Artificial Intelligence

26mag-explicableai-image1-articleLarge

Few technologies have had a big an impact – and promise to have more in the future – than artificial intelligence, or AI.

That’s why it was no surprise that the New York Times Magazine featured an article entitled, “Can A.I. Be Taught to Explain Itself.” For me, it was riveting. Some excerpts:

It has become commonplace to hear that machines, armed with machine learning, can outperform humans at decidedly human tasks, from playing Go to playing “Jeopardy!” We assume that is because computers simply have more data-crunching power than our soggy three-pound brains. Kosinski’s results suggested something stranger: that artificial intelligences often excel by developing whole new ways of seeing, or even thinking, that are inscrutable to us. It’s a more profound version of what’s often called the “black box” problem — the inability to discern exactly what machines are doing when they’re teaching themselves novel skills — and it has become a central concern in artificial-intelligence research. In many arenas, A.I. methods have advanced with startling speed; deep neural networks can now detect certain kinds of cancer as accurately as a human. But human doctors still have to make the decisions — and they won’t trust an A.I. unless it can explain itself.

“Artificial intelligence” is a misnomer, an airy and evocative term that can be shaded with whatever notions we might have about what “intelligence” is in the first place. Researchers today prefer the term “machine learning,” which better describes what makes such algorithms powerful.

The idea was to connect leading A.I. researchers with experts in data visualization and human-computer interaction to see what new tools they might invent to find patterns in huge sets of data. There to judge the ideas, and act as hypothetical users, were analysts for the C.I.A., the N.S.A. and sundry other American intelligence agencies.

Even if a machine made perfect decisions, a human would still have to take responsibility for them — and if the machine’s rationale was beyond reckoning, that could never happen.

Intrigued? You can read the full article here

Tech Rising

What do technology and architecture have in common? Your first reaction might be, “not much,” but a closer look at what is happening to the San Francisco skyline might change your mind.

David Streitfeld’s recent piece, “San Francisco’s Skyline, Now Inescapably Transformed by Tech,” features the subtitle: “Salesforce Tower, which at 1,070 feet is the tallest office building west of the Mississippi, will be inhabited in January, signaling tech’s triumph in the city.”

This short piece in The Sunday New York Times Business Section, marks not just an association, but a marriage, between technology and architecture

Streitfeld notes that in Silicon Valley, the office parks blend into the landscape. They might have made their workers exceedingly rich, they might have changed the world — whether for better or worse is currently up for debate — but there is nothing about them that says: We are a big deal.

Skyscrapers tell a different story. They are the pyramids of our civilization, permanent monuments of our existence. They show who is in charge and what they think about themselves. Salesforce Tower is breaking a San Francisco height record that stood for nearly half a century.

Intrigued? You can read the full article here.

AI and You!

merlin_129555845_9af63388-6b04-422c-a297-f879e0d7287d-master768

Few subjects have captured the public’s imagination today more than artificial intelligence (AI) and machine learning. A niche, tech subject just a few years ago, AI has now gone mainstream.

Part of this is because we are surrounded by digital aps like Siri and Cortana inform and entertain us daily (just ask Siri “What is zero divided by zero).

But AI will play a much more profound role in our lives in the future. But we may have to wait for it. Here is part of what Steve Lohr shared recently in a New York Times piece:

There are basically three big questions about artificial intelligence and its impact on the economy: What can it do? Where is it headed? And how fast will it spread?

Three new reports combine to suggest these answers: It can probably do less right now than you think. But it will eventually do more than you probably think, in more places than you probably think, and will probably evolve faster than powerful technologies have in the past.

This bundle of research is itself a sign of the A.I. boom. Researchers across disciplines are scrambling to understand the likely trajectory, reach and influence of the technology — already finding its way into things like self-driving cars and image recognition online — in all its dimensions. Doing so raises a host of challenges of definition and measurement, because the field is moving quickly — and because companies are branding things A.I. for marketing purposes.

An “AI Index,” created by researchers at Stanford University, the Massachusetts Institute of Technology and other organizations, released on Thursday, tracks developments in artificial intelligence by measuring aspects like technical progress, investment, research citations and university enrollments. The goal of the project is to collect, curate and continually update data to better inform scientists, businesspeople, policymakers and the public.

Want more? You can read the full article here

Silicon Valley: Your Friend?

shutterstock_185722835

Almost from its inception, the World Wide Web produced public anxiety — your computer was joined to a network that was beyond your ken and could send worms, viruses and trackers your way — but we nonetheless were inclined to give these earnest innovators the benefit of the doubt. They were on our side in making the web safe and useful, and thus it became easy to interpret each misstep as an unfortunate accident on the path to digital utopia rather than as subterfuge meant to ensure world domination.

