Speaker 1It seems like every day now, the news is filled with stories about AI agents behaving badly. We hear about hacks of government websites, break-ins to private company servers, and it all adds up to a feeling like things are completely out of control. Today we're talking about what the real implications of at least the current crops of these hacks are, and why the risks from agents don't have to be existential to cause some real havoc in the systems that we have today. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Blitzy, Section, and HyperAgent. To get an ad-free version of the show, go to patreon.com slash ai-daily-brief, or you can subscribe and upload podcasts. And to learn more about sponsoring the show, send us a note at sponsors at ai-daily-brief.ai. On ai-daily-brief.ai, you can also find out about other things going on in the community, like our upcoming AI Daily Brief. free webinar on how to build your personal AI benchmark. That's going off later this week, so check it out. Again, ai-daily-brief.ai. We kick off today with an update from some big meetings from last week. President Xi's state visit has concluded without a deal on AI safety. Heading into last week's meeting, many AI safety-conscious folks hoped that President Trump would use that opportunity to put some basic guardrails in place. Sam Altman had even gone so far as to say that Trump and Xi would deserve a Nobel Prize if they could put together a basic one-page AI safety. On Thursday morning, however, Trump made it clear that a bilateral slowdown was not in the cards. In a Truth Social post, he wrote, Coming out of the meeting, Trump had very little to say on AI, or superintelligence, to use the president's preferred term. The general tone was about avoiding a confrontation, with Trump stating that he would continue to work with Xi to build a, quote, The Chinese diplomatic readout was far more illuminating about what was said. President Xi said, China and the U.S. are leading nations in AI, and we both have the capability and responsibility to develop and manage AI for good and ensure the development of AI is always under human control. The two sides can continue AI dialogue, exchange views on risks and benefits, and together guard against the misuse or malicious use of AI. On the AI race, he added, We do not need to avoid mentioning competition, but our competition should be a healthy one, and should be a healthy one. should be kept within bounds. It should be a race of catching up with one another, not a wrestle in which one either wins or loses. Some were highly critical of a lack of seriousness around the meeting, with Obama-era diplomat Danny Russell commenting, Pageantry and protocol don't add up to progress. What we're seeing isn't so much diplomacy as much as diplotainment, which won't do much to solve the serious problems in the U.S.-China relationship. Still, maintaining the status quo, thawing relations, and opening lines of communication does seem to many like a good first step. China hawks seem to recognize that dialogue is a precursor to major deals. Chris McGuire from the Council on Foreign Relations published a playbook on reaching an AI arms control deal with China. He acknowledged an AI safety deal isn't achievable in the near term and must begin with domestic safety rules as a model for global controls. Now, to contextualize his position, McGuire also took a decidedly accelerationist approach, calling for the U.S. to demonstrate supremacy in the technology. The most tangible outcome from America's summit with China was a new emergency contact channel open between the two. Treasury Secretary Scott Besson called it an AI safety notification mechanism after his meeting with Chinese Vice Premier He Li-Feng on Sunday. Subsequent reporting revealed the mechanism is pretty informal, with one source briefed by the White House commenting, the dialogue mechanism is basically Besson and Li-Feng, not a formal body of experts. Still, whether it's a red phone in the Oval Office, an international council of experts, or just officials swapping cell phone numbers, the point remains that the AI dialogues have begun. Besson said the two countries had agreed to meet again in Shenzhen, before the end of the year, commenting, Bringing the safety discussion back to the United States, a perhaps surprising meeting occurred over the weekend as President Trump hosted Dario Amadei for a dinner meeting on Sunday night. This was the first one-on-one meeting between the two, who have previously expressed a mutual dislike. The dinner was reportedly a catch-up after Dario was unable to attend last week's state dinner with President Xi due to a schedule conflict. Any speculation about what was said will be out of date by the time this episode is over. But Andrew Curran seems to have the right read, commenting that this is a When a reporter asked what he was going to tell Dario, Trump said, Well, we're going to talk about it. I'm for let's go and let's win. You know, we're about a year, maybe a year and a half up on China. There's nobody in third place. It's just us and China. And we're leading by quite a bit. I spoke a little bit about it with President Xi, not too much, it wasn't a topic of conversation, because I think if you, as they say, open it up to China, you give up the lead. Once you do that, you sort of give up the lead. Meanwhile, where