The boys sit down with Max Armbruster to talk RPA... Artificial intelligence is so last month. Meet your future in RPA.

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Chad: Whew.

Joel: Mad Max is on the show today.

Chad: I know. It's good shit, dude.

Joel: Ah, yeah. Welcome to the show, everybody. I'm Joel Cheesman, your co-host, along with-

Chad: Chad Sowash.

Joel: And on today's show, we're talking AI versus RPA. And if you're like me, RPA stands for Rapid Projectile Anonymity or something. I don't know. Max, welcome to the show. How are you?

Max: I'm very well. Thank you, Joel.

Joel: You're very welcome. So you wrote... Well, look, before we get to that, you are CEO and co-founder of Talkpush. So get the elevator pitch and plug out of the way before we get into the real stuff.

Chad: Push it real good.

Max: Thank you. Thank you. Talkpush is a slogan first of all. Talkpush it real good, by copyright Chad and Joel.

Max: But beyond that, we're a messaging platform to help engage with candidates at scale, and we automate a lot of the initial engagements with a candidate to the front of the funnel. And we work in a dozen countries and engage with millions of candidates across messaging platforms like Messenger, SMS, WhatsApp, and automates a lot of the recruitment process after that.

Joel: And I will throw in a Death Match alumni.

Chad: That's right.

Joel: Which is always a solid, solid thing to put on your resume.

Chad: You can't beat that.

Max: I survived-

Max: Barely.

Chad: So you wrote an article that said, “Will the Real AI Please Stand Up?” And in Eminem fashion, “Please stand up, please stand up.” And it says, "Why the recruitment industry needs to stop fawning over AI, embrace the RPA, the Robotic Process Automation revolution." Why did you write this?

Joel: Wait, what does RPA stand for again?

Chad: Robotic Process Automation.

Joel: Got it?

Max: Right. Well, I think anybody who listens to this show probably empathizes with a feeling of we're a little saturated with AI, the AI pitch and sell. And from my end, as a vendor, I'm still getting probably a quarter or a third of inquiries coming in from people who are asking for AI, and I don't really know what it means most of the time, and it doesn't feel like it's been really thought through.

Chad: Do they know what it means? Do they give you a definition of what they think AI is so that you can try to fit-

Joel: Oh, no, they don't know what it means.

Chad: So you can fit in their box.

Joel: That is one big pile of shit.

Max: I think, unfortunately, they did read the same books as I have, so they know what machine learning is. They know what the state of the art is, and that's what they want. They want the state of the art AI. They want something that's going to be a machine that's going to learn on top of the data that is continuously feeding itself.

Joel: You're giving them way too much credit my friend.

Chad: Yeah.

Joel: I think they just want to check it off the list of things that they need to do right below chatbot and right above programmatic.

Max: I do get some of those guys too. I'm talking about the digital transformation experts that are sending out call for tenders, RFPs specifically with the idea of, “I'm going to grill these guys.” And I'm sitting on these calls answering questions about technology that I don't even know how it's going to be used, so that's where the frustration originally comes from. And I can talk about RPA a little bit, and why I think it's a little bit more of a pragmatic approach.

Max: I mean you've had a number of podcasts and shows where you talked about what is AI exactly. There's so many different definitions, but the reality usually falls very short from what people imagine.

Joel: But if you read between the lines with your customers and prospects, like what do they really want? Because you have a great section of your post where it's not the fancy, shiny stuff that they're actually using. It's the other stuff.

Joel: So HireVue is one of your examples where people aren't using HireVue to like read facial expressions and whether someone's lying, they're using it to create efficiencies around better interviewing through video. Correct?

Max: Yeah, the great benefit of video interviewing is the asynchronous conversation. The fact that you don't have to sit through 20 minutes of live call, one after another, because that would take days to go through all that. And instead, you can ask everybody to record, and you can listen to all of them in one go, and you can skip them. I mean it's basically the same value proposition as an answering machine back from the '90s. You know just having all your answers recorded in one place, so you can listen to them in sequence.

Joel: Mm-hmm (affirmative).

