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Reimagining the Future of Business and Tech

The CEO of Sinovation Ventures shares his thinking and predictions on AI’s potential applications, its social impact, and the regulations required to tame it.

AI will play an increasingly important role in business and society. At the same time, human capabilities like imagination and empathy will be also become more important — to uncover new paths to growth and to connect and build trust with others. AI expert Kaifu Lee, author of “AI 2041”, and Martin Reeves, Chairman of the BCG Henderson Institute and author of “The Imagination Machine”, discuss how these two very different sets of forces will reshape business.

Thank you Kai-Fu for joining me today to share your perspectives on the intersection of human cognition and artificial intelligence. To start: Your book AI 2041 is about the wide-ranging implications of technology. How will artificial intelligence technologies shape the future of business?

AI will be a ubiquitous and omni-use technology that will bring dramatic changes to industries such as transportation, manufacturing, healthcare, retail — almost every imaginable industry. The technology behind AI is a set of algorithms that takes data and makes decisions, predictions and classifications in ways that previously required human intelligence. If companies don’t embrace AI quite simply they will be left behind.

You make the case in AI 2041 that there’s an inevitability to the ubiquity of such technologies. You point out that we are dealing here not with new technologies but rather with ones that are already fully functional today. On the other hand, we’ve heard this before with technologies such as blockchain — whose prospects now seem to have been exaggerated, at least from today’s perspective. What do you base this belief on?

The most likely impact in the near term will be from extrapolations of Robotic Process Automation (RPA) and Natural Language Processing (NLP) technologies. Effectively, that means taking the workflow in your company and installing software to execute many elements more effectively.

So, for example, if you have an HR department, AI could start by using Natural Language Processing to help you sort candidates, propose the right candidates, or provide better matches for review. If that works well, it could directly send emails to these candidates and arrange interviews that can be scheduled without human intervention. Going further, it could potentially conduct salary negotiations, make offers, or triage between interviewers and their comments and try to find the right kind of offer for each candidate.

And when that starts to show promise, you are likely to replace some of the people — maybe even most of the people — in your recruiting department. You might then start thinking about how to use AI for new employee orientations or for tracking employee performance. You might consider how it can help employee training or self-enrichment, and very soon you would see the value of AI within HR — you’re getting more value at lower cost.

Then you might say “perhaps I should use this in the finance department.” And you will immediately see how tasks like expense reports or audit alerts — many of the things that entry-level accountants are often asked to do — can be automated. Then, you’re going to move to the legal department, the marketing department and then customer service — and you’ll see that AI can answer most of the phone calls or reply to most of the emails. And it will actually lead to not only equivalent or greater customer satisfaction and a comparable resolution rate, but also that it can intelligently try to upsell your products at the end of each customer service case.

This would go on and on. I think companies that start to use AI will reap the rewards and will experience this type of snowball effect that will build their company’s overall knowledge, connect their data together, service their customers better and save them money. Of course, this will lead ultimately to a displacement of a certain percentage of routine workers’ jobs.

Let’s explore that. A couple of questions arise from your example of the HR department and the snowball effect. You seem to imply that much of what we might call management today is routine, in the sense that it is substitutable by AI. How much of what we call management today will eventually be inevitably substituted?

I think some of it is management, but a lot of it is workers who are basically doing routine tasks. I don’t think every job will be fully automated, but I think that a percentage of each job will be automated. And so when you look at a corporation in aggregate, this will add up to substantial numbers.

There are also cases where it goes beyond just replacing the routine and can help you gain a competitive edge. If we go back to the recruiting example, there are companies that will do recruiting with an AI Avatar that will interview your candidates for you. Not to make the final interview decision, but as the initial screen. I think that is incredibly valuable, because often the initial screen will determine the overall quality of the entry-level or the campus hires that you are reviewing. With humans, you can only afford to screen so many candidates, but with AI there’s almost no marginal cost to screening more. You can screen 10 times more candidates and be assured of a greater pool that will further be interviewed by humans, so the process doesn’t change — you just get a better pipeline coming in.

Another example is in the financial sector. If you give out loans, you can improve your margins by having AI determine who is likely to default and who is likely to pay you back. If you’re in insurance, AI can help you determine how to construct a better insurance product.

And the list goes on and on — it’s not just about job displacement but also helping you to improve your competitiveness in many key aspects of your business.

You mentioned building competitive advantage through AI. A lot of the algorithms for AI are open-source, and one could take the view that if this is something that we can all use, AI will merely raise the minimum standard for efficiency in business, but not necessarily build advantage. Is there is a sustainable, competitive advantage in these applications? And if so, where does the advantage come from?

That’s a great question Martin. I’ll give my answer in two parts.

I think that, first, there is arguably not that much competitive advantage in the actual technologies themselves. However, most traditional businesses are not really thinking deeply about what AI can do for the business, partly because it sounds like science fiction to them and partly because people don’t know where to start. And I think this will continue for a while. Think about the time when people were about to embrace the Internet, and people didn’t know whether to embrace it and how it fitted it into their company. But now, almost every company relies on the Internet and if you didn’t you wouldn’t be around today.

