Thursday, 27 February 2014

Jobs For The Machines: The Story of Your Unenslavement

Jobs For The Machines
The Story of Your Unenslavement



Jobs For The Machines



Artificial intelligence researcher and entrepreneur Jeremy Howard spoke recently on the impact of machine learning on productivity, and what the potential consequences may be for employment.




     





Jeremy Howard recently spoke at the Davos World Economic Forum, on the impact of machine learning on productivity, and what the potential consequences may be for employment (video below).

Before the industrial revolution, most people worked in agriculture, recounts Howard, decades after machines took those jobs, he claims that eighty percent of the workers were much worse off, in fact they did not have a basic living wage.


With machine learning, Howard claims this is about to happen again.  Such a view is also supported by Brynjolfsson and McAfee in their books, Race Against the Machine and The Second Machine Age.

According to Howard, the economic data is already pointing out the fact that technological obsolescence is already upon us.  Productivity is at record levels, whereas employment is stagnant or even going down. 



Howard concludes, "Be aware of the exciting opportunities of machine learning,  but also be aware of the threats to our socio-economic systems."

A serial entrepreneur, business strategist, software developer, and committed educator, Jeremy is developing a new startup, Strategic Data Science, which aims to make machine learning accessible to non-experts. He is also currently a faculty member at Singularity University, where he teaches data science to government leaders, business executives, research scientists, and graduate students in order to "educate, inspire, and empower" them to apply exponential technologies to address some of humanity's most pressing challenges.

He was president and chief scientist at Kaggle, a consulting platform that hosts competitions in which scientists from many disciplines use predictive modeling to solve problems that require analyzing large amounts of data.

Howard studied philosophy and worked as a management consultant before developing a passion for applying algorithms to data. Today he competes regularly in data mining competitions, which he uses to test himself and stay on the leading edge of machine learning and predictive modeling technology.





Note - The audio quality of the video is not the best, don't forget to turn down the volume after viewing. 

From 33rd Square @ http://www.33rdsquare.com/2014/02/jobs-for-machines.html



  
Slavery By Consent


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2 comments:

  1. In fact the gap between automated production and employment is much greater. The decline of employment began to go way down around the year 1913 when machines began to produce more than labor alone. That's when we learned that when we increased the kilowatt hours used to operate the production and distribution process (energy consuming devices i.e machines productivity) labor began to decrease. In other words we were able to produce much more with less man hours of human labor... This trend continues on today... One way in which they continue to prop up the so called employment numbers is through government jobs (unnecessary jobs) you know the kind, paper pushing waste jobs that have nothing whatsoever to do with the production and distribution process... Politicos are a fine example of what is NOT necessary in the production process, they simply ACT as interference elements. Lawyers ACT as other interference elements, and accountants, etc.... All these jobs are jokes for keeping deception games going. They're used to keep a bogus, wasteful, and deadly scarcity based value system going, but not growing.

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  2. Aye, and remember the biggest, grubbiest, most obese parasites of all - the finance 'industry' and religions ;)

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