Humans supervise these AI programs and make the ultimate decisions, but white-collar workers are understandably starting to worry about the day when AI can go it alone.
Don’t panic: Though the AI Revolution is underway, it is unlikely to eliminate many office jobs within the next five to 10 years. Current AI research and usage only targets specific tasks, like image recognition or data analysis, while most jobs require workers to draw on a broad range of skills.
But I think it’s important to understand why the job market will change. There have been important advances in AI in recent years, especially in the area known as deep learning. Rather than telling a computer exactly how to do a task with step-by-step programming, researchers employing a deep learning system step back and let it apply techniques such as pattern recognition and trial and error to teach itself how — techniques humans use. To be clear, “artificial intelligence” does not mean that such machines are sentient, as they are portrayed in science fiction; only that given more data, they may perform a task better.
by Ji Shisan
Ji Shisan is the pen name under which Ji Xiaohua, a science writer with a Ph.D. in neurobiology, has been publishing for many years. He is the founder of Guokr.com and Guokr MOOC Academy, a popular science website and an MOOC platform in China, and the founder of Zaih.com, a knowledge service platform helping users to connect with experts in different fields.
嵇晓华（1977－），网名姬十三，果壳网创始人兼CEO，神经生物学博士，科学松鼠会和果壳网创始人。生于舟山，现居上海。
http://www.nytimes.com/2015/12/10/opinion/the-end-of-work.html
Turning Point: An AI system teaches itself how to play and win video games without any programming.
Welcome to the era of AI-human hybrid intelligence, where people and artificial intelligence systems work together seamlessly. Picture the scene from the 1986 movie “Aliens,” where Sigourney Weaver slips into a humanoid, semi-robotic weight-lifting unit to fight the alien queen — that’s about where we are today. (A number of companies around the world are developing versions of such devices for industrial and medical use, with some already on the market.)
— The Associated Press is using Automated Insights’ software to produce thousands of articles about corporate earnings each year, freeing up staff for other reporting. Humans expand and polish a few of the most important articles.
— While Facebook’s virtual assistant M, introduced in the San Francisco Bay Area in 2015, uses AI to answer user questions, humans vet the answers to improve them.
— IBM’s Watson is employed at some hospitals in the United States to determine the best course of treatment for individual cancer patients. Watson analyzes genetic information and the medical literature, and then provides suggestions to the doctors in charge.
Humans supervise these AI programs and make the ultimate decisions, but white-collar workers are understandably starting to worry about the day when AI can go it alone.
Don’t panic: Though the AI Revolution is underway, it is unlikely to eliminate many office jobs within the next five to 10 years. Current AI research and usage only targets specific tasks, like image recognition or data analysis, while most jobs require workers to draw on a broad range of skills.
But I think it’s important to understand why the job market will change. There have been important advances in AI in recent years, especially in the area known as deep learning. Rather than telling a computer exactly how to do a task with step-by-step programming, researchers employing a deep learning system step back and let it apply techniques such as pattern recognition and trial and error to teach itself how — techniques humans use. To be clear, “artificial intelligence” does not mean that such machines are sentient, as they are portrayed in science fiction; only that given more data, they may perform a task better.
A team of researchers from Google announced a breakthrough in machine learning in 2012. They had created a network of 16,000 computer cores that was partly modeled on the human brain, with a billion connections between simulated neurons. The researchers fed 10 million images to the AI over three days and, unsupervised, it taught itself to recognize categories like human bodies and — the Internet’s favorite — cats. In 2015 a group from DeepMind, a company acquired by Google, published research showing that a neural network had been given the same inputs as a human on dozens of Atari games from the ’70s and ’80s — the pixels and the score — and had become an expert player at some of them without having been given any prior instruction or the rules for the games.
As the technology improves, we are giving AI systems more and more work to do, just as we did with computers in their infancy. In 2014 and 2015, Skype introduced simultaneous translation in English, French, German, Italian, Mandarin and Spanish. Apple’s Siri, Amazon’s Alexa and Microsoft’s Cortana are all digital assistants that can carry out basic commands such as making to-do lists, playing music and tracking flights. Google has been testing self-driving cars and hopes to bring them to the public within the next four years.
