If you thought you'd heard everything from the Chad & Cheese European Tour in Lisbon for TAtech, well, think again. Here's their session on A.I. from RECex.
Enjoy this Uncommon exclusive.
PODCAST TRANSCRIPTION sponsored by:
Chad: Enjoy this special RECex edition of the Chad & Cheese from TAtech Europe after a quick word from our sponsor.
Chad: Dude, we're always talking about cool new tech, but it's hard for hiring companies to change. I mean adoption's a bitch.
Chad: New tech can get them to qualify candidates so much faster.
Joel: I know man, but recruiters already have their routine in place. And nobody wants to jump into another platform, especially when it's expensive and also requires hours, maybe days of training.
Chad: Exactly, but that's where Uncommon's new service comes into play. Uncommon pairs expert recruiters with inhouse kickass technology.
Joel: All right. Interesting. Interesting. It sounds like Uncommon understands the problem of change.
Chad: That's why they hand select veteran recruiters, train them on this kickass technology that has access to over 100 million active profiles.
Joel: Yeah, yeah. But I bet they're expensive and I bet it requires some kind of annual commitment or contract, right?
Chad: No, man. Uncommon is not an agency. They don't require a contract, any contingencies. All they do, they charge one flat fee per project, saving, I don't know, anywhere from 50 to 80% on each hire versus the average agency cut.
Joel: Oh, snap. Companies could save big stacks of paper, especially if they're rapidly scaling and need hires today.
Chad: Yup. And all you have to do is reach out to Teg and the Uncommon crew at uncommon.co. That's uncommon.co.
Joel: Change doesn't have to be a pain if you're using Uncommon.
Announcer: Hide your kids. Lock the doors. You're listening to HR's most dangerous podcast, Chad Sowash and Joel Cheesman are here to punch the recruiting industry right where it hurts. Complete with breaking news, rash opinion and loads of snark. Buckle up boys and girls. It's time for the Chad & Cheese Podcast.
Joel: Wake up all you Euro trash fuckers.
Joel: Chad, we're screwed dude. The presentation before us said they'd make up their minds in three seconds.
Chad: They've already made up their minds.
Joel: Totally. Who's a listener? A few of you. Excellent, excellent. If you don't, something's wrong with you and you should tune in.
Joel: So we're here to talk about what? AI, automation, the end of the world as we know it, basically.
Chad: Jobs. Yeah, yeah. So, first and foremost, who is sick and tired of hearing AI all the goddamn time?
Joel: I'm sick of seeing at every booth in every trade show that you see.
Chad: Yeah. It's interesting because when we sat down with a bunch of individuals from SHRM who are on the Talent Acquisition and HR side, their hands went up quickly, but yet they didn't feel like they would even be engaging or using AI. And, in most cases-
Joel: But they've got to buy it because everyone says I need AI, even though I'm not really sure what AI is and I don't know what your AI is versus the other vendors' AI.
Chad: But the big question is, why is it so hard to understand what AI is?
Joel: There's many different types of AI, Chad, and I think you've been to Wikipedia recently and you know if you have the different variations of a-
Chad: I'll get my phone out. Okay, so we hear the ... just breaking it down easy because we're dumb guys and we like to make it easy. Narrow AI, also known as weak AI, if you remember Garry Kasparov getting beat by IBM, the chess master getting beat by IBM, that is what you would call narrow AI. That means that algorithm was smarter than that man, that grand champion wizard master, whatever the hell he was.
Joel: It's a bit more decision tree and machine learning kind of AI versus the actual self aware stuff that Google and Microsoft are working on.
Chad: Yeah, but, see, and that's the problem. See, that's where people get hung up is they think AI, every aspect of AI, is self aware, but it's not. It's baby steps to be able to get to the super-
Joel: We've got a while before the Terminator shows up.
Chad: So yeah.
Joel: And the sex robots, unfortunately.
Chad: And fortunately for China. So narrow AI, do we have that today in our industry? Yes, we do have narrow AI in our industry. You take a look at some of the technologies that are out there today, just one quick example. Three years ago, a little company called Brilent 4:44] went to SourceCon, came in third and that algorithm did in six seconds what the winner did in, I think it took 24 hours.
Joel: So it took on three other humans sources, I believe. Experts.
