Tag Archives: Deep learning

Disruption. Part 1

 

We often associate the term disruption with a snag in our phone, internet or other infrastructure service, but there is a larger sense of the expression. Technological disruption refers the to phenomenon that occurs when innovation, “…significantly alters the way that businesses operate. A disruptive technology may force companies to alter the way that they approach their business, risk losing market share or risk becoming irrelevant.”1

Some track the idea as far back as Karl Marx who influenced economist Joseph Schumpeter to coin the term “creative destruction” in 1942.2 Schumpeter described that as the “process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.” But it was, “Clayton M. Christensen, a Harvard Business School professor, that described it’s current framework. “…a disruptive technology is a new emerging technology that unexpectedly displaces an established one.”3

OK, so much for the history lesson. How does this affect us? Historical examples of technological disruption go back to the railroads, and the mass produced automobile, technologies that changed the world. Today we can point to the Internet as possibly this century’s most transformative technology to date. However, we can’t ignore the smartphone, barely ten years old which has brought together a host of converging technologies substantially eliminating the need for the calculator, the dictaphone, land lines, the GPS box that you used to put on your dashboard, still and video cameras, and possibly your privacy. With the proliferation of apps within the smartphone platform, there are hundreds if not thousands of other “services” that now do work that we had previously done by other means. But hold on to your hat. Technological disruption is just getting started. For the next round, we will see an increasingly pervasive Internet of Things (IoT), advanced robotics, exponential growth in Artificial Intelligence (AI) and machine learning, ubiquitous Augmented Reality (AR), Virtual Reality (VR), Blockchain systems, precise genetic engineering, and advanced renewable energy systems. Some of these such as Blockchain Systems will have potentially cataclysmic effects on business. Widespread adoption of blockchain systems that enable digital money would eliminate the need for banks, credit card companies, and currency of all forms. How’s that for disruptive? Other innovations will just continue to transform us and our behaviors. Over the next few weeks, I will discuss some of these potential disruptions and their unique characteristics.

Do you have any you would like to add?

1 http://www.investopedia.com/terms/d/disruptive-technology.asp#ixzz4ZKwSDIbm

2 http://www.investopedia.com/terms/c/creativedestruction.asp

3 http://www.intelligenthq.com/technology/12-disruptive-technologies/

See also: Disruptive technologies: Catching the wave, Journal of Product Innovation Management, Volume 13, Issue 1, 1996, Pages 75-76, ISSN 0737-6782, http://dx.doi.org/10.1016/0737-6782(96)81091-5.
(http://www.sciencedirect.com/science/article/pii/0737678296810915)

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A facebook of a different color.

The tech site Ars Technica recently ran an article on the proliferation of a little-known app called Facewatch. According to the articles writer Sebastian Anthony, “Facewatch is a system that lets retailers, publicans, and restaurateurs easily share private CCTV footage with the police and other Facewatch users. In theory, Facewatch lets you easily report shoplifters to the police, and to share the faces of generally unpleasant clients, drunks, etc. with other Facewatch users.” The idea is that retailers or officials can look out for these folks and either keep an eye on them or just ask them to leave. The system, in use in the UK, appears to have a high rate of success.

 

The story continues. Of course, all technologies eventually converge, so now you don’t have to “keep and eye out” for ner-do-wells your CCTV can do it for you. NeoFace from NEC works with the Facewatch list to do the scouting for you. According to NECs website: “NEC’s NeoFace Watch solution is specifically designed to integrate with existing surveillance systems by extracting faces in real time… and matching against a watch list of individuals.” In this case, it would be the Facewatch database. Ars’ Anthony, makes this connection: “In the film Minority Report, people are rounded up by the Precrime police agency before they actually commit the crime…with Facewatch, and you pretty much have the same thing: a system that automatically tars people with a criminal brush, irrespective of dozens of important variables.”

Anthony points out that,

“Facewatch lets you share ‘subjects of interest’ with other Facewatch users even if they haven’t been convicted. If you look at the shop owner in a funny way, or ask for the service charge to be removed from your bill, you might find yourself added to the ‘subject of interest’ list.”

The odds of an innocent being added to the watchlist are quite good. Malicious behavior aside, you could be logged as you wander past a government protest, forget your PIN number too many times at the ATM, or simply look too creepy in your Ray Bans and hoody.

The story underscores a couple of my past rants. First, we don’t make laws to protect against things that are impossible, so when the impossible happens, we shouldn’t be surprised that there isn’t a law to protect against it.1 It is another red flag that technology is moving, too fast and as it converges with other technologies it becomes radically unpredictable. Second, that technology moves faster than politics, moves faster than policy, and often faster than ethics.2

There are a host personal apps, many which are available to our iPhones or Androids that are on the precarious line between legal and illegal, curious and invasive. And there are more to come.

