Polymarket’s Big Social Video Bet

**SPEAKER_1** (0:00)
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, a senior partner, IBM Consulting, to learn why.

**Caitlin Ostroff** (0:15)
Hey, TNB listeners.

**SPEAKER_3** (0:16)
Have you ever seen a post on social media that you thought was real, only to later realize it was AI generated?

**Ray Smith** (0:22)
We want to hear from you.

**Caitlin Ostroff** (0:24)
What did you see?

**SPEAKER_3** (0:25)
Why did you believe it? How did you feel afterwards? Shoot us an e-mail to tnb.wsj.com, or leave us a voicemail at 212-416-2236.
That's 212-416-2236.
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.

**Belle Lin** (0:56)
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 crap shoot, 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. 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. 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. 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.

**Caitlin Ostroff** (2:39)
Let's start with where things are now. What are some of the challenges with the way most companies hire today?

**Ray Smith** (2:44)
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.
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.

**Caitlin Ostroff** (3:23)
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?

**Ray Smith** (3:37)
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. So for instance, these AI tools will basically have skills-based questions rather than those sort of, again, soft questions that really don't tell you how someone will perform at 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, or it can just be simply a round of exercises that you have to perform, AI-powered, that basically reveal in the end whether you can actually handle that job or not.

**Caitlin Ostroff** (4:38)
What are the biggest concerns people have about these tools?

**Ray Smith** (4:40)
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. It's basically this fear that AI can be flawed, that AI can sometimes even be reflective of the biases of their creators.