The Cross-Industry Value of AI

Joshua Jackson – AI Association

About this episode

In this episode, we speak with Joshua Jackson from the AI Association, a group of industry leaders advocating for the innovation and collaboration necessary to support the economic growth and leadership in the AI and Automation industry.

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Interview Transcript

Jordi Torras:
Welcome to The Future of Customer Service podcast, where we explore trends in Artificial Intelligence, customer service, customer interaction management.

Jordi Torras:
So we are really happy today to have Josh Jackson, who is a founding member of The AI Association. So Josh, how are you?

Josh Jackson:
I’m doing well, Jordi. Thanks for having me and excited to be here on The Future of Customer Service.

Jordi Torras:
Absolutely. Thank you. Thank you for being here. So the first thing that, of course, we would like to know is about you and about The AI Association. That sounds like a super exciting concept, so we want to know more about that.

Josh Jackson:
Yeah. Again, great to be here and it’s definitely one of those passion projects that we’re excited about in terms of business. I always like looking toward the future. What’s going to happen and where are things going to go? And how it started was really random. I come from a legal background, was working with some law professors and computer scientists on developing artificial intelligence in the RegTech & LegalTech space, and I went to a wedding. I think this is one of those ‘you never know what’s going to happen’. I was at a wedding, sat next to someone that happened to be working on a LegalTech artificial intelligence product, and we just started talking and next thing you know, he said, “Hey, we’ve been trying to find certain ways to collaborate with other folks. There’s no association that helps folks collaborate. I have this other buddy that’s building a fintech platform. So we said ‘Let’s start an association‘ literally right before the wedding.

Josh Jackson:
And we started brainstorming, we started putting stuff on paper, and next thing you know, we started having members. And one of our first members was part of the origination of Skynet back in 1984. So we thought about educating the government and developing this public policy around artificial intelligence. That was the birth of the AI Association.

Jordi Torras:
Wow. That’s fascinating. I’m not sure I quite get when was that happening. When did the association start operating?

Josh Jackson:
Yeah. So it was probably August/September of 2019. Then, we went to launch the association literally a week before we all went on lockdown. It was, I don’t know, the worst timing in the world, but we’re still at the forefront of government plans about automation and artificial intelligence, and we’re really starting to think about how technology plays a role in the economics of business, as well as the humanitarian role that it’s going to play across the globe and how the United States government, as well as the private-public partnership, are going to have a say in that arena?

Jordi Torras:
Absolutely. Maybe you can share some of the members of this association with the audience.

Josh Jackson:
Yeah. So I will say that some of the members come from big banks and legal teams in these big banks, as well as some of the RegTech companies, fintech companies, and consultants. Then we have some cybersecurity folks.

Josh Jackson:
One big piece around cybersecurity—and I think this is an interesting piece of it—is that we’re looking at the algorithms and embedding ransomware and malware within these algorithms. So it’s slowly starting to take over among the cybersecurity folks who say, “Hey, we want to start using this technology. How do we use the technology to protect our members and our businesses, and then start communicating with the government on that?

Jordi Torras:
Absolutely. Wow. That’s just great and it’s amazing how these two apparently very different worlds, which is lawyers and the law and the fintech … It looks like fintech is all about the numbers, so I’m assuming that when it comes to artificial intelligence, machine learning is about how we have all these gigantic mountains of data and we can get logic out of it. That’s the magic of machine learning.

Jordi Torras:
And then from the other hand, from a legal perspective, I believe that there is a lot in artificial intelligence about understanding language and being able to get the logic behind the words. As I said, I am not a lawyer so I have a lot of difficulties understanding legal terms, but it’s all about language, right?

Josh Jackson:
All about language, and I think it’s putting that context into play. I know we’ll talk about this with natural language processing, but there’s a lot of context that goes into language and it is the word that we’re associating. Does it have a particular meaning across the entire ecosystem and across the entire legal world? Is that the same within everyday public society language? And making a lot of those connections is hard. It’s difficult.

Josh Jackson:
I like to tell the story of a friend of mine. He has his Ph.D. in Semitic languages, and we talk a lot about pronunciation, tones, punctuation. There, you have a written word, but there’s no punctuation, so how do you start to distinguish what those mean? Here in the US, you put one comma in the wrong place it could cost you a million dollars. So it’s difficult, that’s the easy way of saying it.

