4. Fast Four: The Reality, Ethics, and Risks of AI.

Reputation Nation hosts Anne Marie Malecha and Stacy Bratcher examine how AI is reshaping crisis, regulatory, and reputation landscapes, spotlighting Penske Media’s antitrust lawsuit alleging Google’s AI Overviews siphon traffic from outlets like Rolling Stone and threaten digital media economics.

They break down a federal ruling that lets Particle Health’s antitrust claims proceed against Epic Systems, a pivotal test of alleged EMR market power and data-access gatekeeping with industry-wide implications for health data competition. The episode also unpacks Shein’s AI-generated model controversy as a cautionary tale on vendor oversight and human-in-the-loop approvals, then turns to the Workday hiring-bias case, where a rare collective action highlights algorithmic discrimination risks for employers at massive scale.

Actionable takeaways. Pressure-test AI vendor practices, add human review to AI workflows, and prepare legal-comms strategies now for antitrust and bias scrutiny in the AI gold rush era.

Fast Four: The Reality, Ethics, and Risks of AI Transcript

AMM (00:00)

Welcome to Reputation Nation Fast Four where Stacy and I will spend a few minutes on headlines that have caught our eye. In each Fast Four episode, we’ll dive into four timely stories where we’ll provide a quick summary of why it’s interesting to us in the Reputation Nation and leave you with an actionable insight or two. For Dez Reads fans, this is the audio visual version of Dez Reads, which was the brainchild of my colleague, Josh Culling, with a slant on what’s making headlines in the legal crisis, regulatory, and reputation realm.

Stacy (00:09)

This week’s Fast Four has a two letter through line, AI. Artificial intelligence may be changing the way we work, the technology we use and how we live our lives, but it’s also making an impact legally and reputationally. We may be in an AI gold rush, but it can and will be cooled by crisis. Let’s get into it.

AMM (00:29)

We’re kicking things off in the fast forward today with Rolling Stone Publishers Sues Google over AI summaries. This was in the Wall Street Journal. Penske Media Corporation, they’re the publisher of Rolling Stone, sued Google claiming that its AI generated summaries, which if you’re Googling anything you’re seeing now, unlawfully uses its journalism and has led to significant drop in traffic and revenue for its sites.

This lawsuit specifically challenges Google’s use of AI to create these summaries, arguing that they diminish user engagement with the original articles and threaten the future of digital media. And I’ll admit, I have looked at these summaries if I just needed quick info and I have moved on, not clicking on any of the sources that they come from, which I think is the problem.

You know, what I find really interesting about this particular suit with Penske and Google is that they filed an antitrust lawsuit, whereas others have filed class action cases when it comes to publishing rights. I think this is going to be one that maybe sets a tone, but I’m really curious your take on that.

Stacy (12:59)

Well, Anne Marie, companies engage in anti-competitive, you know, market controlling behavior all the time. And it is a business tactic. I was recently talking with an antitrust defense lawyer and he was telling me about a great result that he got for a client. A CEO gave him a high five with a $500 million settlement. And the defense lawyer was sort of, you know, shocked by that. And the CEO said, $500 million for a monopoly I had for 20 years is the sale of the century. So these tactics are, there’s a business reason behind them.

AMM (13:35)

Yeah, absolutely. I mean that gets to an artwork defining what your objective is. In so many litigation cases, the goal isn’t necessarily to get them thrown out. It’s to reduce the liability that you’re facing and to the point of the attorney that you talked about with their client.

$500 million was a fee that they were happy to pay because think of what the upside was on that. And for anybody that is potentially up against a company like a Google or in an antitrust monopoly situation, don’t expect regulators to do your bidding. And you may need to find other solutions to create revenue. And if you’re on the other side of that and you’re the one that is being the subject of potentially the antitrust litigation, If it works, it works.

