Tag Archives: AI

Corporate Sci-Fi.

Note: Also published on LinkedIn

 

Why your company needs to play in the future.

As a professor of design and a design fiction researcher, I write academic papers and blog weekly about the future. I teach about the future of design, and I create future scenarios, sometimes with my students, that provoke us to look at what we are doing, what we are making, why we are making it and the ramifications that are inevitable. Primarily I try to focus both designers and decision makers on the steps they can take today to keep from being blindsided tomorrow. Futurists seem to be all the rage these days telling us to prepare for the Singularity, autonomous everything, or that robots will take our jobs. Recently, Jennifer Doudna, co-inventor of the gene editing technique called CrisprCas9 has been making the rounds and sounding the alarm that technology is moving so fast that we aren’t going to be able to contain a host of unforeseen (and foreseen) circumstances inside Pandora’s box. This concern should be prevalent, however, beyond just the bioengineering fields and extend into virtually anywhere that technology is racing forward fueled by venture capital and the desperate need to stay on top of whatever space in which we are playing. There is a lot at stake. Technology has already redefined privacy, behavioral wellness, personal autonomy, healthcare, labor, and maybe even our humanness, just to name a few.

Several recent articles have highlighted the changing world of design and how the pressure is on designers to make user adoption more like user addiction to ensure the success of a product or app. The world of behavioral economics is becoming a new arena in which we are using algorithms to manipulate users. Some designers are passing the buck to the clients or corporations that employ them for the questionable ethics of addictive products; others feel compelled to step aside and work on less lucrative projects or apply their skills to social causes. Most really care and want to help. But designers are uniquely positioned and trained to tackle these wicked problems—if we would collaborate with them.

Beyond the companies that might be deliberately trying to manipulate us, are those that unknowingly, or at least unintentionally, transform our behaviors in ways that are potentially harmful. Traditionally, we seek to hold someone responsible when a product or service is faulty, the physician for malpractice, the designer or manufacturer when a toy causes injury, a garment falls apart, or an appliance self-destructs. But as we move toward systemic designs that are less physical and more emotional, behavioral, or biological, design faults may not be so easy to identify and their repercussions noticeable only after serious issues have arisen. In fact, we launch many of the apps and operating systems used today with admitted errors and bugs. Designers rely on real-life testing to identify problems, issue patches, revisions, and versions.

In the realm of nanotechnology, while scientists and thought leaders have proposed guidelines and best-practices, research and development teams in labs around the world race forward without regulation creating molecule-sized structures, machines, and substances with no idea whether they are safe or what might be long-term effects of exposure to these elements. In biotechnology, while folks like Jennifer Doudna appeal to a morally ethical cadre of researchers to tread carefully in the realm of genetic engineering (especially when it comes to inheritable gene manipulation) we do not universally share those morals and ethics. Recent headlines attest to the fact that some scientists are bent on moving forward regardless of the implications.

Some technologies such as our smartphones have become equally invasive technology, yet they are now considered mundane. In just ten years since the introduction of the iPhone, we have transformed behaviors, upended our modes of communication, redefined privacy, distracted our attentions, distorted reality and manipulated a predicted 2.3 billion users as of 2017. [1] It is worth contemplating that this disruption is not from a faulty product, but rather one that can only be considered wildly successful.

There are a plethora of additional technologies that are poised to refine our worlds yet again including artificial intelligence, ubiquitous surveillance, human augmentation, robotics, virtual, augmented and mixed reality and the pervasive Internet of Things. Many of these technologies make their way into our experiences through the promise of better living, medical breakthroughs, or a safer and more secure life. But too often we ignore the potential downsides, the unintended consequences, or the systemic ripple-effects that these technologies spawn. Why?

In many cases, we do not want to stand in the way of progress. In others, we believe that the benefits outweigh the disadvantages, yet this is the same thinking that has spawned some of our most complex and daunting systems, from nuclear weapons to air travel and the internal combustion engine. Each of these began with the best of intentions and, in many ways were as successful and initially beneficial as they could be. At the same time, they advanced and proliferated far more rapidly than we were prepared to accommodate. Dirty bombs are a reality we did not expect. The alluring efficiency with which we can fly from one city to another has nevertheless spawned a gnarly network of air traffic, baggage logistics, and anti-terrorism measures that are arguably more elaborate than getting an aircraft off the ground. Traffic, freeways, infrastructure, safety, and the drain on natural resources are complexities never imagined with the revolution of personal transportation. We didn’t see the entailments of success.

