Minds in the Machines

Artificial Intelligence conjures up a wide range of images in the collective consciousness. From killer robots to mechanical galactic overlords, we are fascinated with – and fearful of – sentient machines. Is that rooted in reality, or is the application of AI more mundane and (perhaps) beneficial?  In this episode, Eric is joined by co-host Dominic Artzis to shake things up in the studio. Pop quizzes, movie quotes and more abound as we kick off our series on artificial intelligence, its applications in finance, and whether it will save us all – or destroy our lives.


Dominic Artzis is the head of Research at Zoot Enterprises, a global provider of advanced origination, acquisition and decision management solutions for financial institutions. As a digital native, Dominic understands the power of technology and offers a unique perspective to those around him.

Dominic: 00:02 One day the AI’s are going to look back on us the same way we look at fossil skeletons on the plains of Africa. An upright ape, living in dust with crude language and tools, all set for extinction¹.

Eric: 00:15 Wow, that’s a bit heavy.

Dominic: 00:16 Is it though?

Eric: 00:24 Welcome to the Finance Frontier. I’m your host, Eric Hathaway.

Dominic: 00:27 And I’m your guest host, Dominic Artzis, and today is episode one, of our four part series on artificial intelligence and it’s use in the financial world.

Dominic: 00:41 So Eric, to start this off I’ve got a pop quiz for you. We’ll see how you do.

Dominic: 00:45 What is the difference between artificial intelligence, machine learning, and deep learning?

Eric: 00:51 That’s a great question. It’s one that I think is extremely confusing across the general public and even in the tech world, with people that understand the technologies.

Eric: 01:01 I think in it’s simplest form, machine learning is the piece where machines are now compiling data and starting to make decisions based on that data. Deep learning takes it a step further, where it’s starting to pull a lot of information from different networks. So, I think, there’s neural networks that we talk about later in the show. And then artificial intelligence is really the decisioning piece of that, where it’s using that data to actually make decisions, as in driverless vehicles. But, it’s extremely confusing and I think it’s something that is going to have to come to the forefront so that we can find a little bit more consumer adoption of artificial intelligence, to stop using all these big words and large terminologies that are very much intertwined.

Dominic: 01:46 Yeah and it’s really the evolution of taking tech from this human manipulated state to the no-intervention-by-a-human. It’s kind of a simplistic way to look at it.

Eric: 01:56 Exactly. There’s a ton of benefits to implementing AI, or artificial intelligence, from both a business perspective and the consumer side. But the cultural portrayal has been a little dark, especially over the years as Hollywood has sort of steered us in a way that it’s evil, right.

Dominic: 02:21 Mm-hmm (affirmative). And we really first saw that in 1927, in a silent film called Metropolis. Long story short, this creator builds this robot named Maria, and all the townspeople have no idea it’s actually a robot. It’s not revealed until the very end when they burn this robot at the stake, that it’s actually a machine. That’s one of the first kind of dark spins on what AI could look like in the real life through film.

Eric: 02:48 I haven’t seen that one, I’ve got to go back and check it out, because I’m a big SciFi fan, but yeah, The Matrix, The Terminator, Ex Machina, which I think is where that quote at the beginning came from. And I guess what is the reality of the situation? Is it really that dark? Is that where it’s headed?

Dominic: 03:06 Yeah, and I think that’s a really poor portrayal of the technology on the whole. I think back in 1956, John McCarthy kind of coined the term, artificial intelligence, and that same year saw one of the first AI programs running and demonstrated. So I think in the last 60 years, we’ve got this film portrayal that’s been pretty rough, pretty kind of bleak looking, and then we’ve got kind of the real world, use cases that have happened over time. And with the addition of computational power and accessibility to data stores, we’re seeing the use exponentially increased from applications in finance to everyday household materials. So I think that’s a pretty focused view of the negative aspects of artificial intelligence. But there is an interesting data point that I came across, that 75% of business execs surveyed in the intelligence unit report, stated that their companies would actively be implementing AI within the next three years. That quote came out in 2017², so I think we’re kind of at that precipice, where we’ll start seeing AI become mainstream in all that we do.

