The book carries huge credibility as it is written by a well-known AI expert, Kai Fu Lee. The book displays the complete command on the understanding of the AI ecosystem in China and the US. Kai Fu figured in the top 100 influential people of 2013.
A beautiful book tells the history of AI, its development in the US, and China. The book tells how China picked up the AI fever. Though China did not have any pioneering advantage, the approach it took, to climb the charts, cast its own universe and help the world too. The book contains various instances on how ruthless and ferocious the Chinese companies were in establishing their dominance in the local market.
The author states the difference between the AI ecosystem, and what gives benefit for China. Kai Fu also elaborates on the studies done on the effect of AI on the society, and how the society should be ready for bracing the impact sooner which will come much faster than the change due to industrial and the information technology revolution.
The book is a must-read for IT managers, so they know what aggression is and how revolutionary IT will work. Engineers from many countries should now pull up their socks and be creative. The administrators and strategy makers should also learn from this book on how China did it. Half-hearted measures will only leave half-baked results, which will be vulnerable for overpowering by any means.
While it’s all AI discussion, the author also says that AI can never substitute for love and care we humans can share with each other. We have to be considerate and society should use AI for improving the quality of life if used wisely.
I would also like to thank Tabish Akhlaq for recommending the book to me. The book is a great read and quite educating.
The author starts with the story of a Go game match between Ke Jie and AlphaGo in 2017. Though AlphaGo was spectacularly winning against the Go World Champion, the emotional journey of Ke Jie was startling the people. Emotionally attached to Chinese people for centuries, the machine playing the Go game, and displayed its practical power. This was the Sputnik moment for China. While the companies were working on AI and other routine stuff from the private players, the Chinese government woke up seeing the strength of AI in the practical world.
The Chinese central government issued comprehensive guidelines stating the benchmark for the progress by 2020 and 2025. It aimed to be a world’s center of global innovation by 2030. In 2017 itself, China surpassed the US in global funding of the AI projects. China’s share in AI projects was 48% of the total funding worldwide.
But why did even the victory of the blue gene computer in chess not be an eye opener for the Chinese government? The chinese government saw that there was only progress in the research areas of AI and less related to practice life.
Though AI started in 1950 itself, due to lack of computing power, the field remained as an object of research only. Marvin Minsky, John McCarthy, and Herbert Simon have been the stalwarts of AI during these years, but they did not hog the limelight as the AI was undergoing the “AI Winter” which ended in 1993.
Further, the author explains the 2 approaches to solve AI problems, rules, and neural-based approaches. Earlier it was a rules-based approach, and many scientists pitched for it. The reliability of the neural approach was less. Later as the computing power and the amount of data increased, the neural approach overpowered the rule-based approach. By the mid-2000s, Geoffery Hinton made a big technical breakthrough on how to train new layers on the neural networks. The technique showed its power in the 2012 Computer Vision Contest.
Now AI has moved from theory to implementation, from expertise to data. Deep-learning pushed the limits higher, with a lot of data (big data), computing power and AI educated workforce, the entrepreneurs now pulled up the sleeves to make practical applications.
China had more advantage, above all this, they got an AI friendly policy environment too. China had an advantage in terms of data as well. Being bigger and more populated than the US, it generated much more data that could be used by the AI companies around. But China had their disadvantage too. Piracy and copying ideas were one thing that anyone with power could do. So they had to build a defense around it. Other companies poach the employees or do something harmful to the business to steal the idea. These views resonate with the other article on my review of the book “The Hundred Years Marathon“.
Like a moat, the integration of the service with offline sources gave strength to the idea. China exceeded it. WeChat is one big example. Anyone in China could literally do anything and everything with WeChat. Apart from chatting, pay someone, book appointments with a doctor, buy tickets, file tax, organize parties, and whatnot can you think of.
Chinese used this app and weChat got the data, and data is about all the aspects of the person. So this itself was a big gold-mine. Chinese were not too concerned about privacy and they were fine with getting more convenience at the cost of some privacy.
PwC estimates that the AI revolution will add $21 Trillion to the global GDP by 2030, of which $7 Trillion will go to China and $ 3.5 Trillion to the US. This is expected to give a soft-jolt to the US and will be perceived as a tilt of (soft) power.
The author says that the AI revolution will lead to huge job losses. Many professions will completely vanish. Accountants, Doctors, paralegals, truckers, and whatnot. This change will not take the time that the Industrial revolution took in changing professions, but much faster. What percentage of people will be changing jobs are debatable and there are various schools of thought in this regard. The author will be discussing them in the subsequent chapters.