This is not always true. There have often been scientists and thought leaders who were waving the yellow flag of caution. I have written about how, “back in 1975, scientists and researchers got together at Asilomar because they saw the handwriting on the wall. They drew up a set of resolutions to make sure that one day the promise of Bioengineering (still a glimmer in their eyes) would not get out of hand.”[2] Indeed, researchers like Jennifer Doudna continue to carry the banner. A similar conference took place earlier this year to alert us to the potential dangers of technology and earlier this year another to put forth recommendations and guidelines to ensure that when machines are smarter than we are they carry on in a beneficent role. Too often, however, it is the scientists and visionaries who attend these conferences. [3] Noticeably absent, though not always, is corporate leadership.

Nevertheless, in this country, there remains no safeguarding regulation for nanotech, nor bioengineering, nor AI research. It is a free-for-all, and all of which could have massive disruption not only to our lifestyles but also our culture, our behavior, and our humanness. Who is responsible?

For nearly 40 years there has been an environmental movement that has spread globally. Good stewardship is a good idea. But it wasn’t until most corporations saw a way for it to make economic sense that they began to focus on it and then promote it as their contribution to society, their responsibility, and their civic duty. As well intentioned as they may be (and many are) much more are not paying attention to the effect of their technological achievements on our human condition.

We design most technologies with a combination of perceived user need and commercial potential. In many cases, these are coupled with more altruistic motivations such as a “do no harm” commitment to the environment and fair labor practices. As we move toward the capability to change ourselves in fundamental ways, are we also giving significant thought to the behaviors that we will engender by such innovations, or the resulting implications for society, culture, and the interconnectedness of everything?

Enter Humane Technology

Ultimately we will have to demand this level of thought, beginning with ourselves. But we should not fight this alone. Corporations 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.

Humane technology considers the socio-behavioral ramifications of products and services: digital dependencies, and addictions, job loss, genetic repercussions, the human impact from nanotechnologies, AI, and the Internet of Things.

To whom do we turn when a 14-year-old becomes addicted to her smartphone or obsessed with her social media popularity? We could condemn the parents for lack of supervision, but many of them are equally distracted. Who is responsible for the misuse of a drone to vandalize property or fire a gun or the anticipated 1 billion drones flying around by 2030? [4] Who will answer for the repercussions of artificial intelligence that spouts hate speech? Where will the buck stop when genetic profiling becomes a requirement for getting insured or getting a job?

While the backlash against these types of unintended consequences or unforeseen circumstances are not yet widespread and citizens have not taken to the streets in mass protests, behavioral and social changes like these may be imminent as a result of dozens of transformational technologies currently under development in labs and R&D departments across the globe. Who is looking at the unforeseen or the unintended? Who is paying attention and who is turning a blind eye?

It was possible to have anticipated texting and driving. It is possible to anticipate a host of horrific side effects from nanotechnology to both humans and the environment. It’s possible to tag the ever-present bad actor to any number of new technologies. It is possible to identify when the race to master artificial intelligence may be coming at the expense of making it safe or drawing the line. In fact, it is a marketing opportunity for corporate interests to take the lead and the leverage their efforts to preempt adverse side effects as a distinctive advantage.

Emphasizing humane technology is an automatic benefit for an ethical company, and for those more concerned with profit than ethics, (just between you and me) it offers the opportunity for a better brand image and (at least) the appearance of social concern. Whatever the motivation, we are looking at a future where we are either prepared for what happens next, or we are caught napping.

This responsibility should start with anticipatory methodologies that examine the social, cultural and behavioral ramifications, and unintended consequences of what we create. Designers and those trained in design research are excellent collaborators. My brand of design fiction is intended to take us into the future in an immersive and visceral way to provoke the necessary discussion and debate that anticipate the storm should there be one, but promising utopia is rarely the tinder to fuel a provocation. Design fiction embraces the art critical thinking and thought problems as a means of anticipating conflict and complexity before these become problems to be solved.

