Tag Archives: artificial intelligence

Power sharing?

Just to keep you up to speed, everything is on schedule or ahead of schedule.

In the race toward a superintelligence or ubiquitous AI. If you read this blog or you are paying attention at any level, then you know the fundamentals of AI. But for those of you who don’t here are the basics. Artificial Intelligence comes from processing and analyzing data. Big data. Then programmers feed a gazillion linked-up computers (CPUs) algorithms that can sort this data and make predictions. This process is what is at work when the Google search engine makes suggestions concerning what you are about to key into the search field. These are called predictive algorithms. If you want to look at pictures of cats, then someone has to task the CPUs with learning what a cat looks like as opposed to a hamster, then scour the Internet for pictures of cats and deliver them to your search. The process of teaching the machine what a cat looks like is called machine learning. There is also an algorithm that watches your online behavior. That’s why, after checking out sunglasses online, you start to see a plethora of ads for sunglasses on just about every page you visit. Similar algorithms can predict where you will drive to today, and when you are likely to return home. There is AI that knows your exercise habits and a ton of other physiological data about you, especially when you’re sharing your Fitbit or other wearable data with the Cloud. Insurance companies extremely interested in this data, so that it can give discounts to “healthy” people and penalize the not so healthy. Someday they might also monitor other “behaviors” that they deem to be not in your best interests (or theirs). Someday, especially if we have a “single-payer” health care system (aka government healthcare), this data may be required before you are insured. Before we go too far into the dark side (which is vast and deep), AI can also search all the cells in your body and identify which ones are dangerous, and target them for elimination. AI can analyze a whole host of things that humans could overlook. It can put together predictions that could save your life.

Googles chips stack up and ready to go. Photo from WIRED.

Now, with all that AI background behind us, this past week something called Google I/O went down. WIRED calls it Google’s annual State-of-the-Union address. There, Sundar Pichai unveiled something called TPU 2.0 or Cloud TPU. This is something of a breakthrough, because, in the past, the AI process that I just described, even though lighting fast and almost transparent, required all those CPUs, a ton of space (server farms), and gobs of electricity. Now, Google (and others) are packing this processing into chips. These are proprietary to Google. According to WIRED,

“This new processor is a unique creation designed to both train and execute deep neural networks—machine learning systems behind the rapid evolution of everything from image and speech recognition to automated translation to robotics…

…says Chris Nicholson, the CEO, and founder of a deep learning startup called Skymind. “Google is trying to do something better than Amazon—and I hope it really is better. That will mean the whole market will start moving faster.”

Funny, I was just thinking that the market is not moving fast enough. I can hardly wait until we have a Skymind.

“Along those lines, Google has already said that it will offer free access to researchers willing to share their research with the world at large. That’s good for the world’s AI researchers. And it’s good for Google.”

Is it good for us?

Note:
This sets up another discussion (in 3 weeks) about a rather absurd opinion piece in WIRED about why we should have an AI as President. These things start out as absurd, but sometimes don’t stay that way.

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Humanity is not always pretty.

The Merriam-Webster online dictionary among several options gives this definition for human: “[…]representative of or susceptible to the sympathies and frailties of human nature human kindness a human weakness.”

Then there is humanity which can either confer either the collective of humans, or “[…]the fact or condition of being human; human nature,” or benevolence as in compassion and understanding. For the latter, it seems that we are the eternal optimists when it comes to describing ourselves. Hence, we often refer to the humanity of man as one of our most redeeming traits. At the same time, if we query human nature we can get, “[…]ordinary human behavior, esp considered as less than perfect.” This is a diplomatic way of acknowledging that flaws are a characteristic of our nature. When we talk about our humanity, we presumptively leave out our propensity for greed, pride, and the other deadly sins. We like to think of ourselves as basically good.

If we are honest with ourselves, however, we know this is not always the case and if we push the issue we would have to acknowledge that this not even the case most of the time. Humanity is primarily driven by the kinds of things we don’t like to see in others but rarely see in ourselves. But this is supposed to be a blog about design and tech, isn’t it? So I should get to the point.

