Blog: August 2023 Archives

Own Your Own Government Surveillance Van

A used government surveillance van is for sale in Chicago:

So how was this van turned into a mobile spying center? Well, let’s start with how it has more LCD monitors than a Counterstrike LAN party. They can be used to monitor any of six different video inputs including a videoscope camera. A videoscope and a borescope are very similar as they’re both cameras on the ends of optical fibers, so the same tech you’d use to inspect cylinder walls is also useful for surveillance. Kind of cool, right? Multiple Sony DVD-based video recorders store footage captured by cameras, audio recorders by high-end equipment brand Marantz capture sounds, and time and date generators sync gathered media up for accurate analysis. Circling back around to audio, this van features seven different audio inputs including a body wire channel.

Only $26,795, but you can probably negotiate them down.

Posted on August 31, 2023 at 7:06 AM15 Comments

When Apps Go Rogue

Interesting story of an Apple Macintosh app that went rogue. Basically, it was a good app until one particular update…when it went bad.

With more official macOS features added in 2021 that enabled the “Night Shift” dark mode, the NightOwl app was left forlorn and forgotten on many older Macs. Few of those supposed tens of thousands of users likely noticed when the app they ran in the background of their older Macs was bought by another company, nor when earlier this year that company silently updated the dark mode app so that it hijacked their machines in order to send their IP data through a server network of affected computers, AKA a botnet.

This is not an unusual story. Sometimes the apps are sold. Sometimes they’re orphaned, and then taken over by someone else.

Posted on August 30, 2023 at 9:39 AM14 Comments

Identity Theft from 1965 Uncovered through Face Recognition

Interesting story:

Napoleon Gonzalez, of Etna, assumed the identity of his brother in 1965, a quarter century after his sibling’s death as an infant, and used the stolen identity to obtain Social Security benefits under both identities, multiple passports and state identification cards, law enforcement officials said.


A new investigation was launched in 2020 after facial identification software indicated Gonzalez’s face was on two state identification cards.

The facial recognition technology is used by the Maine Bureau of Motor Vehicles to ensure no one obtains multiple credentials or credentials under someone else’s name, said Emily Cook, spokesperson for the secretary of state’s office.

Posted on August 29, 2023 at 7:03 AM12 Comments

Remotely Stopping Polish Trains

Turns out that it’s easy to broadcast radio commands that force Polish trains to stop:

…the saboteurs appear to have sent simple so-called “radio-stop” commands via radio frequency to the trains they targeted. Because the trains use a radio system that lacks encryption or authentication for those commands, Olejnik says, anyone with as little as $30 of off-the-shelf radio equipment can broadcast the command to a Polish train­—sending a series of three acoustic tones at a 150.100 megahertz frequency­—and trigger their emergency stop function.

“It is three tonal messages sent consecutively. Once the radio equipment receives it, the locomotive goes to a halt,” Olejnik says, pointing to a document outlining trains’ different technical standards in the European Union that describes the “radio-stop” command used in the Polish system. In fact, Olejnik says that the ability to send the command has been described in Polish radio and train forums and on YouTube for years. “Everybody could do this. Even teenagers trolling. The frequencies are known. The tones are known. The equipment is cheap.”

Even so, this is being described as a cyberattack.

Posted on August 28, 2023 at 7:05 AM50 Comments

Friday Squid Blogging: China’s Squid Fishing Ban Ineffective

China imposed a “pilot program banning fishing in parts of the south-west Atlantic Ocean from July to October, and parts of the eastern Pacific Ocean from September to December.” However, the conservation group Oceana analyzed the data and figured out that the Chinese weren’t fishing in those areas in those months, anyway.


blockquote>In the south-west Atlantic moratorium area, Oceana found there had been no fishing conducted by Chinese fleets in the same time period in 2019. Between 1,800 and 8,500 fishing hours were detected in the zone in each of the five years to 2019. In the eastern Pacific zone, China’s fishing fleet appeared to fish only 38 hours in the year before the ban’s introduction.

“Ending squid fishing in areas where there is no fishing does nothing to protect squid,” said Oceana’s campaign director, Max Valentine.



As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Posted on August 25, 2023 at 5:06 PM78 Comments

Hacking Food Labeling Laws

This article talks about new Mexican laws about food labeling, and the lengths to which food manufacturers are going to ensure that they are not effective. There are the typical high-pressure lobbying tactics and lawsuits. But there’s also examples of companies hacking the laws:

Companies like Coca-Cola and Kraft Heinz have begun designing their products so that their packages don’t have a true front or back, but rather two nearly identical labels—except for the fact that only one side has the required warning. As a result, supermarket clerks often place the products with the warning facing inward, effectively hiding it.


Other companies have gotten creative in finding ways to keep their mascots, even without reformulating their foods, as is required by law. Bimbo, the international bread company that owns brands in the United States such as Entenmann’s and Takis, for example, technically removed its mascot from its packaging. It instead printed the mascot on the actual food product—a ready to eat pancake—and made the packaging clear, so the mascot is still visible to consumers.

