Machine Learning impact on humans

Just listened to an interesting Ted Talk by Jeremy Howard in Brussels which led me to view the Tedx talk in SF 

Things I loved:

  • Machine Learning is a fascinating field
  • In 2011, an algorithm was created that had better recognition of stop signs than humans
  • Similarities of Machine Learning to the Industrial Revolution, but not exact comparison
  • Opportunity to predict continued evolution and focus on quality of life – using the ‘good’ not fearing the ‘bad’
  • LOVED the demo of the auto recognition – and the learning ability to sort fronts from backs of cars

If the learning curve (pardon the pun) of machine learning is truly exponential when compared to the linear curve of the industrial revolution, we indeed need to address how humans and machines contribute to society.

Income tax and labor fees no longer apply. Should government fees that are used to make our lives safer and easier (public services, roads and infrastructure) be applied to machines? How will upkeep and continued positive contribution by machines be assessed and managed?

Simply with what is already released, this could be commercialized into short-term machine learning innovations that will make our lives safer and more pleasant.

It’s simple to imagine forward-facing cameras on cars. Identify stop signs and warn driver if speed is high when approaching a stop sign. The upgrade path here is obvious: red lights, crossing pedestrians, bicyclists, oncoming traffic, etc. Key issues will be what is the reaction –  the device should simply alert the driver in the short term. Later the insurance industry will begin offering financial incentive to tie reactions to automatic braking.

 

 

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