Ultimately we have to depart from the idea that technology will be the magic pill to solve the ills of humanity, design fiction, and other anticipatory methodologies can help to acknowledge our humanness and our propensity to foul things up. If we do not self-regulate, regulation will inevitably follow, probably spurred on by some unspeakable tragedy. There is an opportunity, now for the corporation to step up to the future with a responsible, thoughtful compassion for our humanity.

 

 

1. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/

2. http://theenvisionist.com/2017/08/04/now-2/

3. http://theenvisionist.com/2017/03/24/genius-panel-concerned/

4. http://www.abc.net.au/news/2017-08-31/world-of-drones-congress-brisbane-futurist-thomas-frey/8859008

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How should we talk about the future?

 

Imagine that there are two camps. One camp holds high confidence that the future will be manifestly bright and promising in all aspects of human endeavor. Our health will dramatically improve as we eradicate disease and possibly even death. Artificial Intelligence will be at our beck and call to make our tough decisions, order our lives, fight our wars, watch over us, and keep us safe. Hence, it is full speed ahead. The positives outweigh the negatives. Any missteps will be but a minor hiccup, and we’ll cross those bridges when we come to them.

The second camp believes that many of these promises are achievable. But they also believe that we are beginning to see strong evidence that technology is indeed moving exponentially and that we are at a trajectory point in the curve that where will see what many experts have categorized as impossible or a “long way off” now is knocking at our door.

Kurzweil’s Law of Accelerating Returns, is proving remarkably accurate. Sure we adapted from the horse and buggy to the automobile, and from there to air travel, to an irritatingly resilient nuclear threat, to computers, and smartphones and DNA sequencing. But these changes are arriving more rapidly than their predecessors.

“‘As exponential growth continues to accelerate into the first half of the twenty-first century,’ [Kurzweil] writes. ‘It will appear to explode into infinity, at least from the limited and linear perspective of contemporary humans.’”1

The second camp sees this rapid-fire proliferation as alarming. Not because we will get to utopia faster, but because we will be standing in the midst of a host of disruptive technologies all coming to fruition at the same time without the benefit of meaningful oversight or the engagement of our societies.

I am in the second camp.

Last week, I talked about genetic engineering. The designer-baby question was always pushed aside as a long way off. Not anymore. That’s just one change. Our privacy, in the form of “big data,” from seemingly innocent pastimes such as Facebook, is being severely compromised. According to security technologist Bruce Schneier,

“Facebook can predict race, personality, sexual orientation, political ideology, relationship status, and drug use on the basis of Like clicks alone. The company knows you’re engaged before you announce it, and gay before you come out—and its postings may reveal that to other people without your knowledge or permission. Depending on the country you live in, that could merely be a major personal embarrassment—or it could get you killed.”

Facebook is just one of the seemingly benign things we do every day. By now, most of us consider that using our smartphones 75 percent of our day is also harmless, though we would also have to agree that it has changed us personally, behaviorally, and societally. And while the societal outcry against designer babies has been noticeable since last weeks stories about CrisprCas9 gene splicing with human embryos, how long will it be before we accept it as the norm, and feel pressure in our own families to participate to stay competitive, or maybe even just to be insured.

The fact is that we like to think that we can adapt to anything. To some extent, we pride ourselves on this resilience. Unfortunately, that seems to suggest that we are also powerless to affect these technologies and that we have no say in when, if, or whether we should make them in the first place. Should we be proud of the fact that we are adapting to a complete lack of privacy, to the likelihood of terrorism or being replaced by an AI? These are my questions.

So I am encouraged when others also raise these questions. Recently, the tech media which seems to be perpetually enamored of folks like Mark Zuckerberg and Elon Musk, called Zuckerberg a “bad futurist” because of his over optimistic view of the future.

The article came from the Huffington post’s Rebecca Searles.
According to Searles,

“Elon Musk’s doomsday AI predictions aren’t “irresponsible,” but Mark Zuckerberg’s techno-optimism is.”3

According to a Zuckerberg podcast,

“…people who are arguing for slowing down the process of
building AI, I just find that really questionable… If you’re arguing against AI, then you’re arguing against safer cars that aren’t going to have accidents and you’re arguing against being able to better diagnose people when they’re sick.”3

Technology hawks are always promising safer, and healthier as their rationale for unimpeded acceleration. I’m sure that’s the rah-rah rationale for designer babies, too. Think of all the illnesses we will be able to breed out of the human race. Searles and I agree that negative outcomes deserve equally serious consideration as well, and not after they happen. As she aptly puts it,

“Tackling tech challenges with a build-it-and-see-what-happens approach (a la Zuckerberg’s former “move fast and break things” development mantra) just isn’t suitable for AI.”

