Monday Mornings with Madison

Remaining Relevant in 2017 and Beyond, Part 1

The world’s most sophisticated computers can out-think most humans today.  They have more memory, greater instant access to information and don’t need anything except electricity (and maybe an Internet connection) to keep going 24 hours a day.  Even the average laptop is able to perform many tasks that once required human involvement.  And, as robotics are infused into more machinery and engineering, the work once done by humans to make things is also being increasingly replaced by computerized machines.  Robots don’t need sleep, hydration, nutrition or oxygen to breath.  Robots don’t take vacations, don’t go on maternity leave, don’t need coffee breaks (or coffee, for that matter), or want fringe benefits like increasingly expensive health insurance.  Robots don’t have bad days, sick kids or aging parents.  Computers and robots have a shorter life span, but can be depreciated and written off on taxes, along with other equipment.  In short, technological innovations are increasingly making some jobs obsolete.

This could be of deep concern for those who are being phased out with each new technological development.   Technology can cause some individuals to become unemployed and maybe even unemployable.  For those who are afraid of become obsolete, consider that there are certain skills that even the most intelligent computers and sophisticated robots cannot do, and likely will never be able to do (or at least not in the foreseeable future).   So what are those skills?

Smarter than the Smartest Computer

Watson, created by IBM, is a question-answering computer system capable of answering questions posed in natural language.  It was developed in IBM’s DeepQA project by a research team led by principal investigator David Ferrucci.  Watson was named after IBM’s first CEO and industrialist Thomas J. Watson.  It is considered the smartest computer on the planet today.

What prompted IBM to create Watson?  Originally, people were fascinated when an IBM computer named Deep Blue beat the best chess player in the world.  After Deep Blue’s victory over Garry Kasparov in chess in 1997, IBM had been on the hunt for a new challenge.  The idea surfaced as many great ideas do… during dinner.  In 2004, IBM Research manager Charles Lickel was at dinner with coworkers when he noticed that the restaurant they were in had fallen silent. He discovered the cause of the hush.  Ken Jennings, a contestant on the program Jeopardy!, was in the middle of his successful 74-game winning streak on the show.  All of the restaurant’s patrons had stopped eating to watch the program.  Intrigued by the quiz show as a possible challenge for IBM, Lickel shared his idea at work.  In 2005, IBM Research executive Paul Horn embraced Lickel’s idea, asking for someone in his department to take up the challenge of developing a computer system that could play Jeopardy! and win.  Initially, no one wanted to take on the challenge because a game that involved questions looked infinitely harder than a silent game like Chess.  Eventually David Ferrucci took up the challenge.

In competitions managed by the U.S. government, Watson’s predecessor, a system named Piquant, was usually able to respond correctly to only about 35% of the clues on a game of Jeopardy! and often required several minutes to respond. To compete successfully on Jeopardy!, the computer would need to respond correctly most of the time and in no more than a few seconds.   In initial tests run in 2006 by David Ferrucci, the senior manager of IBM’s Semantic Analysis and Integration Department, Watson was given 500 clues from past Jeopardy! programs. While the best human competitors responded correctly to as many as 95% of clues, Watson’s first try generated correct answers to 15% of the clues.  In 2007, the IBM team was given three to five years and a staff of 15 people to solve the problems.  By 2008, Watson’s capabilities had improved so much that it could compete with Jeopardy! contestants, and by February 2010, Watson could beat human Jeopardy! contestants on a regular basis.  Finally, in 2011, Watson competed on Jeopardy! against former Jeopardy! champions Brad Rutter and Ken Jennings.  During the game, Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage but was not connected to the Internet during the game.  Watson won and received the first place prize of $1 million.

By all accounts, this was considered pretty impressive.  And yet Watson’s performance was not perfect.  There were things Watson simply could not do.  In one instance, Watson repeated a reworded version of an incorrect response offered by another player.  Jennings said “What are the ’20s?” in reference to the 1920s. Then Watson said “What is 1920s?”  Because Watson could not recognize other contestants’ responses, it did not know that Jennings had already given the same response.   The computer could not refine his answer based on additional feedback from other players.   Being able to take verbal and physical cues from others to reach conclusions is something that is still uniquely human.

