All posts by lghtstrm

After many years as an award-winning, globally experienced, creative director / designer with mastery of integrated visual design, branding and expert-level command of 2D and 3D visualization, I have completed an advanced degree in Design Development. I am currently Assistant Professor of Design Foundations at The Ohio State University. My research focuses on the provocations of design fiction to better equip us to understand the ramifications of design and its synergistic influence on culture.

Autonomous Assumptions

I’m writing about a recent post from futurist Amy Webb. Amy is getting very political lately which is a real turn-off for me, but she still has her ear to the rail of the future, so I will try to be more tolerant. Amy carried a paragraph from an article entitled, “If you want to trust a robot, look at how it makes decisions” from The Conversation, an eclectic “academic rigor, journalistic flair” blog site. The author, Michael Fisher, a Professor of Computer Science, at the University of Liverpool, says,

“When we deal with another human, we can’t be sure what they will decide but we make assumptions based on what we think of them. We consider whether that person has lied to us in the past or has a record for making mistakes. But we can’t really be certain about any of our assumptions as the other person could still deceive us.

Our autonomous systems, on the other hand, are essentially controlled by software so if we can isolate the software that makes all the high-level decisions – those decisions that a human would have made – then we can analyse the detailed working of these programs. That’s not something you can or possibly ever could easily do with a human brain.”

Fisher thinks that might make autonomous systems more trustworthy than humans. He says that by software analysis we can be almost certain that the software that controls our systems will never make bad decisions.

There is a caveat.

“The environments in which such systems work are typically both complex and uncertain. So while accidents can still occur, we can at least be sure that the system always tries to avoid them… [and] we might well be able to prove that the robot never intentionally means to cause harm.”

That’s comforting. But OK, computers fly and land airplanes, they make big decisions about air traffic, they are driving cars with people in them, they control much of our power grid, and our missile defense, too. So why should we worry? It is a matter of definitions. We use terms when describing new technologies that clearly have different interpretations. How you define bad decisions? Fisher says,

“We are clearly moving on from technical questions towards philosophical and ethical questions about what behaviour we find acceptable and what ethical behaviour our robots should exhibit.”

If you have programmed an autonomous soldier to kill the enemy, is that ethical? Assuming that the Robocop can differentiate between good guys and bad guys, you have nevertheless opened the door to autonomous destruction. In the case of an autonomous soldier in the hands of a bad actor, you may be the enemy.

My point is this. It’s not necessarily the case that we understand how the software works and that it’s reliable, it may be more about who programmed the bot in the first place. In my graphic novel, The Lightstream Chronicles, there are no bad robots (I call them synths), but occasionally bad people get a hold of the good synths and make them do bad things. They call that twisting. It’s illegal, but of course, that doesn’t stop it. Criminals do it all the time.

You see, even in the future some things never change. In the words of Aldous Huxley,

“Technological progress has merely provided us with more efficient means for going backwards.”

 

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Heady stuff.

Last week we talked about how some researchers and scientists on the cutting edge are devising guidelines to attempt to ensure that potentially transformative technologies (like AI) remain safe and beneficial, rather than becoming a threat to humanity. And then, there were industries (like nanotech) that have already blown past any attempt at a meaningful review and now exist in thousands of consumer products, and nobody knows if their safe and the companies who produce them don’t even have to tell us they are part of the composition.

This week I’m going to talk about why I look askance at transformative technologies. Maybe it is because I am a writer at heart. Fiction, specifically science fiction, has captured my attention since childhood. It is my genre of choice. Now that nearly all of the science-based science fiction is no longer fiction, our tendency is to think that the only thing left to do is react or adapt. I can understand this since you can’t isolate a single technology as a thing, you can’t identify precisely from where it started, or how it morphed into what it is. Technologies converge, and they become systems, and systems are dauntingly complex. As humans, we create things that become systems. Even in non-digital times, the railroad ushered in a vastly complex system so much so that we had to invent other things just to deal with it, like a clock. What good was a train if it wasn’t on time? And what good was your time if it wasn’t the same as my time?