 

1 Quoting Selinger from Wood, David. “The Naked Future — A World That Anticipates Your Every Move.” YouTube. YouTube, 15 Dec. 2013. Web. 13 Mar. 2014.
2. Quoting Richards from Farivar, Cyrus. “DOJ Calls for Drone Privacy Policy 7 Years after FBI’s First Drone Launched.” Ars Technica. September 27, 2013. Accessed March 13, 2014. http://arstechnica.com/tech-policy/2013/09/doj-calls-for-drone-privacy-policy-7-years-after-fbis-first-drone-launched/.
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The foreseeable future.

From my perspective, the two most disruptive technologies of the next ten years will be a couple of acronyms: VR and AI. Virtual Reality will transform the way people learn, and their diversions. It will play an increasing role in entertainment and gaming to the extent that many will experience some confusion and conflict with actual reality. Make sure you see last week’s blog for more on this. Between VR and AI so much is happening that these could easily outnumber a host of other topics to discuss on this site next year. Today, I’ll begin the discussion with AI, but both technologies fall into my broader topic of the foreseeable future.

One of my favorite quotes of 2014 (seems like ancient history now) was from an article in Ars Technica by Cyrus Farivar 1. It was a drone story about FBI proliferation to the tune of $5 million that occurred gradually over the period of 10 years, almost unnoticed. Farivar cites a striking quote from Neil Richards, a law professor at Washington University in St. Louis: “We don’t write laws to protect against impossible things, so when the impossible becomes possible, we shouldn’t be surprised that the law doesn’t protect against it…” I love that quote because we are continually surprised that we did not anticipate one thing or the other. Much of this surprise I believe, comes from experts who tell us that this or that won’t happen in the foreseeable future. One of these experts, Miles Brundage, a Ph.D. student at Arizona State, was quoted recently in an article in WIRED. About AI that could surpass human intelligence, Brundage said,

“At the point where we are today, no AI system is at all capable of taking over the world—and won’t be for the foreseeable future.”

There are two things that strike me about these kinds of statements. First is the obvious fact that no one can see the future in the first place, and secondly that the clear implication is, that it will happen, just not yet. It also suggests that we shouldn’t be concerned; it’s too far away. This article was about Elon Musk is open-sourcing something called OpenAI. According to Nathaniel Wood reporting for WIRED, OpenAI is deep-learning code that Musk and his investors want to share with the world, for free. This news comes on the heels of Google’s open-sourcing of their AI code called TensorFlow, immediately followed by a Facebook announcement that they would be sharing their BigSur server hardware. As the article points out, this is not all magnanimous altruism. By opening the door to formerly proprietary software or hardware folks like Musk and companies like Google and Facebook stand to gain. They gain by recruiting talent, and by exponentially increasing development through free outsourcing. A thousand people working with your code are much better than the hundreds inside your building. Here are two very important factors that folks like Brundage don’t take into consideration. First, these people are in a race and, through outsourcing or open-sourcing their stuff they are enlisting people to help them in the race. Secondly, there is that term, exponential. I use it most often when I refer to Kurzweil’s Law of Accelerating Returns. It is exactly these kinds of developments that make his prediction so believable. So maybe the foreseeable future is not that far away after all.

All this being said the future is not foreseeable, and the exponential growth in areas like VR and AI will continue. The WIRED article continues with this commentary on AI, (which we all know):

“Deep learning relies on what are called neural networks, vast networks of software and hardware that approximate the web of neurons in the human brain. Feed enough photos of a cat into a neural net, and it can learn to recognize a cat. Feed it enough human dialogue, and it can learn to carry on a conversation. Feed it enough data on what cars encounter while driving down the road and how drivers react, and it can learn to drive.”

Despite their benevolence, this is why Musk and Facebook and Google are in the race. Musk is quick to add that while his motives have an air of transparency to them, it is also true that the more people who have access to deep-learning software, the less likely that one guy will have a monopoly on it.

Musk is a smart guy. He knows that AI could be a blessing or a curse. Open sourcing is his hedge. It could be a good thing… for the foreseeable future.

 

1. Farivar, Cyrus. “DOJ Calls for Drone Privacy Policy 7 Years after FBI’s First Drone Launched.” Ars Technica. September 27, 2013. Accessed March 13, 2014. http://arstechnica.com/tech-policy/2013/09/doj-calls-for-drone-privacy-policy-7-years-after-fbis-first-drone-launched/.
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