The author further states that as we move forward, we have to change the way we work and new professions will come up. As we adjust with the new time, mankind will adjust and thrive forward.
The author discusses that many Chinese entrepreneurs tried to mimic the success of the west (the US to be specific) by copying the existing applications. They failed many times but ultimately succeeded in a few. Friendster copy in China failed, while Facebook copy, Xiaonei succeeded. It became Renren further. Many companies tried to copy Groupon, but one 1 gained steam and that was Meituan. Over time it beat more than 5000 companies and had a valuation of $30 Billion. There was one name that cracked all this code, and it was Wang Xing.
The key to success in the Chinese market was that who is leaner, meaner, nimbler, and faster. Who can launch campaigns, cut down the price to the bones, force users to switch the loyalties, and even get the other party in some or the other problem? Few even went to the extent of getting the CEOs arrested.
The author explains the difference between the thought process of the Silicon valley and the Chinese ecosystem. While the Silicon valley folks focus more on a mission, innovation, and a sense of achievement (pushed by the ecosystem), which drives them, the Chinese are more driven from the market sense. They look forward to reaping money out of it. Parents in Chinese ecosystem followed conservative approach. They look forward to financial safety and a stable life for their children.
The chinese ecosystem looked at copying as a base start and further looked to mastery of that system. Scarcity dictated the prices of the service. No one was willing to spend, until there was a service at a bare minimum cost. A service that would be required for all. The price would state the loyalty of the service.
This copycat approach not only fueled innovation, but it also generated entrepreneurs, and gave silicon valley the same approach. Facebook is seen to be the most Chinese company in the silicon valley, as they never hesitated to copy any good feature floated by some other company. Social ostracism (exclusion from a society or group), antimonopoly investigations, and costly lawsuits did not stop chinese entrepreneurs. Infact absence of these from the chinese ecosystem, gave them the courage to strike back with a bigger blow and proceed with their improvement sprees with the power of money and conviction.
In one of the examples, Tencent and Qihoo 360 locked horns in a dirty battle to catch each other’s users by aggressive strategies. Qihoo got its antivirus also installed when its browser was installed on a machine. Further, it prompted a warning as soon as the Tencent site or product opened. Tencent even tried to get Qihoo CEO Zhou Hongyi arrested. But Zhou also evaded arrest by running away to Hong Kong. Tencent also took various dirty tricks to make the users choose between Qihoo and Tencent. The battle was so intense that the Government had to intervene for the ceasefire.
It was not that China has always been seen as a copycat country. The author being in a senior position in Google China, took Europeans and Americans on tours showing the authenticity of Chinese culture. One of them was watch making in Canton province. It was one of the most complex arts which flourished there. European tradesmen motivated the same when they brought their clocks in Chinese markets.
The concept of copying the concepts received a mixed response in Chinese market. Few concepts succeeded without issues, while others fell flat. Copy of Disneyland succeeded, while the copy of Google interface and other sites fell flat.
Throes – a hard or painful struggle. Example – the throes of revolutionary social change; throes of childbirth. The word throes are used in a context that the Chinese ecosystem underwent throes when the internet entered China. From 0.2 percent in 1998 to current levels. While the US had a 30 percent population with the internet at the same time.
The chinese market also had different dynamics. This was not clear to the westerners. The author stated the example of a fight between Alibaba and eBay, Google and Baidu. eBay while charged for listing the products, Alibaba charged only for promoting them. Google chose to remain on the same window when a user clicks on a link, Baidu users got the link open in the new window keeping the search result intact. These sorts of cultural differences led to frustration in the Chinese workforce in the companies of the west and forced them to leave. This was also an opportunity for them to start new ventures like the author did. There are many other examples where companies tried to kick out the other using any tactics, without the fear of law.
The aggressiveness was so high that when the author started his company sinovation in the bay area and wanted some work to be delivered over the weekend, the vendor clearly refused to be treated as a Chinese company.
Furthermore, the author states that the AI revolution will be further fueled by the entrepreneurs (new industry), data (New oil), and research and development in AI (the new electricity). He hopes to see that China generates and uses this new petroleum in the coming age.
In this chapter the author states that China’s Internet ecosystem grew rapidly and took its own unique characteristics.
Starting in 2010, in NorthWest of Beijing an area called Zhongguancun (“jong-gwan-soon”), developed as a technology area. All the startups wanted to be there. A Chinese government official Guo Hong incepted and promoted it. It contained all that was needed for a startup to run. Offices of the investors, designing, hardware & software companies that would complement each other. The government also supported as the startups would get subsidy in the rent and in many cases even the funding.