Fast forward. Does the clock have any behavioral effect in your life?

My oft-quoted scholars at ASU, Allenby, and Sarewitz see things like trains as level one technologies. They spawn systems in the level two realm that are often far more intricate than figuring out how to get this train contraption to run on rails across the United States.

So the nature of convergence and the resulting complexity of systems is one reason for my wariness of transformative tech.Especially now, that we are building things and we don’t understand how they work. We are inventing things that don’t need us to teach them, and that means that we can’t be sure what they are learning or how. If we can barely understand the complexity of the system that has grown up around the airline industry (which we at one time inherently grasped), how are we going to understand systems that spring up around these inventions that, at the core, we know what they do, but don’t know how?

The second reason is human nature. Your basic web dictionary defines the sociology of human nature as: “[…]the character of human conduct, generally regarded as produced by living in primary groups.” Appreciating things like love and compassion, music and art, consciousness, thought, languages and memory are characteristics of human nature. So are evil and vice, violence and hatred, the quest for power and greed. The latter have a tendency to undermine our inventions for good. Sometimes they are our downfall.

With history as our teacher, if we go blindly forward paying little attention to reason one, the complexity of systems, or reason two, the potential for bad actors, or both, that does not bode well.

I’ve been rambling a bit, so I have to wrap this up. I’ve taken a long way around to say that if you are among those who look at all this tech, and the unimaginable scope of the systems we have created and that the only thing left to do is react or adapt, that this is not the case.

While I can see the dark cloud behind every silver lining, it enables me to bring an umbrella on occasion.

Paying attention to the seemingly benign and insisting on a meaningful review of that which we don’t fully understand is the first step. It may seem as though it will be easier to adapt, but I don’t think so.

I guess that’s the reason behind this blog, behind my graphic novel, and my ongoing research and activism through design fiction. If you’re not paying attention, then I’ll remind you.

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The right thing to do. Remember that idea?

I’ve been detecting some blowback recently regarding all the attention surrounding emerging AI, it’s near-term effect on jobs, and it’s long-term impact on humanity. Having an anticipatory mindset toward artificial intelligence is just the logical thing to do. As I have said before, designing a car without a braking system would be foolish. Anticipating the eventuality that you might need to slow down or stop the car is just good design. Nevertheless, there are a lot of people, important people in positions of power that think this is a lot of hooey. They must think that human ingenuity will address any unforeseen circumstances, that science is always benevolent, that stuff like AI is “a long way off,” that the benefits outweigh the downsides, and that all people are basically good. Disappointed I am that this includes our Treasury Secretary Steve Mnuchin. WIRED carried the story and so did my go-to futurist Amy Webb. In her newsletter Amy states,

“When asked about the future of artificial intelligence, automation and the workforce at an Axios event, this was Mnuchin’s reply: ‘It’s not even on our radar screen,’ he said, adding that significant workforce disruption due to AI is ‘50 to 100’ years away. ‘I’m not worried at all’”

Sigh! I don’t care what side of the aisle you’re on, that’s just plain naive. Turning a blind eye to potentially transformative technologies is also dangerous. Others are skeptical of any regulation (perhaps rightly so) that stifles innovation and progress. But safeguards and guidelines are not that. They are well-considered recommendations that are designed to protect while facilitating research and exploration. On the other side of the coin, they are also not laws, which means that if you don’t want to or don’t care to, you don’t have to follow them.

Nevertheless, I was pleased to see a relatively comprehensive set of AI principles that emerged from the Asilomar Conference that I blogged about a couple of weeks ago. The 2017 Asilomar conference organized by The Future of Life Institute,

“…brought together an amazing group of AI researchers from academia and industry, and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI.”

The gathering generated the Asilomar AI Principles, a remarkable first step on the eve of an awesome technological power. None of these people, from the panel I highlighted in the last blog, are anxious for regulation, but at the same time, they are aware of the enormous potential for bad actors to undermine whatever beneficial aspects of the technology might surface. Despite my misgivings, an AGI is inevitable. Someone is going to build it, and someone else will find a way to misuse it.