The problem is, that Zuckerberg is not alone, nor is last weeks
Shoukhrat Mitalipov. Ultimately, this reality of two camps is the rationale behind my approach to design fiction. As you know, the objective of design fiction is to provoke. Promising utopia is rarely the tinder to fuel a provocation.

Let’s remember Charles Dickens’ story of Ebenezer Scrooge. The ghost of Christmas past takes him back in time where, for the first time, he sees the truth about his past. But this revelation does not change him. Then the ghost of Christmas present opens his eyes to everything around him that he is blind to in the present. Still, Scrooge is unaffected. And finally, the ghost of Christmas future takes him into the future, and it is here that Scrooge sees the days to come as “the way it will be” unless he changes something now.

Somehow, I think the outcome would have been different if that last ghost said, ”Don’t worry. You’ll adapt.”

Let’s not talk about the future in purely utopian terms nor total doom-and-gloom. The future will not be like one or the other any more than is the present day. But let us not be blind to our infinite capacity to foul things up, to the potential of bad actors or the inevitability of unanticipated consequences. If we have any hope of meeting our future with the altruistic image of a utopian society, let us go forward with eyes open.

 

1. http://www.businessinsider.com/ray-kurzweil-law-of-accelerating-returns-2015-5

2. “Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World”

3. http://www.huffingtonpost.com/entry/mark-zuckerberg-is-a-bad-futurist_us_5979295ae4b09982b73761f0

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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

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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/
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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.

 

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An example of impending convergence.

 

The IBM Research Alliance and partners have announced this week that they have developed “…an industry-first process to build silicon nanosheet transistors that will enable 5 nanometer (nm) chips – achieving a scale of 30 billion switches on a fingernail-sized chip that will deliver significant power and performance enhancements over today’s state-of-the-art 10nm chips.”

Silicon nanosheet transistors at 5nm

Along with this new development there, of course, come promises that the technology

“…can deliver 40 percent performance enhancement at fixed power, or 75 percent power savings at matched performance. This improvement enables a significant boost to meeting the future demands of artificial intelligence (AI) systems, virtual reality and mobile devices.”

That’s a lot of tech-speech, but essentially it means your computing will happen faster, your devices will be more powerful and use less battery life.

In a previous blog, I discussed the nanometer idea.

“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.”

Right now, IBM and their partners see this new development as a big plus to the future of their cognitive systems. What are cognitive systems?

IBM can answer that:

“Humans are on the cusp of augmenting their lives in extraordinary ways with AI. At IBM Research Labs around the globe, we envision and develop next-generation systems that work side-by-side with humans, accelerating our ability to create, learn, make decisions and think. We also architect the future of Watson, which has evolved from an IBM Research project to the world’s first and most-advanced AI platform.”

So it’s Watson and lots of other AI that may see the biggest benefits as a result of this new tech. With smaller, faster, more efficient chips AI can live a more robust life inside your phone or another device. But thinking phone is probably thinking way too big. Think of something much smaller but just as powerful.

Of course, every new technology comes with promises.

“Whether exploring new technical capabilities, collaborating on ethical practices or applying Watson technology to cancer research, financial decision-making, oil exploration or educational toys, IBM Research is shaping the future of AI.”

It’s all about AI and how we can augment “our lives in extraordinary ways.” Assuming that everyone plays nice, this is another example of technology poised for great things for humankind. Undoubtedly, micro-sized AI can be used for all sorts of nefarious purposes so let’s hope that the “ethical practices” part of their research is getting equal weight.

The question we have yet to ask is whether a faster, smaller, more powerful, all-knowing, steadily accelerating AI is something we truly need. This is a debate worth having. In the meantime, a 5 nm chip breakthrough is an excellent example of how a new, breakthrough technology awaits application by others for a myriad of purposes, advancing them all, in particular ways, by leaps and bounds. Who are these others? And what will they do next?

The right thing to do. Remember that idea?

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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?

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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Autonomous Assumptions

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

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

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

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

There is a caveat.

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

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

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

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

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

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

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

 

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