Tag Archives: dystopia

What did one AI say to the other AI?

I’e asked this question before, but this is an entirely new answer.

We may  never know.

Based on a plethora of recent media on artificial intelligence (AI), not only are there a lot of people working on it, but many of those on the leading edge are also concerned with what they don’t understand in the midst of their ominous new creation.

Amazon, DeepMind/Google, Facebook, IBM, and Microsoft teamed up to form the Partnership on AI.(1) Their charter talks about sharing information and being responsible. It includes all of the proper buzz words for a technosocial contract.

“…transparency, security and privacy, values and ethics, collaboration between people and AI systems, interoperability of systems, and of the trustworthiness, reliability, containment, safety, and robustness of the technology.”(2)

They are not alone in this concern, as the EU(3) is also working on AI guidelines and a set of rules on robotics.

Some of what makes them all a bit nervous is the way AI learns, the complexity of neural networks and inability to go back and see how the AI arrived at its conclusion. In other words, how do we know that its recommendation is the right one? Adding to that list is the discovery that AIs working together can create their own languages; languages we don’t speak or understand. In one case, at Facebook, researchers saw this happening and stopped it.

For me, it’s a little disconcerting that Facebook, a social media app is one of those corporations leading the charge and leading the research into AI. That’s a broad topic for another blog, but their underlying objective is to market to you. That’s how they make their money.

To be fair, that is at least part of the motivation for Amazon, DeepMind/Google, IBM, and Microsoft, as well. The better they know you, the more stuff they can sell you. Of course, there are also enormous benefits to medical research as well. Such advantages are almost always what these companies talk about first. AI will save your life, cure cancer and prevent crime.

So, it is somewhat encouraging to see that these companies on the forefront of AI breakthroughs are also acutely aware of how AI could go terribly wrong. Hence we see wording from the Partnership on AI, like

“…Seek out, support, celebrate, and highlight aspirational efforts in AI for socially benevolent applications.”

The key word here is benevolent. But the clear objective is to keep the dialog positive, and

“Create and support opportunities for AI researchers and key stakeholders, including people in technology, law, policy, government, civil liberties, and the greater public, to communicate directly and openly with each other about relevant issues to AI and its influences on people and society.”(2)

I’m reading between the lines, but it seems like the issue of how AI will influence people and society is more of an obligatory statement intended to demonstrate compassionate concern. It’s coming from the people who see huge commercial benefit from the public being at ease with the coming onslaught of AI intrusion.

In their long list of goals, the “influences” on society don’t seem to be a priority. For example, should they discover that particular AI has a detrimental effect on people, that their civil liberties are less secure, would they stop? Probably not.

At the rate that these companies are racing toward AI superiority, the unintended consequences for our society are not a high priority. While these groups are making sure that AI does not decide to kill us, I wonder if they are also looking at how the AI will change us and are those changes a good thing?

(1) https://www.fastcodesign.com/90132632/ai-is-inventing-its-own-perfect-languages-should-we-let-it

(2) https://www.partnershiponai.org/#

(3) http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//NONSGML%2BCOMPARL%2BPE-582.443%2B01%2BDOC%2BPDF%2BV0//EN

Other pertinent links:



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On utopia and dystopia. Part 2.

From now on we paint only pretty pictures. Get it?

A couple of blarticles (blog-like articles) caught my eye this week. Interestingly, the two blarticles reference the same work. There was a big brew-haha a couple of years ago about how dystopian science fiction and design fiction with dystopian themes were somehow bad for us and that people were getting sick of it. Based on the most recent lists of bestselling books and films, that no longer seems to be the case. Nevertheless, some science fiction writers like Cory Doctorow (a fine author and Hugo winner) think that possibly more utopian futures would be better at influencing public policy. As he wrote in Boing Boing earlier this month,

“Science fiction writers have a long history of intervening/meddling in policy, but historically this has been in the form of right-wing science fiction writers…”

Frankly, I have no idea what this has to do with politics as there must certainly be more left handed authors and filmmakers in Hollywood than their right-sided counterparts. He continues:

“But a new, progressive wing of design fiction practicioners [sic] are increasingly involved in policy questions…”

Doctorow’s article cites a long piece for Slate, by the New America Foundation’s Kevin Bankston. Bankston says,

“…a stellar selection of 64 bestselling sci-fi writers and visionary filmmakers, has tasked itself with imagining realistic, possible, positive futures that we might actually want to live in—and figuring out we can get from here to there.”