There are plenty more technologies that pose questions. One is nanotechnology. Unlike AI, Hollywood doesn’t spend much time painting nanotechnological dystopias, perhaps that along with the fact that they’re invisible to the naked eye, lets the little critters slip under the radar. While researching a paper for another purpose, I decided to look into nanotechnology to see what kinds of safeguards and guidelines are in place to deal with that rapidly emerging technology. There are clearly best practices by reputable researchers, scientists, and R&D departments but it was especially disturbing to find out that none of these are mandates. Especially since there are thousands of consumer products that use nanotechnology including food, cosmetics, clothing, electronics, and more. A nanometer is very small. Nanotech concerns itself with creations that exist in the 100nm range and below, roughly 7,500 times smaller than a human hair. In the Moore’s Law race, nanothings are the next frontier in cramming data onto a computer chip, or implanting them into our brains or living cells. However, due to their size, nanoparticles can also be inhaled, absorbed into the skin, flushed into the water supply and leeched into the soil. We don’t know what happens if we aggregate a large number of nanoparticles or differing combinations of nanoparticles in our body. We don’t even know how to test for it. And, get ready. Currently, there are no regulations. That means manufacturers do not need to disclose it, and there are no laws to protect the people who work with it. Herein, we have a classic example of bad decisions in the present that make for worse futures. Imagine the opposite: Anticipation of what could go wrong and sound industry intervention at a scale that pre-empts government intervention or the dystopian scenarios that the naysayers claim are impossible.

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The genius panel has some serious concerns.

Occasionally in preparing this blog, there are troughs in the technology newsfeed. But not now, and maybe never again. So it is with technology that accelerates exponentially. This idea, by the way, is a concept of which I will no longer try to convince my readers. I’m going to stop referencing why Kurzweil’s theorem, that technology advances exponentially is no longer a theorem and just move forward with the assumption that you know that it is. If you don’t agree,  then scout backwards—probably six months of previous blogs—and you’ll be on the same page. From here on, technology advances exponentially! With that being said, we are also no longer at the base of the exponential curve. We are beginning a steep climb.

Last week I highlighted Kurzweil’s upgraded prediction on the Singularity (12 years). I agree, though now I think he may be underselling things. It could easily arrive before that.

Today’s blog comes from a hot tip from one of my students. At the beginning of each semester, I always turn my students on to the idea of GoogleAlerts. It works like this: You tell Google to send you anything and everything on whatever topic interests you. Then, anytime there is news online that fits your topic, you get an email with a list of links from Google. The emails can be inundating so choose your search wisely. At any rate, my student who drank the GoogleAlert kool-aid sent me a link to a panel discussion that took place in January of 2017. The panel convened at something called Beneficial AI 2017 in Asilomar, California. And what a panel it was. Get this: Bart Selman (Cornell), David Chalmers (NYU), Elon Musk (Tesla, SpaceX), Jaan Tallinn (CSER/FLI), Nick Bostrom (FHI), Ray Kurzweil (Google), Stuart Russell (Berkeley), Sam Harris, Demis Hassabis (DeepMind). Sam is a philosopher, author, neuroscientist and noted secularist. I’ve cited nearly all of these characters before in blogs or research papers, so to see them all on one panel was, for me, amazing.

L to R: Elon Musk, Stuart Russell , Bart Selman, Ray Kurzweil, David Chalmers, Nick Bostrom, Demis Hassabis, Sam Harris, Jaan Tallinn.

 

Why were they there? The Future of Life Institute (FLI) organized the BAI 2017 event:

“In our sequel to the 2015 Puerto Rico AI conference, we brought together an amazing group of AI researchers from academia and industry, and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI.”