A recent article on the blog site QUARTZ, Sarah Kessler’s article, “Algorithms are failing Facebook. Can humanity save it?” poses an interesting question and one that I’ve raised in the past. We like to think that technology will resolve all of our basic human failings—somehow. Recognizing this, back in 1968 Stewart Brand introduced the first Whole Earth Catalog with,

“We are as gods and might as well get good at it.”

After almost 50 years it seems justified to ask whether we’ve made any improvements whatsoever. The question is pertinent in light of Kessler’s article on the advent of Facebook Live. In this particular FB feature, you stream whatever video you want, and it goes out to the whole world instantly. Of course, we need this, right? And we need this now, right? Of course we do.

Like most of these wiz bang technologies they are designed to attract millennials with, “Wow! Cool.” But it is not a simple task. How would a company like Facebook police the potentially billions of feeds coming into the system? The answer is (as is becoming more the case) AI. Artificial Intelligence. Algorithms will recognize and determine what is and is not acceptable to go streaming out to the world. And apparently, Zuck and company were pretty confident that they could pull this off.

Let’s get this thing online. [Photo: http://wersm.com]

Maybe not. Kessler notes that,

“According to a Wall Street Journal tally, more than 50 acts of violence, including murders, suicides, and sexual assault, have been broadcast over Facebook Live since the feature launched 13 months ago.”

Both articles tell how Facebook’s Mark Zuckerberg put a team on “lockdown” to rush the feature to market. What was the hurry, one might ask? And Kessler does ask.

“Let’s make sure there’s a humanitarian angle. Millennials like that.” [Photo: http://variety.com]

After these 13 months of spurious events, the tipping point came with a particularly heinous act that ended up circulating on FB Live for nearly 24 hours. It involved a 20-year-old Thai man named Wuttisan Wongtalay, who filmed himself flinging his 11-month-old daughter off the side of a building with a noose around her neck. Then, off-camera, he killed himself.

“In a status update on his personal Facebook profile, CEO Mark Zuckerberg, himself the father of a young girl, pledged that the company would, among other things, add 3,000 people to the team that reviews Facebook content for violations of the company’s policies.”

Note that the answer is not to remove the feature until things could be sorted out or to admit that the algorithms are not ready for prime time. The somewhat surprising answer is more humans.

Kessler, quoting the Wall Street Journal article states,

“Facebook, in a civic mindset, could have put a plan in place for monitoring Facebook Live for violence, or waited to launch Facebook Live until the company was confident it could quickly respond to abuse. It could have hired the additional 3,000 human content reviewers in advance.

But Facebook ‘didn’t grasp the gravity of the medium,’ an anonymous source familiar with Facebook’s Live’s development told the Wall Street Journal.”

Algorithms are code that helps machines learn. They look at a lot of data, say pictures of guns, and then they learn to identify what a gun is. They are not particularly good at context. They don’t know, for example, whether your video is, “Hey, look at my new gun?” or “Die, scumbag.”

So in addition to algorithms, Zuck has decided that he will put 3,000 humans on the case. Nevertheless, writes Kessler,

“[…]they can’t solve Facebook’s problems on their own. Facebook’s active users comprise about a quarter of the world’s population and outnumber the combined populations of the US and China. Adding another 3,000 workers to the mix to monitor content simply isn’t going to make a meaningful difference. As Zuckerberg put it during a phone call with investors, “No matter how many people we have on the team, we’ll never be able to look at everything.”[Emphasis mine.]

So, I go back to my original question: We need this, right?

There are two things going on here. First is the matter of Facebook not grasping the gravity of the medium (which I see as inexcusable), and the second is how the whole thing came around full circle. Algorithms are supposed to replace humans. Instead we added 3,000 more jobs. Unfortunately, that wasn’t the plan. But it could have been.

Algorithms are undoubtedly here to stay, but not necessarily for every application and humans are still better at interpreting human intent than machines are. All of this underscores my position from previous blogs, that most companies when the issue is whether they get to or stay on top, will not police themselves. They’ll wait until it breaks and then fix it, or try to. The problem is that as algorithms get increasingly more complicated fixing them gets just as tricky.