Jordi Torras:
Yes, yes, absolutely. The field that teaches machines to understand the human language—or natural language, as we call it— is the space of natural language processing. It’s the capacity to take something that is inherently stupid, which is a computer, a big calculator with a lot of memory—that’s what it is at the end, at the core— and try to make it behave as if the computer could understand us, while making sense of our questions and answering questions in a way that we would. If we can pretend from all perspectives that software or a computer program is intelligent… Then, it’s intelligent.

Jordi Torras:
So what do you think…? There’s this status of natural language processing and the capacity for machines to understand the language. How do you see that from your perspective in the association?

Josh Jackson:
Yeah. I like using analogies or funny stories. Let’s take the things that we see on TV, i.e. we’ve all seen when Facebook was asked, “How do you make money? We don’t understand how you make money.” That is hard to fathom. So it’s breaking it down. It’s how simple can you break some of these things down.

Josh Jackson:
For us, we start from what’s data, and then how do we process that data? So this is the action to get to particular information. Normally when people say artificial intelligence, they just go straight from data to intelligence. The computer’s in the middle and then there’s the intelligence, but there’s a bunch of different steps. You probably know this better than I do actually. But once you get that information, then there’s that cognitive piece to create that knowledge.

Josh Jackson:
And I think we’re getting better at cognition, at developing computers to cognitively process the information and turn it into knowledge, but we’re really good at the next step of pattern recognition. So whatever knowledge is there, and a lot of times that’s where the input is, then the computer can make these models to then put them in output, and we say, “This is the understanding.” The really hard part is this inference. Taking the understanding of what output is and then creating that intelligent piece.

Josh Jackson:
So in terms of cognition, we still have a really hard time developing the computers to take that information and knowledge and then from the understanding to the intelligence, we have a really hard … Computers aren’t there for making that inference. So there’s a long way to go.

Jordi Torras:
There’s a long way to go and there’s also a long road already traveled. At the end of the day, the whole thing of natural language processing started in the ’60s and it was government-led funding, and the interest back then was to be able to translate, to massively translate, Russian into English. That was the whole thing because, hey, Cold War. So that was the national interest at that time. And the whole investments there were, basically, to be able to do that until somebody said, “Hey, it is impossible to translate without understanding.” And that was like a big backslash.

Jordi Torras:
But nowadays, there are pretty good translating tools out there we’re using all the time, especially if the domain is known and they work. I’m not sure if Google Translate actually understands what I’m saying, but translations are mostly all good enough, I would say. So I think that the whole purpose of artificial intelligence is making sure that it can do what humans can do only good enough so it takes boring stuff out of our plates, and we can work on other more interesting things.

Josh Jackson:
Yeah. I mean, I think that’s a great point. One thing, side note, is that I love that you brought history into it because the more you get into it, the more history you start to see come out and you get deeper into the history. And I’ll say from a social intelligence standpoint and going through this processing, the cognition piece, I really started digging into the social intelligence of the British rule in India in 1870. So even when you go that far back, you start to see how you have all this information, but it’s all coming at you in a decent centralized form, and now you have to start making this pattern recognition. Well, they were doing it then.

Josh Jackson:
And then you go even further back and to antiquity, way, way back, they were developing their own algorithms. So in 2,500 BCE, they had already developed algorithms. So it’s now just starting to catch up on these pieces. And now if you can compute at a faster rate then, hopefully, the program will continue to learn and develop, while hitting all those points, cognition and inference, as they are the two hard ones, and create intelligence.

Jordi Torras:
The word “algorithm” comes from Arabic, so it’s been there for a long time. Listen, that’s fascinating. And one of the areas that, of course, we, at Inbenta, are working in, but there’s a whole explosion now of vendors and technologies, is conversational AI. So it’s not only, “Okay, how can I translate the text or how can I have a search that is intelligent?“, but also how can we have software or a computer that is able to engage in an intelligent conversation?

Jordi Torras:
What is your vision of that from within the association? What members do you have? What are the learnings that you’ve been able to collect during this time?

Josh Jackson:
So you’re talking about the artificial intelligence conversing, not what the conversations have been like around artificial intelligence?

Jordi Torras:
Exactly. You know, chatbots, right?

Josh Jackson:
Yeah.

Jordi Torras:
Now the fancy name for chatbots is conversational AI, but it’s a chatbot, which is a name that was used, I think, for the first time in the ’70s or the ’80s. So it’s been a long time. There was ELIZA, the first intelligent chatbot, but how is that going along? What do you think?