Stacy

Well, headline number two is Particle Health versus Epic Systems. Judge rules Epic must face monopoly claims. This was in Stat News and this is a case that I’m following closely. For those of you not acquainted, Epic Systems is really the largest and most pervasive electronic medical record system in the country. And Particle Health is kind of an up and comer looking at building a payer platform and other information sharing services for Health care related entities. So a federal court found that Particle Health could maintain an antitrust case against Epic. This has an interesting story to it. A little over a year and a half ago, Particle Health was caught up in allegations that they misused protected health information as part of a health information exchange. Folks may not be aware, but there are these sort of collectives where providers and others that have a legitimate reason to access what’s called PHI can do so through a collective. And Particle Health got investigated by Cary Quality, which is one of those Health information exchanges for inappropriate use of PHI. And Epic is a very big member, an influential member in Cary quality and got Particle. They allege that that Particle was banned and had their access curtailed. So Particle responded. They’re represented by Quinn Emmanuel, which is a very aggressive law firm. They alleged antitrust against Epic, which I thought was a brilliant move. And just recently, the court held that that case could go forward, challenging epics near monopoly in the EMR field. So I’m watching this one, my popcorn is out. I could give folks a lot of tips on maintaining good business practices and not having a monopoly. There’s gonna be more that comes out in this case and I’m gonna be watching it closely, Anne Marie.

AMM (04:49)

I think we’re going to have a lot to talk about. And I think you raised the point of the fact that this is competitor on competitor violence. This didn’t start with this lawsuit. This is now the next piece in the corporate law fair that’s occurring. And I’m from Madison, Wisconsin, which is where Epic is based out of. So I have just a natural interest in what happens here. And I think this case is going to have some likes and really potentially set some serious precedent. And the company that’s doing this, Particle, is venture backed.

These are aggressive, maybe up and comers that have an investment they want to protect and they are the first, but they probably will not be the last.

Stacy (05:25)

Amen. I second that. So the actionable insight in the Particle versus Epic is when you’re up against it, against a big Goliath, like a Google, like an Epic, you need to think creatively about how you can get out of that corner. And I think that’s what we saw, what we’re seeing in the case that Particle brought against Epic. Actually, when the case was announced last summer in 2024, I was actually quite impressed because Particle, as I said earlier, was banned, was getting banned from these Health information exchanges, which basically, you know, obfuscated their whole business. having creative counsel, folks that can think outside the box. And as I think we’re going to see, Particle Health is opening the door for a lot more criticism against the Goliath of Epic Systems.

AMM (15:09)

I would guess that we’re going to see Particle Health out in the world in a bigger way throughout this process and that this lawsuit set the foundation for them to do that. And this is the exact kind of work that we like to do from a high stakes lawfare perspective. And Quinn Emanuel’s filing read just like a strategy plan. It’s going to be really great to see.

AMM (05:28)

All right, next up we have clothing manufacturer Shein pulls listing that used Luigi Mangione’s likeness to model a shirt. This was an NBC News headline. It was covered pretty broadly. So Shein is a company that sells clothes. They put up product photos all the time, all over their website and their social channels and their advertising. They used a model that appeared to look like Luigi Mangione, despite the fact he’s incarcerated and alleged of committing murder. It really sparked questions about both the marketing side of things, how that impacts the business overall, and also using AI. Shein’s reaction when called to the coin on this was that, you know, we use a third party vendor that uses AI and they put together a picture that just happened to look like this guy. You know, I’ve got two schools of thought here.

One, If I’m Shein and I’m looking to make headlines and I need to juice sales, no better way to get folks to go look at your website than to do something like this. That is a classic PR stunt. However, as a company, they have a lot of reputational challenges already. And I’m more inclined to think somebody didn’t talk to somebody else in the marketing department. And this came to be by accident. You know, they’re a Chinese company. They’re a fast fashion company.

They’ve got a decent amount of Washington issues. There’s a lot of regulatory and tariff conversation around things between China and the US right now. So my hope is that they are smart enough to fall into the category of we don’t want to actively do any harm. And this was just an unforced error, not something that was orchestrated. But for me, there’s a few things that this raises on the AI side of things.

these AI systems, these LLMs are being trained in part by what’s available on the internet. So if there’s a news story about an alleged murderer that is really getting a lot of traffic and that face is in all of the photos that are in Getty Images and elsewhere, that’s likely gonna be something that AI picks up on more so than my picture, which just happens to be in a few places on the internet. That’s gonna be a real challenge and I think it’s gonna be something that both the tech companies running these AI platforms need to look at and also anybody using AI generated images needs to be mindful of. And the other thing it raises for me is that companies need checks and balances that include humans before things go out. Particularly when it comes to marketing organizations need clear approval processes that include the human element that can discern something that they may have seen or just have a little spidey sense that says maybe we should look at this one more time.

