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When the current tech talent isn’t enough

Super proud of all you guys sticking to the newsletter! Thank you! Three weeks now running The Aleph
When the current tech talent isn’t enough
By Alex Barrera • Issue #3 • View online
Super proud of all you guys sticking to the newsletter! Thank you! Three weeks now running The Aleph Report and the family keeps growing. As we don’t grow based on traffic (we’ll leave the round and acquisition news to others :P), if you enjoy the articles, feel free to invite people that might enjoy them too to subscribe to the newsletter :) This week I took a different angle and went more on the humanistic side, instead of the hardware-based innovation. I hope you enjoy it!

When the current tech talent isn’t enough
Technology is becoming ubiquitous in any company, but not all companies use technology in the same way. Some organizations use technology to aid their processes. Others make technology their core business.
Using technology to support your business is not enough anymore. The market is demanding more complex products and services, products that require sophisticated approaches that most companies aren’t able to provide. Only the use of advanced technology can render such products.
Digital Transformation isn’t a new trend; it’s the tax of doing business. No matter your industry, your size or your market. Not moving technology to the core of your operations will kill your business in the next few years.
But digital transformation assumes there is enough technical talent in the market. There isn’t. New incumbents need to fight, not only with the technology corporates but with a massive drought of talent.
The use of Artificial Intelligence, Machine Learning algorithms and data aggregation is becoming critical for survival.
Digital transformation isn’t enough either. Digitalizing your product catalog won’t cut it anymore. Switching to a mobile site won’t make you sell more. Despite what many business owners think, the use of Artificial Intelligence, Machine Learning algorithms and data aggregation is becoming critical for survival.
The problem is, these cutting-edge methods beseech out-of-the-ordinary talent. It’s not enough to be a Computer Science graduate.
Machine Learning or Deep Learning methods need a multi-disciplinary approach. Something most current engineers aren’t good at. It entreats the use of sophisticated mathematical techniques, paired with probabilistic views.
The use and adoption of new technology go faster than our capacity to train people (4-5 years degrees).
Where is the talent?
The question is, how are we mitigating this? The answer is, we aren’t. If you aren’t one of the big technology companies, you are at a massive disadvantage. Not only you’ll find it hard to attract talent without exciting, billion-people-impact projects. You’ll have a hard time matching their salaries too.
Source: 2017 State Of Global Tech salaries
Source: 2017 State Of Global Tech salaries
Source: 2017 State Of Global Tech salaries
Source: 2017 State Of Global Tech salaries
Source: 2017 State Of Global Tech salaries
Source: 2017 State Of Global Tech salaries
The top technology organizations are having a devastating effect on the market. To keep expanding their systems, they’re hiring experts at an ever-increasing rate. They’re quite literally, draining the talent pool. They aren’t just pulling new and old graduates, but also University professors into their midst.
This is having a dire effect on the incumbent players. Not only they won’t find talent. The talent they gain will be sub-prime. Even worse, the sucking out of professors will hinder the ability of many institutions to produce top rate graduates in the future.
“With more than half of new CS Ph.D.s drawn to opportunities in industry, hiring and retaining CS faculty is currently an acute challenge that limits institutions’ abilities to respond to increasing CS enrollments.”

(Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments Report by the National Academy Press.)
Many are turning to Massive Open Online Courses (MOOCs) as the solution. If we can retrain talent from other specialties and do it fast and cheap, we might be able to offset some of the demand.
The reality though is different. MOOCs aren’t reaching the scale that the industry needs. Quite the opposite. Completion rates for MOOCs hoover between 7% – 10%. Despite all the hype, it seems that the open-to-all approach isn’t yielding the rates that the industry expects. In some instances, the rates of completion are even worse than traditional higher education institutions.
In 2013, some MOOC providers started pivoting to different approaches. What’s clear is that free on-demand courses don’t work. People need incentives. Paid certifications, semi-synchronous and instructor-led courses are crucial for better completion rates.
Some providers are partnering up with existing higher education institutions delivering MOOC-based degrees.
Coursera Launches Two New Masters Degrees, Plans to Offer Up to 20 Degree Programs
Coursera Launches Two New Masters Degrees, Plans to Offer Up to 20 Degree Programs
Others like Udacity, are approaching the problem by involving the technology industry instead. They’re creating Nanodegrees that are aligned with the needs of the industry.
Udacity is tuning their Nanodegrees to the most exciting fields of Technology right now. Their Self-Driving Car or Flying car Nanodegrees, for example, are drawing massive success (18.000 Nanodegree graduates, 4x up from 2016).
The key to their success is double. They’re teaching applied Artificial Intelligence use cases, instead of just the dry mathematical approach taken by traditional universities. Also, they’re enrolling the top experts in the industry to give the classes and showcase their work. These are the same experts, big tech giants, are looting from university R&D labs.
Technology organizations are getting involved on these Nanodegrees, both with talent and money. Their goal is to hire the junior students of such Nanodegrees to populate their labs. Companies like IBM Watson, Google or Didi Chuxing, are betting on this approach.
Other companies, like WeWork, the global coworking company, are buying boot camp schools altogether. This way they’re able to offer a new source of talent to their customers. It seems that the industry is investing heavily in alternative talent pools.
The question is, for all those incumbents out there, what exactly are they doing to foster talent?
While technology corporations might seem to be fixed in their industry, they’re expanding and owning adjacent sectors at a rapid pace.
As the education moves from “open” to scarce, limited and expensive, how can we retrain minorities and other at-risk groups? Ignoring this rift will only increase the chasm between the technology elites and the rest of the population.
The gap between the capacity of technology corporations to amass talent and all the rest is widening exponentially every month. The more it swells, the harder it will be for other industries to compete with them. And while technology corporations might seem to be fixed in their industry, they’re expanding and owning adjacent sectors at a rapid pace.
Incumbents should invest in supporting alternative talent pools for their purpose. They should embrace challenging projects that can be interesting to potential candidates.
Despite all this, the truth is that the automation of many jobs is accelerating the rate at which we destroy jobs. While automation also creates new job positions, the speed imbalance between both is increasing too.
The problem is so acute that some organizations are, paradoxically, investing in even more automation. Two reasons are driving this. It’s harder than ever to find the talent they need. And the complexity of the new products requires a super-specialized workforce. A workforce that’s impossible to grow and train at the industry’s rate.
What are top corporations doing? They’re training their AIs to do these jobs. Train an AI once, replicate ad infinitum. This is precisely what Foxconn is doing with their micro robotic arms or Google’s DeepMind:
Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play.
[…]
It is able to do this by using a novel form of reinforcement learning, in which AlphaGo Zero becomes its own teacher.

(Mastering the game of Go without human knowledge, Nature 550.)
I wouldn’t be surprised that, as I mentioned in the Quantum Computing article, more companies turn to AI-based employees, instead of training humans.
The development of such algorithms isn’t trivial and requires extensive mathematical knowledge. Something that isn’t common. […] As a side note, I wonder if the current Deep Learning models can’t be applied to the task of developing new Quantum Algorithms.
Conclusions
It’s hard to predict how this will end. What’s true is that the situation is grim. Access to advance training is expensive and limited. If you’re not investing in securing your access to talent, it might be too later for you.
It’s worrisome to see that there are no structured plans to retrain any displaced labor due to increased automation in the workplace. If organizations fail to upgrade, drastically, their workforce, they’ll face significant problems. They won’t be able to grow and compete with other offerings. Technology-based aggregators will surpass them and asphyxiate their market share.
How is your organization upgrading their talent? Human-resources one-time workshops don’t cut it anymore. How are you enhancing your skills, personally? And more importantly, how are you preparing your children for the future?
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Alex Barrera

The Aleph Report

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