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This book starts off pretty well. There is a short history of China's rise in technology under the shadow of the United States' dominance. There is a broader comparison between the two countries, their political climates, and their differing tech cultures. There is a quick lesson on neural networks and deep learning, as well as analysis on what sectors artificial intelligence have had and might have a significant impact on. However, the author takes an unexpected turn towards his reflection on his life and career after being diagnosed with cancer, how that changed his morality and priorities. He ends with a prescription of how to use AI for good, and it's not a particularly convincing transition.
The author is incredibly bullish on artificial intelligence changing our lives for the better. And as the cover of this book might suggest, he is certainly of the opinion that China is or will be very soon the world leaders in AI. The author has every incentive to convince the reader why China is ripe for growth in AI, as he is the CEO of an investment firm in Chinese tech companies. Still, he is a leader in the field and uniquely qualified to compare the tech culture between China's startup world and Silicon Valley. Here, he does a good job matching up the AI superpowers.
He argues that job losses from AI advancement will come largely from industries getting replaced, rather than occupations or tasks getting replaced. Think news companies without editors, or grocery stories and their shopping experience without any humans on-site, putting pressure on existing companies which employ humans. Which industries? One consideration is that machines are good at pattern recognition (such as diagnosing cancer for a doctor), but still lag far behind humans in fine motor skills (such as cleaning for a hotel maid). Put another way, AI algorithms may hit white-collar workers and cognitive tasks first, whereas robotics are not far along yet to hit blue-collar workers and hands-on tasks as quickly. While this was an interesting aha moment for me, this does lead to his prediction that one day, all doctors will become "compassionate caregivers" while the algorithms run the diagnosis.
Speaking of compassion, his epiphany comes from facing his own mortality with lymphoma. It led the author to a monastery, which led him to reflect on his life as a workaholic, which led him to appreciate his family more. It was certainly a strange pivot in the middle of the book, but his conclusion after that just seems out of left field. He talks through universal basic income, and how to prevent AI from displacing many jobs: by focusing on (financially) incentivizing volunteer and human care work. The author provides at least a framework for thinking about how to encourage social work, even if the proposals aren't particularly convincing or fully formed.
While the last third of the book took a bit of a detour, there are good lessons to be had. This book ultimately provides a helpful framework for tech leaders on how to think about AI permeating our world, and about the future in the race between the US and China towards leveraging AI. It is worth the read for that alone, even if the book falls a bit flat in the end.
The author is incredibly bullish on artificial intelligence changing our lives for the better. And as the cover of this book might suggest, he is certainly of the opinion that China is or will be very soon the world leaders in AI. The author has every incentive to convince the reader why China is ripe for growth in AI, as he is the CEO of an investment firm in Chinese tech companies. Still, he is a leader in the field and uniquely qualified to compare the tech culture between China's startup world and Silicon Valley. Here, he does a good job matching up the AI superpowers.
He argues that job losses from AI advancement will come largely from industries getting replaced, rather than occupations or tasks getting replaced. Think news companies without editors, or grocery stories and their shopping experience without any humans on-site, putting pressure on existing companies which employ humans. Which industries? One consideration is that machines are good at pattern recognition (such as diagnosing cancer for a doctor), but still lag far behind humans in fine motor skills (such as cleaning for a hotel maid). Put another way, AI algorithms may hit white-collar workers and cognitive tasks first, whereas robotics are not far along yet to hit blue-collar workers and hands-on tasks as quickly. While this was an interesting aha moment for me, this does lead to his prediction that one day, all doctors will become "compassionate caregivers" while the algorithms run the diagnosis.
Speaking of compassion, his epiphany comes from facing his own mortality with lymphoma. It led the author to a monastery, which led him to reflect on his life as a workaholic, which led him to appreciate his family more. It was certainly a strange pivot in the middle of the book, but his conclusion after that just seems out of left field. He talks through universal basic income, and how to prevent AI from displacing many jobs: by focusing on (financially) incentivizing volunteer and human care work. The author provides at least a framework for thinking about how to encourage social work, even if the proposals aren't particularly convincing or fully formed.
While the last third of the book took a bit of a detour, there are good lessons to be had. This book ultimately provides a helpful framework for tech leaders on how to think about AI permeating our world, and about the future in the race between the US and China towards leveraging AI. It is worth the read for that alone, even if the book falls a bit flat in the end.