Josh Jackson:
I mean, I think it’s getting there… I think the adoption hasn’t been huge. I think the market is right for it and that you guys are doing a great job going down that path because it’s a need. I still interact with a lot of them, we call them robocalls, where it’s … That’s how I look at a lot of it. It’s definitely been around the Turing test of, “Okay, well, this is clearly a robot. It’s not a person.

Josh Jackson:
But I had one the other day that got a lot closer. It was a robot, but it sounded better. I could still make the distinction between the two, but it was totally getting to the point of I’m having a conversation with someone next door. Now, what’s interesting that I think is missing, and I’ll actually do this on purpose, is use pauses and ums and hums just for the sake of saying, “This is a person and we are human beings that are imperfect.” And I think a lot of times with artificial intelligence, everything wants to be completely error-free, which takes out the human element of the imperfect.

Josh Jackson:
Does that make sense? I don’t even know if that answers your question, but that’s how I see it.

Jordi Torras:
I think it does. I think it does. And that relates to what, I believe, you said before. You were, “What is the word that I’m looking for?” And I can imagine a computer saying, “Dude, you have the fastest memory.” You have to find the word in milliseconds, if not, or nanoseconds. That’s great.

Jordi Torras:
We know you guys work with fintech and within the law space and many other areas. What are the areas your association covers when it comes to customer service and AI?

Josh Jackson:
We focus a lot on what the law looks like. In terms of customer service, we haven’t spent a lot of time on it, but I’ll use one example that gets us closer to the customer service and that goes back to the humanitarian aspect. And, for me, I mean, I like putting the two together: humans, humanitarian, customer service… All go hand in hand.

Josh Jackson:
We’re collaborating with Georgetown Law in some of their tech work. Before I got there, I’ve collaborated with some smaller institutions, as well as Emory. I’m an Emory alum. So Emory University is in Atlanta, Georgia. Some people don’t know that. I’ll put a plug out there for that. And then Carthage College, which is in Kenosha, Wisconsin, so a small liberal arts school. They have a big NASA contract. They have a wide reach around NASA. Georgetown Law is right down the street from the Capitol and that’s where a lot of these policymakers interact.

Josh Jackson:
And in terms of interaction with people, we’re really thinking about how artificial intelligence is being used in Afghanistan. And we’re thinking about … And this is big, but it’s a need. How is the Taliban using social media and technology to interact with people that they rule over? And I think the hard part for public policy is you have to think in law, you have to think about every aspect. So we go back to that convo, which is a million dollars.

Josh Jackson:
If we’re not having the conversation about customer service, then we’re, basically, getting rid of a huge part of the population that is going to be using artificial intelligence. It’s going to be interacting with previous laws of discrimination so you’ve got to think about discrimination. You have to think about privacy.

Josh Jackson:
So we’re looking at it right now as a narrow piece. And I use that loosely here, but a narrow aspect of artificial intelligence on, “Okay, it’s currently happening in this scenario and how is it being used to affect a particular group?” And once we learn more about that then I think, from an association standpoint, we can start having a broader conversation about customer service in general.

Jordi Torras:
Absolutely. Wow. That’s fascinating. And I indeed didn’t expect that to come to talk about the Taliban. So that’s amazing how everything, at the end of the day, is connected.

Jordi Torras:
So how do you see the future of artificial intelligence in particular and how the role of the association can be in it?

Josh Jackson:
So I see a really good future for artificial intelligence. We see businesses putting a lot of effort into it. Your business is one example of that. Governments are putting a lot of emphasis on it. So if you already look at history, the European Union is playing a huge role in how they think they can regulate artificial intelligence. They’ve done a great job at pushing forward with the GDPR. And now it’s just a stable. It’s something that everybody has to think about, from Canada to the US, all over the globe, on what that will look like.

Josh Jackson:
In terms of the US, you see that they’ve been thinking about it from the National Defense Authorization Act. You see it happening in the previous administration. With the Trump administration, they had an AI portion right within their office and now they’ve broadened it even more under this administration. So I think both administrations have started … And this goes back away now. They’re putting a lot of emphasis on artificial intelligence and they have their own ai.gov, where you can basically see what the federal government is thinking about in terms of artificial intelligence.

