But The Beginning Of What?

As powerful as advanced AI might be someday, we need to understand it first and think carefully about how it should be applied.  The best thing we can do is make sure we have the best minds working on AI and support research that helps us develop it faster.  Again, it’s just math.  Not magic.
At a very basic level, I think AI is good and not something we should be afraid of.  We’re already seeing examples of how AI can unlock value and improve the world.  If we can choose hope over fear — and if we advance the fundamental science behind AI — then this is only the beginning.
—    Mark Zuckerberg
Quoted by:   Jason Tanz
In his article:  “A To-Do List For The Tech Industry“
Appearing in:  Wired Magazine;  dtd:  November 2016
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We Need To Continue Experimenting

This is a more fruitful approach than trying to erase dialog from the Internet altogether.  We can all agree that material that incites violence doesn’t belong online.  But when ISIS raises questions about the world, you can’t just wipe that from the Internet.  Ideas need to be raised and confronted and disputed.  Right now, it can feel dangerous to challenge extremism online.  ­ People get shouted down, harassed, or worse.  That gives power to the bad guys, because it shuts reasonable people out of the conversation, leaving just the violent voices.
We haven’t seen a terrorist organization as digitally savvy as ISIS before, but when you think about it, much of what it’s doing isn’t all that different from what any teenager can do;  you wouldn’t be surprised if your 14-year-old daughter made a video and put it online.  It’s only surprising because we have this idea of terrorists as old, bearded men hiding out in the mountains.  Terrorist groups are evolving like the rest of us.  We need to continue experimenting with solutions that meet these groups where they connect with the rest of the world.
—    Yasmin Green
Quoted by:   Jason Tanz
In his article:  “A To-Do List For The Tech Industry“
Appearing in:  Wired Magazine;  dtd:  November 2016
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Slowly Cutting Their Own Throats

This all may sound obvious, but far too little of the tech industry operates this way today.  We’ve gotten to a point where companies aren’t even trying to build a business that will produce profits;  they are just trying to stay funded long enough for another company to acquire them.  They are actively chasing the waste instead of the win.  That misplaced focus isn’t just annoying, it contributes to global inequality, because it emphasizes capturing value instead of creating it.  It reminds me of Wall Street in 2007.
And it echoes the story of the economy writ large.  Over the past 30 years, wages have largely flatlined as corporate profits have surged, which means that companies in other sectors too are capturing more wealth than they are creating.  This is a recipe for economic stagnation.  Consumer demand is 70 percent of GDP.  So when companies treat people solely as an expense to be automated away, or as mere supply of wealth to be extracted, they are slowly cutting their own throats.
—    Tim O’Reilly
Quoted by:  Jason Tanz
In his article:  “A To-Do List For The Tech Industry“
Appearing in:  Wired Magazine;  dtd:  November 2016
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Control In The Age Of Entanglement

The implications of an unparsable machine language aren’t just philosophical.  For the past two decades, learning to code has been one of the surest routes to reliable employment — a fact not lost on all those parents enrolling their kids in after-school code academies.  But a world run by neurally networked deep-learning machines requires a different workforce.  Analysts have already started worrying about the impact of AI on the job market, as machines render old skills irrelevant.  Programmers might soon get a taste of what that feels like themselves.
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This explosion of indeterminacy has been a long time coming.  It’s not news that even simple algorithms can create unpredictable emergent behavior — an insight that goes back to chaos theory and random number generators.  Over the past few years, as networks have grown more intertwined and their functions more complex, code has come to seem more like an alien force, the ghosts in the machine ever more elusive and ungovernable.  Planes grounded for no reason.  Seemingly unpreventable flash crashes in the stock market.  Rolling blackouts.
These forces have led technologist Danny Hillis to declare the end of the age of Enlightenment, our centuries-long faith in logic, determinism, and control over nature.  Hillis says we’re shifting to what he calls the age of Entanglement.  “As our technological and institutional creations have become more complex, our relationship to them has changed,” he wrote in the Journal of Design and Science.  “Instead of being masters of our creations, we have learned to bargain with them, cajoling and guiding them in the general direction of our goals.  We have built our own jungle, and it has a life of its own.”  The rise of machine learning is the latest — and perhaps the last — step in this journey.
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To nerds of a certain bent, this all suggests a coming era in which we forfeit authority over our machines.  “One can imagine such technology outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand,” wrote Stephen Hawking — sentiments echoed by Elon Musk and Bill Gates, among others.  “Whereas the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all.”
—    Jason Tanz
From his article:  “The End Of Code“
Appearing in the June 2016 issue of Wired Magazine
[Every 10 years or so we are cautioned about computers, the end of programming, Artificial Intelligence and “the end of code”.  And, as always, I am reminded of the quote:  “The survival value of human intelligence has never been satisfactorily demonstrated.”   —   Michael Crichton from his book:  “The Andromeda Strain“.   I guess we may see, sooner rather than later.   —   kmab]
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