Posted on August 25, 2023 at 7:03 AM24 Comments

December’s Reimagining Democracy Workshop

Imagine that we’ve all—all of us, all of society—landed on some alien planet, and we have to form a government: clean slate. We don’t have any legacy systems from the US or any other country. We don’t have any special or unique interests to perturb our thinking.

How would we govern ourselves?

It’s unlikely that we would use the systems we have today. The modern representative democracy was the best form of government that mid-eighteenth-century technology could conceive of. The twenty-first century is a different place scientifically, technically and socially.

For example, the mid-eighteenth-century democracies were designed under the assumption that both travel and communications were hard. Does it still make sense for all of us living in the same place to organize every few years and choose one of us to go to a big room far away and create laws in our name?

Representative districts are organized around geography, because that’s the only way that made sense 200-plus years ago. But we don’t have to do it that way. We can organize representation by age: one representative for the thirty-one-year-olds, another for the thirty-two-year-olds, and so on. We can organize representation randomly: by birthday, perhaps. We can organize any way we want.

US citizens currently elect people for terms ranging from two to six years. Is ten years better? Is ten days better? Again, we have more technology and therefor more options.

Indeed, as a technologist who studies complex systems and their security, I believe the very idea of representative government is a hack to get around the technological limitations of the past. Voting at scale is easier now than it was 200 year ago. Certainly we don’t want to all have to vote on every amendment to every bill, but what’s the optimal balance between votes made in our name and ballot measures that we all vote on?

In December 2022, I organized a workshop to discuss these and other questions. I brought together fifty people from around the world: political scientists, economists, law professors, AI experts, activists, government officials, historians, science fiction writers and more. We spent two days talking about these ideas. Several themes emerged from the event.

Misinformation and propaganda were themes, of course—and the inability to engage in rational policy discussions when people can’t agree on the facts.

Another theme was the harms of creating a political system whose primary goals are economic. Given the ability to start over, would anyone create a system of government that optimizes the near-term financial interest of the wealthiest few? Or whose laws benefit corporations at the expense of people?

Another theme was capitalism, and how it is or isn’t intertwined with democracy. And while the modern market economy made a lot of sense in the industrial age, it’s starting to fray in the information age. What comes after capitalism, and how does it affect how we govern ourselves?

Many participants examined the effects of technology, especially artificial intelligence. We looked at whether—and when—we might be comfortable ceding power to an AI. Sometimes it’s easy. I’m happy for an AI to figure out the optimal timing of traffic lights to ensure the smoothest flow of cars through the city. When will we be able to say the same thing about setting interest rates? Or designing tax policies?

How would we feel about an AI device in our pocket that voted in our name, thousands of times per day, based on preferences that it inferred from our actions? If an AI system could determine optimal policy solutions that balanced every voter’s preferences, would it still make sense to have representatives? Maybe we should vote directly for ideas and goals instead, and leave the details to the computers. On the other hand, technological solutionism regularly fails.

Scale was another theme. The size of modern governments reflects the technology at the time of their founding. European countries and the early American states are a particular size because that’s what was governable in the 18th and 19th centuries. Larger governments—the US as a whole, the European Union—reflect a world in which travel and communications are easier. The problems we have today are primarily either local, at the scale of cities and towns, or global—even if they are currently regulated at state, regional or national levels. This mismatch is especially acute when we try to tackle global problems. In the future, do we really have a need for political units the size of France or Virginia? Or is it a mixture of scales that we really need, one that moves effectively between the local and the global?

As to other forms of democracy, we discussed one from history and another made possible by today’s technology.

Sortition is a system of choosing political officials randomly to deliberate on a particular issue. We use it today when we pick juries, but both the ancient Greeks and some cities in Renaissance Italy used it to select major political officials. Today, several countries—largely in Europe—are using sortition for some policy decisions. We might randomly choose a few hundred people, representative of the population, to spend a few weeks being briefed by experts and debating the problem—and then decide on environmental regulations, or a budget, or pretty much anything.

Liquid democracy does away with elections altogether. Everyone has a vote, and they can keep the power to cast it themselves or assign it to another person as a proxy. There are no set elections; anyone can reassign their proxy at any time. And there’s no reason to make this assignment all or nothing. Perhaps proxies could specialize: one set of people focused on economic issues, another group on health and a third bunch on national defense. Then regular people could assign their votes to whichever of the proxies most closely matched their views on each individual matter—or step forward with their own views and begin collecting proxy support from other people.

This all brings up another question: Who gets to participate? And, more generally, whose interests are taken into account? Early democracies were really nothing of the sort: They limited participation by gender, race and land ownership.

We should debate lowering the voting age, but even without voting we recognize that children too young to vote have rights—and, in some cases, so do other species. Should future generations get a “voice,” whatever that means? What about nonhumans or whole ecosystems?

Should everyone get the same voice? Right now in the US, the outsize effect of money in politics gives the wealthy disproportionate influence. Should we encode that explicitly? Maybe younger people should get a more powerful vote than everyone else. Or maybe older people should.

Those questions lead to ones about the limits of democracy. All democracies have boundaries limiting what the majority can decide. We all have rights: the things that cannot be taken away from us. We cannot vote to put someone in jail, for example.