That’s great, because, as I said, I am all about making alternative futures legible for people to consider and contemplate. In the process, however, I don’t think we should give dystopia short shrift. The problem with utopias is that they tend to be prescriptive, in other words, ”This is a better future because I say so.”

The futures I conjure up are neither utopian nor dystopian, but I do try to surface real concerns so that people can decide for themselves, kind of like a democracy. History has proven that regardless of our utopian ideals we more often than not mess things up. I don’t want it to be progressive, liberal, conservative or right wing, and I don’t think it should be the objective of science fiction or entertainment to help shape these policies especially when there is an obvious political purpose. It’s one thing to make alternative futures legible, another to shove them at us.

As long as it’s fiction and entertaining utopias are great but let’s not kid ourselves. Utopia and to some extent dystopia are individual perspectives. Frankly, I don’t want someone telling me that one future is better for me than another. In fact, that almost borders on dystopia in my thinking.

I’m not sure whether Bruce Sterling was answering Cory Doctorow’s piece, but Sterling’s stance on the issue is sharper and more insightful. Sterling is acutely aware that today is the focus. We look at futures, and we realize there are steps we need to take today to make tomorrow better. I recommend his post. Here are a couple of choice clips:

“*The “better future” thing is jam-tomorrow and jam-yesterday talk, so it tends to become the enemy of jam today. You’re better off reading history, and realizing that public aspirations that do seem great, and that even meet with tremendous innovative success, can change the tenor of society and easily become curses a generation later. Not because they were ever bad ideas or bad things to aspire to or do, but because that’s the nature of historical causality. Tomorrow composts today.”

“*If you like doing incredible things, because you’re of a science fictional temperament, then you should frankly admit your fondness for the way-out and the wondrous, and not disingenuously pretend that it’s somehow bound to improve the lot of the mundanes.”

Prettier pictures are not going to save us. Most of the world needs a wake-up call, not another dream.

In my humble opinion.


How science fiction writers’ “design fiction” is playing a greater role in policy debates

Various sci-fi projects allegedly creating a better future

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On utopia and dystopia. Part 1.

A couple of interesting articles cropped up in that past week or so coming out of the WIRED Business Conference. The first was an interview with Jennifer Doudna, a pioneer of Crispr/Cas9 the gene editing technique that makes editing DNA nearly as simple as splicing a movie together. That is if you’re a geneticist. According to the interview, most of this technology is at use in crop design, for things like longer lasting potatoes or wheat that doesn’t mildew. But Doudna knows that this is a potential Pandora’s Box.

“In 2015, Doudna was part of a broad coalition of leading biologists who agreed to a worldwide moratorium on gene editing to the “germ line,” which is to say, edits that get passed along to subsequent generations. But it’s legally non-binding, and scientists in China have already begun experiments that involve editing the genome of human embryos.”

Crispr May Cure All Genetic Disease—One Day

Super-babies are just one of the potential ways to misuse Crispr. I blogged a longer and more diabolical list a couple of years ago.

Meddling with the primal forces of nature.

In Doudna’s recent interview, though she focused on the more positive effects on farming, things like rice and tomatoes.

You may not immediately see the connection, but there was a related story from the same conference where WIRED interviewed Jonathan Nolan and Lisa Joy co-creators of the HBO series Westworld. If you haven’t seen Westworld, I recommend it if only for Anthony Hopkins’ performance. As far as I’m concerned Anthony Hopkins could read the phone book, and I would be spellbound.

At any rate, the article quotes:

“The first season of Westworld wasted no time in going from “hey cool, robots!” to “well, that was bleak.” Death, destruction, android torture—it’s all been there from the pilot onward.”

Which pretty much sums it up. According to Nolan,
“We’re inventing cautionary tales for ourselves…”

“And Joy sees Westworld, and sci-fi in general, as an opportunity to talk about what humanity could or should do if things start to go wrong, especially now that advancements in artificial intelligence technologies are making things like androids seem far more plausible than before. “We’re leaping into the age of the unfathomable, the time when machines [can do things we can’t],”

Joy said.