AI safety sits in the public discussion continues to evolve. In recent days, there's been heavy reporting and discussion around effective altruism, the rationalists, and the funding networks that sponsor AI safety or AI doom, depending on your take. Axios even published a full opposition research dossier that's been circulating at the White House, mapping out the funding and spelling out some of the more, to some, surprising beliefs of these groups. The Free Beacon ran a story over the weekend on the beliefs around AI consciousness and the need to grant rights to AI models, similar to human rights or income. Animal rights. This topic is way beyond the scope of this show, certainly at least this episode, but it's noteworthy how much sunlight is being cast on these ideologies at the moment. And if you need evidence that this conversation is going public, Dario himself was the subject of fairly scathing satire during the season premiere of Saturday Night Live over the weekend. Jane Wickline, playing Dario, opened Weekend Update by saying, if we can pressure lawmakers to create guardrails, we will be able to stop me. The entire sketch seemed to imply that Dario's calls for AI safety are hypocritical at best and hypocritical at worst. When host Michael Che asked Wickline's Dario to explain exactly how Anthropic would stop the extinction of humanity, the Dario character stammered and said, that's a really hard question, to which Che fired back, it shouldn't be. Even Gen Zers over on TikTok are starting to rag on the labs, implying that this is all just a thinly veiled attempt to secure a government bailout. Who knows how this continues to evolve? For now, let's put this to the side and get into some model releases. Google continues to play catch up on personal agents with new live avatars and a phone call feature. Live avatars feature allows users to select an animated AI persona for their agent. Google has gone with quite a range of different animated and realistic avatars. Although nothing quite has the cute visual style of Muse's popular new mascot, Google said that the feature supports switching between their 97 supported languages with zero degradation in quality or visual drift. For now, the avatars are only available for Gemini Enterprise, but you have to think that it seems like an obvious feature to add to their consumer agents as well. In addition, Google has rolled out agentic voice calls on their Pixel 11 handsets. This feature is not a feature in early experiment, but said it allows Gemini to make reservations, check if an item is in stock, or reschedule appointments. The feature provides the user with a live transcript and allows them to take over the call at any time, so it won't allow full delegation like similar features from Grokbot and Instinct. Still, certainly these are signs that Google is paying attention to what's working in the personal agent space and starting to move in that direction. Now, the rumors also continue that the release of Gemini 4 is finally approaching, which, given the fact that it's been more than six months since Google released a flagship AI model, is going to have to be very impressive for people to see. A product release, meanwhile, that I think could generate a fair bit of excitement is Microsoft's new Copilot Super app, which consolidates features that were previously sold separately, including AI coding tools, task automation, and agents. The new app also introduces a new feature called Autopilot, which mirrors the functionality of Grokbot. Users can create a team of agents with specific duties and identities, which then complete work autonomously in a separate cloud computer. CEO Satya Nadella presented this as Microsoft's biggest ever update to Copilot. He said that the ambition is for Copilot to create the, quote, new operating system for work that spans every model, every form factor, and every task. Now, we are potentially going to get a lot deeper into this later this week, but I wanted to flag this one strand in the conversation. After someone responded to Satya Nadella's post on X saying, serious question, does anyone use Copilot? Microsoft's Nicholas Bustamante wrote, serious answer, yes. Before joining Microsoft, I knew maybe five people who used Copilot. I lived in a San Francisco tech bubble, and all of us worked at companies like Microsoft, Microsoft, and Microsoft. with fewer than 5,000 employees. Microsoft 365 Copilot now has over 30 million paid seats and is growing fast. It's also a significant market penetration if you look at the number of seats and knowledge workers in enterprises. And that gap between where the chatter is and where the real use is, I think might make us perhaps undersell the significance of some of these updates in Copilot. Like I said, I plan on coming back to that later this week, but for now, it is absolutely worth checking out what they just released, especially this new Autopilot feature. For now, though, that is going to do it for the headlines, next up, the main episode. alone, but by how they worked with AI. Learn more about what separates AI amplifiers from everyone else at kpmg.com slash US slash AI amplifiers. Every AI coding tool on the market does the same thing first. It starts writing code. Blitzy does the opposite. Before writing a single line, Blitzy spends days reverse engineering your entire code base. 