The point is that although AI is open-source, in traditional businesses the adoption is still in the single digits. So if you try to find the right place to start incorporating AI, I do think you will have a competitive advantage, not because the technology is so hard to build but because your competitors are probably not thinking about it yet.

Secondly, to do this right it’s important to either hire someone really good to your company or appoint someone to serve as the acting chief AI officer, if you will. Perhaps you want to have someone like BCG as your partner to build this, or perhaps you will want to find a private company to partner with you. But it’s incredibly important that you find the right first applications for AI, because we’ve seen about as many failures as successes in its implementation. And the failures usually result from the CEO having either too optimistic or naive view of what AI is: perhaps they didn’t realize the cost and the resource requirements to get the data together, or they picked the wrong area to apply AI. So if you haven’t already, I think it’s really important that you find the right partner or hire someone good to get started. If you don’t, I think there’s a good chance you’ll be disappointed — not because AI doesn’t work, but maybe you applied it to the wrong area or need to reset your expectations.

Let’s talk about another dimension of competitive advantage or disadvantage, which is digitally native vs non-digitally native companies. Is it really a level playing field between the two?

Let’s say, for the moment, that we drop the perfect management team into a traditional business to disrupt it with AI. Hypothetically, in 99 cases out of 100, the traditional company will win because they’ve already established the workflow, the process, the supply chain, the customer relationships, and most importantly — the data.

For AI to work, data is critical. Having the data gives you a huge advantage. You’ve already got the customers using your products, and it’s as a matter of capturing their data and securing your advantage by using AI the right way. That means that traditional, established companies should be the de facto winners.

However, in reality, traditional companies are often run by people who may not understand AI, may not get the right help, might be too optimistic or too pessimistic. That will actually open up opportunities for new digitally native startups to compete.

So if they take what I say seriously, traditional companies will realize that it’s their game to lose. They must become digitally capable, get the data, and use it to build business intelligence and artificial intelligence. The barrier of entry for AI start-ups is just hiring a bunch of smart, AI PhDs — but traditional companies can do that too.

That’s a really good answer. Now, we’ve talked about the substitution factor — what can AI do better than humans. But, of course, there’s the flip side to that question, which is the focus of my book: what can humans do better than AI? In my view, the differential value of human cognition increases in areas like imagination, ethics, or purpose. What is your view on how we can migrate human cognition to more uniquely human tasks in the corporation of 2041?

If we think 20 years out, most of the routine tasks currently executed by humans will have been replaced by AI, so people will have to migrate to things AI cannot do or to new opportunities that AI will create.

I think what AI cannot do falls in the areas that you talked about — creativity, thinking across dimensions, thinking outside of the box. That’s one category that we can call creativity or imagination.

The other category is human-to-human touch. That’s something AI can emulate, but cannot do well. People really don’t want to trust an AI to be their psychiatrists, for example, or their healthcare professionals. I think there’ll be a huge number of job opportunities where human-to-human interaction is required or where the job is to build human-to-human trust. I think that for at least 20 years, if not longer, that will still be a role that humans will hold.

Of course, there will be many professional jobs that will benefit from AI tools, so there will be an upgrading and redefinition of the job of a lawyer, accountant, doctor or scientist. Humans will find their new roles by working symbiotically — doing what people can do that AI cannot, while leveraging AI as a tool.

I also think there will be many jobs that AI will create. Although I can’t enumerate all of them, I can say that there will certainly be robot repair people, autonomous vehicle repair people, robotics scientists, AI researchers, data scientists or individuals who collect data. AI is all about data, so that’s one category of roles I can predict, but I do think there will be many more that are hard to predict today but that will certainly emerge.

So humans will have to figure out how to work with AI — to build what we’ve called a “bionic organization”. So we will have to think about questions like what will humans will do, what will the machines do, what will the machines help the humans do, what will the humans help the machines do, how will the interfaces between the two work and so on. What’s your vision of what your children will mean by the word “organization” in 2041?

Wow, that’s a very tough one to predict. In my book, I don’t go into corporate leadership and management, but some things I know for sure are that more corporations will be managing the businesses with data, and by predictions and “what ifs.”

Today, a lot of that work is being done by people. I imagine that at the top of the corporation there will still be the same people who will have proven themselves to be true leaders. The CEOs who have demonstrated their leadership, compassion, strategy abilities, communication skills and so on will still be leaders of organizations in 2041.

What will be different is that some of the jobs that you delegate to your direct reports will be done by AI. For example, if you want to know what your strategy should be and what stocks you should buy if the trade war between US and China escalates, AI will do that for you. Or if you have any exposures and vulnerabilities in your portfolio if the Panama Canal is clogged for another week, or if you should rethink your logistics or talent strategy if elections are won by such-and-such person next year — these are questions that you ask your staff today, but by 2041 many of them will be addressable with AI. AI won’t be just pretty pictures or three-dimensional graphs that your staff prepares to show you, rather it will go one step further and do the analysis, assess the pros and cons, and show you the most cogent answer — which will be, in general, more comprehensive and valuable to help you make the right decisions.

Kai-Fu, thank you so much for spending time with me discussing your perspective on the future of AI and on the intersection between AI and human capabilities.

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