Westworld’s Creators Know Why Sci-Fi Is So Dystopian

To me, this sounds familiar. It is the essence of my particular brand of design fiction. I don’t always set out to make it dystopian but if we look at the way things seem to naturally evolve, virtually every technology once envisioned as a benefit to humankind ends up with someone misusing it. To look at any potentially transformative tech and not ask, “Transform into what?” is simply irresponsible. We love to sell our ideas on their promise of curing disease, saving lives, and ending suffering, but the technologies that we are designing today have epic downsides that many technologists do not even understand. Misuse happens so often that I’ve begun to see us a reckless if we don’t anticipate these repercussions in advance. It’s the subject of a new paper that I’m working toward.

In the meantime, it’s important that we pay attention and demand that others do, too.

There’s more from the science fiction world on utopias vs. dystopias, and I’ll cover that next week.



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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) with 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 stacked 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?

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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Are you listening to the Internet of Things? Someone is.

As usual, it is a toss up for what I should write about this week. Is it, WIRED’s article on the artificial womb, FastCo’s article on design thinking, the design fiction world of the movie The Circle, or WIRED’s warning about apps using your phone’s microphone to listen for ultrasonic marketing ‘beacons’ that you can’t hear? Tough call, but I decided on a different WIRED post that talked about the vision of Zuckerberg’s future at F8. Actually, the F8 future is a bit like The Circle anyway so I might be killing two birds with one stone.

At first, I thought the article titled, “Look to Zuck’s F8, Not Trump’s 100 Days, to See the Shape of the Future,” would be just another Trump bashing opportunity, (which I sometimes think WIRED prefers more than writing about tech) but not so. It was about tech, mostly.

The article, written by Zachary Karabell starts out with this quote,

“While the fate of the Trump administration certainly matters, it may shape the world much less decisively in the long-term than the tectonic changes rapidly altering the digital landscape.”

I believe this statement is dead-on, but I would include the entire “technological” landscape. The stage is becoming increasingly “set,” as the article continues,

“At the end of March, both the Senate and the House voted to roll back broadband privacy regulations that had been passed by the Federal Communications Commission in 2016. Those would have required internet service providers to seek customers’ explicit permission before selling or sharing their browsing history.”

Combine that with,

“Facebook[s] vision of 24/7 augmented reality with sensors, camera, and chips embedded in clothing, everyday objects, and eventually the human body…”

and the looming possibility of ending net neutrality, we could be setting ourselves up for the real Circle future.

“A world where data and experiences are concentrated in a handful of companies with what will soon be trillion dollar capitalizations risks being one where freedom gives way to control.”

To add kindling to this thicket, there is the Quantified Self movement (QS). According to their website,

“Our mission is to support new discoveries about ourselves and our communities that are grounded in accurate observation and enlivened by a spirit of friendship.”

Huh? Ok. But they want to do this using “self-tracking tools.” This means sensors. They could be in wearables or implantables or ingestibles. Essentially, they track you. Presumably, this is all so that we become more self-aware, and more knowledgeable about our selves and our behaviors. Health, wellness, anxiety, depression, concentration; the list goes on. Like many emerging movements that are linked to technologies, we open the door through health care or longevity, because it is an easy argument that being healty or fit is better than sick and out of shape. But that is all too simple. QS says that that we gain “self knowledge through numbers,” and in the digital age that means data. In a climate that is increasingly less regulatory about what data can be shared and with whom, this could be the beginings of the perfect storm.

As usual, I hope I’m wrong.




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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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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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Now I know that Kurzweil is right.


In a previous blog entitled “Why Kurzweil is probably right,” I made this statement,

“Convergence is the way technology leaps forward. Supporting technologies enable formerly impossible things to become suddenly possible.”

That blog was talking about how we are developing AI systems at a rapid pace. I quoted a WIRED magazine article by David Pierce that was previewing consumer AIs already in the marketplace and some of the advancements on the way. Pierce said that a personal agent is,

“…only fully useful when it’s everywhere when it can get to know you in multiple contexts—learning your habits, your likes and dislikes, your routine and schedule. The way to get there is to have your AI colonize as many apps and devices as possible.”

Then, I made my usual cautionary comment about how such technologies will change us. And they will. So, if you follow this blog, you know that I throw cold water onto technological promises as a matter of course. I do this because I believe that someone has to.

