March 23, 2020

AI for evil. AI for good.

AI for evil. AI for good.

Is Artificial Intelligence all about robots? With Fox Professor Bertrand Guillotin, we try to unravel some layers of AI, dig deep into countries decoding it in their own way and find the emerging winner of this global race.

“The catalyst for AI is the race towards innovation leadership and the race to have the most productive country in the global economy.” -Bertrand Guillotin, Fox Department of Strategic Management

Artificial intelligence (AI) is based on the principle that machines, with the help of algorithms, can mimic human intelligence and will eventually develop superhuman capabilities to handle complex problems. 

Today, AI is everywhere. In our phones, our cars, even our fridges. Computers are designed to help us make decisions, be more productive and get more out of our lives. But is this a good thing?

In this episode of Catalyst, the podcast from the Fox School of Business, we sit down with subject matter expert Bertrand Guillotin, assistant professor of instruction in the Department of Strategic Management Bertrand shares his thoughts on how the global leaders in AI—from the U.S. to China—are showing the ways AI can improve our lives, from increasing safety in driving to using facial recognition to distribute toilet paper in public restrooms. 

What industries are adopting AI? What are consumers’ reactions? Should we be wary of AI or should we embrace it? Listen to this episode of Catalyst to find out. 

Catalyst is a podcast from Temple University’s Fox School of Business about the pivotal moments that shape business and the global economy. We interview experts and dig deep into today’s most pressing questions, such as: What is the future of work? Will the robots really take our jobs? And how is my company using my data? We explore these questions so you can spark change in your work. Episodes are timely, provocative and designed to help you solve today’s biggest challenges. Subscribe today.

Is Artificial Intelligence all about robots? With Fox Professor Bertrand Guillotin, we try to unravel some layers of AI, dig deep into countries decoding it in their own way and find the emerging winner of this global race.

Podcast Transcript

Host: Hi, Welcome to Catalyst, the podcast of Temple University’s Fox School of Business. I’m your host, Tiffany Sumner and today we will explore a concept that has created a lot of buzz around the world: artificial intelligence. A.I. is based on the principle that machines, with the help of algorithms, can mimic human intelligence and will eventually develop superhuman capabilities to handle complex problems. I interviewed subject matter expert Bertrand Guillotin of the Department of Strategic Management. He was kind enough to share his knowledge around the catalysts for A.I. Bertrand also shared his perspective on the sweeping changes in A.I. that often play under the radar of those of us [00:01:00] who are not deeply involved in cutting edge research. To get us started, it’s important to understand who the top players are in artificial intelligence. 

Bertrand Guillotin: That’s a great question and I actually would have expected Japan to be in the top players but they are not at this point due to many factors. Basically A.I. has a lot of potential but the implementation in the social aspect of A.I. in terms of creative destruction — you’re going to have jobs created but jobs destroyed. 

Japan is based on full long-term, if not lifelong, employment. Their culture is very group oriented, not individualistic so maybe it is slowing them down and daunting A.I. as much as I would have expected them to. What we do see China, which is more individualistic. We see the U.S. and some leading economies and countries in Europe taking the lead. So basically, China is number one in terms of spending [00:02:00] . Again, at the government level. And then basically you have the U.S. and then you have countries such as the U.K., Germany and so forth. 

Host: So, you say China is the world leader in A.I.?

Bertrand Guillotin: That’s correct. 

Host: And what are they doing differently to make them dominate this market?