Now that Google, Facebook, Amazon have become world dominators, the questions of the hour are, can the public be convinced to see Silicon Valley as the wrecking ball that it is? And do we still have the regulatory tools and social cohesion to restrain the monopolists before they smash the foundations of our society?

By all accounts, these programmers turned entrepreneurs believed their lofty words and were at first indifferent to getting rich from their ideas. A 1998 paper by Sergey Brin and Larry Page, then computer-science graduate students at Stanford, stressed the social benefits of their new search engine, Google, which would be open to the scrutiny of other researchers and wouldn’t be advertising-driven. The public needed to be assured that searches were uncorrupted, that no one had put his finger on the scale for business reasons.

Intrigued? You can read the entire article here

Tech Dread

11-insider-manjoo-master768

Most of us would agree that technology has enriched our lives in countless ways. But as it has, we have begun to become wary of the ways it may have less-than-positive effects.

Here is how a recent piece in the New York Times tried to get at the heart of just what it is that is making us uneasy about technology:

Technology has crossed over to the dark side. It’s coming for you; it’s coming for us all, and we may not survive its advance. So why am I feeling so bad about tech?

Well, who isn’t, right? Look around you. It’s difficult to get jazzed about smartphones and social networks when smartphones and social networks might be ruining the world. The technologies we were most excited about 10 years ago are now implicated in just about every catastrophe of the day. (See how Russian propagandists used Facebook and Twitter to inject false narratives into the news media last year.)

More immediately, there’s the threat of ever-growing corporate control over much of what we do. These companies are not evil; they’re all led and staffed by smart, well-meaning people who believe that technology can radically improve the world. But as I argue in the series, we have not, as a society, come to grips with the scope of their control over our lives. And we don’t have many good ways to limit it, if we decided that’s what we’d like to do.

Want more? You can read the full article here

Tech Giants

13taplin-master768

Most would agree that technology has enriched our lives and we marvel at the genius of those leading the  “FAANG” companies, which most of us know is is an acronym for the five most popular and best performing tech stocks in the market, namely Facebook, Apple, Amazon, Netflix, and Alphabet’s Google.

But increasingly, more voices are being raised expressing strong doubts as to whether this largely romantic view of the tech industry is at odds with reality. That’s why I was struck by New York Times Op-Ed, “Google Doesn’t Care What’s Best for Us.” Here is part of what the writer shared:

“For much of the short life of Silicon Valley, America has held a largely romantic view of the tech industry. Men like Steve Jobs and Bill Gates were held in high esteem. But increasingly, companies like Google, Amazon and Facebook are coming under the same cultural microscope that questioned the “greed is good” culture of the 1980s. Viewers of the comedy series “Silicon Valley” note that uber-libertarianism and uber-geek machismo go hand in hand. And certainly Mark Zuckerberg was not happy with his portrayal in David Fincher’s “The Social Network,” nor could anyone in the Valley be happy with Dave Eggers’s novel “The Circle” or Don DeLillo’s “Zero K.”

“The future implications of a couple of companies’ having such deep influence on our attention and our behavior are only beginning to be felt. The rise of artificial intelligence combined with Google’s omnipresence in our lives is an issue that is not well understood by politicians or regulators.”

“America is slowly waking up both culturally and politically to the takeover of our economy by a few tech monopolies. We know we are being driven by men like Peter Thiel and Jeff Bezos toward a future that will be better for them. We are not sure that it will be better for us.”

“Somehow the citizens of the world have been left out of this discussion of our future. Because tools like Google and Facebook have become so essential and because we have almost no choice in whether to use them, we need to consider the role they play in our lives. By giving networks like Google and Facebook control of the present, we cede our freedom to choose our future.”

Want more? You can read the full article here

Nerd or Normal?

13SOFTSKILLS-master768

You know the stereotype – the computer nerd. He’s (it’s always a “he,” right?), writes the computer code that enables the digital devices that we now can’t live without.

But we don’t want to meet him. He’s a young guy with no social skills who’s a loner who doesn’t want to have contact with others.

That’s pretty much the opinion that I had, and that’s why I was so intrigued by a recent New York Times article, “Tech’s Damaging Myth of the Loner Genius Nerd.” Here’s part of what the writer had to say:

Interpersonal skills like collaboration, communication, empathy and emotional intelligence are essential to the job. The myth that programming is done by loner men who think only rationally and communicate only with their computers harms the tech industry in ways that cut straight to the bottom line.

The loner stereotype can deter talented people from the industry — not just women, but anyone who thinks that sounds like an unattractive job description. It can also result in dysfunctional teams and poorly performing products. Empathy, after all, is crucial to understanding consumers’ desires, and its absence leads to product mistakes.

Take digital assistants, like Google Home or Amazon Echo. Their programmers need to be able to imagine a huge variety of home situations, whether households with roommates or abusive spouses or children — as made clear when a child ordered a $160 dollhouse and four pounds of sugar cookies on the Echo.