FLI works together with CSER. (The Centre for the Study of Existential Risk). I confess that I was not aware of either organization, but this is encouraging. For example, CSER’s mission is stated as

“[…]within the University of Cambridge dedicated to the study and mitigation of human extinction-level risks that may emerge from technological advances and human activity.”

FLI describes themselves thus:

“We are a charity and outreach organization working to ensure that tomorrow’s most powerful technologies are beneficial for humanity […] We are currently focusing on keeping artificial intelligence beneficial and we are also exploring ways of reducing risks from nuclear weapons and biotechnology.”

Both organizations are loaded with scientists and technologists including Steven Hawking, Bostrom, and Musk.

The panel of genius’ got off to a rocky start because there weren’t enough microphones to go around. Duh. But then things got interesting. The topic of safe AI or what these fellows refer to as AGI, Artificial General Intelligence, is a deep well fraught with promise and doom. The encouraging thing is that these organizations realize the potential for either, the discomforting thing is that they’re genuinely concerned.

As I have discussed before, this race to a superintelligence which Kurzweil moved up to 2029 a few weeks ago, is moving full speed ahead and it is climbing in a steep exponential incline. It is likely that we will be able to build it long before we have figured out how to keep it from destroying us. I’m on record as saying that even the notion of a superintelligence is an error in judgment. If what you want to do is cure disease, aging, and save the planet, why not stop short of full-tilt superintelligence. Surely you get a very, very, very intelligent AI to give you what you want and go no further. After hearing the panel discussion, however, I see this as naive. As Kurzweil stated in the discussion,

“…there really isn’t a foolproof technical solution to this… If you have an AI that is more intelligent than you and is out for your destruction, it’s out for the world’s destruction, and there is no other AI that is superior to it, that’s a bad situation. So that’s the specter […] Imagine that we’ve done our job perfectly, and we’ve created the most safe, beneficial AI possible, but we’ve let the political system become totalitarian and evil, either an evil world government or just a portion of the globe, that is that way, it’s not going to work out well. So part of the struggle is in the area of politics and policy to have the world reflect the values we want to achieve. Human AI is by definition at human levels and therefore is human. So the issue is, ‘How do we make humans ethical?’ is the same issue as, ‘How we make AIs that are at human level, ethical?’”

So there we have the problem of human nature, again. If we can’t fix ourselves if we can’t even agree on what’s broken, how can we build a benevolent god? Fortunately, brilliant minds are honestly concerned about this but that doesn’t mean they’re going to put on the brakes. It was stated in full agreement by the panel: a superintelligence is inevitable. If we don’t build it, someone else will.

It is also safe to assume that our super ethical AI won’t have the same ethics as someone else’s AI. Hence, Kurzweil’s specter. I could turn this into an essay, but I’ll stop here for now. What do you think?

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But nobody knows what better is.

South by Southwest, otherwise known as SXSW calls itself a film and music festival and interactive media conference. It’s held every spring in Austin, Texas. Other than maybe the Las Vegas Consumer Electronics Show or San Diego’s ComicCon, I can’t think of many conferences that generate as much buzz as SXSW. This year it is no different. I will have blog fodder for weeks. Though I can’t speak to the film or music side, I’m sure they were scintillating. Under the category of interactive, most of the buzz is about technology in general, as tech gurus and futurists are always in attendance along with celebs who align themselves to the future.

Once again at SXSW, Ray Kurzweil was on stage. In my blogs, Kurzweil is probably the one guy I quote the most throughout this blog. So here we go again. Two tech sites caught my eye they week, reporting on Kurzweil’s latest prediction that moves up the date of the Singularity from 2045 to 2029; that’s 12 years away. Since we are enmeshed in the world of exponentially accelerating technology, I have encouraged my students to start wrapping their heads around the idea of exponential growth. In our most recent project, it was a struggle just to embrace the idea of how in only seven years we could see transformational change. If Kurzweil is right about his latest prognostication, then 12 years could be a real stunner. In case you are visiting this blog for the first time, the Singularity to which Kurzweil refers is, acknowledged as the point at which computer intelligence exceeds that of human intelligence; it will know more, anticipate more, and analyze more than any human capability. Nick Bostrom calls it the last invention we will ever need to make. We’ve already seen this to some extent with IBM’s Watson beating the pants off a couple of Jeopardy masters and Google’s DeepMind handily beat a Go genius at a game that most thought to be too complex for a computer to handle. Some refer to this “computer” as a superintelligence, and warn that we better be designing the braking mechanism in tandem with the engine, or this smarter-than-us computer may outsmart us in unfortunate ways.