Max: And the majority of customers that I've spoken to... I'm sure if you get somebody from HireVue on the show, they'll tell you about what the analytics do for their customers. It'll be a different story perhaps. I mean they still sit through the interview. They still watch the videos, and they don't let the machine make the decision for them, for the most part.

Chad: Before we get into the RPA piece, right, you write, "The rise of the AI

junkie." So people are becoming AI junkies. Why is that?

Max: You know I read the Ray Kurzweil book about singularity, and I was reading science fiction from a young age. So I'm also really excited by the fact that the machines can help us make better decisions, and I love the promise of AI, but I think that the imagination has just caught on fire over the last four or five years.

Max: When I started Talkpush five years ago, and I said, "I'm going to create a robot that interviews people."

Max: People really looked at me weird, and said, "What a stupid idea." You know?

Max: "No one will ever let a robot talk to their candidates."

Max: And like two or three years later, people were asking, "Oh, that's great. Can your robot tell me if a candidate is lying? And how honest it is? And can I get a full psychometric analysis?"

Max: It happened almost overnight. I mean it was over a two, three year period, but that's how it felt for me.

Joel: Max, I've heard some people talk that I believe know this subject pretty well, and they've said things like, "There are only about five or six actual AI companies in the world."

Max: Mm-hmm (affirmative).

Joel: Your Googles, your Microsofts, your Alibabas, you know these kinds of big companies. Is there anyone even in the employment space that you would point to, to say like, “Yeah, they're really onto something,” aside from Google who's getting into the space and maybe LinkedIn/Microsoft? Is there anyone really doing AI in terms of your perspective?

Max: I don't want to play that game because I don't know, and I'm trying to get away from that game myself. Hey, I mean I think you're right that the real deep AI, Google and Facebook have a leg up on everybody else, and it's out of my reach. But I think-

Joel: I'll take that as a no.

Max: Yeah, you can take that as a no. I mean but we all get enough data sets that we can create some sort of... We process millions of candidates every year or so. Of course, we can do some regression analysis and come up with some pretty interesting insights, but I wouldn't call that sort of deep AI where the machine is built to understand what the candidates are saying. Some of the people in our space have hired PhDs who focus on natural language processing, and they may be a little bit deeper and more academic into the topic than we are, but that's all I can say on this topic.

Chad: So let's get into RPA. So I've challenged many of these AI vendors over the years in saying, “What you're doing really sounds like it's glorified RPA,” and that's not a bad thing. Right? Because what is RPA, and how could RPA help?

Max: RPA is beautiful. What is RPA? Is identifying a process that humans are doing.

Chad: Right.

Max: And then repeating it and automating it. And the big rise in RPA, which happened over the last three, four years, is backed, you could say, by AI. By the technology that recognizes what a user is doing on his computer and is able to repeat that behavior. So it could be somebody clicking on a mouse and moving a window from one place to another, and when the computer recognizes this sequence happens over and over again, can then automate it.

Max: So in itself, there is of course some AI building blocks necessary to deliver that, but what I love about it is that it just focuses on the user. And in our case, the user is the recruiter because we work in talent acquisition. And it's eerie how so many of those companies in our space, we don't even talk about the recruiter.

Max: We focus on automation and AI, and this is what the buyers are interested in talking about, automated engagement and AI, but not so much on the actual individual behavior and actions of the recruiter who is the main user. And if we shift the conversation to RPA, we can focus a little bit more on the user, who is the recruiter, and that's still probably 60%, 70% of the cost per hire. You know the total loaded cost per hire is probably linked to the human.

Joel: And so speaking about cost per hire, in your LinkedIn posts, you have a list of items that can be automated. Some of those are like scheduling interviews, background checks, running assessments. For the company out there that's looking at what kind of hierarchy or priority list should we have around, what are the first three things that maybe we should automate to save that 80% on cost per hire? What are some of the things that you think in your list should be on the top of an employer's list to automate?

Max: Usually the low-hanging fruit is automating that scheduling in a pre-screening because a lot of time is being wasted in just going back-and-forth trying to schedule first and second interviews, so that would be the low-hanging fruit.