Op-Ed: The promise and perils of Artificial Intelligence – The Coronado News

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George Galdorisi, a Coronado resident and New York Times bestselling author, says we can manage AI, and it will not manage us.

The headline on the first page of the New York Times Sunday Opinion page in early July could not have been more stark or more menacing: “The True Threat of Artificial Intelligence: Technology Forged by Private Markets Won’t Solve the World’s Problems. It Will Only Amplify Them.”

It that statement doesn’t get your attention, it’s likely that nothing will.

It would be difficult to identify a technology that has been talked and written about than those under the umbrella of artificial intelligence or AI.

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Who’s Driving?

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Full disclosure: I love to drive. When people started talking about self-driving cars, the first thing I asked myself was: What question is this the answer to?

But people who thought they were the greatest idea ever were undaunted. Predictions about self-driving cars being on the roads in huge numbers by this year were everywhere.

Now we have hit the brakes. I read an article recently, “The Costly Pursuit of Self-Driving Cars Continues On. And On. And On.” It’s subtitle is revealing: “Many in Silicon Valley promised that self-driving cars would be a common sight by 2021. Now the industry is resetting expectations and settling in for years of more work.” Here is how it begins:

It was seven years ago when Waymo discovered that spring blossoms made its self-driving cars get twitchy on the brakes. So did soap bubbles. And road flares.

New tests, in years of tests, revealed more and more distractions for the driverless cars. Their road skills improved, but matching the competence of human drivers was elusive. The cluttered roads of America, it turned out, were a daunting place for a robot.

The wizards of Silicon Valley said people would be commuting to work in self-driving cars by now. Instead, there have been court fights, injuries and deaths, and tens of billions of dollars spent on a frustratingly fickle technology that some researchers say is still years from becoming the industry’s next big thing.

Now the pursuit of autonomous cars is undergoing a reset. Companies like Uber and Lyft, worried about blowing through their cash in pursuit of autonomous technology, have tapped out. Only the deepest-pocketed outfits like Waymo, which is a subsidiary of Google’s parent company, Alphabet; auto giants; and a handful of start-ups are managing to stay in the game.

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Who’s on Top?

We all recognize that big tech, especially the FAANG Five (Facebook, Amazon, Apple, Netflix, and Alphabet (Google parent) have an increasingly dominant position in our lives.

Like it or not, we depend on this technology not only to enhance our lives, but to do the very basics of day-to-day living.

As one indication as to how the FAANG Five dominate our lives, one needs only look to what happened at an Amazon warehouse in Alabama. Here is how a recent article began the tale:

It is easy to imagine that Amazon executives popped champagne corks over the weekend after quashing the union drive in Bessemer, Ala. After a bruising fight, workers at the warehouse, in a suburb of Birmingham, rejected joining a union by more than a two-to-one ratio, chilling future union organizing efforts at the nation’s second-largest private employer.

In its bitter battle against the Retail, Wholesale and Department Store Union, Amazon won much more than a reprieve from labor’s advances; at stake in Alabama was securing corporate America’s carefully constructed supremacy over its workers.

Amazon was standing up for the big guys.

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Tech Rising – and Dominating

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We all know, intuitively, that big tech has grown during Covid-19 since so many of us are working from home and using all sorts of technology to stay connected.

But for me, I had no idea of how much tech had grown until I read an article, “How Big Tech Got Even Bigger.” Here is how it begins:

Technology giants such as Alphabet, Amazon and Apple are more dominant than a year ago thanks to a greater reliance on their services during the pandemic. The forces propelling them to new heights are expected to outlast Covid-19.

The tech industry’s titans were already huge before Covid-19, the subject of soaring valuations and snowballing antitrust investigations. The pandemic has only made them bigger. A lot bigger.

In almost every facet of life—the tools we use to work, study, and play; how we shop and interact; the way companies operate and market their products—people and businesses have become more reliant on technology over the past year. Even amid one of the most punishing economic downturns on record, spending surged on computers, videogames, online retail, cloud-computing services and digital advertising.

The result was dizzying growth for some of the largest corporations in history—and for their stock prices. At a time when companies such as airlines and bricks-and-mortar retailers struggled to survive, combined revenue for the five biggest U.S. tech companies— Apple Inc., AAPL 0.02% Microsoft Corp. , Amazon.com Inc., AMZN -0.81% Google-parent Alphabet Inc., and Facebook Inc. FB -1.38% —grew by a fifth, to $1.1 trillion. Their aggregate profit rose an even faster 24%. And their combined market capitalization soared by half over the past year to a staggering $8 trillion.