Bertrand Guillotin: I think what they’re doing is using what I call a multi-pronged strategy. They are using all the angles, again the national pride. If we want to be the most modern, most respected country in the world, we have already blown records in terms of the growth of the economy for 30 years. We need to gain traction, innovation and productivity. So, when you don’t get the research of many of my colleagues, basically what makes a country rich — and China used to be rich a long time ago but they also suffered [00:03:00] through the last centuries and they don’t want to get back into those social turmoil situations where people don’t have enough to eat. So, the bottom line, there are 1.4 billion people by race so more than four times the size of the U.S. The bottom line is that, for them to be a rich country or to maintain the level of development, they have to innovate. To innovate they have to collaborate and so they have a lot at stake to prove to their partners that number one, they are going to respect intellectual property rights more than they have in the past. They will be leading the patent filings and they will basically be respected as regular players the same way players like Germany, Canada, the U.K. and France will be respected. Right so, you want to earn the respect and you want to show the world they can do it and so they are using the multi-pronged strategy, getting everybody fired up about it. Running experiments with KFC for example, [00:04:00] using facial recognition for people to place their order, making payments at all kinds of restaurants. This is a strange example but I am going to use it anyway; distributing toilet paper in public rest-rooms based on facial recognition with A.I. right? 

Host: That’s terrifying [laughs], I don’t even know what that means. Logistically how does that work? 

Bertrand Guillotin: I know but that’s now and some articles and I told you it was going to be a strange example so I– 

Host: No, it’s a great example. 

Bertrand Guillotin: But in other words, they are showing the applications, the usefulness right so, the usefulness, the improvements you can have in life. The improvements in productivity and everything will come once the growth has been basically across industries and across regions. So, I think they are using a lot of creativity to roll out their strategy where as of last year, it’s an official strategy [00:05:00] of the government of China to make it the world’s leading A.I. innovation center. 

So, they are putting billions toward new centers on innovation outside of Beijing. They are getting that sense of national pride and they are finding those patents. They are getting a lot of respect, as matter of fact within a year… I shared that example with you, the Chin brothers developed a super incredible microchip, that’s the best way I can describe it. In 2013, in terms of A.I. and deep learning that replaced the power of 16,000 microprocessors from google and their research lab on deep learning basically you can only imagine what has happened in the last 5 years. How fast it is going. How fast basically the world is developing A.I. learning, deep learning application so that we do increase productivity. [00:06:00] 

We’ll also increase safety, safety in driving. Imagine the trucking companies using A.I. and not having as many casualties on the highways. We are using A.I.’s, A.I. applications to do things that we don’t want to do or don’t like to do. Right? 

Host: Yeah, I think that’s a really — I’m really glad that you grounded this very quickly because when I think of A.I. I typically think of people building robots and them like taking over the world, right? Like so, it’s just funny to think how we are actually using this and when you hear and read some much about A.I. it’s also hard not to imagine it’s a little bit hyperbolic, it’s little bit hype versus reality so you’re giving some real world examples which I think are great and I’d love to hear more about what industries you think are embracing it well and specifically how consumers are reacting to this.

Bertrand Guillotin: So, I think you have to go case by case but in terms of industries [00:07:00] and adopting it… For example, Vanguard which is in our region and basically, they are doing a password verification based on your recorded voice. Right so, you call Vanguard and you say my voice is my password and basically, they log you in and you don’t punch the numbers in, you don’t use your social of course anymore. They are using A.I. to do this and it is used to direct you to a live agent, a live person very quickly if you need it. Right, so they don’t use those gimmicks anymore and people spend 20 minutes on the phone to get the service that they want and need really quick. 

McDonald’s is doing the same thing; they just acquired a company focused on A.I. and they are going to use A.I. around their drive through. Right so, maybe they’ll recognize you the same way Apple does [00:08:00] with their phones right. You look at your phone and same thing… your phone opens up or not. If I use my wife’s phone, it’s not going to work if I don’t know the digits for her password. 

Host: So, does that mean you can order McDonald’s or KFC, whatever the case through your phone?

Bertrand Guillotin: Exactly, or through facial recognition. A.I. basically is a form of animation so not too far off from the robots. The robots are now able to by away, perceive your feelings, your emotions. They’re learning almost with no direct supervision, which is scary. 

Host: I mean it depends like if it’s in relation to food, I’m ok with that [laughs]. 

Bertrand Guillotin: It will make your life easier because I could imagine you pulled in at KFC or McDonald’s, they’ll recognize you and say “Hi Tiffany” [00:09:00] in a happy voice. Whether or not this will happen before, the consistency of it happening is very rare actually right. When you look at the data, only Chick-fil-A has very consistent customer service and they basically go beyond expectations on being extremely courteous and so forth to their customers. 