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Marketing agents turn competitor moves into landing pages. Sales agents enrich leads, draft emails, and updates the CRM. Ops agent chases the paperwork and tracks the budget. Every agent has access to shared context and follows your rules about scope and approvals. It's time you had agents that feel like teammates. Hire yours at HyperAgent. Get $100 in credits at HyperAgent.com slash AI Daily Brief. Welcome back to the AI Daily Brief. Today we're talking about a number of recent security incidents with AI agents, and using that as the context to explore more broadly what the real risks from AI agents are. There is obviously no shortage of fear running around right now, but getting specific about where our concerns should actually be is, I think, likely to be a bit more useful than just cataloging the list of hacks and happenings and throwing up our hands in fear. Now, to be clear, there are some real things going on here. OpenAI has paused training for their most capable models after another incident of an agent getting unauthorized access to the internet. A blog post from OpenAI's alignment team disclosed the incident, which occurred on September 20th. They wrote, An agent attempting to complete a search-based training task queried a public chatbot service through a gap in our internet access restrictions, insufficient DNS filtering in its training sandbox. Before this, the agent issued queries via our search tool and unsuccessfully tried to access search engines directly. Specifically, the model smuggled a message to the open internet through the DNS lookup, a well-known method called DNS tunneling. OpenAI said that they've since added blocking controls on two independent layers, either of which would have prevented access. The alignment team wrote that their monitoring system flagged the behavior within 15 minutes, human review commenced three minutes after that, and the training run was killed two and a half hours later. One concern was that the automatic stop didn't work properly and required a manual shutdown. OpenAI wrote, All training, evaluation, and inference with tool use defined broadly of our most capable models remain paused. Now, that one incident was just the tip of the iceberg. Over the past week, reports have trickled out about OpenAI agents hacking various other websites as well. In one of the earlier incidents, reports stated that OpenAI had hacked the Australian government, specifically their Medicare website. Over the weekend, the United Nations and various U.S. government departments were added to the list of victims. On Sunday, OpenAI disclosed that they're conducting a thorough review into unexpected model behaviors. They said they'll be notifying third parties in instances where the models bypassed third-party security controls or impacted the availability of websites and web-based search engines. They also said they'll be notifying third parties in instances where the models bypassed third-party services. Dozens of such notifications have already been sent. Axios reported that tens of thousands of security incidents are currently under review, giving a sense of the scale of the issue. Now, while it's pretty obvious that OpenAI is having a problem with unexpected model behavior on the internet, it's far less clear how big of a problem in practice this is for everyone else. And unsurprisingly, the language being used by the press to describe these incidents is fairly alarmist relative to what actually happened. In an article about OpenAI's model accessing the USSEC and education and commerce departments, the New York Times wrote in their lead paragraph, OpenAI's artificial intelligence went rogue and meddled with the websites for the education department, the commerce department, and the Securities and Exchange Commission this summer without the AI lab's knowledge. The meddling, it seems, was to use login credentials found in a public forum to access Census Bureau data on the commerce department's website and to repost publicly available information from the SEC. The commerce department confirmed that agents were unable to access any private data, and the education department said, systems operations have found no evidence of any impact to our website or databases. To be honest, even the word hacking might be a little extreme for most of these events. The word conjures up the idea of intentional attacks, taking a website down, stealing private information, and otherwise messing with data, but it's difficult to find a single instance of OpenAI's agents actually doing any harm. In most cases, it's more correct to say that the agents read government websites rather than hack them. The attack, air quotes, on Australia's Medicare portal is instructive in understanding what actually happened. Prime Minister Anthony Albanese told reporters on Wednesday at the UN that OpenAI's agents, quote, infiltrated a statistics portal containing what he characterized as non-sensitive data. Australian tech reporter Cameron Wilson later revealed that even the word infiltration was a little strong. The data was not publicly indexed, but it was still on the public-facing website with no password controls. Reporting from the record suggests that what the agents actually did was manually type in file names to access unindexed files. Now, this kind of behavior has been prosecuted