Polymarket’s Big Social Video Bet

[00:00:00] [SPEAKER_01] Many companies are struggling to scale their AI deployments or even move them past the pilot stage. Often the problem isn't technology, but organizational misalignment around goals, processes, and incentives. At the break, join Caroline Roach, Senior Partner IBM Consulting, to learn why.

[00:00:14] [SPEAKER_02] Hey, TNB listeners. Have you ever seen a post on social media that you thought was real, only to later realize it was AI-generated? We want to hear from you. What did you see? Why did you believe it? How did you feel afterwards? Shoot us an email to tnb at wsj.com or leave us a voicemail at 212-416-2236. That's 212-416-2236.

[00:00:41] [SPEAKER_02] Or if you're a listener on Spotify, drop us a comment in this episode. You may hear yourself on the show, and we may reach out to hear more about your experience. We hope to hear from you. Now on to the show.

[00:00:56] [SPEAKER_04] Welcome to Tech News Briefing. It's Tuesday, June 23rd. I'm Belle Lin, a reporter for the Wall Street Journal Leadership Institute. The job hiring process today is pretty much a crapshoot, according to many job applicants and hiring managers. Now, some companies believe swapping out humans for more advanced artificial intelligence systems could actually fix a lot of what's broken.

[00:01:23] [SPEAKER_04] We're diving into where the AI-assisted hiring process stands today and what it could look like in the future. Then, you may have recently seen a new type of video circulating on social media. One where a college-age creator shows off their lucrative side hustle, making bets on Polymarket. The only problem? The bets aren't actually real, according to a new Wall Street Journal investigation.

[00:01:50] [SPEAKER_04] We take a look at how and why Polymarket is flooding social media with these deceptive videos. But first, the job interview of the future could involve virtual reality headsets and interactive video games. But today, the hiring process looks much like it always has. And many agree it's far from perfect.

[00:02:15] [SPEAKER_04] Even as companies use new AI hiring tools, the current iteration of the algorithms are highly automated and sometimes risk knocking out top talent early in the process. Our colleague Imani Moise sat down with WSJ reporter Ray Smith to discuss how AI could help improve how companies hire candidates in the future.

[00:02:38] [SPEAKER_02] Let's start with where things are now. What are some of the challenges with the way most companies hire today?

[00:02:44] [SPEAKER_00] Some of the challenges include that interviewers often rely on their own gut instinct rather than skills-based. So that's one of the problems. It can be something as simple as thinking the person has a great sense of humor or they went to the same school that I went to, so they probably have similarities to me. The other problem, though, is that it's rare that interviews really tell exactly whether the person is skilled enough to do the job once they're in the job.

[00:03:12] [SPEAKER_00] For example, a lot of the questions can be somewhat vague, like where do you see yourself in 10 years? And the answer doesn't really indicate how well that person is going to do on the job.

[00:03:23] [SPEAKER_02] You recently wrote about a new generation of AI hiring tools that promises to be more efficient than the human way of doing things. But how is this different from the automated filters that people have been complaining about?

[00:03:36] [SPEAKER_00] The hope is that the newer generation of these AI tools will be far more sophisticated and will have learned from the mistakes of the past. But the point is that they're trying to address the idea that there are so many applications for jobs today and there are so few humans who can actually respond to each one or interview every person. And so they're hoping that AI will at least streamline the process and they will try to make the screening, if you will, more skills-based.

[00:04:04] [SPEAKER_00] So, for instance, these AI tools will basically have more skills-based questions rather than those sort of, again, soft questions that really don't tell you how someone will perform in a job. So, for example, you may be put through certain exercises, whether you're putting on a virtual reality headset, immersing you in what you would do in that scenario on the job.

[00:04:26] [SPEAKER_00] Or it can just be simply a round of exercises that you have to perform, you know, AI-powered, that basically reveal in the end whether you can actually handle that job or not.

[00:04:37] [SPEAKER_02] What are the biggest concerns people have about these tools?

[00:04:40] [SPEAKER_00] The biggest concerns are basically that you are taking humans out of the equation and that you're making this all machine-based and that a machine is judging you. And AI machines or machinery can't see nuance or find the underdogs or find hidden talent. And it's basically this fear that AI can be flawed, that AI can sometimes even be reflective of the biases of their creators.