Right now I’m preparing my collaborative design studio course. We’re going to be focusing on AR and VR, but since convergence is an undeniable influence on our techno-social future, we will have to keep AI, human augmentation, the Internet of Things, and a host of other emerging technologies on the desktop as well. In researching the background for this class, I read three articles from Peter Diamandis for the Singularity Hub website. I’ve written about Peter before, as well. He’s brilliant. He’s also a cheerleader for the Singularity. So that being said, these articles, one on the Internet of Everything (IoE/IoT), Artificial Intelligence (AI), and another on Augmented and Virtual Reality (AR/VR), are full of promises. Most of what we thought of as science fiction, even a couple of years ago are now happening with such speed that Diamandis and his cohorts believe they are imminent in only three years. And by that I mean commonplace.

If that isn’t enough for us to sit up and take notice, then I am reminded of an article from the Silicon Valley Business Journal, another interview with Ray Kurzweil. Kurzweil, of course, has pretty much convinced us all by now that the Law of Accelerating Returns is no longer hyperbole. If anyone thought that it was only hype, sheer observation should have brought them to their senses. In this article,
Kurzweil gives this excellent illustration of how exponential growth actually plays out—no longer as a theory but—as demonstrable practice.

“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.”

When you combine that with the nearly exponential chaos of hundreds of other converging technologies, indeed the changes to our world and behavior are coming at us like a bullet-train. Ask any Indy car driver, when things are happening that fast, you have to be paying attention.
But when the input is like a firehose and the motivations are unknown, how on earth do we do that?

Personally, I see this as a calling for design thinkers worldwide. Those in the profession, schooled in the ways of design thinking have been espousing our essential worth to realm of wicked problems for some time now. Well, problems don’t get more wicked than this.

Maybe we can design an AI that could keep us from doing stupid things with technologies that we can make but cannot yet comprehend the impact of.

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Big-Data Algorithms. Don’t worry. Be happy.


It’s easier for us to let the data decide for us. At least that is the idea behind global digital design agency Huge. Aaron Shapiro is the CEO. He says, “The next big breakthrough in design and technology will be the creation of products, services, and experiences that eliminate the needless choices from our lives and make ones on our behalf, freeing us up for the ones we really care about: Anticipatory design.”

Buckminster Fuller wrote about Anticipatory Design Science, but this is not that. Trust me. Shapiro’s version is about allowing big data, by way of artificial intelligence and neural networks, to become so familiar with us and our preferences that it anticipates what we need to do next. In this vision, I don’t have to decide what to wear, or eat, or how to get to work, or when to buy groceries, or gasoline, what color trousers go with my shoes and also when it’s time to buy new shoes. No decisions will be necessary. Interestingly, Shapiro sees this as a good thing. The idea comes from a flurry of activity about something called decision fatigue. What is that? In a nutshell, it says that our decision-making capacity is a reservoir that gradually gets depleted the more decisions we make, possibly as a result of body chemistry. After a long string of decisions, according to the theory, we are more likely to make a bad decision or none at all. Things like willpower disintegrate along with our decision-making.

Among the many articles in the last few months on this topic was FastCompany, who wrote that,

“Anticipatory design is fundamentally different: decisions are made and executed on behalf of the user. The goal is not to help the user make a decision, but to create an ecosystem where a decision is never made—it happens automatically and without user input. The design goal becomes one where we eliminate as many steps as possible and find ways to use data, prior behaviors and business logic to have things happen automatically, or as close to automatic as we can get.”

Supposedly this frees “us up for the ones we really care about.”
My questions are, who decides which questions are important? And once we are freed from making decisions, will we even know that we have missed on that we really care about?

Google Now is a digital assistant that not only responds to a user’s requests and questions, but predicts wants and needs based on search history. Pulling flight information from emails, meeting times from calendars and providing recommendations of where to eat and what to do based on past preferences and current location, the user simply has to open the app for their information to compile.”

It’s easy to forget that AI as we currently know it goes under the name of Facebook or Google or Apple or Amazon. We tend to think of AI as some ghostly future figure or a bank of servers, or an autonomous robot. It reminds me a bit of my previous post about Nick Bostrom and the development of SuperIntelligence. Perhaps it is a bit like an episode of Person of Interest. As we think about designing systems that think for us and decide what is best for us, it might be a good idea to think about what it might be like to no longer think—as long as we still can.



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