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Job Automation. Then How To Defendby@bryanjordan
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Job Automation. Then How To Defend

by Bryan JordanFebruary 27th, 2019
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It’s unsurprising to find that the likes of Apple, Amazon, Facebook and Google, with their army of engineers totalling a near collective of 150,000 (approximately 30,000/company), represent the most impactful companies ever assembled. From market capitalisations totalling over $1 trillion (Apple, Amazon), controlling 60% of the internet’s web servers (Amazon), receiving 2 billion monthly users (Facebook) and 3.5 billion search requests per day (Google), these companies are seizing the global economy. The tech industry is expected to be 8% of global GDP by 2038. It doesn’t help that federal governments and regulatory bodies have failed to curb improper and reckless conduct by these companies.

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Ways to Defend against Job Automation’s Inevitable Domination

It’s unsurprising to find that the likes of Apple, Amazon, Facebook and Google, with their army of engineers totalling a near collective of 150,000 (approximately 30,000/company), represent the most impactful companies ever assembled. From market capitalisations totalling over $1 trillion (Apple, Amazon), controlling 60% of the internet’s web servers (Amazon), receiving 2 billion monthly users (Facebook) and 3.5 billion search requests per day (Google), these companies are seizing the global economy. The tech industry is expected to be 8% of global GDP by 2038. It doesn’t help that federal governments and regulatory bodies have failed to curb improper and reckless conduct by these companies.

But this has helped a type of innovation that seeks to upturn what it means to be human.

Fuelling this innovation is a mixture of frontier-like internal cultures, myopic senior leadership and a seemingly profit-driven directorship from board members wishing to quench the ever-unending thirst of shareholders.

While this radioactivity surely propels companies, the fallout reveals trajectories that not even the navigators understand. As the competence of these companies in delivering ideas ripens, so too does their product range. From the detonation of any product-launch, it becomes obvious to any privy eye that the blow-back from releasing more sophisticated products is only further burying the idealism that humans are irreplaceable, untouchable and made in ‘some’ image of a god.

Mapping the technological sophistication of humans across time reveals exponential development. From the emergence of Homo erectus 2 million years ago, it wasn’t until around 200,000 years ago that Homo sapiens emerged from the sub-Saharan deserts. After the migration from Africa around 70,000 years ago it took 60,000 years for the Neolithic transition where humans began developing permanent settlement to support agriculture. Around 3,400 BCE the Sumerians started writing to maintain accountancy and it took 2,000 years for us to reach Gutenberg’s printing press.

Contrast the speed of pre-history’s technological innovation with that of computers in the modern age. It only took around 60 years from Alan Turing’s 1936 thesis on ‘Turing completeness’ which formed the theoretical foundations of computers, to the patenting of Wi-Fi by Dr. John O’Sullivan’s team.

Dissecting the historic accomplishments that engineers and scientists work from shows an ever-strengthening type of concrete that’s a mixture of globalisation, richer inner-community ties, improvements in medical treatment, decreasing poverty rates, expanding educational opportunities and greater modes of transport. In short, the utility value of each human is only increasing each year thanks to the chemistry of these minerals.

The residue from our arising has cultivated machines. Our unending desire to improve our livelihood has seen us develop a general investment criteria -“Is there a cheaper way to accomplish this task?”. Like humans that developed as an evolutionary mutation from the Homo genus and subsequently carried ourselves off the trend line of nature and take control of our destiny, we’ve increasingly gifted machines with the ability to do the same. A self-mutation of humanity’s desires to improve their livelihood has culminated in the world developing an emulation of humanity to do humanity’s work.

Over time, we’ve seen a growing list of outperformances with decreasing application costs. Consider the Gutenberg printing press in 1450 taking 3 years to produce 180 bibles. Now consider not just the speed of printing 180 bibles today but also the surrounding infrastructure — Wi-Fi, colour ink, automated internationalisation, international delivery, and then the expanded capabilities of a printer — scanning, faxing, uploading directly to either a USB or cloud-based storage service, digital editing and so on.