In an article in Scientific American, Northwestern University psychology professor Paul Weber says we are bombarded each day with about 2.5 exabytes of data and that the human brain can only store an estimated 2.5 petabytes (a million gigabytes). Of course, the bombardment will continue to increase. Another voice that emerges in this discussion is Rob High IBM’s vice president and chief technology officer. According to the futurism tech blog, High was part of a panel discussion at the American Institute of Aeronautics and Astronautics (AIAA) SciTech Conference 2017. High said,

“…we have a very desperate need for cognitive computing…The information being produced is far surpassing our ability to consume and make use of…”

On the surface, this seems like a compelling argument for faster, more pervasive computing. But since it is my mission to question otherwise compelling arguments, I want to ask whether we actually need to process 2.5 exabytes of information? It would appear that our existing technology has already turned on the firehose of data (Did we give it permission?) and now it’s up to us to find a way to drink from the firehose. To me, it sounds like we need a regulator, not a bigger gullet. I have observed that the traditional argument in favor of more, better, faster often comes wrapped in the package of help for humankind.

Rob High, again from the futurism article, says,

“‘If you’re a doctor and you’re trying to figure out the best way to treat your patient, you don’t have the time to go read the latest literature and apply that knowledge to that decision’ High explained. ‘In any scenario, we can’t possibly find and remember everything.’ This is all good news, according to High. We need AI systems that can assist us in what we do, particularly in processing all the information we are exposed to on a regular basis — data that’s bound to even grow exponentially in the next couple of years.’”

From another futurism article, Kurzweil uses a similar logic:

“We’re going to be able to meet the physical needs of all humans. We’re going to expand our minds and exemplify these artistic qualities that we value.”

The other rationale that almost always becomes coupled with expanding our minds is that we will be “better.” No one, however, defines what better is. You could be a better jerk. You could be a better rapist or terrorist or megalomaniac. What are we missing exactly, that we have to be smarter, or that Bach, or Mozart are suddenly inferior? Is our quality of life that impoverished? And for those who are impoverished, how does this help them? And what about making us smarter? Smarter at what?

But not all is lost. On a more positive note, futurism in a third article (they were busy this week), reports,

“The K&L Gates Endowment for Ethics and Computational Technologies seeks to introduce the thoughtful discussion on the use of AI in society. It is being established through funding worth $10 million from K&L Gates, one of the United States’ largest law firms, and the money will be used to hire new faculty chairs as well as support three new doctoral students.”

Though I’m not sure whether we can consider this a regulator, rather something to lessen the pain of swallowing.

Finally (for this week), back to Rob High,

“Smartphones are just the tip of the iceberg,” High said. “Human intelligence has its limitations and artificial intelligence is going to evolve in a lot of ways that won’t be similar to human intelligence. But, I think they will work best in the presence of humans.”

So, I’m more concerned with when artificial intelligence is not working at its best.

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A guerrilla future realized.