But while we can’t vote a particular publication out of existence, we can to some degree regulate speech. In this hypothetical community, what are our rights as individuals? What are the rights of society that supersede those of individuals?

Personally, I was most interested in how these systems fail. As a security technologist, I study how complex systems are subverted—hacked, in my parlance—for the benefit of a few at the expense of the many. Think tax loopholes, or tricks to avoid government regulation. I want any government system to be resilient in the face of that kind of trickery.

Or, to put it another way, I want the interests of each individual to align with the interests of the group at every level. We’ve never had a system of government with that property before—even equal protection guarantees and First Amendment rights exist in a competitive framework that puts individuals’ interests in opposition to one another. But—in the age of such existential risks as climate and biotechnology and maybe AI—aligning interests is more important than ever.

Our workshop didn’t produce any answers; that wasn’t the point. Our current discourse is filled with suggestions on how to patch our political system. People regularly debate changes to the Electoral College, or the process of creating voting districts, or term limits. But those are incremental changes.

It’s hard to find people who are thinking more radically: looking beyond the horizon for what’s possible eventually. And while true innovation in politics is a lot harder than innovation in technology, especially without a violent revolution forcing change, it’s something that we as a species are going to have to get good at—one way or another.

This essay previously appeared in The Conversation.

Posted on August 23, 2023 at 7:06 AM68 Comments

Applying AI to License Plate Surveillance

License plate scanners aren’t new. Neither is using them for bulk surveillance. What’s new is that AI is being used on the data, identifying “suspicious” vehicle behavior:

Typically, Automatic License Plate Recognition (ALPR) technology is used to search for plates linked to specific crimes. But in this case it was used to examine the driving patterns of anyone passing one of Westchester County’s 480 cameras over a two-year period. Zayas’ lawyer Ben Gold contested the AI-gathered evidence against his client, decrying it as “dragnet surveillance.”

And he had the data to back it up. A FOIA he filed with the Westchester police revealed that the ALPR system was scanning over 16 million license plates a week, across 480 ALPR cameras. Of those systems, 434 were stationary, attached to poles and signs, while the remaining 46 were mobile, attached to police vehicles. The AI was not just looking at license plates either. It had also been taking notes on vehicles’ make, model and color—useful when a plate number for a suspect vehicle isn’t visible or is unknown.

Posted on August 22, 2023 at 7:04 AM26 Comments

White House Announces AI Cybersecurity Challenge

At Black Hat last week, the White House announced an AI Cyber Challenge. Gizmodo reports:

The new AI cyber challenge (which is being abbreviated “AIxCC”) will have a number of different phases. Interested would-be competitors can now submit their proposals to the Small Business Innovation Research program for evaluation and, eventually, selected teams will participate in a 2024 “qualifying event.” During that event, the top 20 teams will be invited to a semifinal competition at that year’s DEF CON, another large cybersecurity conference, where the field will be further whittled down.


To secure the top spot in DARPA’s new competition, participants will have to develop security solutions that do some seriously novel stuff. “To win first-place, and a top prize of $4 million, finalists must build a system that can rapidly defend critical infrastructure code from attack,” said Perri Adams, program manager for DARPA’s Information Innovation Office, during a Zoom call with reporters Tuesday. In other words: the government wants software that is capable of identifying and mitigating risks by itself.

This is a great idea. I was a big fan of DARPA’s AI capture-the-flag event in 2016, and am happy to see that DARPA is again inciting research in this area. (China has been doing this every year since 2017.)

Posted on August 21, 2023 at 7:10 AM28 Comments

Friday Squid Blogging: Squid Brand Fish Sauce

Squid Brand is a Thai company that makes fish sauce:

It is part of Squid Brand’s range of “personalized healthy fish sauces” that cater to different consumer groups, which include the Mild Fish Sauce for Kids and Mild Fish Sauce for Silver Ages.

It also has a Vegan Fish Sauce.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Posted on August 18, 2023 at 5:02 PM65 Comments

Bots Are Better than Humans at Solving CAPTCHAs

Interesting research: “An Empirical Study & Evaluation of Modern CAPTCHAs“:

Abstract: For nearly two decades, CAPTCHAS have been widely used as a means of protection against bots. Throughout the years, as their use grew, techniques to defeat or bypass CAPTCHAS have continued to improve. Meanwhile, CAPTCHAS have also evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots (machines) and humans. Given this long-standing and still-ongoing arms race, it is critical to investigate how long it takes legitimate users to solve modern CAPTCHAS, and how they are perceived by those users.

In this work, we explore CAPTCHAS in the wild by evaluating users’ solving performance and perceptions of unmodified currently-deployed CAPTCHAS. We obtain this data through manual inspection of popular websites and user studies in which 1, 400 participants collectively solved 14, 000 CAPTCHAS. Results show significant differences between the most popular types of CAPTCHAS: surprisingly, solving time and user perception are not always correlated. We performed a comparative study to investigate the effect of experimental context ­ specifically the difference between solving CAPTCHAS directly versus solving them as part of a more natural task, such as account creation. Whilst there were several potential confounding factors, our results show that experimental context could have an impact on this task, and must be taken into account in future CAPTCHA studies. Finally, we investigate CAPTCHA-induced user task abandonment by analyzing participants who start and do not complete the task.

