Ernest Hemingway famously quipped that going bankrupt happens “Gradually and then suddenly.”
We have become dependent on ‘smart’ technology and we didn’t even notice. Suddenly everybody is talking about automation, artificial intelligence and machine learning as if it is something new. When you look at your car, phone, TV or even your kitchen appliances you realise that this technology has been creeping up on us for quite some time. Now imagine if suddenly all of these new systems did not work, we can then begin to understand how this technology has changed our world.
Engineers have built very clever algorithms for many of the common technologies we use on a day to day basis. Some of these algorithms build up a body of data about how we interact with them in order to shape that interaction. Every time we use Google, Facebook, Amazon or a myriad of web services, we are interacting with machine learning and artificial intelligence. As I said before our cars, phones, thermostats, refrigerators and even the software we use at work like Microsoft PowerPoint, Excel and Word all contain ‘intelligent’ algorithms.
Hollywood has imprinted the ‘rise of the machines’ scenario on our psyche, which probably explains some of the negative press this emerging technology receives. Some marketers have even taken advantage of the ‘artificial intelligence’ component of this mythology to promote new products and services like IBM’s Watson. For simplicity sake I’ll combine all the technologies involved, machine learning, deep learning, speech recognition, natural language processing and robotic process automation into the common description as ‘artificial intelligent’ systems.
Does Watson think ?
The advancement in computation power and the ability to correlate data in real-time produces accurate results that previously took hours or even days. The simple truth is that software engineers have become very adept at mimicking intelligence by creating algorithms that are capable of rapid correlation and analysis to produce what looks like intelligence to us humans. Watson is a good example of how this new class of algorithms can do the massive analysis necessary to produce results not previously achievable. Pattern analysis, correlation analysis and predictive analysis are areas where Watson excels. It does not have the ability to reason and hence does not ‘think’ in the human sense. This makes it an ‘expert system’ or a ‘narrow intelligence’ system.
When will machines actually think?
‘Strong artificial intelligence’ or a ‘conscious machine’ is still something scientists are working on and there are mixed views as to when it will be achieved. The consensus is that this is still decades in the future, an optimistic estimate puts it at 2040 and a more conservative view is 2075.
A lot of people are reacting to hype and not the science of the technology right now. The impending ‘robot apocalypse’ is a common description of how industries will eliminate millions of jobs and how we will need to institute a universal basic income to help those displaced workers.
The robots are coming..the robots are coming…..
When an emerging technology threatens systems, either economic or social, critics emerge with opinions that dismiss the new technology.
“The Americans have need of the telephone, but we do not. We have plenty of messenger boys.” — Sir William Preece, chief engineer of the British Post Office, 1876
I would imagine that some of those ‘messenger boys’ eventually made their way into the telecommunications industry that exploded across the globe.
“The horse is here to stay but the automobile is only a novelty — a fad.” — The president of the Michigan Savings Bank advising Henry Ford’s lawyer, Horace Rackham, not to invest in the Ford Motor Co., 1903
The ‘fad’ transformed the world economy.
“Television won’t be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night.” — Darryl Zanuck, executive at 20th Century Fox, 1946
Television’s impact on popular culture, education, business and economics is akin to the internet today.
The growth of the Internet will slow drastically, as the flaw in “Metcalfe’s law” — which states that the number of potential connections in a network is proportional to the square of the number of participants — becomes apparent: most people have nothing to say to each other! By 2005 or so, it will become clear that the Internet’s impact on the economy has been no greater than the fax machine’s. — Paul Krugman Nobel Prize Winner and Op-Ed Columnist for the New York Times
Obviously Mr. Krugman was applying the rules to a technology he did not fully understand at the time.
Each one of these innovations displaced many jobs in the short term but added far more over time. The detractors have faded into the past as footnotes in history and as examples of predictions gone wrong. But an interesting characteristic of human nature is that negative, ‘the sky is falling’, opinions are the ones that get most attention. I think that most people are really afraid of change and negative opinions about the future reinforce that fear.
We live in our ‘opinion bubbles’ and seek out information that validates those opinions. We form these opinions by anticipating that the jouney into the unknown will end in disaster. The brave few that charge into the unknown with the anticipation of discovery use fear as the fuel that keeps their imaginations burning with the possible rather than the probable.
What does the near future look like ?
The rapid development of artificial intelligent systems yields great benefits. This new technology is exponentially more powerful than what human are capable of. Here are five examples to illustrate some of these benefits.
- Environmental impact analysis: Using the new approaches to data analysis we can monitor and model the environment. Using information from all over the globe these new approaches will show us how we impact our air, soil and water in real time.
- Autonomous Cars: What we get with safer automotive transportation is fewer accidents, our insurance costs are lowered or eliminated and we get to know exactly when we will arrive at our destination
- Accurate health care diagnosis: Artificial Intelligent systems (like Watson today) will scan vast amounts of data to help doctors diagnose illness. Having an accurate algorithm to assist with medical diagnosis will not only help patients but also help doctors be more effective with their day to day activity.
- Safer rail, airlines: Rail systems are notoriously outdated as are many airline systems. Once we have upgraded these systems to allow machine learning and artificial intelligent systems to manage and control traffic flows both rail and air travel will be more efficient and safer.
- Banking and Financial services: Any data that has a pattern, is rules based can become the raw material for analytic algorithms. Investment banks are racing to invest in specialized systems that help with decision making. Kensho is a good example of software that was created to help investment professionals with their trading decisions. It is only a matter of time until these specialized systems become mainstream and retail investors will benefit.
A brave new world
The rapid adoption of world changing technologies is dramatic when you compare what we have today with what we had twenty years ago. We have amazing communication devices, incredible choices in entertainment, long distance phone calls are a thing of the past, now we simply “Facetime” or “Skype”. Our gaming platforms have so much ‘smart’ technology that the lines between human and computer are blurring. We now talk to our cars, smart phones and even our homes to get information and execute tasks, activities that were only found in the pages of science fiction in the recent past.
So.. why so pessimistic ? Do we underestimate how resilient humanity is ? Do we always adapt to changes in our environment ?
If we assume that we maintain existing forms of learning and ignore the digital language of the future then maybe ‘the robot apocolypse’ is a possibility. But we always adapt to the changing circumstance of our environment by changing how we learn, someting we have done for hundreds of years. We will incorporate digital literacy as a basic foundational principle of learning and future generations will be more conversant than the previous one.
There is little doubt that disruption will occur in many sectors of the economy. If history is any indication of how the future will unfold we have seen that innovation always creates whole new categories of businesses and services and consequently more jobs.
Thanks for reading
Best regards: Norman King
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