Chad: It took on more than that. So being able to actually outpace humans in a much faster, quicker, more efficient way is, obviously, part of that definition, so narrow AI. Just like, again, IBM computer, Big Blue beating, or Deep Blue beating Garry Kasparov, right? What did that computer do well? Chess. Could it make tea? No. Could it do anything else? No. Could it even tell the difference between a dog and a cat? No. It could do chess.
Joel: Shallow, I get it. I get it, I'm with you.
Chad: Narrow or weak. So the next level would be general or strong AI, which we're not even close to approaching yet. That would allow that narrow band to actually broaden up and do much more of those different tasks. Not separate algorithms, but an algorithm to be able to actually do more of those tasks just as well as, obviously, human beings and then "Super" is pretty much Terminator, life's over.
Joel: So June 13th, 2016, does anyone know what happened on that day? On that day, Microsoft announced its acquisition of LinkedIn. And I would argue that that was the start of the arms race in our industry for AI automation in employment. So 26 billion dollars was the acquisition cost, actually 26.2 billion. At that point, Google said, "Holy shit." Facebook said, "Holy shit." Up until then, classified was like a one billion dollar a year business, Monster's valuation was around there at the time. So that wasn't really enough to get their heart racing, but 26 billion for a little 500 million people in a directory got their attention.
Joel: So, when we look at who's on the cutting edge of the AI that you're talking about beyond the shallow stuff, you've got to look at Microsoft, Google and Facebook in our industry. Those guys are doing real AI stuff. In fact, I would argue that many of the vendors in our space are leveraging their APIs to say that they have AI, even though they're really leveraging Watson, Microsoft or Google.
Chad: Right. And asking CEO Scott Gutz of Monster who, they need some fucking product, their answer was, "Yeah, we should take a look at products like that and build around them. I mean, that's strong, those are strong products, we should built around those products." So does it make sense that these big companies should be driving our industry, or they have been.
Joel: Yeah, and it's a double-edged sword because you're using Google Search to power all your job search activities, but, guess what? Google's learning a lot by having you plug their Search capabilities into your job board or corporate website. So, in a way, you're sort of sticking the knife into your own back by letting Google into the house, a Trojan horse, if you will, to learn more about how people search for jobs and what they're looking for. Although you're getting a good search technology and you're able to lay off a lot of tech people and save a lot of money in the process.
Chad: Save a lot of money, not to mention, you just get better results overall, better candidate engagements, getting your candidates to stick around longer to be able to actually apply to jobs. Companies are actually saying more performance-based [crosstalk 00:08:16]-
Joel: There are tons of stories on saving money on customer service. Apparently, there are a lot fewer calls coming in about, "How do I search for a job," doing a Google search, yeah because of your search sites.
Chad: And then moving beyond that, the applicant tracking system, which is also embedded with AI and automation. One of the big pieces that, and they just went, believe it or not, enterprise, "enterprise", with Hire, by Google. The thing that I love seeing within it, and something that Opening.io does as well, is the candidate matchup piece, being able to utilize the data you already have in your database, or your client already has in their database, and they've already spent money on those candidates to be able to surface them and get that hopefully in the pipeline much quicker. That's already embedded in Hire, by Google.
Chad: The big question is, when's that going to be popped out as an enterprise API? Because it will be popped out as an Enterprise API, which means everybody else is going to have the same type of technology, AI, embedded into their-
Joel: And, by the way, how does that impact job postings? If I can just search for candidates already in my database or this whole thing called LinkedIn which is 650 and growing, million user profiles around the world, how important is actually posting a job which impacts a lot of you who may be at job boards? I would contend that job boards are becoming less important and commoditized, which I believe, Google for
jobs is also doing as well.
Chad: Yeah, see, and I don't believe that because I believe job boards are still strong from one standpoint, and that's data. That's one of the reasons why they're getting so much traffic, not from traffic from the standpoint of actual dollars, so much of investment dollars is because of the data. If they can use that AI, if they can use that matching to be able to ensure that they can get to the candidate much quicker, that's one of the things that job boards can do to pivot into this new age of tech.
Joel: Well, if you'd rather have Monster's data than LinkedIn's data, then you have at it. But I'd rather have LinkedIn's data and Google's data.
Chad: Well, Google buys Monster's data. I don't think that works.
Joel: No one's buying Monster, let's get that out of the way.
Chad: So from a sourcing standpoint, you take a look at it ... when we were talking to, and actually had a sourcer get pissed off at me on Facebook this week because we were talking about-