Slashdot thread.

And let’s all rewatch this great ad from 2022.

Posted on August 18, 2023 at 7:04 AM20 Comments

UK Electoral Commission Hacked

The UK Electoral Commission discovered last year that it was hacked the year before. That’s fourteen months between the hack and the discovery. It doesn’t know who was behind the hack.

We worked with external security experts and the National Cyber Security Centre to investigate and secure our systems.

If the hack was by a major government, the odds are really low that it has resecured its systems—unless it burned the network to the ground and rebuilt it from scratch (which seems unlikely).

Posted on August 16, 2023 at 7:17 AM14 Comments

Zoom Can Spy on Your Calls and Use the Conversation to Train AI, But Says That It Won’t

This is why we need regulation:

Zoom updated its Terms of Service in March, spelling out that the company reserves the right to train AI on user data with no mention of a way to opt out. On Monday, the company said in a blog post that there’s no need to worry about that. Zoom execs swear the company won’t actually train its AI on your video calls without permission, even though the Terms of Service still say it can.

Of course, these are Terms of Service. They can change at any time. Zoom can renege on its promise at any time. There are no rules, only the whims of the company as it tries to maximize its profits.

It’s a stupid way to run a technological revolution. We should not have to rely on the benevolence of for-profit corporations to protect our rights. It’s not their job, and it shouldn’t be.

Posted on August 15, 2023 at 7:03 AM28 Comments

China Hacked Japan’s Military Networks

The NSA discovered the intrusion in 2020—we don’t know how—and alerted the Japanese. The Washington Post has the story:

The hackers had deep, persistent access and appeared to be after anything they could get their hands on—plans, capabilities, assessments of military shortcomings, according to three former senior U.S. officials, who were among a dozen current and former U.S. and Japanese officials interviewed, who spoke on the condition of anonymity because of the matter’s sensitivity.


The 2020 penetration was so disturbing that Gen. Paul Nakasone, the head of the NSA and U.S. Cyber Command, and Matthew Pottinger, who was White House deputy national security adviser at the time, raced to Tokyo. They briefed the defense minister, who was so concerned that he arranged for them to alert the prime minister himself.

Beijing, they told the Japanese officials, had breached Tokyo’s defense networks, making it one of the most damaging hacks in that country’s modern history.

More analysis.

Posted on August 14, 2023 at 7:02 AM20 Comments

Friday Squid Blogging: NIWA Annual Squid Survey

Results from the National Institute of Water and Atmospheric Research Limited annual squid survey:

This year, the team unearthed spectacular large hooked squids, weighing about 15kg and sitting at 2m long, a Taningia—­which has the largest known light organs in the animal kingdom­—and a few species that remain very rare in collections worldwide, such as the “scaled” squid Lepidoteuthis and the Batoteuthis skolops.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Posted on August 11, 2023 at 5:09 PM68 Comments

The Inability to Simultaneously Verify Sentience, Location, and Identity

Really interesting “systematization of knowledge” paper:

“SoK: The Ghost Trilemma”

Abstract: Trolls, bots, and sybils distort online discourse and compromise the security of networked platforms. User identity is central to the vectors of attack and manipulation employed in these contexts. However it has long seemed that, try as it might, the security community has been unable to stem the rising tide of such problems. We posit the Ghost Trilemma, that there are three key properties of identity—sentience, location, and uniqueness—that cannot be simultaneously verified in a fully-decentralized setting. Many fully-decentralized systems—whether for communication or social coordination—grapple with this trilemma in some way, perhaps unknowingly. In this Systematization of Knowledge (SoK) paper, we examine the design space, use cases, problems with prior approaches, and possible paths forward. We sketch a proof of this trilemma and outline options for practical, incrementally deployable schemes to achieve an acceptable tradeoff of trust in centralized trust anchors, decentralized operation, and an ability to withstand a range of attacks, while protecting user privacy.

I think this conceptualization makes sense, and explains a lot.

Posted on August 11, 2023 at 7:08 AM10 Comments

Using Machine Learning to Detect Keystrokes

Researchers have trained a ML model to detect keystrokes by sound with 95% accuracy.

“A Practical Deep Learning-Based Acoustic Side Channel Attack on Keyboards”

Abstract: With recent developments in deep learning, the ubiquity of microphones and the rise in online services via personal devices, acoustic side channel attacks present a greater threat to keyboards than ever. This paper presents a practical implementation of a state-of-the-art deep learning model in order to classify laptop keystrokes, using a smartphone integrated microphone. When trained on keystrokes recorded by a nearby phone, the classifier achieved an accuracy of 95%, the highest accuracy seen without the use of a language model. When trained on keystrokes recorded using the video-conferencing software Zoom, an accuracy of 93% was achieved, a new best for the medium. Our results prove the practicality of these side channel attacks via off-the-shelf equipment and algorithms. We discuss a series of mitigation methods to protect users against these series of attacks.

News article.