In another similar instance, Watson was initially given credit for a response of “What is leg?” after another contestant incorrectly responded “What is: he only had one hand?” to a clue about George Eyser.  The correct answer was, “What is: he’s missing a leg?”.  Unlike a human, Watson could not have been responding to the other player’s mistake so it was decided that this response was incorrect.  Again a computer is unable to accept additional feedback in order to better or more fully craft a response.

Also, Watson was the only contestant to miss the Final Jeopardy! response in the category U.S. CITIES.  The clue was “Its largest airport was named for a World War II hero; its second largest for a World War II battle.”  The two human contestants gave the correct response of Chicago, but Watson’s response was “What is Toronto???”.  Toronto is not even a U.S. city.  Ferrucci offered reasons why Watson would appear to have guessed a Canadian city if the category was U.S. CITIES.  The phrase “U.S. city” did not appear in the question, there are cities in the U.S. named Toronto, and Toronto in Ontario has an American League baseball team.  This could cause a computer to combine information about Toronto with the U.S.  It was also suggested Watson may not have been able to correctly parse the second part of the clue, “its second largest, for a World War II battle” (which was not a standalone clause despite it following a semicolon, and required context to understand that it was referring to a second-largest airport. Watson – a mere computer — could not aggregate information in order to determine which was a more viable answer, and did not possess the comparative knowledge to discard a potential response as not viable.

These are ways in which a computer is unable to do what a human can do.  But it does not end there.  There are many things that a computer or robot cannot do and likely will never be able to do.  Here are a few more skills beyond the capabilities of any computer or robot today.

1. Cull important data

As anyone who has ever used a search engine can attest, a computer system is great at searching and finding a LOT of data.  But it is not as good at parsing that data to pinpoint a specific piece of information.  A search today on Google for “Why can’t computers cull important data?” gave search results that included 2) a primer on data encryption practices for law firms, 3) five ways to back up data, and 5) Cull cows with carcass data.  (If you don’t believe it, do the search yourself.)  What do these things have to do with the ability of computers to cull data?  Nothing, which proves the point.  Search engines are very weak at segregating clearly non-relevant information from relevant information.  Only a human can gather all the data, sort through it, and hone in on information that is on point.

2.  Collaborate

Computers are able to gather information from many sources, but it lacks the skills to collaborate or work as a team with others – whether people or computers – to tackle problems, create solutions or innovate processes.  The ability to exchange information and then combine new information with existing information to find a better way of doing things is something that people do well and computers cannot do, as seen by Watson’s performance.

3.  Find a Problem

Not only can a computer not work with others to find solutions, it is unable to find a problem or pose a question.  A computer can only work with what it knows.  It cannot analyze a situation and identify that what is falls short of what should be.  It cannot ask “why?”  It can only provide answers that already exist.

4.  Apply values to a situation

Computers and robots are inherently amoral because they are not alive.  They cannot determine right from wrong.  They can be told that something is right or wrong, but they cannot deduce based on values or morals whether a given situation is right or wrong.  So a computer could be instructed that it is wrong to lie.  But the computer would not be able to discern the difference between a little white lie and a lie that causes harm.  For example, a computer would not understand the difference between lying and telling someone their new haircut looks good when it doesn’t and lying and telling someone to invest in a fraudulent scheme that causes him to lose his life savings.    A computer will never be able to judge or weigh situations against a set of values.

Next week, we will look at eight more skills that no computer or robot can do, and will likely never be able to do.  Stay tuned!

Quote of the Week

“Existence is no more than the precarious attainment of relevance in an intensely mobile flux of past, present, and future.” Susan Sontag

 

 

© 2017 – 2016, Written by Keren Peters-Atkinson, CMO, Madison Commercial Real Estate Services. All rights reserved.

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