From Discovery to Implementation
Interview with Dr. Kai-Fu Lee, Chairman & CEO, Sinovation Ventures – President, Sinovation Ventures AI Institute
Where do you think the next big AI technologies will be developed and in which fields?
I personally think that making all the known technologies really honed to fit actual applications will be the largest social contribution to humanity. If you look at the history of speech recognition or computer operating systems, or the notion of the Internet, there’s an age of discovery followed by an extended age of implementation. They were experimental in laboratory conditions and not yet applied in industry. Which are the early adopters? Which ones are the momentum drivers? Which are mainstream usages? Fixing and tweaking technologies so they can be applicable – that will be the most important thing.
From the moment Internet was discovered until it changed the world was a good 20 years. AI will maybe take a bit less time but it will take maybe 10, 20 years or more to penetrate every corner and every application.
Kai-Fu Lee
It’s kind of a self-limiting question to look for the next breakthrough. People didn’t ask: what is the next operating system breakthrough? There were some obviously. 3G, 4G and 5G made a big difference to penetration and fitting everything in the phone made a big difference to the OS – those are the kinds of things that will happen to AI. There will be so much money and so many people working on that problem.
The next possible big breakthrough could come from the combination of brain sciences and AI – capturing something about our logical and illogical thinking, or from quantum computing or hardware, or semantics or language understanding. Each of the three has a 5 percent to 20 percent chance of making a big difference.
In the next five years, probably Internet and financial and e-commerce are the biggest industries that will be affected, where there are immediate transactions of money. After that we will see an impact on areas such as retail, healthcare, manufacturing, education, transportation and automotive and logistics including warehousing/transportation/delivery. Eventually AI will penetrate everything.
You talk about the role data is playing in fueling AI development, but different countries have different regimes. What impact will that have on the way AI develops?
Eventually every country will have different data laws. China has strong data laws not with respect to individual privacy but with respect to companies that sell and use data without user consent, such as in the Facebook and Cambridge Analytica case which would have been punished by imprisonment. The EU has GDPR and the US is figuring something out. We are in uncharted waters in figuring out how to deal with individual data management and privacy and what is legal and what is not. I doubt there is one answer for every country, given the different cultures and user expectations in the East and West. Instead I think we are at the beginning of a crowdsourcing project. GDPR is one of the first most visible efforts. I don’t think it’s a very good design but I think we will tweak it. Maybe we will have three sets of data laws – EU, China and US – and there will be some commonalities but also differences.
What are the shortfalls of the GDPR at the moment?
The government is playing the role of product manager. It’s doing the brute force – let’s give every user the choice of every permutation for every website, so the responsibilities are shifted back to the users. These pop-up windows keep coming up, people get sick and tired and just click yes. A very tiny percentage of people will click ‘no’ a lot and miss out on the convenience while a large number of people will just get annoyed with the pop-up windows. It's a pretty poor user experience.
Is there a risk of a race to the bottom, where countries compete to have the least effective data privacy?
More data collection involves the highest risk of damaging individual privacy, which will then damage corporations and that will force countries to have stricter laws. It’s like capital punishment: you could argue that countries with the strictest laws have the least crime, but there are side effects of that. I’m not an expert in policy and governance, so I can only point out the possible benefits and downsides.
Do you think attitudes to IP rights vary in different parts of the world?
Overall AI is not very heavily patented because the originators of the discovery of deep learning didn’t patent it. It’s unclear whether each permutation warrants a patent. There are some patents held by AI giants. Judging by how much the algorithms are proliferating, I would guess there are not many extremely strong patents that could be enforced at this time, such as the voicemail patents or some of the encryption security patents.
We encourage our portfolio companies to file patents but only when they have something valuable. Theoretically if a company has a paramount advantage in IP, that is absolutely something we would consider as part of the investment and business strategy process – but it’s all theoretical. We have never invested in a company purely based on the strength of a patent. If you have something defensible and get sued, you can use it to defend yourself. These are nice to have. In no case have patents been the number one consideration. Again, we look at founders' and companies' critical abilities to implement technologies into products and business, beyond inventing them.
Are there any other areas in the world that you think will emerge in AI in coming years?
In terms of research, I think in Canada there is extraordinary talent and there are several other fairly strong countries. Hong Kong and Singapore are decent. But in terms of implementation, none of these countries have an ecosystem to turn the expertise into economic advantage. You need a strong venture capital ecosystem to drive the technologies to the right application areas and relentlessly focus on user needs and use that to push the scientists to improve the technologies. Outside the U.S. and China there are no countries with such ecosystems. Israel to some extent has them but I don’t think many countries are aware of that. They are focused on technologies targeting their own industries and that is where they go wrong.