A.I. produces that customer experience that’s positive, where you get the right order for your fast food, you’re on your way and maybe there’s actually something nice being said. Even if it’s an agent somewhere in the cloud, I think it will make a difference, it will simply find a lot of frustrations, and eliminate those frustrations. 

And also, it’ll be predictive. So, if you change the way you order or if you don’t come to the same fast food outlet, on the same days with the kids maybe they’ll pick up on that [00:10:00] and be like “oh, would you like a mini wrap today and a salad?” or you know, they are going to make the connections humans got tired of making because of the volume, also the low pay. 

Those jobs are not high paying jobs so if we enhance the experience, all the customer service-based companies, industries will benefit. Productivity will be higher; customer satisfaction will be higher and then the other candidates on the lists are basically the one associated with human error. When you think about human error in terms of driving, 90% of the accidents are by human error. If we could reduce that in half we would save millions of lives in the next 10 to 20 years. 

The investment in A.I. is definitely very easy to make in the business case for that adaption. And also, the human errors in terms of hospital treatments, the right diagnosis by the surgeon who’s [00:11:00] been already working 65 hours a week. Looking at your X-rays and making a mistake because he’s human or she’s human. A.I. would prevent that from happening. 

Host: I would have to ask, what does this mean for jobs?

Bertrand Guillotin: I think we would see a lot of jobs being created. People will be analyzing data that may have been computed by an artificial intelligence agent and they will see whether it makes sense or not. Whether or not we want to act on the data and the conclusion of the analysis right. And then we will see basically, industry by industry, if the cost benefit is there. 

If the social adoption is there, it’s clear to me that the last strike which was the record strike in terms of the union fighting for better benefits and so forth. They are also scared to death to not be needed anymore and they are basically transmission workers who [00:12:00] know their jobs are going to be eliminated with electric vehicles. 

Humans are social animals, we want to contribute, we want to be needed, we want to be in groups even if we care for our own destiny in an individual way, especially in the U.S. and China, as opposed to Japan but we do want to be needed and useful. A.I. is frightening people because it’s taking everything away all of a sudden. 

Host: Ok, so to rephrase… you’re saying people may do the jobs they have less but there will be different jobs for them to do?

Bertrand Guillotin: Correct.

Host: Which will require retraining?

Bertrand Guillotin : Yes, because basically we are going up the value chain, if I use that analogy in terms of we won’t– if you look at A.I., I think the purpose is to have humans doing jobs that are at the human brain level. We should also make sure people understand right now [00:13:00] the A.I. brain capacity is equivalent to the brain of a rat. It’s not sophisticated to say the least… yet, it is moving fast. Things are happening at the same time like never before in terms of algorithm techniques, computer power and data availability. That’s why it’s catching on like wildfire. 

So, if anything the purpose of A.I. is to improve productivity, people’s lives, increase safety. It’s A.I. for good. It would lift up the majority of the routine based boring and not so fulfilling jobs to a higher level of fulfillment and yes there will be retraining but it will be exciting and that’s why Germany has turned their fears into strengths. They are not pushing for A.I. to be adopted in manufactures because they know that it is a strength if you embrace it. 

Host: Right, well I think the fear obviously is lack of jobs or losing jobs [00:14:00] but I think there is also the fear of the unknown so that’s great that there is this democratic very moral and conscientious attention to using A.I. for good but it does beg the question “What are the treats?” and is there a military threat involved in this? And again, it sounds like I’m reading a lot of Sci-Fi but I think that this is a sort of fear that people have when thinking about A.I. not only will they be replaced but how can and will this technology be used against us? 

Bertrand Guillotin: I think the risks are real. Actually, there was a survey from Deloitte Consulting recently across seven different countries, close to 2,000 senior executives and line managers who are directly involved with A.I. across the seven countries — and actually in Europe especially, the fear that the risks are such that we could not address [00:15:00] them if they materialized. 

