Using Generative AI for Surveillance
Generative AI is going to be a powerful tool for data analysis and summarization. Here’s an example of it being used for sentiment analysis. My guess is that it isn’t very good yet, but that it will get better.
Entries Tagged "AI"
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FTC’s Voice Cloning Challenge
The Federal Trade Commission is running a competition “to foster breakthrough ideas on preventing, monitoring, and evaluating malicious voice cloning.”
Ten Ways AI Will Change Democracy
Artificial intelligence will change so many aspects of society, largely in ways that we cannot conceive of yet. Democracy, and the systems of governance that surround it, will be no exception. In this short essay, I want to move beyond the “AI-generated disinformation” trope and speculate on some of the ways AI will change how democracy functions—in both large and small ways.
When I survey how artificial intelligence might upend different aspects of modern society, democracy included, I look at four different dimensions of change: speed, scale, scope, and sophistication. Look for places where changes in degree result in changes of kind. Those are where the societal upheavals will happen.
Some items on my list are still speculative, but none require science-fictional levels of technological advance. And we can see the first stages of many of them today. When reading about the successes and failures of AI systems, it’s important to differentiate between the fundamental limitations of AI as a technology, and the practical limitations of AI systems in the fall of 2023. Advances are happening quickly, and the impossible is becoming the routine. We don’t know how long this will continue, but my bet is on continued major technological advances in the coming years. Which means it’s going to be a wild ride.
So, here’s my list:
- AI as educator. We are already seeing AI serving the role of teacher. It’s much more effective for a student to learn a topic from an interactive AI chatbot than from a textbook. This has applications for democracy. We can imagine chatbots teaching citizens about different issues, such as climate change or tax policy. We can imagine candidates deploying chatbots of themselves, allowing voters to directly engage with them on various issues. A more general chatbot could know the positions of all the candidates, and help voters decide which best represents their position. There are a lot of possibilities here.
- AI as sense maker. There are many areas of society where accurate summarization is important. Today, when constituents write to their legislator, those letters get put into two piles—one for and another against—and someone compares the height of those piles. AI can do much better. It can provide a rich summary of the comments. It can help figure out which are unique and which are form letters. It can highlight unique perspectives. This same system can also work for comments to different government agencies on rulemaking processes—and on documents generated during the discovery process in lawsuits.
- AI as moderator, mediator, and consensus builder. Imagine online conversations in which AIs serve the role of moderator. This could ensure that all voices are heard. It could block hateful—or even just off-topic—comments. It could highlight areas of agreement and disagreement. It could help the group reach a decision. This is nothing that a human moderator can’t do, but there aren’t enough human moderators to go around. AI can give this capability to every decision-making group. At the extreme, an AI could be an arbiter—a judge—weighing evidence and making a decision. These capabilities don’t exist yet, but they are not far off.
- AI as lawmaker. We have already seen proposed legislation written by AI, albeit more as a stunt than anything else. But in the future AIs will help craft legislation, dealing with the complex ways laws interact with each other. More importantly, AIs will eventually be able to craft loopholes in legislation, ones potentially too complicated for people to easily notice. On the other side of that, AIs could be used to find loopholes in legislation—for both existing and pending laws. And more generally, AIs could be used to help develop policy positions.
- AI as political strategist. Right now, you can ask your favorite chatbot questions about political strategy: what legislation would further your political goals, what positions to publicly take, what campaign slogans to use. The answers you get won’t be very good, but that’ll improve with time. In the future we should expect politicians to make use of this AI expertise: not to follow blindly, but as another source of ideas. And as AIs become more capable at using tools, they can automatically conduct polls and focus groups to test out political ideas. There are a lot of possibilities here. AIs could also engage in fundraising campaigns, directly soliciting contributions from people.
- AI as lawyer. We don’t yet know which aspects of the legal profession can be done by AIs, but many routine tasks that are now handled by attorneys will soon be able to be completed by an AI. Early attempts at having AIs write legal briefs haven’t worked, but this will change as the systems get better at accuracy. Additionally, AIs can help people navigate government systems: filling out forms, applying for services, contesting bureaucratic actions. And future AIs will be much better at writing legalese, reducing the cost of legal counsel.
- AI as cheap reasoning generator. More generally, AI chatbots are really good at generating persuasive arguments. Today, writing out a persuasive argument takes time and effort, and our systems reflect that. We can easily imagine AIs conducting lobbying campaigns, generating and submitting comments on legislation and rulemaking. This also has applications for the legal system. For example: if it is suddenly easy to file thousands of court cases, this will overwhelm the courts. Solutions for this are hard. We could increase the cost of filing a court case, but that becomes a burden on the poor. The only solution might be another AI working for the court, dealing with the deluge of AI-filed cases—which doesn’t sound like a great idea.
- AI as law enforcer. Automated systems already act as law enforcement in some areas: speed trap cameras are an obvious example. AI can take this kind of thing much further, automatically identifying people who cheat on tax returns or when applying for government services. This has the obvious problem of false positives, which could be hard to contest if the courts believe that “the computer is always right.” Separately, future laws might be so complicated that only AIs are able to decide whether or not they are being broken. And, like breathalyzers, defendants might not be allowed to know how they work.
- AI as propagandist. AIs can produce and distribute propaganda faster than humans can. This is an obvious risk, but we don’t know how effective any of it will be. It makes disinformation campaigns easier, which means that more people will take advantage of them. But people will be more inured against the risks. More importantly, AI’s ability to summarize and understand text can enable much more effective censorship.
