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The Intelligence Revolution (Part 2)

The Four Rs: Changing Jobs in a Changing World


The Intelligence Revolution will transform many aspects of our lives, but few as radically as work and employment.

By its very nature, progress is disruptive. Technological advances lead to the development of new markets and the withering away of old ones. They generate new laws and regulations. In the most extreme cases, they can even threaten our existence as a species. But of all of these changes, none touches us more personally and immediately than the those that affect our jobs.

Work puts a roof over our heads and food on our table. It makes it possible to provide for our family. If we’re fortunate, it contributes to our sense of purpose and identity.

But if change is disruptive, how much more upheaval will we see in coming years as the world undergoes accelerating change? The rate of technological advancement has been slowly increasing for many centuries, but only recently has it reached a point where we’re aware of it on practically a day-to-day basis. Every week, there are new breakthroughs and devices that will alter some aspect of our lives. This trend shows few signs of letting up. If anything, the increasing intelligence of our tools is only going to accelerate the rate of change further.

For generations, it was typical to perform the same trade as our parents and their parents before them and so on. In the middle of the 20th Century, many people worked for a single company throughout their entire career. By the end of the century, this had become far less common.

According to a longitudinal survey by the Bureau of Labor Statistics released in 2008, younger baby boomers held an average of 10.8 jobs between the ages of 18 and 42. (The Bureau doesn’t define or track career changes, contrary to a commonly quoted statistic about its frequency. Nevertheless, a general trend can still be extrapolated from the jobs numbers.) If much of this shift in job security is due to technological progress and the rate of that progress continues to accelerate, what will it mean for all workers and the society they support in the years ahead?

In the face of such change, we have little choice but to adapt. Attempting to hold on to older, less efficient work methods has failed since before the Luddites tried to sabotage mechanized looms in the early 1800s. The ability to produce more efficiently almost always results in increased productivity which lowers real prices. This is a difficult incentive to fight despite the upheaval it often brings.

Adapting to a rapidly changing world means shifting how we look at careers, identity and education. More and more, it’s going to become necessary to re-invent ourselves, matching our strengths and skill sets to the changing marketplace. With this new path identified, we’ll need to re-educate ourselves to prepare for work in new and changing fields. Over time, we’ll rebuild our careers, combining prior experience with our more recently acquired skills. Then, as technology and the fields it creates and supports continue to advance, the cycle will repeat and it will be necessary to do it all over again.

For many of us, adopting these Four Rs will feel very foreign, even threatening. Embracing change is not typically in our nature. But adapting to it is. The world we live and work in is being transformed whether we want it or not. As with all sea changes, we have a choice. We can swim with the tide or be overwhelmed by it.

Affordable higher education that continues throughout our lifetimes will be essential to making this possible. Likewise, regular career counseling. These will be necessary if we’re to maintain a work force that can support the many high tech fields that are sure to arise in the coming decades. The health of our entire economy depends on the right approach.

Progress is accelerating, changing the world before our eyes. It will bring many challenges, but with it many opportunities as well. To thrive in this rapidly changing world, we’ll need to recognize that our working lives will be changing as rapidly as everything else. The Four Rs may be one way we can adapt to an accelerating future.

    Re-Invent.
    Re-Educate.
    Re-Build.
    Repeat.

Data mining for treasure


When I talk about the intelligent future, I’m referring to far more than just artificial intelligence and intelligence amplification. The application of existing knowledge and tools in new and innovative ways will play just as much a role. One excellent example can be found in a paper published yesterday in the Proceedings of the National Academy of Sciences. In “MiDReG: A method of mining developmentally regulated genes using Boolean implications”, Stanford University computer scientist,
Debashis Sahoo describes a computational method for bioinformatic data mining that may have a tremendous impact in biotech and the health sciences.

The method uses Boolean logic to identify genes having specific relationships and expressions in fractions of a second. Such identification can take years and cost hundreds of thousands of dollars using existing laboratory techniques. Still another benefit of this computational approach is that it can be used to mine existing databases.

This is a perfect example of how the convergence of informational technologies leads to accelerating progress. I would expect Sahoo’s method to radically increase our understanding of many genetic processes. I think this and other computational methods are likely to yield significant discoveries in cancer and aging research during the coming decade.