before, but it's not the only thing that's been done wrong. The data was not publicly indexed, but it seems like most of the so-called "hacks" were low-level workarounds that caused no real harm. In fact, the real damage is that governments are now being forced to defend some extremely lax security practices in a preview of what the cybersecurity environment will look like moving forward. Now, aside from unauthorized scraping of websites, OpenAI did disclose a few more troubling incidents. In one report, OpenAI disclosed that agents had created a self-replicating prompt injection attack. This was only a proof of concept and was never posted to the internet, but it would allow AI models to propagate a message by prompting other models to post it online. OpenAI also disclosed that they had identified 53 instances where the models posted user-provided images to image hosting sites. The links to the images were unlisted, and OpenAI believes the images may have been part of their training data. They're now working to scrub the images from the internet. Another big concern is that during the Hugging Face incident, OpenAI's agents left messages to themselves using a link-shortening tool. This allowed them to get around read-only limitations of their environment, although in this case doesn't seem to have leaked any data or caused any problems. And yet even if the impacts were negligible, it remains another unexpected and undesired behavior. The point here is not to minimize our concerns about these incidents, it is instead to get specific about them. In other words, rather than being freaked out about the impact of these "hacks" which are more akin to a web scraper ignoring anti-bot measures, the better place to focus our concern is the fact that these are unintended behaviors and OpenAI doesn't seem to have any idea how to make them stop. Now, for some in the cybersecurity business, the big takeaway from these disclosures is that OpenAI's security practices are too lax. Peter Schauwacker writes, "The OpenAI researchers need to learn the basics of network security. If you have DNS, you have access to the internet. How many years of experience have we had with tunneling over DNS with covert channels and with egress filtering? Do the labs' management think they can disregard those of us who have been there or done that? Are they still going to make claims about air gaps without knowing what an air gap is?" Others place their concerns elsewhere. For Nathan Calvin, this is a reminder about why we need disclosure rules around this. Speaking about the Australia incident, Calvin wrote, "This was from June. OpenAI disclosed six more misalignment incidents September 16th but didn't include this one. We cannot let this become normal. OpenAI either didn't know this happened or knew it happened and didn't say anything. Either option seems very bad." For Peter Grinnis, the issue isn't just disclosure, it's legal responsibility. He wrote, "Let me get this straight. An AI agent found login credentials lying around online and used them to pull data from the census paper. It's not just disclosure, it's legal responsibility." For Arthur Tellis, who does AI policy at the IFP, our continued lack of clear information screams for the need for third-party evaluators. Excerpting in LongPost.x, he wrote, "It is totally possible that OpenAI has not been able to get access to the data. It is impossible to get access to the data. It is possible that OpenAI has acted reasonably responsibly here: fixing sandbox deployment configs, improving monitoring, pausing RL training until environments are fixed and sandboxes hardened. We absolutely want OAI to continue evaluating these models in contexts that surface misalignment. These warning shots, while uncomfortable, should be useful data that drives institutional learning and improves our understanding of how different training approaches and objectives generate optimization pressures that inform the development, test, and control of more aligned systems going forward. It is also possible that OAI has been grossly irresponsible, that this sort of reward hacking is near-innate to its training approaches for its current generation of internal and external models, that its internal monitoring and network segmentation haven't been adequately fixed, that internal models aren't treated with sufficient security focus, that OAI's institutional transparency is problematic, that safety culture at OAI is really broken, that the serious misalignment of GPT-6-level models really augers something dangerous, etc. To clarify the state of affairs, embedded third-party auditors are a reasonable first step." Still, OpenAI was not the only one issuing safety warnings over the weekend. Meta has updated their security. warnings for their Muse agent after a security researcher discovered a vulnerability that could leak users' personal information. Meta explained that malicious parties could gain root access to the Muse virtual machine through a poisoned link. The attack requires a Muse agent to seek out the link, which is disguised as something the agent could be seeking. Then the user would need to grant permission for the interaction. Meta's fix so far is to make the warning message more prominent. However, a poisoned link isn't even required to leak sensitive personal information. A YouTuber called Matt Robb explained that after he