The Story of the Future of Work — Part 1

Jason J Sosa
Blackbox AI
Published in
5 min readJun 4, 2018

“The future is already here — it’s just not very evenly distributed.” — William Gibson

Part 1: Introduction — The Past

Technologies have progressed exponentially — such that a massively scalable, distributed, and efficient organization can emerge equipped to excel in the future of work. But to explain the future, the past and present must be understood.

Work is one of the many things we spend a lifetime doing, but only a moment truly contemplating. Today, artificial intelligence is diagnosing disease, providing legal advice, and it’s estimated that half of US jobs are at risk of automation in the next five years. What is the future of work?

The challenge is that the rate of change driven by technology is not linear, but it is exponential. Technology compounds on itself, as reflected in Moore’s law.

Moore’s law is an observation made by Intel co-founder Gordon Moore in 1965. He noticed that the number of transistors per square inch on integrated circuits had doubled every year since their invention. Moore’s law predicts that this trend will continue into the foreseeable future.

The power of the computer has been doubling on itself for the past 40 years, and will likely continue to do so. At the same time, the cost of technology has dropped significantly.

So, why should you care? Well, due to this exponential rate of change, we can no longer wait to adapt — there simply isn’t time. Our only hope is to anticipate the coming changes, or much like the dinosaur, we too will become extinct.

My generation perceives the pace of change as evolutionary. I grew up blowing dust out of video game cartridges in the 80s. Today, I have a supercomputer that fits in my pocket.

To put this technology acceleration in perspective: imagine the pace of change in the 20th century, starting from 1900 to the year 2000 — just 100 years of technological change. By contrast, the next 100 years (21st century) will experience 20,000 years of relative technological change. That’s 20,000 years crammed into 100 (source: Ray Kurzweil).

There are 50 million Americans in the gig economy and will represent 40% of the US workforce in the next five years. The days of being trapped in one location for a job may not be the norm in the future. Today, it’s common to work on multiple projects at the same time — with ad hoc teams of people based all over the world, all working remotely from a coffee shop, dining room, home office, or hotel lounge.

Automation won’t be confined to just blue-collar manufacturing work or retail jobs. Jobs in computer programming could be impacted by artificial intelligence as well. An AI could steal bits of code from other programs, thus being able to write itself.

We’ve seen it before: farmers went to work in the factory. Factory workers moved into the service occupations. Retail workers transferred to personal care roles. Previously, we had generations to make these transitions. This time, it’s happening intra-generationally due to an exponentially accelerating rate of change.

We are at a unique moment in time. We are no longer able to adapt fast enough. Technologically-driven changes are outpacing our ability to understand, regulate, or control them. We have passed the point of no return, where the rate of change exceeds the rate at which we can adapt.

To regain our ability to evolve, we need to accelerate our rate of learning — and be willing to learn continuously from this point forward.

The end of the human workforce has been predicted before. During the industrial era of the 19th century, farmworkers were left behind. The arrival of steam power threatened employees. In the 1950s, early computers caused concern that machines would take over. Why is this time any different?

The challenge with exponential change is that we overestimate what it can do in a year, and underestimate what it can do in a decade.

Society has made transitions in the past, but this reality is extremely troublesome. According to an Oxford study, half of US jobs are threatened by automation. In China, more than ⅔ of the work done by humans could be done by robots.

People will say, “Oh, don’t worry about it — we’ll create more jobs.” But the individuals who have done the research — from the World Economic Forum to the White House — show that the world of work faces massive change. This means we will not be able to sustain the same level of employment through new jobs alone.

Large proportions of those put out of work will be in their late 40s and 50s, with decades to wait before they can claim social security if such a thing will even exist. With limited employment options, a new poverty trap may be emerging.

Automation will replace workers throughout the employment ladder.

Customer service workers will be replaced by kiosks. Augmented reality avatars could replace clerks and service attendants entirely. It’s hard to imagine now, but in the not so distant future, a digital world will soon be layered on top of the physical world at all times. Today, we’re able to do things that would seem unimaginable ten years ago. Likewise, in just a few years, reality itself will be affected by the digital revolution.

Technology is reaching “hockey stick growth,” with billions of dollars pouring into artificial intelligence companies. The next era of technology is enormously consequential.

My home town of Holland Michigan has a regional population of 280,000. Our economy has a 14% dependence on manufacturing, compared to a 7% nationally. The current unemployment rate is 2.9%. Even if they wanted to bring more work, there simply wouldn’t be enough people to fill the roles.

As a community dependent on manufacturing jobs, we need to confront this question before it is upon us: if machines are capable of doing almost any work humans can do, what will humans do?

Presently, most of the jobs at risk of automation are lower-skilled service jobs like call centers or in manufacturing — but office jobs are in danger of automation as well.

Read The Story of Work Part II

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Jason J Sosa
Blackbox AI

Founder/CEO of Azara.ai - We build AI Employees for Enterprise