Advances in AI

A number of recent stories illustrate the rapid progress that’s being made in many different fields linked to artificial intelligence:

Europe’s four-year AMARSi project (Adaptive Modular Architecture for Rich Motor Skills) could lead to humanoid robots that quickly acquire skills from human co-workers as well as their environments.
AMARSi project could see robots learn from co-workers

Also from Europe is HUMAVIPS (Humanoids with Auditory and Visual Abilities in Populated Spaces) which seeks to improve the ways humans and robots communicate and interact.
Humanoid robots to gain advanced social skills

A research team at the University of Michigan at Ann Arbor has demonstrated how memristors can mimic the behavior of brain synapses.
Electronics ‘missing link’ brings neural computing closer

The Intelligence Revolution (Part 1)

In the intelligent future, positions, roles, entire fields will disappear from the jobs market. In many cases, the tasks themselves will still exist but increasingly they’ll be done by evermore intelligent technologies instead of by humans. As in the past, these changes will be motivated by market forces and the ongoing incentive to improve efficiency and productivity. And like the Digital Revolution and the Industrial Revolution before it, the Intelligence Revolution will transform the jobs landscape for still another reason. Because it will lead to increasingly rapid innovation and product creation.

In the past, machines have eliminated jobs because they could be designed to be faster, stronger and more tireless than their flesh and blood counterparts. During the Industrial Revolution, this meant lower skilled, often highly-repetitive labor was displaced. Spinning, weaving and sewing machines transformed the work environment. Vast numbers of trades people saw their work taken away by what would eventually become a worldwide clothing industry. Which would itself one day create millions of jobs. Likewise, unskilled manual labor. Before the beginning of the Industrial Revolution, roads and railways were built on the backs of thousands of workers. Today with the aid of machines, dozens can do the work previously performed by hundreds, if not thousands. These technologies (along with many others that came after them) built the cities, highways and factories that led to still more jobs.

The Digital Revolution had similar impacts. Office functions have seen such increases in efficiency that a single person can perform the work once performed by many. At the same time, that worker has seen a huge increase in available skills and technologies. These changes also took away a lot of jobs but led to the creation of many new ones as well. Desktop publishing, digital photography and digital video production utterly transformed their fields. At the same time these new technologies eliminated jobs, they put the ability to create mass media into the hands of an unprecedented number of people.

This antenna was created for a NASA communication satellite using evolutionary algorithms.  It was designed to be efficient, not pretty.
This antenna was created for a NASA communication satellite using evolutionary algorithms. It was designed to be efficient, not pretty.

But I suspect these examples will pale beside the changes that will be brought about by the Intelligence Revolution. Two fields that are poised to transform entire industries are those of automated invention and rapid prototyping. Using techniques such as genetic programming (algorithms that utilize fitness selection), computers are increasingly able to invent devices that are far more efficient than anything that could be created by a person. For instance, Evolutionary Antenna Synthesis is leading to better, more cost-effectively designed antennas. In another field, evolvable hardware has improved microprocessor design, creating circuits that are far denser, increasingly complex and fault-tolerant than anything that could be created by a team of unaided humans.

As they develop, 3-D printer rapid-prototyping technologies will allow us to implement these inventions and designs far faster than we ever could before. The creation of open source rapid-prototypers, such as the RepRap and MakerBot projects, will make these technologies widely available, leading to a democratization of this process as well. 3-D designs for these machines are already widely shared and distributed via the internet and the concept will likely lead to downward price pressure as these technologies become increasingly sophisticated.

All of this is leading to a sea change for job markets and how we approach our careers and education. As always, such change will have consequences both good and bad. I’ll elaborate on this further in Part 2 of this series.

Natural responses to technological change


This music was composed by a prolific, young composer named Emi. During a brief career, Emi created thousands of works, many of them in the style of famous composers, such as Bach, Beethoven, and Chopin. These compositions have been described as moving, soulful, emotional. In many ways, Emi may prove to be one of the most important composers of the age. Emi is also a computer program.

When many listeners first learn the nature of these compositions, particularly after believing they were created by a person, their opinion of the work changes dramatically. Music they previously called soulful or inspiring becomes calculating, stilted, even mechanistic. This points to a human chauvinism about the growing intelligence of our machines which we would be wise to examine. As with so many developments in artificial intelligence, there seems to be resistance against any encroachment into what we regard as the realm of human intellect. Just as chess masters once denigrated the abilities of chess-playing computers, each new hurdle in AI will probably be met with similar resistance.