Guo’s mission spread to other cities in China. They were given the goal of “Mass Entrepreneurship and Mass Innovation”. The city mayors had to promote the same and get more and more companies in the same. Under this scheme, more than 6600 startups sprouted all over the country. Funding to these startups went up from $ 7 to $ 27 billion between 2013 to 2015. The startups which flourished did not have more than 10 percent government equity. That also could be bought over by the owners of the company when it is in a good position.
The author’s Sinovation also benefited from it. It got subsidies in rent as well as contacts to invest in 9 such startups which were subsequently acquired by 3 top Chinese giants, Tencent, Baidu, and Alibaba. Earlier the author had to convince good people to join the company, while later people were desperate to join it. The author also states bizarre incidents in this context.
Further on, Chinese companies want to be innovative at scale. The author takes the example of WeChat. This slowly developed as a swiss knife for the users. It could order food, book doctor’s appointments, book flights, trains, transfer money to a friend, call a utility guy for work at home, chat with friends, make groups, crack business deals, and many more. It had few features much before WhatsApp could release them. And not least, all these in Chinese characters. It was a world in itself. Imagine the amount of data mined when a person uses WeChat. Chinese were fine with a bit of privacy compromise for some convenience.
This revolution was very drastic in the country. Most of the startups promoted the O2O (Online to Offline) concept. Food delivery is one such example. By 2016, there were 20 million online food orders across the country, i.e. 10 times more than that of the US. Most of the stores went cashless. Even the thieves cribbed that there is no cash left in the cities. The Chinese spent over $17 trillion in cashless mode. Using innovative schemes, Didi Chuxing kicked out Uber off the China market. Didi pumped up a lot of money in the ecosystem. Riders paid less, and drivers received more. Tujia gave a tough fight to AirBnB. Cleaner rooms and electronic locks gave Tujia much more priority over its competitors.
MoBike crossed all limits, 22 million rides a day. It provided 300 times more rides than the total bike rides in the US and 4 times the rides that Uber gives worldwide. Meituan acquired MoBike for $2.7 Billion in just 3 years. Using a smartphone, one can use Bluetooth, NFC, GPS, to use any bike around.
Government support to the startups gave a special boost to the AI initiatives and turned things around for China.
The author, himself being a data scientist narrates his experience of the interest he saw in the Chinese students in various spheres of life. He said that when he was in the Hefei University of Technology to give a lecture on AI, the hall filled up to an unbelievable extent and the students were sitting even near his feet on the stage to listen to him. They were vehemently noting down every aspect of his speech to extract the maximum benefit. When the author was walking to the university gate, the student followed him silently as if it was a fire drill.
He further narrates that the students caught hold of any AI book translated into Chinese. They studied on the streets as the dorm’s light got off at 11 PM. After all these struggles and hard work, the Chinese students are now in the mainstream of the AI industry.
There are 4 pillars of an AI superpower. They are abundant data, tenacious entrepreneurs, well trained AI scientists, and supportive government policies. With all this, Chinese students were at all the top companies like Google Microsoft, Facebook, Twitter, Baidu, Tencent, and Alibaba. They also were at all the competitions like resnet. Face++ won over all the top companies like Google, Facebook, and Microsoft to be the best Face and object detection software. They won all the top 3 slots leaving all 3 biggies behind.
Slowly the biggies realized that if they have to maintain a lead, they have to stop releasing the code in the open-source world. Now was the time for keeping knowledge “in House”.
These startups not only fueled consumerism but also aimed to improve public governance systems. Few startups made a complete system to monitor the traffic in the city, aimed to decongest and increase the traffic speed, check the accidents (and subsequently systems to get help on the spot). Alibabacloud has implemented this in 23 cities in China. Malaysia is also looking forward to implementing this in its cities.
The cloud concept further fuels it as the complete system is hosted at a central place. Any upgrade in the infrastructure will improve all the systems. AI is also centralized, so they do not need to focus on improving it individually. Alibaba, Google and Amazon also gain financially hosting such systems. In a similar manner, other domains like medical diagnosis, mortgage lending, education can gain from this sort of setups.
With the advent of smartphones, information is readily available in the hands of people. The Chinese government aims to increase power further. They have launched an initiative to make a chip consuming 20 times less power than the latest Nvidia chip. Horizon Robotics, BitMain, and Cambricon Technologies are flushed with money to achieve this objective. This will further fuel the IoT revolution.
