⁰ In medicine, there will be increased ability for individuals to self-diagnose and to identify their own treatment. Even now doctors are Googling symptoms during consultations along with searches for appropriate medicines which might be available for treatment. Take that one step further and Xiaoyi, an AI-powered robot in China, has recently taken the national medical licensing examination and passed with a score of 456 points, which is 96 points above the required marks to be registered as a doctor.¹¹ This robot, developed by leading Chinese AI company iFlytek, had been designed to capture and analyze patient information and then draw appropriate conclusions. They have proven that Xiaoyi could also have enough medical knowledge to be a licensed practitioner.

These examples are simply about someone programming all known knowledge into a system and then designing the selective program on the data to achieve a designated result.

The advances in technological application will have positives as well as negatives effects. As the taxi industry fought Uber, doctors are already insisting that governments legislate for doctors’ prescriptions to be required for most common drugs in a fight against self-service medicine. While people might currently be forced to pay to go to a doctor for a prescription, it will not be long before the same patients realize that it is possible to buy just about anything online. For now, there remains a certain placebo effect and reassurance in seeing a physical doctor, but this will not always need to be the case and GP doctors’ jobs will be gone.

Then again, if the first level of approach in medicine replaces GPs, while computer-simulated body anatomy is available for doctors to understand how it works, where do surgeons get the feel of live tissue with no more dissecting rooms? Obviously onscreen graphics can help teach, but there is a difference in seeing and interacting with a body in real life.

Low on the list of job replacements will be judges where some human int...

Table of contents

• Cover
• Halftitle
• title
• Copyright
• Abstract
• Contents
• 01_Chapter 1
• 02_Chapter 2
• 03_Chapter 3
• 04_Chapter 4
• 05_Chapter 5
• 06_Chapter 6
• 07_Chapter 7
• 08_Chapter 8
• 09_Chapter 9
• 10_Chapter 10
• 11_Chapter 11
• 12_Chapter 12
• 13_Chapter 13
• 14_Chapter 14
• 15_Chapter 15
• 16_Chapter 16
• 17_Chapter 17
• 18_Chapter 18
• 19_Chapter 19
• 20_Chapter 20
• 21_Chapter 21
• 22_Chapter 22
• 23_Chapter 23
• 24_Bios
• 25_Index
• 26_Adpage