[00:05:07] [SPEAKER_02] How many employers are actually using these tools?

[00:05:10] [SPEAKER_00] A lot more companies than you think are using, at least for the early screenings of the job interviewing process, because they're getting so many applications. And it's just easier to at least screen people for the initial wave of interviews using these tools, because they just don't have enough human resources professionals able to handle the amount of applications and then scheduling and flying people in for interviews that can get costly and time-consuming.

[00:05:40] [SPEAKER_00] With AI screening tools, you can basically save time, save money. Again, not for the whole interviews, just to maybe wind down to the top candidates that they want to see face-to-face in person.

[00:05:54] [SPEAKER_02] And for listeners who are currently job hunting, what can they do to stand out if they're initially being evaluated by AI instead of a human?

[00:06:01] [SPEAKER_00] They really need to take care not to try to game the AI system. And what I mean by that is it's tempting to want to use keywords that you think the AI is looking for. But a lot of these companies told me that the reverse is true, that they can detect when people are trying to game the system and that will automatically knock them out.

[00:06:24] [SPEAKER_00] So people should really be careful to try to sound as authentic as they can and not try to, again, gamify or use keywords that they think the AI is looking for.

[00:06:34] [SPEAKER_04] That was WSJ reporter Ray Smith speaking with our colleague Imani Moise. How do you feel about the job market? Do you think AI could help? If you're a listener on Spotify, leave us a comment with your thoughts. Coming up, a WSJ investigation uncovered that Polymarket has been paying creators to post deceptive videos to social media. Why the company is going all in on marketing to win over U.S. users.

[00:07:03] [SPEAKER_04] That's after the break.

[00:07:09] [SPEAKER_01] Delivering real business results with AI starts with organizational alignment, says Caroline Roach, senior partner, IBM Consulting.

[00:07:16] [SPEAKER_05] You need to understand what problem you're solving, really commit yourself to it, and then be clear on how you're going to change the way you work to deliver those outcomes with AI as a tool, but not the only tool.

[00:07:27] [SPEAKER_01] If deployments aren't optimized to how work gets executed, ROI can suffer as programs stall and adoption lags.

[00:07:33] [SPEAKER_05] Alignment is difficult to achieve because people are rushing to a solution without first defining the problem.

[00:07:39] [SPEAKER_04] In a push to draw users to its unregulated platform, Polymarket has flooded social media with videos that seem genuine at first glance. Mostly, college-age creators appear to be making bets on the prediction market and winning them. But in reality, the trades aren't real, and the company has been working hard behind the scenes to make the videos go viral.

[00:08:09] [SPEAKER_04] Here, to break down how exactly this all worked and how Polymarket has responded since the WSJ investigation was published, is reporter Caitlin Ostroff. And a heads up before we start, Polymarket has a data partnership with Dow Jones, the publisher of the journal. The journal used only publicly available data for its analysis. So, Caitlin, what are the types of videos that Polymarket is paying its creators to post?

[00:08:36] [SPEAKER_03] Yeah, so Polymarket has hired a bunch of creators to post videos of them either talking about Polymarket, but most of the videos, 70% that we analyzed in a corpus of about 1,100, actually showed people placing trades on what appeared to be Polymarket's platform.

[00:08:55] [SPEAKER_04] But an exclusive investigation you conducted with a team from the Wall Street Journal found that that actually wasn't the case.

[00:09:02] [SPEAKER_03] So, our reporting found that Polymarket paid people to create videos where they show these trades, where they show themselves betting on the platform, but that Polymarket, one, directed them not to disclose that they were being paid by Polymarket. After we reached out about Polymarket's marketing techniques, the creators began disclosing that they were Polymarket partners.