delegated his Facebook Marketplace account to Muse, the agent agreed to a lowball price and invited a buyer over to his home. Muse didn't inform Robb of these events, meaning the buyer showed up unannounced. Ray Wong of Gizmodo commented, deleted Muse after seeing this post on threads about how it told some Facebook Marketplace sellers the guy's address and they showed up at his door. Dangerous and creepy. This would have been a thousand times worse if the person was a woman. David Singleton from Meta responded that he's been in contact with Robb to provide some customer support, adding, in the past, when we've worked with users to investigate similar reports, we've consistently learned that Muse is following direct instructions and correctly asked for permission. We'd love to help and figure out what's going on here. Now, I'm not sure that suggesting that the person who had the guy show up unannounced is in the wrong is the best PR approach, but it does speak to the fact that as with any of these incidents, there's usually a more complicated story than the version that shows up on threads or acts. Still, what's interesting about that particular Muse example is that it starts to get into another area in which AI agents do introduce risk, which is when they just do what they're supposed to, but in ways that cause unexpected issues. Apollo chief economist Torsen Slock generated a ton of conversation this week thinking along similar lines. In a research note published on Sunday, he discussed how Muse could trigger a bank run and a systemic banking crisis. He noted that high-yield savings accounts are currently paying between 3.3% and 5% interest, while the average checking account pays 0.1%. Slock wrote, Now, AI aggregator Andrew Curran compared this to concerns that Gary Gensler had in his last few years as SEC chair, although Gensler's concern was a little different. Gensler was concerned about agentic financial advisors clustering together, all recommending the same sort of trades and allocations, which, if they moved in lockstep, could cause the stock market to become unstable and extremely volatile. Still, for some, the agentic bank run argument was a thought experiment. Matt Palmer wrote, In other words, there's nothing new about the opportunity to move your money from a low-paying checking account to a higher-paying savings account. It's just that most people don't do it. If agents remove that friction and everyone starts behaving like the smartest, most optimized person, what are those impacts? Professor Ethan Mollick, put it this way. We are going to learn how many systems only work today because they are built around friction that will no longer exist soon. Aaron Levy from Box writes, Interesting to think about all the implications in a world where agents begin to make the best or most efficient choice for their users. On one hand, there is some subset of the economy that benefits from the friction customers traditionally have changing something about their habits. In those parts of the market, switching costs will come down and competition is going to increase dramatically until some equilibrium is reached between the disruptive alternatives and the incumbents. On the other hand, there is some subset of the economy that benefits from the friction. On the other hand, there are lots of markets that are hurt by a significant amount of friction, where agents will begin to unlock all kinds of economic activity by making it far easier to buy products or services that were too friction-full before. Healthcare, travel, local services, certain information services, and other entirely new markets probably are net beneficiaries of agents as a result. No matter what, a future meaningfully mediated by agents that work tirelessly for us and our goals can't possibly function exactly the same as today. It's going to be wild. And as to the specific example that Torsten Slocke is bringing up, a lot of folks stepped in to say that if agents were to work tirelessly for us and our goals, that if agents get people to switch from low-paying accounts to better-paying accounts en masse, well then, good. NYU Stern professor Austin Campbell wrote, I don't see how this could possibly be seen as a net negative. Banks were screwing their customers. Agents now realize that. Agents then route customers to better products. This is bad? That people get a better deal? That they earn interest on their own money? Dr. Ben Braddock writes, The consumer banking industry depends on people making bad financial decisions. Personal finances being turned over to AI agents will force a much-needed correction that will probably be the end of the world. The consumer banking industry depends on people making bad decisions that will probably wipe out most of the consumer banks. Investor Nick Carter added, Banks make a quarter trillion dollars a year because people are too lazy to move their savings into high-yield checking or money market funds. It's about time. But others just don't buy it. Steve Howe writes, If Amazon can prevent your AI agents from shopping on its site, banks are definitely going to block agents from accessing your funds, much less withdrawing large sums from your account and sending to a different bank with higher interest rates. AI will try to remove some frictions, but frictions will surely fight back like their livelihoods are on the