Posted on August 9, 2023 at 7:08 AM10 Comments

You Can’t Rush Post-Quantum-Computing Cryptography Standards

I just read an article complaining that NIST is taking too long in finalizing its post-quantum-computing cryptography standards.

This process has been going on since 2016, and since that time there has been a huge increase in quantum technology and an equally large increase in quantum understanding and interest. Yet seven years later, we have only four algorithms, although last week NIST announced that a number of other candidates are under consideration, a process that is expected to take “several years.

The delay in developing quantum-resistant algorithms is especially troubling given the time it will take to get those products to market. It generally takes four to six years with a new standard for a vendor to develop an ASIC to implement the standard, and it then takes time for the vendor to get the product validated, which seems to be taking a troubling amount of time.

Yes, the process will take several years, and you really don’t want to rush it. I wrote this last year:

Ian Cassels, British mathematician and World War II cryptanalyst, once said that “cryptography is a mixture of mathematics and muddle, and without the muddle the mathematics can be used against you.” This mixture is particularly difficult to achieve with public-key algorithms, which rely on the mathematics for their security in a way that symmetric algorithms do not. We got lucky with RSA and related algorithms: their mathematics hinge on the problem of factoring, which turned out to be robustly difficult. Post-quantum algorithms rely on other mathematical disciplines and problems­—code-based cryptography, hash-based cryptography, lattice-based cryptography, multivariate cryptography, and so on­—whose mathematics are both more complicated and less well-understood. We’re seeing these breaks because those core mathematical problems aren’t nearly as well-studied as factoring is.


As the new cryptanalytic results demonstrate, we’re still learning a lot about how to turn hard mathematical problems into public-key cryptosystems. We have too much math and an inability to add more muddle, and that results in algorithms that are vulnerable to advances in mathematics. More cryptanalytic results are coming, and more algorithms are going to be broken.

As to the long time it takes to get new encryption products to market, work on shortening it:

The moral is the need for cryptographic agility. It’s not enough to implement a single standard; it’s vital that our systems be able to easily swap in new algorithms when required.

Whatever NIST comes up with, expect that it will get broken sooner than we all want. It’s the nature of these trap-door functions we’re using for public-key cryptography.

Posted on August 8, 2023 at 7:13 AM38 Comments

Microsoft Signing Key Stolen by Chinese

A bunch of networks, including US Government networks, have been hacked by the Chinese. The hackers used forged authentication tokens to access user email, using a stolen Microsoft Azure account consumer signing key. Congress wants answers. The phrase “negligent security practices” is being tossed about—and with good reason. Master signing keys are not supposed to be left around, waiting to be stolen.

Actually, two things went badly wrong here. The first is that Azure accepted an expired signing key, implying a vulnerability in whatever is supposed to check key validity. The second is that this key was supposed to remain in the the system’s Hardware Security Module—and not be in software. This implies a really serious breach of good security practice. The fact that Microsoft has not been forthcoming about the details of what happened tell me that the details are really bad.

I believe this all traces back to SolarWinds. In addition to Russia inserting malware into a SolarWinds update, China used a different SolarWinds vulnerability to break into networks. We know that Russia accessed Microsoft source code in that attack. I have heard from informed government officials that China used their SolarWinds vulnerability to break into Microsoft and access source code, including Azure’s.

I think we are grossly underestimating the long-term results of the SolarWinds attacks. That backdoored update was downloaded by over 14,000 networks worldwide. Organizations patched their networks, but not before Russia—and others—used the vulnerability to enter those networks. And once someone is in a network, it’s really hard to be sure that you’ve kicked them out.

Sophisticated threat actors are realizing that stealing source code of infrastructure providers, and then combing that code for vulnerabilities, is an excellent way to break into organizations who use those infrastructure providers. Attackers like Russia and China—and presumably the US as well—are prioritizing going after those providers.

News articles.

EDITED TO ADD: Commentary:

This is from Microsoft’s explanation. The China attackers “acquired an inactive MSA consumer signing key and used it to forge authentication tokens for Azure AD enterprise and MSA consumer to access OWA and All MSA keys active prior to the incident—including the actor-acquired MSA signing key—have been invalidated. Azure AD keys were not impacted. Though the key was intended only for MSA accounts, a validation issue allowed this key to be trusted for signing Azure AD tokens. The actor was able to obtain new access tokens by presenting one previously issued from this API due to a design flaw. This flaw in the GetAccessTokenForResourceAPI has since been fixed to only accept tokens issued from Azure AD or MSA respectively. The actor used these tokens to retrieve mail messages from the OWA API.”

Posted on August 7, 2023 at 7:03 AM30 Comments

Political Milestones for AI

ChatGPT was released just nine months ago, and we are still learning how it will affect our daily lives, our careers, and even our systems of self-governance.

But when it comes to how AI may threaten our democracy, much of the public conversation lacks imagination. People talk about the danger of campaigns that attack opponents with fake images (or fake audio or video) because we already have decades of experience dealing with doctored images. We’re on the lookout for foreign governments that spread misinformation because we were traumatized by the 2016 US presidential election. And we worry that AI-generated opinions will swamp the political preferences of real people because we’ve seen political “astroturfing”—the use of fake online accounts to give the illusion of support for a policy—grow for decades.