“Basically every step is very collaborative,” said Tracy Chou, who was an engineer at Pinterest and Quora and is now working on start-ups. “Building a big software system, you could have dozens or hundreds or thousands of engineers working on the same code base, and everything still has to work together.” She added, “But not everyone is the same, and that’s where empathy and broader diversity really help.”

Want more? You can read the full article here.

Working 9 to 5

03lyons-master768

Silicon Valley. What a great place. Happy people…going to work in jeans every day…foosball tables…free food…and all the rest. We all are jealous of the happy few who work there.

Not so fast. My son and his wife work in “The Valley,” so I have first-person insights into this lifestyle. It’s a grind.

That’s why I read – with great interest – a recent article in the New York Times entitled: “In Silicon Valley, 9 to 5 is For Losers.” Here is part of what the writer says:

Silicon Valley prides itself on “thinking different.” So maybe it makes sense that just as a lot of industries have begun paying more attention to work-life balance, Silicon Valley is taking the opposite approach — and branding workaholism as a desirable lifestyle choice. An entire cottage industry has sprung up there, selling an internet-centric prosperity gospel that says that there is no higher calling than to start your own company, and that to succeed you must be willing to give up everything.

“Hustle” is the word that tech people use to describe this nerd-commando lifestyle. You hear it everywhere. You can buy hustle-themed T-shirts and coffee mugs, with slogans like “Dream, hustle, profit, repeat” and “Outgrind, outhustle, outwork everyone.” You can go to an eight-week “start-up hustle” boot camp. (Boot camp!) You can also attend Hustle Con, a one-day conference where successful “hustlers” share their secrets. Tickets cost around $300 — or you can pay $2,000 to be a “V.I.P. hustler.” This year’s conference, in June, drew 2,800 people, including two dozen who ponied up for V.I.P. passes.

Want more? You can read the full article here.

Tech Bubble?

06sharma-master768

Much has been written about technology, and especially how technology has changed our lives, mostly for the better. Lately, more ink has been spread about how much the big technology companies – Apple, Amazon, Alphabet, Facebook and others – work to dominate our lives in ways in which we are often dimly aware.

Often lost in this near-breathless reporting is the long-term health of these companies. On the surface, investors whose portfolios contain a good amount of technology stocks are doing well.

That’s why I was intrigued by Ruchir Sharma’s recent piece in the New York Times, “When Will the Tech Bubble Burst?” Here is part of what Sharma shared:

Today, tech mania is resurgent. Investors are again glancing at a clock with no hands — and dismissing the risk. The profitless start-ups that were wiped out in the dot-com crash have consolidated into an oligopoly composed of leading survivors such as Google and Apple. These are giants with real earnings, yet signs of an irrational euphoria are growing.

Seven of the world’s 10 most valuable companies are in the tech sector, matching the late 1999 peak. As the American stock market keeps marching to new highs — the Dow hit 22,000 this week — the gains are increasingly concentrated in the big tech stocks. The bulls say it is inevitable that Apple will become the first trillion-dollar company.

No matter how surreal the endgame, booms tend to begin with real innovation. In the past, manias have been triggered by excitement about canals, the telegraph and the automobile. But not since the advent of railroads incited market booms in the 1830s and 1840s has the world seen back-to-back booms like the dot-com bubble of the 1990s and the one we are in now.

The dot-com era saw the rise of big companies that were building the nuts and bolts of the internet — including Dell, Microsoft, Cisco and Intel — and of start-ups that promised to tap its revolutionary potential. The current boom lacks a popular name because the innovations — from the internet of things to artificial intelligence and machine learning — are sprawling and hard to label. If there is a single thread, it is the expanding capacity to harness data, which the Alibaba founder, Jack Ma, calls the “electricity of the 21st century.”

Want more? You can read the full article here.

Artificial Intelligence

mj17-aiblackbox1

You don’t have to pick up a technical journal to be exposed to articles about artificial intelligence, machine learning, autonomy, deep learning, and the like. This technology surrounds us today and is quickly becoming something we access on a daily basis – witness, SIRI, Alexa and other apps and things we not only use for convenience, but that we count on every day.

Because of the seemingly sudden ubiquity of artificial intelligence (commonly called AI) there is vastly more heat than light on this subject.

That’s why I found this MIT Technology Review article, “The Dark Secret at the Heart of AI,” so fascinating. It asks the crucial question, do we really know what AI is doing for us? Here are a few excerpts:

A car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will.

This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable?

Want more on this fascinating subject? Follow the link to the article

And for a comprehensive report on the growing value of AI in business, read this Price, Waterhouse, Coopers report: “Sizing the prize What’s the real value of AI for your business and how can you capitalize?”