The New Paradoxes of the Cloud Computing World

Source:-forbes.com

Sometimes the greatest truths make no sense. That’s not just a paradox, it’s also the definition of one.

Here is a list of paradoxes about the modern world of technology and work. Besides providing work-type entertainment, this list is intended to make a larger point about contending with the great technological changes of our time: When you’re in a landscape of technological novelty as dramatically different as ours is from even the recent past (Pocket computer smartphones! Cloud computing! Artificial intelligence!), locating the major landmarks can be a challenge. Some features are too novel to be well comprehended or applied. Language that described the previous world struggles to describe interactions of the new.

Finding the truth at the heart of certain contradictions may be the best way to move forward. Here are some attempts at new ways of seeing, via illuminating paradoxes:

1. The world’s biggest computer is also the most personal.

The big clouds are global computing systems with over a million servers apiece, cleverly networked to represent millions more computers. At any given time, millions and billions of people are diving in and out of these systems, enjoying their email, their version of the internet, their business experience, etc. No two users are the same, and a service like Google Cloud strives to anticipate particular business and personal needs—some configured by the user, some utilize artificial intelligence “agents” that enable people to write and find documents more effectively.

By comparison, servers and PCs, sold individually by the millions, have traditionally delivered impersonal experiences. The more individualized experiences that we enjoy through these devices today derive largely from the connection of servers and PCs to the cloud, infusing what was limited and cold with unbounded potential for customization.

2. In a digital world of eternal storage, vanishing analog moments rule.

A couple of years back, I calculated that 100 years ago, it cost about $30 in today’s money both to see the opera star Enrico Caruso and to buy one of his records. These days, recorded music is basically free on YouTube or other services, and the average price of a ticket for “Springsteen on Broadway” was almost $1,800 on the open market.

I believe that the reason for this, and the reason for the explosion of conferences and live business events, is that as the number of digital moments has exploded, authentic human moments have become relatively scarce. Adding to the irony, we are seeing smart ways companies are using digital technology to make the human experience more vivid, like when a sports company offers an app for a better experience navigating a sports stadium.

This observation brings me to the next paradox.

3. The jobs are going! Here come the jobs!

There’s significant concern that millions of people will have their lives turned upside down by robots and artificial intelligence (AI). Maybe so, though predictions are mixed—this well-researched McKinsey study projected both major job losses and major job gains.

While we’ve seen some robots doing relatively simple tasks, like moving things around warehouses, the impact on manual labor so far has been relatively small—and for good reason. Jobs like mowing a lawn or driving a truck turn out to require a lot of contextual judgement.

Meantime, the Bureau of Labor Statistics says there are now about 357,000 personal trainers in the U.S., and the category is expected to grow at 13% over the next decade, faster than the average job. There are 160,000 massage therapists, growing at 22%. And 55,000 marriage and family therapists, growing 22%. You get the picture: We’re putting more money toward people who look at us, touch us, and listen to us the way machines don’t.

And that’s before we get to the jobs that didn’t exist 15 years ago: drone pilot, mobile app developer, social media manager, machine learning specialist—you get the idea.

4. Specialize, especially by focusing on general relationships.

In our new data-centric world, software developers who are also experts in a company’s core business are often highly valued. That’s because connected products, the digital expression of that core business, now collect information about the product’s performance in real time, and developers can build in adjustments based on user demands or changing market conditions.

As AI becomes more important, domain-specific data plays an increasingly critical role in how products are built and optimized. The most successful developers have not just the domain expertise of a specialist, but an understanding of what data around that domain matters most, how it’s collected, and how to keep it free of bias. It’s the reason that big technology companies increasingly employ experts in healthcare or transportation or retail, for example, rather than simply hiring engineers with generalized skill sets. No data stands alone, and how things relate matters too.

5. Information is easy. Questions are hard.

A related point to the above: AI can move through unimaginable amounts of data, finding previously unknown patterns and insights. That doesn’t mean the patterns are valuable, as this entertaining chart shows. If you take all of your company’s data, petabytes of it, and only focus on demanding that it make you more money, you’re likely to end up with garbage.

Ask specific questions, however, prioritized based on a company’s core competitive advantages and the best-quality data, and you’ll likely get the most useful results. This can be difficult, but is critically important to deriving real value from data.

6. The only certainty is approximation.

I’m lifting this one from an observation by Jeff Dean, the head of Google’s research and AI efforts. He notes that advanced AI, like deep learning, doesn’t indicate decisions based on certainty, but on likelihood (what he terms “gradient points in the direction of improvement”). Moreover, given the many layers and sequences of a deep learning system, sometimes it’s hard to figure out exactly how the system came to its conclusion. It’s a machine that isn’t always good at explaining itself, unlike, say, a car engine, which can be observed and understood with a lot of certainty (a little bit of gasoline is ignited by a spark plug, causing a piston to move).

In a world increasingly dependent on statistical approximation, many of our existing legal and social rules, which are premised on an illusion of certainty, may be challenged.

7. In an uncertain new world that’s full of cutting-edge technology, the best advice can be found in an 85-year-old religious poem.

T.S. Eliot nailed our situation in one of the choruses from “The Rock”: “They constantly try to escape / From the darkness outside and within / By dreaming of systems so perfect that no one will need to be good.”

In other words, no matter how much we understand and perfect the world, we’ll all still have the hard work of trying to be good. Machines don’t fix that.