It’s true that some sectors may experience a slowdown in hiring as AI handles specific parts of jobs, freeing up workers to focus on other tasks. Financial advisers and insurance agents have already teamed up with AI programs that, respectively, make recommendations for portfolio management and monitor for insurance fraud. This efficiency may mean that new job applicants will be turned away as the number of people required to staff a business declines.
But history shows that employment usually recovers after a technological revolution — though the directions it can take may be unexpected. There is a lot of debate over how much disruption the AI Revolution will bring, but I am optimistic that new jobs will replace the old ones in areas we can’t even imagine yet, just as the working world evolved after the Industrial Revolution. We don’t blame the steam engine or tractors or sewing machines for unemployment now.
AI has already created new opportunities. Consider a service like Magic, an SMS-based delivery startup that serves customers anywhere in the U.S. Magic’s idea is that a user can get anything delivered on demand by text message, through the coordinated efforts of humans and AI. In China, similar startups employ hundreds of customer service staffers to cater to callers’ various needs — though it’s possible that digital assistants may one day take over from “manual intelligence.”
Many people may decide to return to school to gain new skills in these emerging fields. We may also see a surge of interest in jobs that require a broad range of abilities and human intuition, such as nursing, child care and sales. While massive open online courses like those offered on the platform I founded have already helped millions of people around the world to educate themselves, we can expect that working professionals will more routinely pursue further training as they try to stay ahead of the competition.
It seems likely that developed countries will undergo the most disruptive changes — in some economies, the service sector accounts for over 70% of gross domestic product. In developing countries, the impact on white-collar workers is unlikely to be immediate, due to slower adoption of AI technology, though such regions may experience a decline in outsourced manufacturing jobs with further advances in robotics. This sounds worrisome only because we can’t anticipate the new jobs that these technologies will bring and the new businesses that people will devise, as they always have. The future’s still bright, thanks to our creativity — our unique trait.
In July, an open letter from more than 1,000 AI and robotics researchers and other prominent figures — Elon Musk, Stephen Hawking and Steve Wozniak among them — warned against using AI in warfare and called for a ban on autonomous weapons. Even that technology is not as advanced as the sentient robots envisioned in the 2015 movies “Ex Machina” or “Chappie.” These movies imagine “strong” AI, or AI that is generalized, and able to carry out most human activities, as opposed to “weak” or narrow AI, which is task-specific. No one can say whether strong AI will be created, and if so, when. I asked some Chinese AI scientists about it, and given their responses, I may as well have been asking about the possibility of alien life.
That would be a world in which perhaps even child care jobs are threatened, but thank goodness we have many years before the dawn of strong AI-directed robots. In that future, we may not need to work very hard to support ourselves. The robots will be doing most of the labor, while we will have the time and leisure to explore what it is to be human.
(sk)
Eric E. Schmidt の文章と、姬十三（嵇晓华）の文章を読んだだけで、大げさに言えば、アメリカの文化と中国の文化の違いが見えてくる。アメリカ人と中国人の違いと言っていいのかもしれない。
「正しい」「正しくない」「良い」「悪い」というような「白黒はっきりつけたがる」アメリカ人と、実際的で実利的な中国人。
どちらがいいとか悪いとかでなく（と考える時点で、もうすでに私はアメリカ人ではない）、アメリカ人がアメリカ人らしく振舞い、中国人が中国人らしく振舞えば、もうその時点でコミュニケーションは成り立っていない。
お互いを理解しろと言ったところで、お互いのベースが違うのだから、理解しようがない。
発展途上国の人だけでなく、先進国にも、Eric E. Schmidt の文章に反感を持つ人は多い。でも、姬十三の文章に反感を持つ人は、たぶん一人もいないだろう。
19世紀はイギリスの世紀、20世紀がアメリカの世紀、21世紀が中国の世紀ということを言う人がいるけれど、ことはそれほど単純ではない。
それでも、もし個人の時代がくるのだとしたら、中国人のほうに分があるのかもしれない。