This week my brilliant students in Collaborative Studio 4650 provided a real word guerrilla future for the Humane Technologies: Livable Futures Pop-Up Collaboration at The Ohio State University. The design fiction was replete with diegetic prototypes and a video enactment. Out goal was to present a believable future in 2024 when ubiquitous AR glasses are the part of our mundane everyday. We made the presentation in Sullivant Hall’s Barnett Theater, and each member of the team had a set of mock AR glasses. The audience consisted of about 50 students ranging from the humanities to business. It was an amazing experience. It has untold riches for my design fiction research, but there were also a lot of revelations about how we experience, and enfold technology. After the presentation, we pulled out the white paper and markers and divided up into groups for a more detailed deconstruction of what transpired. While I have not plowed through all the scrolls that resulted from the post-presentation discussion groups, it seems universal that we can recognize how technology is apt to modify our behavior. It is also interesting to see that most of us have no clue how to resist these changes. Julian Oliver wrote in his (2011) The Critical Engineering Manifesto,

“5. The Critical Engineer recognises that each work of engineering engineers its user, proportional to that user’s dependency upon it.”

The idea of being engineered by our technology was evident throughout the AugHumana presentation video, and in discussions, we quickly identified the ways in which our current technological devices engineer us. At the same time, we feel more or less powerless to change or effect that phenomenon. Indeed, we have come to accept these small, incremental, seemingly mundane, changes to our behavior as innocent or adaptive in a positive way. En masse, they are neither. Kurzweil stated that,

‘We are not going to reach the Singularity in some single great leap forward, but rather through a great many small steps, each seemingly benign and modest in scope.’

History has shown that these steps are incrementally embraced by society and often give way to systems with a life of their own. An idea raised in one discussion group was labeled as effective dissent, but it seems almost obvious that unless we anticipate these imminent behavioral changes, by the time we notice them it is already too late, either because the technology is already ubiquitous or our habits and procedures solidly support that behavior.

There are ties here to material culture and the philosophy of technology that merits more research, but the propensity for technology to affect behavior in an inhumane way is powerful. These are early reflections, no doubt to be continued.

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Disruption. Part 2.

 

Last week I discussed the idea of technological disruption. Essentially, they are innovations that make fundamental changes in the way we work or live. In turn, these changes affect culture and behavior. Issues of design and culture are the stuff that interests me and my research: how easily and quickly our practices change as a result of the way we enfold technology. The advent of the railroad, mass produced automobiles, radio, then television, the Internet, and the smartphone all qualify as disruptions.

Today, technology advances more quickly. Technological development was never a linear idea, but because most of the tech advances of the last century were at the bottom of the exponential curve, we didn’t notice them. New technologies that are under development right now are going to being realized more quickly (especially the ones with big funding), and because of the idea of convergence, (the intermixing of unrelated technologies) their consequences will be less predictable.

One of my favorite futurists is Amy Webb whom I have written about before. In her most recent newsletter, Amy reminds us that the Internet was clunky and vague long before it was disruptive. She states,

“However, our modern Internet was being built without the benefit of some vital voices: journalists, ethicists, economists, philosophers, social scientists. These outside voices would have undoubtedly warned of the probable rise of botnets, Internet trolls and Twitter diplomacy––would the architects of our modern internet have done anything differently if they’d confronted those scenarios?”

Amy inadvertently left out the design profession, though I’m sure she will reconsider after we chat. Indeed, it is the design profession that is a key contributor to transformative tech and design thinkers, along with the ethicists and economists can help to visualize and reframe future visions.

Amy thinks that voice will be the next transformation will be our voice,

“From here forward, you can be expected to talk to machines for the rest of your life.”

Amy is referring to technologies like Alexa, Siri, Google, Cortana, and something coming soon called Bixby. The voices of these technologies are, of course, only the window dressing for artificial intelligence. But she astutely points out that,

“…we also know from our existing research that humans have a few bad habits. We continue to encode bias into our algorithms. And we like to talk smack to our machines. These machines are being trained not just to listen to us, but to learn from what we’re telling them.”