Their economic sway expanded in other ways, too, including employment: Amazon alone added 500,000 new workers in a single year, roughly equivalent to the entire population of Atlanta.

Lawmakers and regulators may yet find ways to rein them in, but the economic and societal forces propelling Big Tech to even higher heights seem likely to outlast Covid-19. Microsoft Chief Executive Satya Nadella has said that he expects spending on technology to double to 10% of gross domestic product from its current level of 5%. This month he said he now expects that to happen even faster.

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Dedication to a Cause

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Much ink has been spilled about the future of robots and how they will either help – or hurt – humanity. Some still fear HAL from 2001 A Space Odyssey.

That is why I was drawn to a recent piece, “A Case for Cooperation Between Machines and Humans.” The subtitle is revealing: “A computer scientist argues that the quest for fully automated robots is misguided, perhaps even dangerous. His decades of warnings are gaining more attention.” Here is how it begins:

The Tesla chief Elon Musk and other big-name Silicon Valley executives have long promised a car that can do all the driving without human assistance.

But Ben Shneiderman, a University of Maryland computer scientist who has for decades warned against blindly automating tasks with computers, thinks fully automated cars and the tech industry’s vision for a robotic future is misguided. Even dangerous. Robots should collaborate with humans, he believes, rather than replace them.

Late last year, Dr. Shneiderman embarked on a crusade to convince the artificial intelligence world that it is heading in the wrong direction. In February, he confronted organizers of an industry conference on “Assured Autonomy” in Phoenix, telling them that even the title of their conference was wrong. Instead of trying to create autonomous robots, he said, designers should focus on a new mantra, designing computerized machines that are “reliable, safe and trustworthy.”

There should be the equivalent of a flight data recorder for every robot, Dr. Shneiderman argued.

It is a warning that’s likely to gain more urgency when the world’s economies eventually emerge from the devastation of the coronavirus pandemic and millions who have lost their jobs try to return to work. A growing number of them will find they are competing with or working side by side with machines.

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Big Tech and National Security

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There is little question that the United States faces two powerful peer competitors, China and Russia.

There is also no question that we cannot match these powers soldier for soldier or tank for tank. The only way we are likely to prevail is through technological innovation.

The big tech companies – not the traditional defense industry giants – are the ones who can help us achieve that goal. One person, former Google CEO Eric Schmidt, is leading this effort.

A revealing article in the New York Times entitled, “‘I Could Solve Most of Your Problems’: Eric Schmidt’s Pentagon Offensive,” begins this way:

In July 2016, Raymond Thomas, a four-star general and head of the U.S. Special Operations Command, hosted a guest: Eric Schmidt, the chairman of Google.

General Thomas, who served in the 1991 gulf war and deployed many times to Afghanistan, spent the better part of a day showing Mr. Schmidt around Special Operations Command’s headquarters in Tampa, Fla. They scrutinized prototypes for a robotic exoskeleton suit and joined operational briefings, which Mr. Schmidt wanted to learn more about because he had recently begun advising the military on technology.

After the visit, as they rode in a Chevy Suburban toward an airport, the conversation turned to a form of artificial intelligence.

“You absolutely suck at machine learning,” Mr. Schmidt told General Thomas, the officer recalled. “If I got under your tent for a day, I could solve most of your problems.” General Thomas said he was so offended that he wanted to throw Mr. Schmidt out of the car, but refrained.

Four years later, Mr. Schmidt, 65, has channeled his blunt assessment of the military’s tech failings into a personal campaign to revamp America’s defense forces with more engineers, more software and more A.I. In the process, the tech billionaire, who left Google last year, has reinvented himself as the prime liaison between Silicon Valley and the national security community.

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Big Tech

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Many people, perhaps with some justification, feel that big companies dominate the nation (and the world) in unhelpful ways.

That has been an American inclination since the days of the “robber barons” a century ago. Our attitudes mirror those of our ancestors.

Today, it is fashionable to bash “big anything.” At or near the top of the list has been “Big Pharma,” that was, at least, until we now look to them to find a cure for Covid-19.

Big tech has also taken a beating, with calls to break up tech companies. But big tech does more than manufacture gadgets and software. Here is an article about what Salesforce CEO Marc Benioff did to help. It begins….

Sam Hawgood, the chancellor of the University of California, San Francisco, was getting concerned.

It was March 19, coronavirus cases in California were rising at an alarming rate, and U.C.S.F., one of the Bay Area’s major medical providers, was already running perilously low on personal protective equipment.

The university’s usual suppliers in the United States were short on masks and face shields, and there was no sign that the State of California or the federal government was coming to the rescue. “The supply chain had really dried up,” Mr. Hawgood said.

