Tag Archives: artificial intelligence

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:

https://www.fastcompany.com/3064368/we-dont-always-know-what-ai-is-thinking-and-that-can-be-scary

https://www.fastcodesign.com/90133138/googles-next-design-project-artificial-intelligence

Bookmark and Share

Watching and listening.

 

Pay no attention to Alexa, she’s an AI.

There was a flurry of reports from dozens of news sources (including CNN) last week that an Amazon Echo, (Alexa), called the police during a New Mexico incident of domestic violence. The alleged call began a SWAT standoff, and the victim’s boyfriend was eventually arrested. Interesting story, but after a fact-check, that could not be what happened. Several sources including the New York Times and WIRED debunked the story with details on how Alexa calling 911 is technologically impossible, at least for now. And although the Bernalillo, New Mexico County Sheriff’s Department swears to it, according to WIRED,

“Someone called the police that day. It just wasn’t Alexa..”

Even Amazon agrees from a spokesperson email,

“The receiving end would also need to have an Echo device or the Alexa app connected to Wi-Fi or mobile data, and they would need to have Alexa calling/messaging set up,”1

So it didn’t happen, but most agree, while it may be technologically impossible today, it probably won’t be for very long. The provocative side of the WIRED article proposed this thought:

“The Bernalillo County incident almost certainly had nothing to do with Alexa. But it presents an opportunity to think about issues and abilities that will become real sooner than you might think.”

On the upside, some see benefits from the ability of Alexa to intervene in a domestic dispute that could turn lethal, but they fear something called “false positives.” Could an off handed comment prompt Alexa to make a call to the police? And if it did would you feel as though Alexa had overstepped her bounds?

Others see the potential in suicide prevention. Alexa could calm you down or make suggestions for ways to move beyond the urge to die.

But as we contemplate opening this door, we need to acknowledge that we’re letting these devices listen to us 24/7 and giving them the permission to make decisions on our behalf whether we want them to or not. The WIRED article also included a comment from Evan Selinger of RIT (whom I’ve quoted before).

“Cyberservants will exhibit mission creep over time. They’ll take on more and more functions. And they’ll habituate us to become increasingly comfortable with always-on environments listening to our intimate spaces.”

These technologies start out as warm and fuzzy (see the video below) but as they become part of our lives, they can change us and not always for the good. This idea is something I contemplated a couple of years ago with my Ubiquitous Surveillance future. In this case, the invasion was not as a listening device but with a camera (already part of Amazon’s Echo Look). You can check that out and do your own provocation by visiting the link.

I’m glad that there are people like Susan Liautaud (who I wrote about last week) and Evan Selinger who are thinking about the effects of technology on society, but I still fear most of us take the stance of Dan Reidenberg, who is also quoted in the WIRED piece.

“‘I don’t think we can avoid this. This is where it is going to go. It is really about us adapting to that,” he says.’”

 

Nonsense! That’s like getting in the car with a drunk driver and then doing your best to adapt. Nobody is putting a gun to your head to get into the car. There are decisions to be made here, and they don’t have to be made after the technology has created seemingly insurmountable problems or intrusions in our lives. The companies that make them should be having these discussions now, and we should be invited to share our opinions.

What do you think?

 

  1. http://wccftech.com/alexa-echo-calling-911/
Bookmark and Share

Ethical tech.

Though I tinge most of my blogs with ethical questions, the last time I brought up this topic specifically on this was back in 2015. I guess I am ready to give it another go. Ethics is a tough topic. If we deal with this purely superficially, ethics would seem natural, like common sense, or the right thing to do. But if that’s the case, why do so many people do the wrong thing? Things get even more complicated if we move into institutionally complex issues like banking, or governing, technology, genetics, health care or national defense, just to name a few.

The last time I wrote about this, I highlighted Michael Sandel Professor of Philosophy and Government at Harvard’s Law School, where he teaches a wildly popular course called “Justice.” Then, I was glad to see that the big questions were still being addressed in in places like Harvard. Some of his questions then, which came from a FastCo article, were:

“Is it right to take from the rich and give to the poor? Is it right to legislate personal safety? Can torture ever be justified? Should we try to live forever? Buy our way to the head of the line? Create perfect children?”

These are undoubtedly important and prescient questions to ask, especially as we are beginning to confront technologies that make things which were formerly inconceivable or plain impossible, not only possible but likely.

So I was pleased to see last month, an op-ed piece in WIRED by Susan Liautaud founder of The Ethics Incubator. Susan is about as closely aligned to my tech concerns as anyone I have read. And she brings solid thinking to the issues.

“Technology is approaching the man-machine and man-animal
boundaries. And with this, society may be leaping into humanity defining innovation without the equivalent of a constitutional convention to decide who should have the authority to decide whether, when, and how these innovations are released into society. What are the ethical ramifications? What checks and balances might be important?”

Her comments are right in line with my research and co-research into Humane Technologies. Liataud continues:

“Increasingly, the people and companies with the technological or scientific ability to create new products or innovations are de facto making policy decisions that affect human safety and society. But these decisions are often based on the creator’s intent for the product, and they don’t always take into account its potential risks and unforeseen uses. What if gene-editing is diverted for terrorist ends? What if human-pig chimeras mate? What if citizens prefer to see birds rather than flying cars when they look out a window? (Apparently, this is a real risk. Uber plans to offer flight-hailing apps by 2020.) What if Echo Look leads to mental health issues for teenagers? Who bears responsibility for the consequences?”