Eric: 04:20 And I think a lot of people don’t realize that we use AI today in our daily lives. I mean, if you look at Apple Siri, or the Alexa, the Google Home, they’re using pieces of AI in the background as to having conversations, to making decisions. I think the latest one is Google, came out with actually ordering food from a restaurant based on something you’re saying.

Dominic: 04:46 Yeah, Google Duplex.

Eric: 04:48 Yeah, Google Duplex. And I think as we’re shopping, we’re seeing AI in marketing. We’re seeing voice to text when we look at large data accumulation of the written word. With facial recognition even, we’re seeing it not only on our phones, but also in the workplace now, as far as security to recognize employees versus non employees.

Eric: 05:12 In an upcoming episode I’ll be talking with Gary Melling and Tracey Feiber Their point of view that implementation of AI is mandatory for success.

Tracey: 05:21 Artificial intelligence is here now. It’s not something that’s coming. In the past it’s always been coming. It’s here now, so you need to be adopting artificial intelligence machine learning, because your competitors are starting to use it, and you don’t want to get left behind.

Dominic: 05:49 So, I think one of the interesting pieces of AI, and it’s emergence in tech and the world as a whole, is there’s so much excitement, that sometimes we forget there needs to be a good use case, in order to actually take advantage of the technology. I think a lot of businesses are running into the problem of, “well, everyone else is doing it, so we need to start one, and then we’ll figure out what we’re going to use it on later.”

Dominic: 06:16 I think that’s where we start to run into some of the challenges that AI is bringing into the workplace. And poor planning is kind of what spurs the rest of the issues that follow it. To name a few, we’ve got data quality, what you put in matters because it’s using all that information and then spitting out a response. So, off the top of my head Eric, when I think about some of the challenges, that AI faces are as follows, data quality, the black box effect, these technologies having a narrow focus only solving one problem when there’s a plethora of issues that could be solved down the line. And responsibility. When this machine makes a decision it has consequences if they’re poorly made.

Eric: 07:03 I also think to your point, you mentioned earlier a lot of businesses are just jumping on to the AI train without a strategy, and I think that’s a big part of this too. They have to realize these things, but there’s a strategy and they need to go after a certain problem, instead of trying to just say, “Hey, let’s implement AI,” right?

Dominic: 07:20 Yeah, totally. I mean it’s funny, we talk about these technologies having a narrow focus, but you’ve got to kind of narrow down the starting point at least, to have a good approach to expand that program. Because really, they’re quite complex, so I think there’s a misconception that it will solve all our problems. It’s really creating problems until we can get it dialed in.

Eric: 07:41 Absolutely.

Dominic: 07:42 Do you mind chatting about the black box effect and kind of just the stigma behind that?

Eric: 07:46 Yeah, give us a little bit more detail as to what you mean when you talk about black box, because we think of it like an airline, right? The airline has a black box and in a crash scenario…

Dominic: 07:56 Which typically has a little the answers. Correct?

Eric: 07:57 Right, exactly.

Dominic: 07:58 So, that’s a good point you make.

Eric: 08:00 It’s a little different with AI.

Dominic: 08:01 Yeah, I mean the idea is we’re taking an immense amount of data that an individual could not possibly parse and then have it spit out a response. That’s inherently going to be more intelligent than we are, and so how do, in an industry that’s highly regulated, how do we explain how we got from A to B. I think that’s where this black box comes in, as it’s so complex we can’t necessarily nail down where it may have gone wrong.

Eric: 08:29 Yeah it’s tough. I think the black box effect is something that if you don’t know how a decision is being made, I think that’s where that fear factor comes in. I think that black box effect is going to have to be addressed if AI is really going to take off.

Dominic: 08:44 Yeah, and one of the other issues that we’ve seen is, these algorithms are purely rational, too. It cuts out all the emotions, so in some of these instances where a decision is made, a human may have been able to enhance it by being able to feel for whatever that situation may be. So the lack of emotional intelligence can be a problem depending on what industry you’re in and using this technology, because it can’t contextualize that information, properly, per se.