A fundamental force behind technology is its ability to maximise throughput while minimising the necessary costs to do so. In short, technology aims at concentrating itself into just one product. I’ve written about this idea before and described it as the ‘Diamond Theory’. Simply put, the release of one product triggers an explosion of ideas that are derivatives of the initial product and so in time, once the second generation of ideas are delivered, the third-generation will attempt to compress them into one ‘super’ item. Think of the iPhone, the functionality of Facebook, high-end luxury cars and then all the features they’ve encompassed.

It should now be obvious the threat technology presents to humanity. Consequently, the goal appears to be the total annihilation of a human-based workforce. The purpose of machines perfectly remediates our pressure points. Some consider automation as a further propellant in an ‘ever’ expanding/augmenting industries that’ll just re-shape the way we work. This is partly correct as it’ll initially expand the ability of human workers yet eventually there’ll be an inflexion point when a product encompasses all the necessary ‘features’ that humans require to complete their work. We can call this inflexion point the moment when our machines demonstrate ‘general machine-workforce competence’ (GMWC).

So it becomes a matter of time. It should also be obvious that we’re experiencing an exponential rate of technological advancement that’s exploiting a network of other systems that are similarly experiencing exponential improvement. Once GMWC is crossed we’ll be left asking ourselves again — Is there a cheaper way to accomplish this task?. And this time the answer will be no.

The threat of job automation is how people view its borders now. Rather than job automation happening in 30+ years, it’s already begun. As described before in the ‘Diamond Theory’, there’s a slew of alternative features available at the moment but they’re converging towards an all-encompassing machine. It’s best to describe this moment in time as a competition between two vectors — machines and humans. Humans are decelerating in general utility value and machines exponentially increasing.

While it may seem that job automation is an inevitably (and it’s my opinion that reaching GMWC is probable this century) that is futile in fighting against, there are some ways that we can better control our future. Unlike other futuristic threats such as nuclear war initiated by rogue non-states, global warming, asteroid collisions, viral communicable diseases, job automation is uniquely positioned as being something that humans seem to want.

It’s a paradox that gets overlooked by many but it highlights the underlining drivers behind job automation — our own minds. Whether we see job automation as the only bandaid available or perhaps it’s a function of being swindled by big tech corporations, we are uniquely positioned to drive job automation in the way we want to.

With that in mind, here are three ways ordered in increasing time-commitment that can better improve an individual’s handhold on job automation.

Immediate: Ride the wave

Learn how to code so you can be innately involved in developing and commentating on the technology most likely to propel job automation towards GMWC. Preferably learn Python (version 3.5 as of writing) as it’s used in a range of applications including front-end (what users see on a website/app) and back-end (the logic an application has to execute to provide the user with their relevant data) development and machine-learning (exploiting a dataset to derive insights).

Medium-Term: Research alternatives

This includes genetics, psychology, pharmacology, anthropology and history. If the goal of machines is to expend the competence of humanity, then we need to be sure that there aren’t alternatives.

Long-term: Invest in political and social infrastructures

Political involvement and legislation are the only restraints that can properly control a safe transition to job automation if we choose to pursue it. Whether this necessitates passing legislation to make N number of jobs available to humans, curtailing the ability of associated technology (a technically offensive measure that inherently requires innate understanding of how job automation may develop) so to perhaps deliberately reduce the accuracy of automated-services so humans remain skilfully competitive. Alternatively, more intrinsic solutions such as subsidising education or providing financial rewards to use a human-based workforce could be possible workarounds.

It’s important to remember that with anything in motion, there’s a set of variables affecting its trajectory. Some systems have compounding acceleration meaning there’s greater force required in slowing or even halting movement. While anything can appear overwhelming, its nature is a consequence of a set of sub-structures. Attacking these sub-structures handicaps such a force. But inaction needs action.