People are working on this so that designers can see what went wrong, but the technology is not there yet.

And it is not just so that we can determine the difference between porn and breastfeeding. Algorithms are starting to make a lot of high stakes decisions, like autonomous vehicles, autonomous drones, or autonomous (fill in the blank). Until the people who are literally racing each other to be the first step back and ask the tougher questions, these types of unanticipated consequences will be commonplace, especially when the prudent actions like stop and assess are rarely considered. No one wants to stop and assess.

Kessler says it well,

“The combination may be fleeting—the technology will catch up eventually—but it’s also quite fitting given that so many of the problems Facebook is now confronting, from revenge porn to fake news to Facebook Live murders, are themselves the result of humanity mixing with algorithms.” [Emphasis mine.]

We can’t get past that humanity thing.

 

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Augmented evidence. It’s a logical trajectory.

A few weeks ago I gushed about how my students killed it at a recent guerrilla future enactment on a ubiquitous Augmented Reality (AR) future. Shortly after that, Mark Zuckerberg announced the Facebook AR platform. The AR uses the camera on your smartphone, and according to a recent WIRED article, transforms your smartphone into an AR engine.

Unfortunately, as we all know, (and so does Zuck), the smartphone isn’t currently much of an engine. AR requires a lot of processing, and so does the AI that allows it to recognize the real world so it can layer additional information on top of it. That’s why Facebook (and others), are building their own neural network chips so that the platform doesn’t have to run to the Cloud to access the processing required for Artificial Intelligence (AI). That will inevitably happen which will make the smartphone experience more seamless, but that’s just part the challenge for Facebook.

If you add to that the idea that we become even more dependent on looking at our phones while we are walking or worse, driving, (think Pokemon GO), then this latest announcement is, at best, foreshadowing.

As the WIRED article continues, tech writer Brian Barrett talked to Blair MacIntyre, from Georgia Tech who says,

“The phone has generally sucked for AR because holding it up and looking through it is tiring, awkward, inconvenient, and socially unacceptable,” says MacIntyre. Adding more of it doesn’t solve those issues. It exacerbates them. (The exception might be the social acceptability part; as MacIntyre notes, selfies were awkward until they weren’t.)”

That last part is an especially interesting point. I’ll have to come back to that in another post.

My students did considerable research on exactly this kind of early infancy that technologies undergo on their road to ubiquity. In another WIRED article, even Zuckerberg admitted,

“We all know where we want this to get eventually,” said Zuckerberg in his keynote. “We want glasses, or eventually contact lenses, that look and feel normal, but that let us overlay all kinds of information and digital objects on top of the real world.”

So there you have it. Glasses are the end game, but as my students agreed, contact lenses not so much. Think about it. If you didn’t have to stick a contact lens in your eyeball, you wouldn’t and the idea that they could become ubiquitous (even if you solved the problem of computing inside a wafer thin lens and the myriad of problems with heat, and in-eye-time), they are much farther away, if ever.

Student design team from Ohio State’s Collaborative Studio.

This is why I find my student’s solution so much more elegant and a far more logical trajectory. According to Barrett,

“The optimistic timeline for that sort of tech, though, stretches out to five or 10 years. In the meantime, then, an imperfect solution takes the stage.”

My students locked it down to seven years.

Finally, Zuckerberg made this statement:

“Augmented reality is going to help us mix the digital and physical in all new ways,” said Zuckerberg at F8. “And that’s going to make our physical reality better.”

Except that Zuck’s version of better and mine or yours may not be the same. Exactly what is wrong with reality anyway?

If you want to see the full-blown presentation of what my students produced, you can view it at aughumana.net.

Note: Currently the AugHumana experience is superior on Google Chrome.  If you are a Safari or Firefox purest, you may have to wait for the page to load (up to 2 minutes). We’re working on this. So, just use Chrome this time. We hope to have it fixed soon.

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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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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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