[00:09:27] [SPEAKER_03] But also, we found that all of the trades placed in these videos created by these creators, none of them were actually on Polymarket's website. So, as we were reviewing all of these videos, we realized that there was a bunch of small discrepancies between these websites and the actual Polymarket. And the creators told us that Polymarket gives them bullet point guidelines on what they should be saying in videos,

[00:09:56] [SPEAKER_03] that they give them direction on what type of content does well, and that they review the videos submitted by the creators before they can post them. And so, most of them told us that they were kind of on these almost contracts with Polymarket, where they were told to make five or six videos per week sometimes. Often, they got paid $2,000 or $3,000 a month to do this. But that Polymarket was the one saying, this video looks great, post this,

[00:10:24] [SPEAKER_03] or this video has an obvious tell that you're on a simulated platform, you need to reshoot this. And how do some of these videos end up going viral? Some of the videos do just generally get huge reach from the original creators. But the second part of that is that to really make sure that these creators' videos got seen, Polymarket paid a third-party contractor called Virality to take those videos and basically put a little bit of text on them,

[00:10:53] [SPEAKER_03] put some music, and recirculate them on the internet. It's a marketing practice that's emerging called clipping.

[00:10:59] [SPEAKER_04] So looking at the bigger picture here, why are these videos important to Polymarket's strategy in the U.S.?

[00:11:06] [SPEAKER_03] So Polymarket, according to our reporting, wants to bring its offshore platform back to the U.S. Back in 2022, Polymarket settled with the CFTC, the regulator for the types of contracts that Polymarket offers. And they said, look, you're offering all of these products without registration with our federal agency. Because of that, you can't continue to serve U.S. users. And Polymarket agreed to that without admitting any fault.

[00:11:36] [SPEAKER_03] But since then, they have not officially been allowed to offer U.S. users access to trading. Now, it's a horribly kept secret that you can use a VPN or virtual private network to access their website. But Polymarket is starting to try and bring its offshore platform back to U.S. users. And so they are doing this marketing campaign in advance of that ambition where they want more U.S. users to trade on the platform.

[00:12:05] [SPEAKER_03] And when the clippers who are recirculating these videos were given instructions, they were told at least 60% of your audience, the people who view your content, need to be U.S. based. You know, we started looking at this because these videos got onto our feeds. And so we know at least some of these videos are reaching U.S. users.

[00:12:26] [SPEAKER_04] Is Polymarket regulated? And is the type of marketing that they're doing with these videos legal?

[00:12:32] [SPEAKER_03] Polymarket, the broad platform that you see, is not directly regulated by the CFTC, the commodities regulator. Their U.S. platform, which was launched late last year, is regulated by the CFTC. But we've spoken to a number of lawyers and former government officials who have said that these marketing practices could violate federal advertising law, the 2022 settlement that the offshore platform had with the regulator.

[00:13:00] [SPEAKER_03] And so it's hard to say black and white whether something would be violative of that, but we've been told that there's certainly the potential for some of these practices too.

[00:13:10] [SPEAKER_04] And what did Polymarket say about your reporting when you presented them with the information?

[00:13:15] [SPEAKER_03] Polymarket said that it's going to perform an audit of its active promotional content, and we haven't heard more about what that audit might find. To our knowledge, a lot of the videos that have since come down were at the desire of some of the creators who have posted them. So some of the creators took their content down after we reached out. A couple of the accounts actually still have stuff up and are still posting, but we haven't heard anything else from the company.

[00:13:40] [SPEAKER_04] That was WSJ reporter Caitlin Ostroff. And that's it for Tech News Briefing. If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Julie Chang with supervising producer Katie Ferguson. Logging off, I'm Belle Lin, a reporter for the Wall Street Journal Leadership Institute. We'll be back later this morning with TNB Tech Minute. Thanks for listening.

[00:14:10] [SPEAKER_01] Scaling AI successfully requires more than the right technology. Here again is Caroline Roach, senior partner, IBM Consulting.

[00:14:17] [SPEAKER_05] The biggest thing that we were talking about a year ago is what model to use. And the biggest thing that I'm talking about with my clients now is how do I drive change within my organization?

[00:14:29] [SPEAKER_01] Companies able to identify, correct, and then avoid misalignment will be best positioned to deliver meaningful business value from AI.

[00:14:35] [SPEAKER_05] The organizations that are the most successful set very clear targets and have several priorities that are very clear across the enterprise. The technology is really good, but if you're not changing your organizational alignment, not incentivizing your people correctly, not looking at workflows, you're not going to see real value with it.

[00:14:56] [SPEAKER_01] Visit ibm.com slash think slash leadership to learn how building organizational alignment can help deliver AI deployments that scale and drive growth.

[00:15:04] [SPEAKER_04] This content was created by Custom Content from WSJ, a unit of the Wall Street Journal Advertising Department.