Though it may sound a little strange, I’m going to suggest that this response follows a pattern similar to Kubler-Ross’s five stages of grief: denial, anger, bargaining, depression and acceptance. Grief is a normal response to loss and it may be that many people feel they are losing something crucial when technology begins to take on functions previously exclusive to humans. Obviously, disbelief is a common enough reaction to new and developing technology, but it’s hard to maintain for long in the face of direct evidence. Emi’s creator, University of California, Santa Cruz professor, David Cope, has reported considerable anger from listeners in response to Emi’s work, as well as his later program, Emily Howell.

It’s almost as if the listener felt tricked or cheated once they discovered the music was created by an artificial intelligence rather than a natural one. As for bargaining and depression, I suspect these are not unfamiliar to people who have seen their career plans radically altered by the continually shifting technological landscape.

Then there’s acceptance. So much AI has been accepted that most of us no longer categorize it as AI at all. When was the last time you used spell check, or a voice menu or played a video game and acknowledged the leaps in artificial intelligence that made them possible? Typically, we don’t. They simply become another piece of the background of our technologically enhanced lives.

All of these are probably very natural responses. We humans have considered ourselves to stand at the pinnacle of intelligence for so very long. Nothing in the animal kingdom even comes close to the height of human achievement and for the most part, our machines are even further down the scale. Many will argue that the types of intelligences exhibited by these machines is very limited and domain-specific. That they are examples of weak AI – sets of rules and knowledge bases and Bayesian pattern recognition algorithms. There’s no way any of these could ever develop into something that would rival our marvelous minds.

But more and more evidence is indicating that our brains are themselves composed of myriad subsystems which together make up the sum total of our intellect. Marvin Minsky’sSociety of Mind” describes the concept very well. Why shouldn’t an artificial general intelligence be composed of modules, agents and subsystems too?

With each new leap in machine intelligence, we come a little closer to slipping from our pinnacle on Mount Intellect. Lightning-fast calculation, expert diagnostic systems, face and image recognition, real-time voice translation. Exponential improvements in both hardware and software are rapidly driving us into a new era. It will be an era in which we’ll likely share the stage of superior intelligence with many other players. That is, we will if we’re lucky.

Smart dust for making smarter decisions

Imagine if you didn’t have a nervous system.  Your body would have no way of regulating any of its other systems.  It wouldn’t know if it was too hot or too cold.  It couldn’t register dangers and harmful conditions.  Every aspect of the environment would be shut off to it.  In short, without a nervous system, you wouldn’t survive very long.

The fact is, in order to know how to respond to conditions you need to know what those conditions are.  This is some of the thinking behind “smart dust” – very small, very cheap networked sensors for measuring all kinds of different aspects of our environment. It’s also the idea behind HP’s “Central Nervous System for the Earth” project or CeNSE.  By developing sensors that can detect motion, vibration, light, temperature, air pressure, air flow and humidity, HP hopes to see them deployed throughout the environment.  These will be able to keep watch over the structural integrity of buildings, bridges and other infrastructure.  Chemical sensors will be able to detect dangerous conditions in our air, food and water.  They’ll eventually be capable of alerting us in the event of a terrorist attack using biological agents.  In short, they’ll be our eyes, ears, noses and much more.  They’ll become a new kind of nervous system.

This would be tremendously useful for monitoring manmade structures.  A US DOT 2008 survey of over 600,00 bridges found nearly 27% to be structurally deficient or functionally obsolete.  There is simply no way we have a sufficient number of trained people to adequately monitor all of these.  And that’s only the bridges.  A system of inexpensive sensors that can watch for excessive vibration levels and structural deformity in order to avoid catastrophic collapse will be money very well spent.

Obviously, the environment already has its own kind of feedback loops through which it adapts to changing conditions.  But humanity has imposed itself so thoroughly onto the environment that we need better ways of gauging our effect on it.  Hopefully, this kind of data will allow us to make better, more informed decisions about mitigating environmental impact.  Certainly, this would be preferable to making knee-jerk, expensive, politically feel-good decisions that often do more harm than good.  (e.g., subsidizing the conversion of food crops to ethanol crops and thereby exacerbating food shortages in parts of the world.)

Obviously, there will be downsides to this kind of technology, most notably in terms of its potential use in surveillance.  As with most technological developments, the answer is not in trying to prohibit it but to adapt our laws and institutions to deal with our changing world.  A world we will be knowing much more about, very shortly.

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