So Mr. Hawgood called Marc Benioff, the hyperconnected billionaire who is a founder and the chief executive of Salesforce.

In some ways, it was the natural call to make. Mr. Benioff gave the university $100 million to build a children’s hospital in 2010 and remained a major benefactor. But there was no reason to think Mr. Benioff, who runs an enterprise software company, could quickly muster a supply chain for personal protective equipment, especially during a global pandemic.

Nonetheless, that phone call set off a frenzied effort by Mr. Benioff and his team that drew in major companies like FedEx, Walmart, Uber and Alibaba. In a matter of weeks, the team spent more than $25 million to procure more than 50 million pieces of protective equipment. Fifteen million units have already been delivered to hospitals, medical facilities and states, and more are on the way.

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The U.S. and China

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Much ink has been spilled regarding the relationship between the U.S. Federal Government and the Technology Industry. Some of it has been shrill.

That is why I gravitated to a recent op-ed written by former Google CEO Eric Schmidt. The title of the piece, “Silicon Valley Needs the Government” reveals a lot.

Dr. Schmidt has street creds few others possess. He is the chairman of the National Security Commission on Artificial Intelligence and the Defense Innovation Board.

Here is his preamble to his article: “I Used to Run Google. Silicon Valley Could Lose to China. We can’t win the technology wars without the federal government’s help.” Then he continues:

America’s companies and universities innovate like no other places on earth. We are garage start-ups, risk-taking entrepreneurs and intrepid scholars exploring new advances in science and technology. But that is only part of the story.

Many of Silicon Valley’s leaders got their start with grants from the federal government — including me. My graduate work in computer science in the 1970s and ’80s was funded in part by the National Science Foundation and the Defense Advanced Research Projects Agency.

But in recent years, Americans — Silicon Valley leaders included — have put too much faith in the private sector to ensure U.S. global leadership in new technology. Now we are in a technology competition with China that has profound ramifications for our economy and defense — a reality I have come to appreciate as chairman of two government panels on innovation and national security. The government needs to get back in the game in a serious way.

Important trends are not in our favor. America’s lead in artificial intelligence, for example, is precarious. A.I. will open new frontiers in everything from biotechnology to banking, and it is also a Defense Department priority. Leading the world in A.I. is essential to growing our economy and protecting our security. A recent study considering more than 100 metrics finds that the United States is well ahead of China today but will fall behind in five to 10 years. China also has almost twice as many supercomputers and about 15 times as many deployed 5G base stations as the United States. If current trends continue, China’s overall investments in research and development are expected to surpass those of the United States within 10 years, around the same time its economy is projected to become larger than ours.

Unless these trends change, in the 2030s we will be competing with a country that has a bigger economy, more research and development investments, better research, wider deployment of new technologies and stronger computing infrastructure.

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Tech Rising?

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Last month, I blogged about technology and featured an article that asked the question, “Has Technology Peaked?

Piling on to that post, here are the most recent (February 11, 2020) from the Wall Street Journal of those companies with over a one trillion dollar valuation:

  • Microsoft: $1.44 trillion
  • Apple: $1.41 trillion
  • Amazon: $1.06 trillion
  • Alphabet: $1.04 trillion

Oh, and Facebook is the next-most highly valued company at $607 billion.

Has technology peaked? What do you think?

Has Technology Peaked?

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A great deal of ink has been spilled trying to guess where technology is moving in the future. After decades of spectacular advances, many think this progress have peaked.

I don’t think they have, and those thoughts were supported in a recent article by Andy Kessler who follows technology for the Wall Street Journal. Here is how he begins:

Does history rhyme? A century ago, the ’20s boomed, driven by consumer spending on homes, cars, radios and newfangled appliances like refrigerators, sewing machines and vacuum cleaners. Most Americans couldn’t afford the upfront cost of a lot of these goods, so manufacturers and retailers invented installment plans. Debt ruled as 75% of cars, furniture and washing machines were bought on credit.

So what’s next? My fundamental rule for finding growth trends is that you need to see viable technologies today, and then predict which ones will get cheaper and better over time. Microprocessors, storage, bandwidth—all still going strong after half a century.

The fundamental building block of the 2020s will be artificial intelligence, particularly machine learning. Better to ask what it won’t change this decade. The artificial neural networks that made face and voice recognition viable were the low-hanging fruit. Now chips tailor-made for machine learning are increasing speed and cutting costs. A recent Stanford report suggests that the power behind the most advanced AI computations is doubling nearly every three months, outpacing Moore’s Law by a factor of six.

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