Threats of this sort seem urgent and disturbing because they’re salient. We know what to look for, and we can easily imagine their effects.

The truth is, the future will be much more interesting. And even some of the most stupendous potential impacts of AI on politics won’t be all bad. We can draw some fairly straight lines between the current capabilities of AI tools and real-world outcomes that, by the standards of current public understanding, seem truly startling.

With this in mind, we propose six milestones that will herald a new era of democratic politics driven by AI. All feel achievable—perhaps not with today’s technology and levels of AI adoption, but very possibly in the near future.

Good benchmarks should be meaningful, representing significant outcomes that come with real-world consequences. They should be plausible; they must be realistically achievable in the foreseeable future. And they should be observable—we should be able to recognize when they’ve been achieved.

Worries about AI swaying an election will very likely fail the observability test. While the risks of election manipulation through the robotic promotion of a candidate’s or party’s interests is a legitimate threat, elections are massively complex. Just as the debate continues to rage over why and how Donald Trump won the presidency in 2016, we’re unlikely to be able to attribute a surprising electoral outcome to any particular AI intervention.

Thinking further into the future: Could an AI candidate ever be elected to office? In the world of speculative fiction, from The Twilight Zone to Black Mirror, there is growing interest in the possibility of an AI or technologically assisted, otherwise-not-traditionally-eligible candidate winning an election. In an era where deepfaked videos can misrepresent the views and actions of human candidates and human politicians can choose to be represented by AI avatars or even robots, it is certainly possible for an AI candidate to mimic the media presence of a politician. Virtual politicians have received votes in national elections, for example in Russia in 2017. But this doesn’t pass the plausibility test. The voting public and legal establishment are likely to accept more and more automation and assistance supported by AI, but the age of non-human elected officials is far off.

Let’s start with some milestones that are already on the cusp of reality. These are achievements that seem well within the technical scope of existing AI technologies and for which the groundwork has already been laid.

Milestone #1: The acceptance by a legislature or agency of a testimony or comment generated by, and submitted under the name of, an AI.

Arguably, we’ve already seen legislation drafted by AI, albeit under the direction of human users and introduced by human legislators. After some early examples of bills written by AIs were introduced in Massachusetts and the US House of Representatives, many major legislative bodies have had their “first bill written by AI,” “used ChatGPT to generate committee remarks,” or “first floor speech written by AI” events.

Many of these bills and speeches are more stunt than serious, and they have received more criticism than consideration. They are short, have trivial levels of policy substance, or were heavily edited or guided by human legislators (through highly specific prompts to large language model-based AI tools like ChatGPT).

The interesting milestone along these lines will be the acceptance of testimony on legislation, or a comment submitted to an agency, drafted entirely by AI. To be sure, a large fraction of all writing going forward will be assisted by—and will truly benefit from—AI assistive technologies. So to avoid making this milestone trivial, we have to add the second clause: “submitted under the name of the AI.”

What would make this benchmark significant is the submission under the AI’s own name; that is, the acceptance by a governing body of the AI as proffering a legitimate perspective in public debate. Regardless of the public fervor over AI, this one won’t take long. The New York Times has published a letter under the name of ChatGPT (responding to an opinion piece we wrote), and legislators are already turning to AI to write high-profile opening remarks at committee hearings.

Milestone #2: The adoption of the first novel legislative amendment to a bill written by AI.

Moving beyond testimony, there is an immediate pathway for AI-generated policies to become law: microlegislation. This involves making tweaks to existing laws or bills that are tuned to serve some particular interest. It is a natural starting point for AI because it’s tightly scoped, involving small changes guided by a clear directive associated with a well-defined purpose.

By design, microlegislation is often implemented surreptitiously. It may even be filed anonymously within a deluge of other amendments to obscure its intended beneficiary. For that reason, microlegislation can often be bad for society, and it is ripe for exploitation by generative AI that would otherwise be subject to heavy scrutiny from a polity on guard for risks posed by AI.

Milestone #3: AI-generated political messaging outscores campaign consultant recommendations in poll testing.

Some of the most important near-term implications of AI for politics will happen largely behind closed doors. Like everyone else, political campaigners and pollsters will turn to AI to help with their jobs. We’re already seeing campaigners turn to AI-generated images to manufacture social content and pollsters simulate results using AI-generated respondents.

The next step in this evolution is political messaging developed by AI. A mainstay of the campaigner’s toolbox today is the message testing survey, where a few alternate formulations of a position are written down and tested with audiences to see which will generate more attention and a more positive response. Just as an experienced political pollster can anticipate effective messaging strategies pretty well based on observations from past campaigns and their impression of the state of the public debate, so can an AI trained on reams of public discourse, campaign rhetoric, and political reporting.

With these near-term milestones firmly in sight, let’s look further to some truly revolutionary possibilities. While these concepts may have seemed absurd just a year ago, they are increasingly conceivable with either current or near-future technologies.

Milestone #4: AI creates a political party with its own platform, attracting human candidates who win elections.