What’s interesting here with Shein, and I think the actionable insight for anyone to take away is if you’re going to use AI, you still need human involvement in some capacity. In the marketing case, they need clear approval processes that include real people. So someone is looking at those images and going, maybe that doesn’t look quite right. For those using AI for efficiency’s sake, you still need to check work because AI is not in a place where it is human.

We cannot expect artificial intelligence to fully understand cultural flashpoints, particularly in real time. These LLMs are moving fast, but not fast enough to know that yesterday’s news is gonna be something that my marketing campaign needs to take into account.

Stacy (08:22)

The only thing I would add, Anne Marie, is that, you know, knowing the volume of clothing that Shein puts out, we talked about this before, it seems very challenging that if they’re going to use a different model for all of their pieces that they would be able to catch, even if they had a human in the loop. So your caution is well taken that folks need to really look closely at the vendors they’re using and what their AI tools are trained on.

And this is a great segue into the next headline, which is about another vendor of many companies called Workday. The headline is What the Workday Lawsuit Reveals About AI Bias and How to Prevent It. This was in Forbes. This is a very interesting case to me. It is a lawsuit that was brought by Derek Mobley, who is an African-American. He purports to be over 40 and have certain health issues.

He applied for more than 100 jobs at different employers, all who used the Workday hiring recruitment platform. And all of those applications were rejected. Some of them were rejected in the middle of the night. Some of them after, you know, an hour after he applied. And I don’t know how he got the goods, but he got information about the algorithm and was able to show commonality among, at least at this stage, the judge recently approved a collective action, which is a discrimination lawsuit, which is very rare. It is very difficult to show that there’s been uniform common practices that have discriminated against groups of people. AI tools are a great way to show that because they’re built on algorithms and trained on a certain data set.

So this is gonna be very interesting for those of you who may not be aware, Workday is a pervasive, widely used ERP system. And the company themselves said that they, in their court filings, said that 1.1 billion applications have been screened using their tool. So this is a class action of a magnitude we have not ever seen. So again, there’s more and more tools out there, and this Workday is a vendor for many employers. So similar to the Shein situation, you have vendors using tools and puts an incumbency on the companies that work with those vendors to ensure that they are using those tools fairly and that they’re designed fairly.

AMM (10:52)

in hiring, it’s, you post one job on LinkedIn and you get thousands of resumes. I guess the one advantage of LinkedIn is that you generally see, maybe it’s not an advantage, you see a photo. So you would, if you were using the Workday system and you would see that on LinkedIn and you don’t see any African-Americans, that might be a flag to you that something is wrong. I’m curious if it will become apparent throughout the course of this litigation of what folks saw on the hiring manager side versus the ERP itself of, I went in there and I saw a bunch of resumes and everybody’s name was Jane Smith. Or what comes to bear? Because you know that there will be a very interesting and probably long discovery process. Depositions there could be fascinating. And you and I came together initially on a class action that was pretty large. And this one’s going to blow that out of the water.

Stacy (11:41)

No question, no question. And to your point, this is a tip of the iceberg because this is a case against the vendor. But I would anticipate that the companies that used this tool will then be next in line. So it really is a call to action for folks to just really do your diligence. You know, we are, as we said at the outset, in an AI gold rush. Everyone is excited. People are moving fast. but sometimes you gotta go slow to go fast.

AMM (12:09)

Here’s your actionable insight on this one. If you use Workday at your organization, or if you don’t know if you use Workday at your organization and you’re in comms and legal, you need to find out. To start prepping for what may be next, because it is Workday that’s in the hot seat right now. But if we know anything about what class action litigation looks like, it’s always the downline companies next, and there is nothing stopping that. So look hard, look quickly, and get ready.

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