Disrupted Economics – AI makes The Big Short look like a child's maths experiment

Is the Future Terminator and a Financial AI program that goes too far?

iDisrupted Commentary

If you haven’t seen The Big Short, please go and see it, it’s truly excellent. In a nutshell it explains dramatically and humourously just how the financial crash of 2008 – that nearly threw us back into the Stone Age – was caused by contingent bets being made on contingent bets on contingent bets.
Maybe we have seen the start of what could happen if the hedge funds start to use AI to run the shorting bets – no human or collection of humans is smart enough to examine the massive data and form strategies (similar to Go in complexity). AI can, but who supervises it?
Disrupted Economics - AI makes the The Big Short look like a child's maths experimentFrom TechCrunch: “Science has not yet mastered prophecy. We predict too much for the next year and yet far too little for the next ten.”
These words, articulated by Neil Armstrong at a speech to a joint session of Congress in 1969, fit squarely into most every decade since the turn of the century, and it seems to safe to posit that the rate of change in technology has accelerated to an exponential degree in the last two decades, especially in the areas of artificial intelligence and machine learning.
Artificial intelligence is making an extreme entrance into almost every facet of society in predicted and unforeseen ways, causing both excitement and trepidation. This reaction alone is predictable, but can we really predict the associated risks involved?
It seems we’re all trying to get a grip on potential reality, but information overload (yet another side affect that we’re struggling to deal with in our digital world) can ironically make constructing an informed opinion more challenging than ever. In the search for some semblance of truth, it can help to turn to those in the trenches.
In my continued interview with over 30 artificial intelligence researchers, I asked what they considered to be the most likely risk of artificial intelligence in the next 20 years.
Some results from the survey, shown in the graphic below, included 33 responses from different AI/cognitive science researchers. (For the complete collection of interviews, and more information on all of our 40+ respondents, visit the original interactive infographic here on TechEmergence).
Two “greatest” risks bubbled to the top of the response pool (and the majority are not in the autonomous robots’ camp, though a few do fall into this one). According to this particular set of minds, the most pressing short- and long-term risks is the financial and economic harm that may be wrought, as well as mismanagement of AI by human beings.
Dr. Joscha Bach of the MIT Media Lab and Harvard Program for Evolutionary Dynamics summed up the larger picture this way:
“The risks brought about by near-term AI may turn out to be the same risks that are already inherent in our society. Automation through AI will increase productivity, but won’t improve our living conditions if we don’t move away from a labor/wage based economy. It may also speed up pollution and resource exhaustion, if we don’t manage to install meaningful regulations. Even in the long run, making AI safe for humanity may turn out to be the same as making our society safe for humanity.”
Essentially, the introduction of AI may act as a catalyst that exposes and speeds up the imperfections already present in our society. Without a conscious and collaborative plan to move forward, we expose society to a range of risks, from bigger gaps in wealth distribution to negative environmental effects.
Leaps in AI are already being made in the area of workplace automation and machine learning capabilities are quickly extending to our energy and other enterprise applications, including mobile and automotive. The next industrial revolution may be the last one that humans usher in by their own direct doing, with AI as a future collaborator and – dare we say – a potential leader.
Some researchers believe it’s a matter of when and not if. In Dr. Nils Nilsson’s words, a professor emeritus at Stanford University, “Machines will be singing the song, ‘Anything you can do, I can do better; I can do anything better than you’.”
In respect to the drastic changes that lie ahead for the employment market due to increasingly autonomous systems, Dr. Helgi Helgason says, “it’s more of a certainty than a risk and we should already be factoring this into education policies.”
Talks at the World Economic Forum Annual Meeting in Switzerland this past January, where the topic of the economic disruption brought about by AI was clearly a main course, indicate that global leaders are starting to plan how to integrate these technologies and adapt our world economies accordingly – but this is a tall order with many cooks in the kitchen.
Another commonly expressed risk over the next two decades is the general mismanagement of AI. It’s no secret that those in the business of AI have concerns, as evidenced by the $1 billion investment made by some of Silicon Valley’s top tech gurus to support OpenAI, a non-profit research group with a focus on exploring the positive human impact of AI technologies.
Machines will be singing the song, ‘Anything you can do, I can do better; I can do anything better than you’.
— Dr. Nils Nilsson, professor emeritus, Stanford University
“It’s hard to fathom how much human-level AI could benefit society, and it’s equally hard to imagine how much it could damage society if built or used incorrectly,” is the parallel message posted on OpenAI’s launch page from December 2015. How we approach the development and management of AI has far-reaching consequences, and shapes future society’s moral and ethical paradigm.
Philippe Pasquier, an associate professor at Simon Fraser University, said “As we deploy more and give more responsibilities to artificial agents, risks of malfunction that have negative consequences are increasing,” though he likewise states that he does not believe AI poses a high risk to society on its own”…more

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