While an AI is unlikely to be allowed to run for and hold office, it is plausible that one may be able to found a political party. An AI could generate a political platform calculated to attract the interest of some cross-section of the public and, acting independently or through a human intermediary (hired help, like a political consultant or legal firm), could register formally as a political party. It could collect signatures to win a place on ballots and attract human candidates to run for office under its banner.

A big step in this direction has already been taken, via the campaign of the Danish Synthetic Party in 2022. An artist collective in Denmark created an AI chatbot to interact with human members of its community on Discord, exploring political ideology in conversation with them and on the basis of an analysis of historical party platforms in the country. All this happened with earlier generations of general purpose AI, not current systems like ChatGPT. However, the party failed to receive enough signatures to earn a spot on the ballot, and therefore did not win parliamentary representation.

Future AI-led efforts may succeed. One could imagine a generative AI with skills at the level of or beyond today’s leading technologies could formulate a set of policy positions targeted to build support among people of a specific demographic, or even an effective consensus platform capable of attracting broad-based support. Particularly in a European-style multiparty system, we can imagine a new party with a strong news hook—an AI at its core—winning attention and votes.

Milestone #5: AI autonomously generates profit and makes political campaign contributions.

Let’s turn next to the essential capability of modern politics: fundraising. “An entity capable of directing contributions to a campaign fund” might be a realpolitik definition of a political actor, and AI is potentially capable of this.

Like a human, an AI could conceivably generate contributions to a political campaign in a variety of ways. It could take a seed investment from a human controlling the AI and invest it to yield a return. It could start a business that generates revenue. There is growing interest and experimentation in auto-hustling: AI agents that set about autonomously growing businesses or otherwise generating profit. While ChatGPT-generated businesses may not yet have taken the world by storm, this possibility is in the same spirit as the algorithmic agents powering modern high-speed trading and so-called autonomous finance capabilities that are already helping to automate business and financial decisions.

Or, like most political entrepreneurs, AI could generate political messaging to convince humans to spend their own money on a defined campaign or cause. The AI would likely need to have some humans in the loop, and register its activities to the government (in the US context, as officers of a 501(c)(4) or political action committee).

Milestone #6: AI achieves a coordinated policy outcome across multiple jurisdictions.

Lastly, we come to the most meaningful of impacts: achieving outcomes in public policy. Even if AI cannot—now or in the future—be said to have its own desires or preferences, it could be programmed by humans to have a goal, such as lowering taxes or relieving a market regulation.

An AI has many of the same tools humans use to achieve these ends. It may advocate, formulating messaging and promoting ideas through digital channels like social media posts and videos. It may lobby, directing ideas and influence to key policymakers, even writing legislation. It may spend; see milestone #5.

The “multiple jurisdictions” piece is key to this milestone. A single law passed may be reasonably attributed to myriad factors: a charismatic champion, a political movement, a change in circumstances. The influence of any one actor, such as an AI, will be more demonstrable if it is successful simultaneously in many different places. And the digital scalability of AI gives it a special advantage in achieving these kinds of coordinated outcomes.

The greatest challenge to most of these milestones is their observability: will we know it when we see it? The first campaign consultant whose ideas lose out to an AI may not be eager to report that fact. Neither will the campaign. Regarding fundraising, it’s hard enough for us to track down the human actors who are responsible for the “dark money” contributions controlling much of modern political finance; will we know if a future dominant force in fundraising for political action committees is an AI?

We’re likely to observe some of these milestones indirectly. At some point, perhaps politicians’ dollars will start migrating en masse to AI-based campaign consultancies and, eventually, we may realize that political movements sweeping across states or countries have been AI-assisted.

While the progression of technology is often unsettling, we need not fear these milestones. A new political platform that wins public support is itself a neutral proposition; it may lead to good or bad policy outcomes. Likewise, a successful policy program may or may not be beneficial to one group of constituents or another.

We think the six milestones outlined here are among the most viable and meaningful upcoming interactions between AI and democracy, but they are hardly the only scenarios to consider. The point is that our AI-driven political future will involve far more than deepfaked campaign ads and manufactured letter-writing campaigns. We should all be thinking more creatively about what comes next and be vigilant in steering our politics toward the best possible ends, no matter their means.

This essay was written with Nathan Sanders, and previously appeared in MIT Technology Review.

Posted on August 4, 2023 at 7:07 AM33 Comments

The Need for Trustworthy AI

If you ask Alexa, Amazon’s voice assistant AI system, whether Amazon is a monopoly, it responds by saying it doesn’t know. It doesn’t take much to make it lambaste the other tech giants, but it’s silent about its own corporate parent’s misdeeds.

When Alexa responds in this way, it’s obvious that it is putting its developer’s interests ahead of yours. Usually, though, it’s not so obvious whom an AI system is serving. To avoid being exploited by these systems, people will need to learn to approach AI skeptically. That means deliberately constructing the input you give it and thinking critically about its output.

Newer generations of AI models, with their more sophisticated and less rote responses, are making it harder to tell who benefits when they speak. Internet companies’ manipulating what you see to serve their own interests is nothing new. Google’s search results and your Facebook feed are filled with paid entries. Facebook, TikTok and others manipulate your feeds to maximize the time you spend on the platform, which means more ad views, over your well-being.