Such a merger might just be the mix of any technology (name one) with human nature or the human condition: AI meets Mike who lives across the hall. AI becoming acquainted with Mike may have been inevitable, but the fact that Mike happens to be a jerk was less predictable and so the outcome less so. The most significant disruptions of the future are going to come from the convergence of seemingly unrelated technologies. Sometimes innovation depends on convergence, like building an artificial human that will have to master a lot of different functions. Other times, convergence is accidental or at least unplanned. The engineers over at Boston Dynamics who are building those intimidating walking robots are focused a narrower set of criteria than someone creating an artificial human. Perhaps power and agility are their primary concern. Then, in another lab, there are technologists working on voice stress analysis, and in another setting, researchers are looking to create an AI that can choose your wardrobe. Somewhere else we are working on facial recognition or Augmented Reality or Virtual Reality or bio-engineering, medical procedures, autonomous vehicles or autonomous weapons. So it’s a lot like Harry meets Sally, you’re not sure what you’re going to get or how it’s going to work.

Digital visionary Kevin Kelly thinks that AI will be at the core of the next industrial revolution. Place the prefix “smart” in front of anything, and you have a new application for AI: a smart car, a smart house, a smart pump. These seem like universally useful additions, so far. But now let’s add the same prefix to the jobs you and I do, like a doctor, lawyer, judge, designer, teacher, or policeman. (Here’s a possible use for that ominous walking robot.) And what happens when AI writes better code than coders and decides to rewrite itself?

Hopefully, you’re getting the picture. All of this underscores Amy Webb’s earlier concerns. The ‘journalists, ethicists, economists, philosophers, social scientists’ and designers are rarely in the labs where the future is taking place. Should we be doing something fundamentally differently in our plans for innovative futures?

Side note: Convergence can happen in a lot of ways. The parent corporation of Boston Dynamics is X. I’ll use Wikipedia’s definition of X: “X, an American semi-secret research-and-development facility founded by Google in January 2010 as Google X, operates as a subsidiary of Alphabet Inc.”

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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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Of autonomous machines.

 

Last week we talked about how converging technologies can sometimes yield unpredictable results. One of the most influential players in the development of new technology is DARPA and the defense industry. There is a lot of technological convergence going on in the world of defense. Let’s combine robotics, artificial intelligence, machine learning, bio-engineering, ubiquitous surveillance, social media, and predictive algorithms for starters. All of these technologies are advancing at an exponential pace. It’s difficult to take a snapshot of any one of them at a moment in time and predict where they might be tomorrow. When you start blending them the possibilities become downright chaotic. With each step, it is prudent to ask if there is any meaningful review. What are the ramifications for error as well as success? What are the possibilities for misuse? Who is minding the store? We can hope that there are answers to these questions that go beyond platitudes like, “Don’t stand in the way of progress.”, “Time is of the essence.”, or “We’ll cross that bridge when we come to it.”

No comment.

I bring this up after having seen some unclassified documents on Human Systems, and Autonomous Defense Systems (AKA autonomous weapons). (See a previous blog on this topic.) Links to these documents came from a crowd-funded “investigative journalist” Nafeez Ahmed, publishing on a website called INSURGE intelligence.

One of the documents entitled Human Systems Roadmap is a slide presentation given to the National Defense Industry Association (NDIA) conference last year. The list of agencies involved in that conference and the rest of the documents cited reads like an alphabet soup of military and defense organizations which most of us have never heard of. There are multiple components to the pitch, but one that stands out is “Autonomous Weapons Systems that can take action when needed.” Autonomous weapons are those that are capable of making the kill decision without human intervention. There is also, apparently some focused inquiry into “Social Network Research on New Threats… Text Analytics for Context and Event Prediction…” and “full spectrum social media analysis.” We could get all up in arms about this last feature, but recent incidents in places such as, Benghazi, Egypt, and Turkey had a social networking component that enabled extreme behavior to be quickly mobilized. In most cases, the result was a tragic loss of life. In addition to sharing photos of puppies, social media, it seems, is also good at organizing lynch mobs. We shouldn’t be surprised that governments would want to know how to predict such events in advance. The bigger question is how we should intercede and whether that decision should be made by a human being or a machine.