Josh Jackson:
They’re thinking about new ways of putting in more money and funding these initiatives and open data, “Can we give it to the private sector and let them use that to make better products, flourish the economy and create jobs? ” So that’s one aspect.

Josh Jackson:
The other aspect, I think, too, is what does the future workforce look like? We’ve seen the data through surveys and self-reporting of different groups, that they want to hire folks that have an understanding of artificial intelligence. This could be from the sales team to the customer service, to the programming team. If you know something about it, then you have a higher likelihood of getting a job, and having that career, because it’s just going to be a part of everyday life of interacting with computers, and then being able to communicate that to the rest of the team to fulfill the mission of the organization. So we see this happening in enterprises.

Josh Jackson:
And then at the agency level, you see that the agency employees want to learn more about artificial intelligence because contracts are coming up, people are wanting it, program managers, executive officers at these agencies are saying, “We need this. We can’t fulfill the need of our agency without using computers and the technology there.” So it’s a great time for enterprises to even get into the public sector selling around artificial intelligence.

Jordi Torras:
Well, that’s fascinating. And I have heard, as well, maybe not lately, but at some point: “Oh, AI is here to take away our jobs.” That was the mantra at some point. And some of our customers are telling us, “Well, we buy artificial intelligence because we want to keep our talented employees that are in customer service.” You cannot keep them doing the same thing over and over. So they need to start thinking in terms of being strategic and can they create content and how they can start these conversations? Ultimately, conversations that implement all that.

Jordi Torras:
So some of our customers are buying AI to make sure that their employees don’t leave. That’s an interesting alternative view.

Jordi Torras:
So what is your vision about employment and AI and how … Because my vision is AI is here not to destroy jobs, but to improve the economy and, ultimately, create jobs. What do you think about that?

Josh Jackson:
Yeah, I’m in agreement with you. I mean, even to the point, let’s say … And I don’t want to get into the piece around the economic relief and unemployment benefits that are currently happening, but I will say that I think it brings an opportunity for more innovation. Even if we continue down this path of universal basic income, we think about these sorts of things. It looks like Elon Musk from Tesla is going to start building his own robots because it’s inevitable that robots are going to be around.

Josh Jackson:
But let’s take McDonald’s as an example, as they’re starting to use robots. And I have no affiliation with McDonald’s, but as they start using robots, they’re going to need people to service those robots all the way down to changing out, say, a spatula on the robot that is flipping the burgers. They’re going to need some way of changing it out or cleaning it or inspecting it, or whatever. Now, is it using computer vision? Is it using a new program? Maybe, but probably, and my bet is on this end, someone has to go in there and take it off, clean it, put it back on, reprogram. And so they’re starting to build those skills.

Josh Jackson:
So is it that new trade that is being developed? I think it is, and I think you’re starting to see these schools and institutions thinking about, “Okay, what is the piece that’s missing besides just the computer programming?” Because there’s going to be an overlap.

Jordi Torras:
Totally, totally. Absolutely. Listen, I could be here talking with you for a long time, but we’re on our podcasts and length. What I would say to our audience, who is, for sure, super interested in what you say is, how can they contact you? What is the best way to find you?

Josh Jackson:
Yeah. I mean, I’m on LinkedIn for theaiassociation.org, so [email protected] is a way to email me. I’m super happy to have a conversation either through LinkedIn, through email, or directly through our website. You can find all my information and give me a call and we’ll start talking. As you said, the public policy piece is what I love. It helps drive these initiatives. It helps build your business as we move forward to get the adoption of government thinking about the benefits of artificial intelligence.

Jordi Torras:
Absolutely. All right. Thank you so much, Josh. I’m pretty sure that you’re going to get some inquiries about that because the topic has been amazing.

Josh Jackson:
Thanks, Jordi.

Jordi Torras:
Absolutely. Thank you for being with us. And, for the audience, get excited for our next episode about The Future of Customer Service. That’s going to go live very soon. Thank you. Goodbye. Bye-bye.

Thanks so much for tuning in. This podcast was brought to you by Inbenta. Inbenta symbolic AI implements natural language processing that requires no training data with Inbenta’s extensive lexicon and patented algorithms. Check out this robust customer interaction platform for your AI needs, from chatbots to search to knowledge centers and messenger platforms. Just go to our website to request a demo at inbenta.com. That’s I-N-B-E-N-T-A.com and if you liked what you heard today, please be sure to subscribe to this podcast and leave us a review. Thank you.

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