What distinguishes AI systems from these other internet services is how interactive they are, and how these interactions will increasingly become like relationships. It doesn’t take much extrapolation from today’s technologies to envision AIs that will plan trips for you, negotiate on your behalf or act as therapists and life coaches.

They are likely to be with you 24/7, know you intimately, and be able to anticipate your needs. This kind of conversational interface to the vast network of services and resources on the web is within the capabilities of existing generative AIs like ChatGPT. They are on track to become personalized digital assistants.

As a security expert and data scientist, we believe that people who come to rely on these AIs will have to trust them implicitly to navigate daily life. That means they will need to be sure the AIs aren’t secretly working for someone else. Across the internet, devices and services that seem to work for you already secretly work against you. Smart TVs spy on you. Phone apps collect and sell your data. Many apps and websites manipulate you through dark patterns, design elements that deliberately mislead, coerce or deceive website visitors. This is surveillance capitalism, and AI is shaping up to be part of it.

Quite possibly, it could be much worse with AI. For that AI digital assistant to be truly useful, it will have to really know you. Better than your phone knows you. Better than Google search knows you. Better, perhaps, than your close friends, intimate partners and therapist know you.

You have no reason to trust today’s leading generative AI tools. Leave aside the hallucinations, the made-up “facts” that GPT and other large language models produce. We expect those will be largely cleaned up as the technology improves over the next few years.

But you don’t know how the AIs are configured: how they’ve been trained, what information they’ve been given, and what instructions they’ve been commanded to follow. For example, researchers uncovered the secret rules that govern the Microsoft Bing chatbot’s behavior. They’re largely benign but can change at any time.

Many of these AIs are created and trained at enormous expense by some of the largest tech monopolies. They’re being offered to people to use free of charge, or at very low cost. These companies will need to monetize them somehow. And, as with the rest of the internet, that somehow is likely to include surveillance and manipulation.

Imagine asking your chatbot to plan your next vacation. Did it choose a particular airline or hotel chain or restaurant because it was the best for you or because its maker got a kickback from the businesses? As with paid results in Google search, newsfeed ads on Facebook and paid placements on Amazon queries, these paid influences are likely to get more surreptitious over time.

If you’re asking your chatbot for political information, are the results skewed by the politics of the corporation that owns the chatbot? Or the candidate who paid it the most money? Or even the views of the demographic of the people whose data was used in training the model? Is your AI agent secretly a double agent? Right now, there is no way to know.

We believe that people should expect more from the technology and that tech companies and AIs can become more trustworthy. The European Union’s proposed AI Act takes some important steps, requiring transparency about the data used to train AI models, mitigation for potential bias, disclosure of foreseeable risks and reporting on industry standard tests.

Most existing AIs fail to comply with this emerging European mandate, and, despite recent prodding from Senate Majority Leader Chuck Schumer, the US is far behind on such regulation.

The AIs of the future should be trustworthy. Unless and until the government delivers robust consumer protections for AI products, people will be on their own to guess at the potential risks and biases of AI, and to mitigate their worst effects on people’s experiences with them.

So when you get a travel recommendation or political information from an AI tool, approach it with the same skeptical eye you would a billboard ad or a campaign volunteer. For all its technological wizardry, the AI tool may be little more than the same.

This essay was written with Nathan Sanders, and previously appeared on The Conversation.

Posted on August 3, 2023 at 7:17 AM60 Comments

New SEC Rules around Cybersecurity Incident Disclosures

The US Securities and Exchange Commission adopted final rules around the disclosure of cybersecurity incidents. There are two basic rules:

  1. Public companies must “disclose any cybersecurity incident they determine to be material” within four days, with potential delays if there is a national security risk.
  2. Public companies must “describe their processes, if any, for assessing, identifying, and managing material risks from cybersecurity threats” in their annual filings.

The rules go into effect this December.

In an email newsletter, Melissa Hathaway wrote:

Now that the rule is final, companies have approximately six months to one year to document and operationalize the policies and procedures for the identification and management of cybersecurity (information security/privacy) risks. Continuous assessment of the risk reduction activities should be elevated within an enterprise risk management framework and process. Good governance mechanisms delineate the accountability and responsibility for ensuring successful execution, while actionable, repeatable, meaningful, and time-dependent metrics or key performance indicators (KPI) should be used to reinforce realistic objectives and timelines. Management should assess the competency of the personnel responsible for implementing these policies and be ready to identify these people (by name) in their annual filing.

News article.

Posted on August 2, 2023 at 7:04 AM14 Comments

Hacking AI Resume Screening with Text in a White Font

The Washington Post is reporting on a hack to fool automatic resume sorting programs: putting text in a white font. The idea is that the programs rely primarily on simple pattern matching, and the trick is to copy a list of relevant keywords—or the published job description—into the resume in a white font. The computer will process the text, but humans won’t see it.

Clever. I’m not sure it’s actually useful in getting a job, though. Eventually the humans will figure out that the applicant doesn’t actually have the required skills. But…maybe.

Posted on August 1, 2023 at 7:11 AM28 Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.