There are lots of other aspects and lots more documents cited in Ahmed’s lengthy albeit activistic report, but the idea here is that rapidly advancing technology is enabling considerations which were previously held to be science fiction or just impossible. Will we reach the point where these systems are fully operational before we reach the point where we know they are totally safe? It’s a problem when technology grows faster that policy, ethics or meaningful review. And it seems to me that it is always a problem when the race to make something work is more important than the understanding the ramifications if it does.

To be clear, I’m not one of those people who thinks that anything and everything that the military can conceive of is automatically wrong. We will never know how many catastrophes that our national defense services have averted by their vigilance and technological prowess. It should go without saying that the bad guys will get more sophisticated in their methods and tactics, and if we are unable to stay ahead of the game, then we will need to get used to the idea of catastrophe. When push comes to shove, I want the government to be there to protect me. That being said, I’m not convinced that the defense infrastructure (or any part of the tech sector for that matter) is as diligent to anticipate the repercussions of their creations as they are to get them functioning. Only individuals can insist on meaningful review.

Thoughts?

 

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Paying attention.

I want to make a Tshirt. On the front, it will say, “7 years is a long time.” On the back, it will say, “Pay attention!”

What am I talking about? I’ll start with some background. This semester, I am teaching a collaborative studio with designers from visual communications, interior design, and industrial design. Our topic is Humane Technologies, and we are examining the effects of an Augmented Reality (AR) system that could be ubiquitous in 7 years. The process began with an immersive scan of the available information and emerging advances in AR, VR, IoT, human augmentation (HA) and, of course, AI. In my opinion, these are a just a few of the most transformative technologies currently attracting the heaviest investment across the globe. And where the money goes there goes the most rapid advancement.

A conversation starter.

One of the biggest challenges for the collaborative studio class (myself included) is to think seven years out. Although we read Kurzweil’s Law of Accelerating Returns, our natural tendency is to think linearly, not exponentially. One of my favorite Kurzweil illustrations is this:

“Exponentials are quite seductive because they start out sub-linear. We sequenced one ten-thousandth of the human genome in 1990 and two ten-thousandths in 1991. Halfway through the genome project, 7 ½ years into it, we had sequenced 1 percent. People said, “This is a failure. Seven years, 1 percent. It’s going to take 700 years, just like we said.” Seven years later it was done, because 1 percent is only seven doublings from 100 percent — and it had been doubling every year. We don’t think in these exponential terms. And that exponential growth has continued since the end of the genome project. These technologies are now thousands of times more powerful than they were 13 years ago, when the genome project was completed.”1

So when I hear a policymaker, say, “We’re a long way from that,” I cringe. We’re not a long way away from that. The iPhone was introduced on June 29, 2007, not quite ten years ago. The ripple-effects from that little technological marvel are hard to catalog. With the smartphone, we have transformed everything from social and behavioral issues to privacy and safety. As my students examine the next possible phase of our thirst for the latest and greatest, AR (and it’s potential for smartphone-like ubiquity), I want them to ask the questions that relate to supporting systems, along with the social and ethical repercussions of these transformations. At the end of it all, I hope that they will walk away with an appreciation for paying attention to what we make and why. For example, why would we make a machine that would take away our job? Why would we build a superintelligence? More often than not, I fear the answer is because we can.

Our focus on the technologies mentioned above is just a start. There are more than these, and we shouldn’t forget things like precise genetic engineering techniques such as CRISPR/Cas9 Gene Editing, neuromorphic technologies such as microprocessors configured like brains, the digital genome that could be the key to disease eradication, machine learning, and robotics.

Though they may sound innocuous by themselves, they each have gigantic implications for disruptions to society. The wild card in all of these is how they converge with each other and the results that no one anticipated. One such mutation would be when autonomous weapons systems (AI + robotics + machine learning) converge with an aggregation of social media activity to predict, isolate and eliminate a viral uprising.

From recent articles and research by the Department of Defense, this is no longer theoretical; we are actively pursuing it. I’ll talk more about that next week. Until then, pay attention.

 

1. http://www.bizjournals.com/sanjose/news/2016/09/06/exclusivegoogle-singularity-visionary-ray.htm
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