Though Silicon valley remains the clear leader in AI initiatives and achievement, China aims to supersede it, and more due to political reasons. Both the US and China have given a special focus on AI initiatives after 2016. They sought its usage in public usage as well as for defense purposes. China launched the “Development Plan for a New Generation of Artificial Intelligence” which clearly outlines the details. One can see the expectations of the POTUS here.
China further aims to be one of the leaders in the AI world by 2020, and be an undisputed leader by 2030.
Furthermore, government support in both cases is important as there are many aspects of AI that need legal, ethical, and social brainstorming to fix the boundaries in public life. Use cases like self-driving cars, who will be fined if some issue happens. What should a car do, in case it has to decide on who has to die, a pedestrian, or the passenger? On the finance side, which startup should be funded and which should not be.
Implementation of AI has been a full time job for all the verticals of the society to get the maximum and right benefits. Society will take time for many regulations to evolve for the right results for all.
The author starts with a story of a brilliant Ph.D candidate, Liu Qingfeng who he wanted to hire as a Microsoft intern in 1999, but he turned down the offer. Liu went ahead to form a startup Iflytek. This company specialized in language translations. This company happens to translate the 60 languages on a fly from one to another seamlessly. It superseded many biggies like Nuance Technologies in the skill and is now the leading translation provided in the world.
Further the author sees that these sorts of applications will be helpful to international travellers, people interacting with different cultures and businesses, and unlock productivity & creativity.
The author further states that usefulness of these types of utilities take time. This is due to the fact that AI also has certain steps/waves. These are
The author states that China has done good in Internet AI, but has still a lot to do in business AI. While the US companies are using AI to improve the processes, in China non-IT companies are still to come to those levels.
As a part of internet AI, there are companies like Toutiao (a news feed platform), which records the clicks and understands your interests. It will show you the feed according to your interest, and even modify the headlines to make it more appealing/sensible. Toutiao recorded the usage of 74 minutes per user per day. AI made this possible for this platform to get this startling success.
Success of other internet companies like Alibaba, Baidu, Tencent also got advantage from the population in China. Number of internet users supersede total users combined in the US and Europe. This led to their multi-billion dollar valuation.
Further business AI is used to cover losses or change the strategy with the help of outlier data. Finding a correlation between behaviors are also some aspects that help a business decide many things. Behaviors and associated characteristics of the loan defaulters, people with some diseases, etc are few examples. Doctors, bankers, accountants, and many other professions will get help from this, as AI-powered software will give them the recommendations for doing the right thing.
While the US has IBM Watson as one of the forefront runners in business AI, Element AI and 4th Paradigm & iFlytek of Canada and China respectively working on serious business AI.
iFlytek even came up with the applications for the Justice department. It gathered all the data of the person in question, as well as the behavioral data of other people in the database to decide the possible course of action. It even ranked the Judges with their behaviour and their judgements. This also will help remove the racial bias which different societies experience.
Furthermore, in the 3rd wave or wave of perception AI, we expect to see AI work in the areas much closer to us. Face recognition, your refrigerator ordering items, opening your bank account on the mobile with your face, are just a few examples. Liveness algorithm is running on these devices.
So you may further see that you simply walk out of the departmental store, just showing your face, and the items get billed. You show your face at the restaurant and the bill is paid. The shopping cart may even act as your guide. I will remind you that you forgot to pick the tomato sauce as it is going to finish at home, guide you to the aisle to pick up nachos in the store. While you check out, it will remind you that it’s your wife’s birthday next week, so pick some wine as well as offer a discount on it.
The author coins the term OMO here. This is ONLINE-Merges-with-OFFLINE. The offline person gets help from the devices running these algorithms. The education sector is one the most lucrative sector for use of this concept. The camera in the class understands what exactly is the behavior of the kid. Is he interested, or not, or most of the kids bored due to the method of teaching, and whatnot one can think of. It can suggest corrective actions and thus tailor-make education as per the kid. VIPKid used the stated techniques and got a valuation of $3 billion in just 3 years.
Scope of OMO is unlimited. Traffic, home, office, kitchen, factories or anything else you can think of, can be benefitted from this sort of paradigm. Companies like Xiaomi (pronounced sheow-me), are working to reduce cost for everyone and build an ecosystem that everyone can take use of. They have set up their manufacturing in ShenZhen (Call in shun-jun), where other ancillary vendors are also located. Any change in idea is implemented very fast and effectively for all. Any vendor can come there, ask for the item and it can be customized as per his needs. Chinese government has also made it very easy for a person to get all the things done in a small area. No running around for visa, hardware/software vendors or other help.
