Hello and welcome to Eye on AI. In this edition….Mobile networks don’t want to miss the AI game but it’s not clear they have the best hand to play; the U.S. State Department starts using AI to help target foreign students for possible deportation; OpenAI finds that chain of thought monitoring can detect ‘reward hacking,’ but only if the model doesn’t know you’re looking; can AI bring us closer to God?
I spent last week at Mobile World Congress in Barcelona, where AI was the overriding theme of the show. But beyond the hype around AI, a hint of desperation lurked behind the flashy stands and demos.
Mobile network providers lament the fact that they provided the essential “pipes” on which the app economy was built in the decade following Apple’s 2007 introduction of the iPhone. Yet most of the value created during the mobile revolution flowed to what the mobile folks call “OTT” (short for over-the-top) companies, such as Meta and other social media apps, ecommerce sites like Amazon, and the streamers, from Spotify to Netflix. Now they are worried that the AI revolution will similarly leave them in the position of being a mere utility—and valued as such by investors—while the big money accrues to the OpenAIs, Anthropics, and Googles of the world.
Hope is not a strategy
But, as they say, hope is not a strategy. And it isn’t entirely clear what these carriers can do to avoid once again being relegated to utility status. French mobile provider Orange has started selling an AI assistant—which it calls Dinootoo—that it orignally built to help its own employees. But it is not clear why businesses would necessarily choose Orange’s Dinootoo over similar products offered by OpenAI, Anthropic, Microsoft, or Salesforce. So I am not convinced the mobile carriers can win at this game.
The fact that a U.S. court has now struck down net neutrality—which forbade carriers from charging customers more to prioritize their traffic across the network—at least at the federal level (some states have their own net neutrality laws), will give some U.S. carriers a chance to grow revenues. But there’s little sign of net neutrality going away in Europe or many other geographies. The carriers are also betting big on the idea that many enterprises will want to set up private 5G—and, yes, future 6G—wide area networks to serve campuses or big geographic footprints. This is a good business, but probably not enough to let carriers claim a big boon from the AI revolution.
The handset makers have an AI play
The mobile handset makers, such as Samsung, and the chipmakers who serve them, such as Qualcomm, have a somewhat more convincing AI story to tell. They see a future in which your interactions with an AI assistant largely take place on your phone. In essence, the AI assistant becomes the phone’s new user interface—interacting with you through multimodal inputs (largely voice, but also text and images taken from your phone’s camera.) The assistant will be an agent, performing tasks for you using your phone’s other apps and the phone’s internet browser.
As AI models deliver more reasoning capabilities in smaller packages, these hardware companies are betting that these models will be able to live on your phone. “AI will have to be hybrid, not everything is going to go to the cloud,” Don McGuire, Qualcomm’s chief marketing officer, told me. “You're going to be able to do lots of things by using Gen AI without you having to ping the cloud. That will create better environments for users and applications from a privacy, safety, personalization, and latency perspective.” It will also, he noted, mean users can access the help of their AI assistant even in cases when they don’t have signal. (Note that in many ways “AI on the edge” is not good news for the network carriers.)
Shopping assistants
One evening in Barcelona, I had the pleasure of moderating a dinner discussion on AI and retail cohosted by Fortune and Shopify. Peyman Naeini, Shopify’s field CTO, talked about a world in which customers increasingly discover products through the recommendations of AI assistants and AI-powered search engines, rather than through traditional search. In many cases, these AI assistants will increasingly act as agents, doing the purchasing on behalf of users. It’s a world that most retailers, Naeini said, are not really prepared for.
How will our AI assistants decide which products to bring to our attention or buy on our behalf? It isn’t entirely clear. (I hope that, however it happens, that we have some insight into the process. If there is a paid relationship between the company providing the AI assistant and the brands being recommended that should be completely transparent. I fear that it won’t be.) Customer reviews might form a key datapoint that an AI assistant considers. But in an era where generative AI makes it easy to produce thousands of convincingly-realistic fake customer reviews at the press of a button, how will we ensure that we can trust such reviews?
Trust as a service
Well, Adrian Blair, the CEO of Denmark-based Trustpilot, which is well known for its customer reviews and ratings of businesses, has spent a lot of time thinking about this problem. Blair told me last week that Trustpilot gathers hundreds of meta datapoints for each review posted—including the customer’s email address, the location and time of day they are posting the review, the kind of device they are using, how much of the review was cut and pasted and how many seconds it took to be written, and many many more. With an average of 190,000 new reviews submitted daily, and a total catalog of more than 300 million reviews, the company has a lot of data from which to build AI models that can assess the likelihood that a review is fake. Last year, about 6% of all the reviews submitted to Trustpilot were blocked or removed on suspicion of being fake, and 82% of these were caught by Trustpilot’s automated systems. The advent of generative AI has seen the number of suspect reviews climb, Blair says, but he says it is more of an incremental increase than a flood.
Yesterday, at the HumanX conference in Las Vegas, Trustpilot announced that it is now making its customer review data available through a platform it is calling TrustLayer. This will let third-parties, including AI assistants and agents, directly access data from Trustpilot’s customer reviews, allowing them to gain insights into how a brand or product is perceived by its customers.
TrustLayer is being primarily marketed at companies that want to monitor their own consumer sentiment more easily—and potentially assess themselves against rival firms. The first announced customers for the new platform are private equity firm Advent and venture capital firm Felix Capital that want to use the data to conduct due diligence on possible investments and also to benchmark how their portfolio companies are performing with customers. But Blair sees companies building AI assistants as a key future customer. “I can definitely see a world where ‘shopping agents’ want to make use of our platform to do a better job themselves,” he told me. And of course, we might be able to rate our AI agent experiences on Trustpilot too.
With that, here’s more AI news.
Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn
Correction, March 12: An earlier version of this story misidentified the country where Trustpilot is headquartered. It is Denmark. Also, a news item in this edition misidentified the name of the Chinese startup behind the viral AI model Manus. The name of the startup is Butterfly Effect.
