When machines learn to do what you do

For a brief time, I was a spy! On a clandestine mission, sending and receiving encrypted messages with my associates. That was for about 5 minutes and then I had to give someone else a go.

Exploring the city of spies @spionagemuseum

On a recent trip to Berlin I visited the German Spy Museum and spent hours upon hours enjoying the exhibits, the interactive displays, and learning so much about the history, and ingenuity of spy craft. One of the many interesting topics was the history of industrial espionage. From navigating to new worlds, metallurgy secrets and weaving cloth, the wealth to be gained was immense. There were clear advantages in these innovations that those who had them went to great lengths to protect what they had. Some others went to great lengths get a hold of it too.

One such innovation, was the automated weaving loom.

The history around the automation of the weaving loom was something I was already familiar with, particularly as Jacquard’s loom inspired Charles Babbage in early computational device design. The Jacquard Loom automated the work of weavers. Changing the punch cards changed the pattern, giving the weaver endless ways to “program” this device and to create intricate tapestries, damasks, brocades and other fabrics. What I did not know before writing this article was the difference between damask and brocade fabrics. Which goes to show that you can learn knew things. More on that later.

What’s the big deal about this automated loom then? Well, traditional silk weavers could produce approximately 2cm of complex fabric in a day. The skilled Jacquard Loom operator, however, could create approximately 50cm of fabric in the same amount of time.

The automated loom, which allowed for an incredible rise in cloth production, and more complex designs, was over 100 years in the making though. The challenges were not just technical. There was considerable opposition to machines destroying the livelihoods of weavers and those that worked in the weaving industry.

No doubt there were some who saw the attempts at automation in the mid 18th century and thought there was no way these clumsy, unreliable, and high maintenance contraptions would ever take the place of a human. Similar to how the Roomba of today does not put any cleaner in fear of replacement. Yet.

The topic of automation eliminating jobs is not a new one. For a many years some researchers and analysts have referred to the industrial revolution as the first machine age where automation changed the nature of repetitive manual work. Some consider us in a second machine age where it is not simply manual work being replaced. Research shows that there are worries about job automation globally.

A quick side note…the Washington Post review of The Second Machine Age, a book by two MIT professors who have coined the phrase, is exceptionally good. Much better than what I could have done, so I’ll link to that Washington Post review.

Back to the machines…What makes the industrial revolution significant over other periods of innovation is that before the first machine age, technological innovation resulted in larger populations, not wealthier populations. Take a look at those Our World In Data charts: https://ourworldindata.org/economic-growth

The real difference was on scale. Machines could make something that was prohibitively expensive, or time consuming, possible. A modern example would be the use of artificial intelligence to analyse sales calls which is what sales managers would do as part of developing their team. The good news is that one manager could potentially have a larger team. The bad news is that there may not be a need for so many managers.

Life long learning

A generation ago, the half-life of a skill was about 26 years, and that was the model for a career. Today, it’s four and half years and dropping

Indranil Roy – Future of Work

Looking back again at the weavers, those who continued in the industry became designers, putting an emphasis on the design and planning skills that were already apart of the weaver job description. They would also have learned the mechanics of the machines that was transforming their industry forever. This is a useful guide for how we should plan for more automation in our careers: constantly updating skills.

Which skills are worth updating though? Perhaps more importantly, how can one identify the skills that one has an ability for? Joseph E. Aoun suggests that there are three disciplines to consider: technical, data and human. These are effectively…

  • awareness and familiarity with the automation technologies emerging.
  • cognitive skills and data literacy so that more information-centric skills can be applied to understand the world around us and devise new strategies based on that understanding.
  • an understanding of creative practices and cultural experiences that develops the ability to take information from one context and apply it to another.

The technical and data abilities are perhaps the easiest to justify spending time and money on because the connection between them and work is much clearer. Deloitte’s Future of Work Centre of Excellence identifies these talents that are needed in the work place. These talents can help assess, and take advantage of, a process or level of quality that previously was too expensive, or impossible, until now. An employee dedicates a few hours a week to study digital marketing and before you know it, the business has a social media strategy.

However, the soft skills that are going to pay off are harder to identify, simply because of the human element. A passion for travel, baking, music or sports may not lead to a new career but can be very rewarding and by sharing that, may reveal new connections or opportunities. That digital marketing expert mentioned earlier may only have taken the initiative because of their interest in photography.

One of my favorite podcasts is NPR’s How I build this and here are just a few examples of people taking their interests, seeing that there’s a gap in the market, and doing more: SoulCycle, KickStarter, method, Drybar. The stories are inspirational but make it clear that even with planning, collaboration and support, success did not come easy.

You may be fortunate to have an employer that supports skill development, either by providing leave to study, or even a contribution to the cost of studying. Quite often the effort that goes into making the case to your employer for training is exactly the right measuring stick to gauge if this is something you really want to do. Perhaps you are not so fortunate and will have to cover the time and cost out of your own free time and pocket. If that’s the case, visit your local library or enterprise board because there may be grants or other schemes available to lessen the burden. Many OECD countries are coming around to be more proactive in supporting skills development in the workforce.

In summary, technological advances will make certain fields of expertise obsolete but will introduce new ones that we should prepare for. The best way to prepare is through learning new skills, but we do have to identify and choose the right ones. There are no easy answers to making that decision. That is, until someone comes up with an AI for exactly that purpose.

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