So, only basically in the U.S. and China, people are extremely optimistic but it’s a big unknown associated with the risk, military use, terrorist use. We already had a flavor of it when Saudi Arabia lost 50 percent of its oil supply due to some low level, cheap drones that basically puts some explosives between the two towers and the oil producing wells– very strategic spot to put it. It basically ground the production of Saudi Arabia almost to a halt right. 50 percent less production… Talk about an impact, this was amazing because it was A.I. remote-controlled weapons, lowcost weapons that by the way took down the multi-billion-dollar investment and high-tech stuff that basically Saudi Arabia had [00:16:00] bought from the U.S. to defend itself against those attacks. 

There was also proof that, yes A.I. and all those automation technologies, remote technologies can be used for evil. Hopefully it is an outlier, it’s not going to happen very often but the risks are there and some people think that if they do materialize or some of them do then we can’t address them. So, it’s like a chain reaction, that the reactor is still burning 30 plus years after. 

Host: Right, that’s scary. 

Bertrand Guillotin: it is scary, it’s hopefully not going to happen because that would be self-destructive, right. Based on that, the same thing, we see a cultural difference between how people embrace those risks. Again, China, the U.S. are very optimistic, even more so in China, people of the national rush, the excitement you know. 

This is the race we want to prove to the world that we are really cool, [00:17:00] innovative and so forth but it’s also — I think going back to that contrary, you know they don’t expect much in terms of data privacy and if anything compared to Saudi Arabia who is rich in oil. China is super rich in data which is one of the key ingredients for A.I. for them to win the race. Why? Because the government connects all the data. So, they do facial recognition on you, on me. If we were Chinese citizens, they would know exactly what we have been up to, if we have been good citizens or bad citizens 

Host : Mhm, opposed to the U.S. where industry, companies collect the data. Although we don’t know if they sell them to the government or not. 

Bertrand Guillotin: That’s right, and the distinction is extremely important. You make a very good point and I think sometimes we also feel that we can protect some of our data. Maybe it’s a myth, I don’t know but I think in China, the majority of people I know don’t even have that realistic expectation. [00:18:00] They know that it is not private for most of it and they live with it, they make the most of it. 

Host: So, the attitude as well as efficiency is helping China be number 1. 

Bertrand Guillotin: Correct, and again they have this resource that nobody has had before which is data. The super-rich data.

Host: It’s hard for me to believe that the U.S. doesn’t have a huge data set though. 

Bertrand Guillotin: Well, you know, the jury is out on this but just to share numbers, four times the size of population — so if you go with the scary example that the government is watching your every move. If the Chinese government has data collected on four times more people’s every move and there is no separation between private and public life, so to speak, of private and public data. 

It’s exponential, you’re right. We are not data poor, to say the least we have a real chance in that race but I think we need a digital strategy in this [00:19:00] country and I am not the one just advocating for it. The former CEO of Sysco, John Chambers has made it very clear to the press and so forth at conferences so we are the only developed country without a digital strategy. 

Host: It would seem to me that our data set is probably fairly fragmented. 

Bertrand Guillotin: It is, I’m sure it is. Yes, and you see that when our different intelligence agencies are trying to work together right. Since 9/11, we have been trying to regroup some of the government agencies to basically use those fragmented data set or whatever it is for, national security or any other topic. You’re exactly right, look at the health care system. It’s the same thing, there are so many errors in it because we don’t have basically one universal consistent system like other governments do. I’m not saying we should pay or not pay, that’s another debate for another day but [00:20:00] having a universal health care system with a representor on patient data right that protects cancer or disease information. All of that can be used for research for better experiments, we don’t have that you’re right so it’s fragmented so.

Host: Let’s talk about the U.S. So, we talked a lot about China. Tell me about artificial intelligence in the U.S.