Eric: 09:15 Yeah it’s interesting. A chat box can often be really disappointing. They’re smart, but they lack that empathy that you speak about.

Eric: 09:21 We had the opportunity to catch up with KayCee Murray, who’s the SVP of IT at Numerica Credit Union, who’s experienced these challenges directly.

KayCee: 09:30 The number one goal is, just give our members a way to interact with their money. One more way that they can do it on their terms and their time. We don’t have the budget of a Bank of America or a Chase as far as technology goes, but that doesn’t mean that we can’t provide a lot of those same services by making really smart partnerships with others.

Eric: 09:47 A lot of banks are getting on board the artificial intelligence train, in fact Accenture just came out with a report that said that within the next three years, banks will turn to artificial intelligence as their primary means of interaction with customers.3

Dominic: 10:00 So it’s pretty crazy to think about going to a bank or financial institution and not actually speaking to someone personally. That’s quite the evolution from where we were back in the 50’s, through even the early 2000’s, where you would go in and have this relationship. A lot of the research that we’re starting to see and Gartner has specifically mentioned this, by 2020 customers will have 85% of their business interactions with no human communication, which is just astounding4.

Eric: 10:26 That’s only a little over a half a year away.

Dominic: 10:29 Yeah, very close.

Eric: 10:30 Wow.

Dominic: 10:38 Eric, we covered a lot here, but is AI just hype?

Eric: 10:41 Dom, that’s a great question. And I don’t particularly believe so, but we did have the opportunity to catch up with Thomas Nield, after he published a fascinating article called “Is Another AI Winter Coming?” And we asked him the same.

Thomas: 10:53 Researchers, when they were having a computer play a game of checkers in the sixties. They were astounded that it could actually beat a person, and they made that leap, saying, “Oh wow, this algorithm is actually thinking.” Just because you found a tool that is great at a very certain number of tasks, does not mean that it can do all tasks equally well.

Eric: 11:15 It’s amazing to me how, and no matter what generation you’re coming from, baby boomers, things that we saw in the Jetsons, which is a cartoon, are coming true today.

Dominic: 11:26 I do know what the Jetsons is, by the way.

Eric: 11:28 Okay, good, good.

Dominic: 11:30 If there’s any confusion.

Eric: 11:31 But even Star Trek, even some of these science fiction movies that we’ve only recently seen in the last 20-30 years, some of the stuff is actually coming to reality.

Dominic: 11:41 Yeah, it’s pretty bizarre first that they had to foresight to even kind of muster up those out of their imagination and now we’re actually seeing those come to fruition. It’s pretty wild.

Eric: 12:05 We have a number of great episodes coming up. And Dom, I wanted to thank you for joining us in the studio today.

Dominic: 12:11 Yeah, I’m glad you had me on and it’s a fascinating landscape that’s on the top of everyone’s mind right now.

Eric: 12:15 It really is.

Eric: 12:22 Since we depend on listeners like you to help us spread the word, we’d love it if you’d take the time and post a review of our podcast on iTunes. Until next time, I’m your host, Eric Hathaway.

  1. Garland, A. (Director). (2015, March 24). Ex Machina[Video file]. IMBD. Retrieved April 15, 2019, from https://www.imdb.com/title/tt0470752/
  2. The Economist Intelligence Unit, & Wipro. (2016). Artificial Intelligence in the Real World: The Business Case Takes Shape(p. 3, Rep.).
  3. Chiang, H. (2018, September 20). Artificial Intelligence in Finance: AI is the New Electricity. I Know First. Retrieved January 19, 2019, from https://iknowfirst.com/rsar-artificial-intelligence-in-finance-ai-is-the-new-electricity

  4. Hinds, R. (2018, April 02). By 2020, You’re More Likely to Have a Conversation With This Than With Your Spouse. Inc. Retrieved March 15, 2019, from https://www.inc.com/rebecca-hinds/by-2020-youre-more-likely-to-have-a-conversation-with-this-than-with-your-spouse.html

Love the show? Want to be featured as a guest? We’d love to hear your questions and comments and welcome guest recommendations. Our producer Sara Tatnall can be reached at sara.tatnall [at] zootweb.com.

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