Finally the fourth wave or the Autonomous AI comes into play. Self-driving cars are the best example. Robots in the factories are already making waves by reducing cost, increasing productivity, but also increasing unemployment. Autonomous AI aims to apply automation wherever machines can see, touch, and make sense of the activity, it will work accordingly. Many repetitive tasks can be automated using this, and can help many. Like old age people, handicapped, work in hazardous conditions, take up jobs repetitive for humans.
It can even take up a bit of complex tasks like picking strawberries. A California-based startup Traptic built a tractor that could pluck strawberries only which are ripe and ready between a sea of foliage.
Warehouses can be managed by just a few people with the help of similar robots. This is especially good in the places where people are difficult to find or labor rates are very high.
Drones are another example of autonomous AI. They have been useful in many spheres of life. Search and rescue operations, monitoring big or remote areas, carrying stuff to remote locations, and many other utilities. DJI leads the drone market worldwide.
In self-driving cars, most of the biggies like Google, Apple, Tesla, Uber in the US are putting in efforts to come out with a robust, cheaper and implementable. Data and AI plays an important part in it. More data, better trained the system is. Thus be more robust and be able to save more lives.
While the American companies took a conservative approach to take care of all the possible cases encountered while driving, Chinese companies took a more practical approach. They even thought to build a completely new ecosystem for the cars, while Americans wanted to make cars for the existing ecosystem. The new ecosystem with battery charging highways and other aspects also covered will make the self-driving car a reality. They believe in adjusting from both ends to come to a practical approach. As an example, the Chinese even went ahead and built a sample area 60 miles south of Beijing, Xiong’an, investing around $583 Billion. This city is built just keeping autonomous vehicles in mind. The way China is progressing, it is expected that they will leave the western countries behind. Companies like Baidu, Momenta, JingChi, and Pony.ai are catching up with the technology and data for this.
Still the challenge remains to map traffic situations in countries like India and Brazil, where pedestrians or cows can popup from anywhere on the streets. The companies who solve that problem will be the winners and be raking the maximum profits. This movement will also lead to political issues between the countries.
Further, the author states that there are 2 schools of thought with respect to AI. Utopian and dystopian. Mainly AI is expected to be AGI (Artificial General Intelligence), which will keep on adding data, and become omnipresent.
Utopians see that AI can be used for the benefit of mankind in all manners. Be it curing diseases, performing repetitive tasks, supporting people, increasing productivity, leaving more time for humans to live life, and not keep slogging only on work.
While the dystopian see this as though it fulfills the above points, but as the AI becomes stronger, they will overpower us. We will be their slaves. It is equivalent to summoning the demon. It may be available for whatever tasks, but it can also command and dictate us further. The biggest fear is the use of AI for military purposes. It will be killer drones or gun-trotting robots, which will reverse all the effects of the advantages the AI gives to humankind. Many fiction books are written, stating the gory picture of AI overpowering humans.
Utopians also believe that AI will never achieve the status of AGI, so expecting AI devices to overpower humans is bleak. The last revolutionary development in AI was that of Geoffrey Hinton on the Layered approach on Neural Network. Until any ground-breaking development happens further, it can take various forms but nothing very revolutionary can happen. It may happen that AI may not do so much harm, but humankind itself may turn against itself and be its own enemy.
Dystopias also see that AI will tear down the social fabric. It will increase the divide between the haves and have-nots. As the AI initiatives eat up the jobs, education will be no guarantee for a good life ahead. People into these initiatives will have so much money that they can buy all the comforts, while other people will not even have a source of income for availing such necessities.
This phenomenon was earlier seen when industrial textile looms came into existence. The British weavers revolted against it as it up to their livelihood. This was called the luddite fallacy or in simple words Technological Unemployment. It did happen that their immediate employment was affected but further as industrialization grew, the people benefitted from it, as better paying jobs were generated.
Even if we look to the past trends, when ATM machines came, all expected that the teller jobs were in danger. But inverse happened, the teller job went in danger but ATMs were established in remote areas of the country. Servicing the ATMs, and keeping the books in the banks led to rising in bank jobs. The jobs which get lost to automation will generate jobs that cannot be automated. This transition takes time as the mindset of the society needs to change for that.