Bertrand Guillotin: So, in the U.S., we love artificial intelligence especially on the West Coast. I think there is a divide there to be honest with you. Between the different regions, especially the manufacturing heritage base of the U.S. right. That’s not necessarily embracing A.I. There is definitely a silicone value story. It’s clear that Google is leading the race, Microsoft is leading the race in terms of investments but sadly if you look at the spending, it’s half of the budget of [00:21:00] Microsoft, Amazon and Google. 

So, in other words I don’t think we are going full thought on it, we are just like, you know… we are third gear right and then we’re like, “Oh, this is good, this is fun,” but I think we can go fourth, fifth gear and push it further. I feel that there is not that sense of urgency right so I think we are missing that. At least that is my perception on these costs. I’ve done some research on it, I do see some conferences gathering a lot of interests. I am not sure the adoption is there, to be honest with you, people are still waiting to see. 

The problem with strategy when you have big shifts, big disruptions like this since I teach it, I see the results basically. When you only put your toes in the water, you don’t go anywhere, you don’t learn how to swim, right? If we don’t go full in, all in on A.I. China, Germany, the U.K, France, somebody is basically going to take the lead [00:22:00]. We have to take the lead, we have to tell people that we are taking the lead and maybe we can work with China and take the lead and have two huge engines driving this process. 

I feel, again there is a lot of excitement but I am starting to feel that it’s lost in the debate. Nobody has this sense of urgency, at least I don’t see it, maybe I’m wrong. I do like quotes for example, from one of the leaders at Google who actually started the deep learning initiative, Andrew Ng and he says “A.I. is a new electricity” so if A.I. is a new electricity and what electricity did to our industry or revolution in this country 100 plus years ago. We should all be talking about it, we should be engaging in it, taking classes which by the way are free. 

I think to lose only time, you can take classes from Cornel, Stanford, MIT through Coursera, you only pay if you complete the class and you want a certificate [00:23:00] but you can learn how to use machine learning in everything you do and again I look at my direct environment whether it is research or practice. I don’t hear many people, maybe one of my colleagues, right as an exception, I am taking a class, I am going to use my learning to see if we can improve decision making. But I think it is months, or maybe years, away from getting traction because it is a very long process to learn how to program, building the apps and interfaces and test them out. So, more excitement would be great for the U.S. 

Host: Right, especially, I guess at the government level.

Bertrand Guillotin: Exactly! I think that is the beauty about the U.S. We have a very solid innovation ecosystem and we rely on private incentives actors and we don’t rely on the government [00:24:00] for innovation and that’s a great point that you’re making. But at this point I think, because China is doing it, we should be doing it. 

Host: Yeah, and how would that work in the U.S.? What’s the solve?

Bertrand Guillotin: So, I think again, it could be a multi-prong strategy. I don’t think that there’s anything wrong with imitating what’s been working in other countries whether it’s Germany, looking at the strengths of A.I. not the fears. Germany has taken people across the spectrum from the fear, the anger and so forth. Although those phases, when you have a big change happening with disruption. They’re focusing on the strengths of A.I. 

France is working, I think they are empowering people to figure out A.I. for good and I’m sure they are going to measure what people do with it and or supervise from a government standpoint. France is very good at keeping an eye on their people typically and they will see if anybody is going a little crazy with it and those experimentations. 

But then again China, doing a lot to basically get [00:25:00] everybody excited about it. The young generation, the older generation and putting money where the mouth is which is typically also going to agnite more private investment. I think we can copy and imitate what seems to be working overseas and then see what it does and maybe we can have another take on it as well. A very American take would be government state funding and then private funding. Maybe tax breaks on investments and so forth, who knows?

Host: I would like to thank Bertrand for joining me today and for sharing information about artificial intelligence. People seem to have a peripheral view of A.I. and that may mean that they feel resistant to it. It’s important to recognize that A.I. can also create jobs, help reduce human error, create productivity, and improve lives and isn’t [00:26:00] that the point of innovation? Maybe a bigger question is, is the word ready for such a symbiosis between humans and machines? I hope you’ll join us next time. Until then, I’m Tiffany Sumner and this is Catalyst.