CascadiaPrime Cognition

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CascadiaPrime Cognition - A Short Introduction to Artifical Intelligence and Aiification

AIification is the process of cognition by artificial intelligence (AI) with machine learning capabilities and is associated with changing over from previous cognitive sources. A precursor revolutionary concept was the "electrification" of our civilization. The broad meaning of Aiification is as it applies to an economic or institutional sector, a region, a national economy or the global economy.

AI take many forms and some in the field do not like the term AI and prefer a wide variety of other terms. Others outside the field prefer euphemisms like "automation" or "digitization" to refer to AI and AIification. Machine learning, deep learning and AI are not synonymous. Artificial General Intelligence refers to the AI with broad capabilities and does not exist as yet. Current AI is "narrow AI" which correctly describes the narrow, limited special purpose capabilities of todays systems.

Public policy makers need an accelerated course in artificial intelligence. AI is advancing at a rate far beyond the adaptive capacity of most political systems. It will impact all aspects of society. It will impact jobs. It will impact some regions worse than others. It will impact power relationships at the sub-state, nation state and international levels. (It has national security and international stability implications of the first order). AI, not climate change, will be the great defining public policy issue of the next fifty years.

Satya Nadella, chief executive of Microsoft at the 2016 WEF in Davos has noted "There is an economic surplus that is going to be created as a result of this fourth industrial revolution"

"The question is how evenly will it be spread between countries, between people in different economic strata and also different parts of the economy."

What he could of said was there will be winners and losers - and the losers are going too be none to happy about it. The maintenance of social cohesion may be a challenge.

First it is important to appreciate that the kind of artificial intelligence involved here is "qualitatively different" than what flies the aircraft on your next flight - for the bulk of its flight. It is different than how the operating system on your computer works and most of its applications. It is different because unlike these programs it is not "written" by humans - in the traditional sense - having once been set up it learns on its own and begins to interact with the world. Machine learning is about to rewrite the rules of the civilization game. It involves computer coding for the initial setup but therafter it learns much as a child learns - by example and interaction. Human cognition is made up of a mosaic of discrete but related cognitive elements - some are more important than others but they likely number in the hundreds and perhaps thousands. Collectively these elements allow us to see, hear, feel, learn, plan and act. So it is with artificial cognition. These kinds of systems are rudimentary now but powerful. They have limited capabilities - for now.

This is not science fiction. Google paid $500 million for a company called Deepmind which has a Wright Brothers like machine learning system and more importantly the know-how to extend its capacity.

Unlike human sharing of knowledge which occurs at great cost over years - the knowledge of these systems can be shared and replicated nearly instantaneously - like updates to your mobile operating system and APPS.

Policy development for AIification (the good and the bad implications) is complicated by the fact that AI is a global phenomena, can be developed by an individual, and complicated by the fact that global institution building is only just beginning to be effective and most polities can't really wrap their head around any kind of global management requirement for mankind.

Like any domain, there is what you know, and what you know that isn't so. And then there is always the issue of what you don't know, that you don't know. So where to start?

While this site as a whole is a tool for an expanding appreciation of AI, CascadiaPrime Cognition has grown substantially and would involve hundreds of hours of your time to read, listen to and view what is referenced. Even a quick survey of the sections and the overall structure may prove daunting to those needing or wanting a "one pager".

This introduction then will be in the manner of a "one pager" of where to concentrate your energies. If you are a government or political leader with command of resources then at an early date you will want to establish a center of excellence in your administration designed keep you abreast of developments and how your administration might employ recent AI developments to advantage while developing social innovations to deal with the economic and social changes it will give rise to. This could be simply one person, full time, to start with given that assigned responsibility. Large national states will assign thousands but create focal points to coordinate action. Central banks and departments of finance will be early centers of excellence focusing on this subject.


Practical Guides to Action

Talks, Discussions and Papers for beginners and not so beginners

  Microsoft: The animated guide to artificial intelligence (Explanimators: Episode 1)( )
  Darpa's John Launchbury on the Three Waves of AI (February 14, 2016)
  Darpa's John Launchbury on the Three Waves of AI (February 14, 2016)
  Microsoft Research's Dr. Harry Shum on the future of AI at the 2017 Future Forum Annual Conference (January 15, 2016)
  NYT Magazine: AI through the lens of Google History (December 14, 2016)
  US Senate Subcommittee on Space, Science, & Competitiveness hearing on The Dawn of Artificial Intelligence (November 30, 2016)
  So…What is Machine Learning? (March 2016)
  Martin Ford - What does the rise of AI imply for jobs and the economy? (January 2016)
  Pedro Domingos on “Five Machine Learning Tribes”
  Pedro Domingos: "The Master Algorithm" | Talks at Google (November 2015)
  Ruslan Salakhutdinov - Deep learning - Changing the playing field of artificial intelligence (CIFAR) (July 2015)
   Demis Hassabis - How Deep Learning Can Give Birth to General Artificial Intelligence (2015)
  Shane Legg - Defining AI - Google Deepmind (2009)
  Paths to Human-level AI | Murray Shanahan (November 2015)
  Miles Brundage - Modeling Progress in AI (December 2015)
  Google's Peter Norvig on the Technological Singularity (December 2015)

Recommended Books

  Andrew McAfee & Erik Brynjolfsson: The Second Machine Age
  Pedro Domingos: The Master Algorithm

Recommended Top Ten to Follow on Twitter

  Erik Brynjolfsson - @erikbryn ?Economics of information and information technology. Professor @MIT. Director @MIT_IDE.
  Andrew McAfee @amcafee Co-author of The Second Machine Age