The author has charted out the safe and dangerous territories in cognitive and physical labor areas. Here too there will be jobs that will get automated but can’t be completed in absence of human veneer (cover something with a decorative layer).
There have been many theories with respect to which jobs will be lost to automation. Various agencies have different outcomes of their studies. While the researchers Frey and Osborne from the University of Oxford states that 47% of the jobs will be lost to automation in a decade or two, the OECD states that it will be just 9 percent jobs that will be affected.
Why was such a huge difference in the study? OECD claims that automation will creep in but it cannot completely replace humans. Mckinsey says that already 50% of jobs are automated in some of the other manners, but that does not mean that person has to change the occupation. It may be that just 14% of people have to change occupations. Bains suggests that the affected percentage will be due to factors like demographics, automation, and inequality in society.
The author states that he expects fast food, security, financial services, and radiology will be the hardest hit professions. Still Moravec’s paradox states AI can do everything of the data, but it does not have sensitivity. It can’t understand a joke, play with a toddler.
The unemployment rendered due to this situation will bring in depression, a sense of worthlessness, and many more issues within the society. Still, that is not the end. The author says the personal values and connections can never be replaced by machines.
What does this mean for China? Automation will erode China’s edge, as the robots can work anywhere.
After a lot of work in the industry, one day the author feels uncomfortable. On medical diagnosis, the author is detected with the 4th stage of Lymphoma. Doctors state to him that you have a few months of life left in you. This was a sky falling down on him. Kai-Fu goes into a retrospective that how he was measuring his efficiency in life.
He felt that work took all his attention and personal life took a complete back seat. He only did a minimal effort to maintain the relationship with the people he loved. Even when his wife was going to give birth to their first kid, work was on priority in his mind. He had to give a presentation on speech recognition to John Sculley, CEO of Apple. Things turned in his favor, as the baby was born at the right time, and he could take care of the presentation as well. But this left guilt in him.
Detection of lymphoma forced him to take a back seat. He questions himself, is it worth giving so much priority to work? Waking up 2 times at night too to answer the emails from cross time zones, working 996 (9 AM to 9 PM, 6 days a week) was too much. He finally switched to 965.
As he thinks forward, even with all the recognition and accolades from the industry, what would be written on his tombstone? He remembers how his mother thought about him when he relocated to the US so that he remains connected with his motherland forever. It was so difficult for him to write his will, as he had never thought about it earlier. He realizes what should have been done, instead of what he does.
After a discussion with a friend, he decides to go to Fo Guang Shan Buddhist monastery in the south of Taiwan. He meets Master Hsing Yun, and in interaction with him, his ambition statement comes out bluntly, which is very embarrassing and completely materialistic. He realizes that since the family had been understanding, they adjusted with him as stated in the Kübler-Ross model. Further Master Hsing Yun advises Kai-Fu, that optimization and quantification are good, but overdoing it will strangulate one thing. That is Love. That can never be quantified and optimized.
Kai-Fu gets himself treated which has been a difficult process, where his family and doctors supported him a lot. Now, he discovers that what AI can’t do, humans can. That is to give selfless sharing love and care. He gives more time to family now. He travels with his wife, spends time with his kids.
The author states here that though AI will reduce the number of jobs, we have to do cultural, social and economic changes. While automation reduces jobs, it can be used for the advantage of mankind. Reduce, Retrain and Redistribute is the new way. Reduce the number of working hours. Retrain the people in new skills, so that they may take up additional work. Redistribute the work. As the work hours reduce, but it can increase the coverage of service. Let’s say instead of working 5 day a week, a person may work 3.5 days a week and give a job to an additional person, so that it increases employment.
Further, there are policy discussions on how to handle job losses. They can be compensated by GMI (Guaranteed Minimum Income) or earlier as the thought of, UBI (Universal Basic Income), but both of them have their own drawbacks in the long term.
Finally the author says that mankind needs to adjust and device ways to include AI within themselves to take maximum benefit from it.
Steve Jobs in his convocation address at Stanford said – “You can’t connect the dots looking forward,You can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future.”
This is true for AI also. We cannot precisely foresee what is in store for all of us in the future, but intent and conviction can lead us to use AI for the benefit of mankind.
The author retrospects what he chose and what he should have chosen while starting an AI career in 1983. While he chose to study the brain, he should have chosen the heart. His disease changed his complete perspective. What the AI can do, let it do and humans should not leave the aspect of love and care. This cannot be replaced by AI. It is either of the AI Superpowers China, silicon valley, or anyone, happiness and compassion have no substitute.
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