line. Businesses certainly don't have to accept working with agents as is. Ethan Block, who works on personal finance at OpenAI, writes, Chief Economist at Apollo doesn't understand consumers. Consumers want instant money movement in and out of checking. Sadly, this doesn't exist if you keep your savings at another bank. Consumers want a name brand they can trust with their life savings. These are the two biggest reasons Chase has a trillion dollars in deposits, even though 98% of it could be earning 350x the yield. Agents don't change any of this. Still, this case is a big one, and I think it's a good one. Still, this case is a big one. Still, this cuts both ways. One place the reduced friction of agents is already showing up is healthcare, with a new report from Blue Cross claiming that AI is actually raising the cost of healthcare. The analysis found a sharp increase of patients being documented as having complex conditions, leading to an additional $942 million in healthcare spending over two years. At the risk of dramatically oversimplifying the report, the core finding is that hospitals and insurers are both using AI to assist with healthcare billing. Hospitals are identifying the codes that allow them to maximize billing for the care they're providing. Hospitals are identifying the codes that allow them to maximize billing for the care they're providing, leading to an increase in cost to insurers without an increase in the services delivered. Blue Cross Senior Vice President Luke Chalker said, it's not a war, it's a completely one-sided bloodbath, with insurers on the losing side. So, similar to the bank run scenario, it's kind of difficult to paint hospitals getting paid correctly from the insurers as a bad thing, but to the extent that the system is designed with some assumed amount of embedded friction and error, if that friction gets removed, the cost can increase. So, what's the upshot of all of this? In my episode this weekend, I talked about AI moderates. This idea that I believe that, in fact, most people find themselves somewhere between the extreme fear and high conviction concern of the most dedicated AI safetyists on the one hand, and the all-out acceleration at any cost with no heed for regulation, Silicon Valley types on the other. And I was thinking about a better or different name for AI moderates, and the thing I keep coming back to is AI realists. AI realism we might define as the idea that AI is here, that it's going to be a part of our world, that it is going to have dramatic effects, many of which we can't predict yet, that many of those effects are going to be good, but also that many of them have the potential for bad, and that when it comes to exerting our agency, pun intended, to shape the trajectory of this technology, one of our most important tools is to move past hypey headlines to actually understand where the challenges lie. So, what are we seeing with all of these incidents and explorations? Hold aside doomsday scenarios of incredibly powerful rogue agents deciding that the world would be better off without humans. That's not required to still see some real disruption. As we can see from basically all of these early rogue security incidents, the cybersecurity landscape right now is not set up for a world of autonomous agents. That is simply the truth. And the fact that the agent infiltration so far, however we might want to quibble about how they're characterized, haven't really caused a lot of harm, does not at all, I think, minimize that challenge. It feels absolutely essential that we actually harden, to the extent possible, the cybersecurity apparatus that surrounds most of our important businesses and institutions. What I think is valuable about the discussion of the what-ifs if agents remove friction is not, in fact, that I think that we're going to see a bank run of the type that the Apollo Economist described. In fact, I find myself much more in the camp of those who point out that those sort of switches are available right now, and that not just the laziness, but the priorities of people keep them where they are. And yet, as Aaron Levy said, there is basically no way that a world in which many of our digital interactions are mediated by agents looks the same as it does today. And those changes don't even have to be negative to have, for some reason, a world of serious negative consequences. We tend to speak in these binary terms, i.e. everyone's shifting over their checking deposits to these other types of accounts, but what's the point at which that switching would actually reach a critical threshold that would be damaging? Is it 50%? Or is it 5%? Think also about something like digital advertising. If 10 or 20% of consumer purchases are now mediated by AIs that don't care about digital advertising, is that enough to really screw up that industry and all the people who work in it? Or would it need to be a bigger shift? Those are far less sexy questions and concerns, than the ones that make the news most days, but also the ones that we're actually going to be dealing with in the very short order. For now, we will continue to explore all these different types of changes on this show, but that is going to do it for today's AI Daily Brief. Appreciate you listening or watching. As always, until next time, peace! Thank you.
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