For me, the answer to that last question is all of us. We should not rely on business and industry to make these decisions, nor expect our government to do it. We have to become involved in these issues at the public level.

Michael Sandel believes that the public is hungry for these issues, but we tend to shy away from them. They can be confrontational and divisive, and no one wants to make waves or be politically incorrect. That’s a mistake.

An image from the future. A student design fiction project that examined ubiquitous AR.

So while the last thing I want is a politician or CEO making these decisions, these two constituencies could do the responsible thing and create forums for these discussions so that the public can weigh in on them. To do anything less, borders on arrogance.

Ultimately we will have to demand this level of thought, beginning with ourselves. This responsibility should start with anticipatory methodologies that examine the social, cultural and behavioral ramifications, and unintended consequences of what we create.

But we should not fight this alone. Corporations and governments concerned with appearing sensitive and proactive toward the environment and social justice need to add a new pillar to their edifice as responsible global citizens: humane technology.

 

Bookmark and Share

An AI as President?

 

Back on May 19th, before I went on holiday, I promised to comment on an article that appeared that week advocating that we would better off with artificial intelligence (AI) as President of the United States. Joshua Davis authored the piece: Hear me out: Let’s Elect
An AI As President, for the business section of WIRED  online. Let’s start out with a few quotes.

“An artificially intelligent president could be trained to
maximize happiness for the most people without infringing on civil liberties.”

“Within a decade, tens of thousands of people will entrust their daily commute—and their safety—to an algorithm, and they’ll do it happily…The increase in human productivity and happiness will be enormous.”

Let’s start with the word happiness. What is that anyway? I’ve seen it around in several discourses about the future, that somehow we have to start focusing on human happiness above all things, but what makes me happy and what makes you happy may very well be different things. Then there is the frightening idea that it is the job of government to make us happy! There are a lot of folks out there that the government should give us a guaranteed income, pay for our healthcare, and now, apparently, it should also make us happy. If you haven’t noticed from my previous blogs, I am not a progressive. If you believe that government should undertake the happy challenge, you had better hope that their idea of happiness coincides with your own. Gerd Leonhard, a futurist whose work I respect, says that there are two types of happiness: first is hedonic (pleasure) which tends to be temporary, and the other is a eudaimonic happiness which he defines as human flourishing.1 I prefer the latter as it is likely to be more meaningful. Meaning is rather crucial to well-being and purpose in life. I believe that we should be responsible for our happiness. God help us if we leave it up to a machine.

This brings me to my next issue with this insane idea. Davis suggests that by simply not driving, there will be an enormous increase in human productivity and happiness. According to the website overflow data,

“Of the 139,786,639 working individuals in the US, 7,000,722, or about 5.01%, use public transit to get to work according to the 2013 American Communities Survey.”

Are those 7 million working individuals who don’t drive happier and more productive? The survey should have asked, but I’m betting the answer is no. Davis also assumes that everyone will be able to afford an autonomous vehicle. Maybe providing every American with an autonomous vehicle is also the job of the government.

Where I agree with Davis is that we will probably abdicate our daily commute to an algorithm and do it happily. Maybe this is the most disturbing part of his argument. As I am fond of saying, we are sponges for technology, and we often adopt new technology without so much as a thought toward the broader ramifications of what it means to our humanity.

There are sober people out there advocating that we must start to abdicate our decision-making to algorithms because we have too many decisions to make. They are concerned that the current state of affairs is simply too painful for humankind. If you dig into the rationale that these experts are using, many of them are motivated by commerce. Already Google and Facebook and the algorithms of a dozen different apps are telling you what you should buy, where you should eat, who you should “friend” and, in some cases, what you should think. They give you news (real or fake), and they tell you this is what will make you happy. Is it working? Agendas are everywhere, but very few of them have you in the center.

As part of his rationale, Davis cites the proven ability for AI to beat the world’s Go champions over and over and over again, and that it can find melanomas better than board-certified dermatologists.

“It won’t be long before an AI is sophisticated enough to
implement a core set of beliefs in ways that reflect changes in the world. In other words, the time is coming when AIs will have better judgment than most politicians.”

That seems like grounds to elect one as President, right? In fact, it is just another way for us to take our eye off the ball, to subordinate our autonomy to more powerful forces in the belief that technology will save us and make us happier.

Back to my previous point, that’s what is so frightening. It is precisely the kind of argument that people buy into. What if the new AI President decides that we will all be happier if we’re sedated, and then using executive powers makes it law? Forget checks and balances, since who else in government could win an argument against an all-knowing AI? How much power will the new AI President give to other algorithms, bots, and machines?

If we are willing to give up the process of purposeful work to make a living wage in exchange for a guaranteed income, to subordinate our decision-making to have “less to think about,” to abandon reality for a “good enough” simulation, and believe that this new AI will be free of the special interests who think they control it, then get ready for the future.

1. Leonhard, Gerd. Technology vs. Humanity: The Coming Clash between Man and Machine. p112, United Kingdom: Fast Future, 2016. Print.

Bookmark and Share

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?

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.

Bookmark and Share

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.

 

Bookmark and Share

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.

Bookmark and Share

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.

Bookmark and Share

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.

Bookmark and Share

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?

Bookmark and Share