- AI as political proxy. Finally, we can imagine an AI voting on behalf of individuals. A voter could feed an AI their social, economic, and political preferences; or it can infer them by listening to them talk and watching their actions. And then it could be empowered to vote on their behalf, either for others who would represent them, or directly on ballot initiatives. On the one hand, this would greatly increase voter participation. On the other hand, it would further disengage people from the act of understanding politics and engaging in democracy.
When I teach AI policy at HKS, I stress the importance of separating the specific AI chatbot technologies in November of 2023 with AI’s technological possibilities in general. Some of the items on my list will soon be possible; others will remain fiction for many years. Similarly, our acceptance of these technologies will change. Items on that list that we would never accept today might feel routine in a few years. A judgeless courtroom seems crazy today, but so did a driverless car a few years ago. Don’t underestimate our ability to normalize new technologies. My bet is that we’re in for a wild ride.
This essay previously appeared on the Harvard Kennedy School Ash Center’s website.
Microsoft is Soft-Launching Security Copilot
Microsoft has announced an early access program for its LLM-based security chatbot assistant: Security Copilot.
I am curious whether this thing is actually useful.
AI and US Election Rules
If an AI breaks the rules for you, does that count as breaking the rules? This is the essential question being taken up by the Federal Election Commission this month, and public input is needed to curtail the potential for AI to take US campaigns (even more) off the rails.
At issue is whether candidates using AI to create deepfaked media for political advertisements should be considered fraud or legitimate electioneering. That is, is it allowable to use AI image generators to create photorealistic images depicting Trump hugging Anthony Fauci? And is it allowable to use dystopic images generated by AI in political attack ads?
For now, the answer to these questions is probably “yes.” These are fairly innocuous uses of AI, not any different than the old-school approach of hiring actors and staging a photoshoot, or using video editing software. Even in cases where AI tools will be put to scurrilous purposes, that’s probably legal in the US system. Political ads are, after all, a medium in which you are explicitly permitted to lie.
The concern over AI is a distraction, but one that can help draw focus to the real issue. What matters isn’t how political content is generated; what matters is the content itself and how it is distributed.
Future uses of AI by campaigns go far beyond deepfaked images. Campaigns will also use AI to personalize communications. Whereas the previous generation of social media microtargeting was celebrated for helping campaigns reach a precision of thousands or hundreds of voters, the automation offered by AI will allow campaigns to tailor their advertisements and solicitations to the individual.
Most significantly, AI will allow digital campaigning to evolve from a broadcast medium to an interactive one. AI chatbots representing campaigns are capable of responding to questions instantly and at scale, like a town hall taking place in every voter’s living room, simultaneously. Ron DeSantis’ presidential campaign has reportedly already started using OpenAI’s technology to handle text message replies to voters.
At the same time, it’s not clear whose responsibility it is to keep US political advertisements grounded in reality—if it is anyone’s. The FEC’s role is campaign finance, and is further circumscribed by the Supreme Court’s repeated stripping of its authorities. The Federal Communications Commission has much more expansive responsibility for regulating political advertising in broadcast media, as well as political robocalls and text communications. However, the FCC hasn’t done much in recent years to curtail political spam. The Federal Trade Commission enforces truth in advertising standards, but political campaigns have been largely exempted from these requirements on First Amendment grounds.
To further muddy the waters, much of the online space remains loosely regulated, even as campaigns have fully embraced digital tactics. There are still insufficient disclosure requirements for digital ads. Campaigns pay influencers to post on their behalf to circumvent paid advertising rules. And there are essentially no rules beyond the simple use of disclaimers for videos that campaigns post organically on their own websites and social media accounts, even if they are shared millions of times by others.
Almost everyone has a role to play in improving this situation.
Let’s start with the platforms. Google announced earlier this month that it would require political advertisements on YouTube and the company’s other advertising platforms to disclose when they use AI images, audio, and video that appear in their ads. This is to be applauded, but we cannot rely on voluntary actions by private companies to protect our democracy. Such policies, even when well-meaning, will be inconsistently devised and enforced.
The FEC should use its limited authority to stem this coming tide. The FEC’s present consideration of rulemaking on this issue was prompted by Public Citizen, which petitioned the Commission to “clarify that the law against ‘fraudulent misrepresentation’ (52 U.S.C. §30124) applies to deliberately deceptive AI-produced content in campaign communications.” The FEC’s regulation against fraudulent misrepresentation (C.F.R. §110.16) is very narrow; it simply restricts candidates from pretending to be speaking on behalf of their opponents in a “damaging” way.
Extending this to explicitly cover deepfaked AI materials seems appropriate. We should broaden the standards to robustly regulate the activity of fraudulent misrepresentation, whether the entity performing that activity is AI or human—but this is only the first step. If the FEC takes up rulemaking on this issue, it could further clarify what constitutes “damage.” Is it damaging when a PAC promoting Ron DeSantis uses an AI voice synthesizer to generate a convincing facsimile of the voice of his opponent Donald Trump speaking his own Tweeted words? That seems like fair play. What if opponents find a way to manipulate the tone of the speech in a way that misrepresents its meaning? What if they make up words to put in Trump’s mouth? Those use cases seem to go too far, but drawing the boundaries between them will be challenging.
Congress has a role to play as well. Senator Klobuchar and colleagues have been promoting both the existing Honest Ads Act and the proposed REAL Political Ads Act, which would expand the FEC’s disclosure requirements for content posted on the Internet and create a legal requirement for campaigns to disclose when they have used images or video generated by AI in political advertising. While that’s worthwhile, it focuses on the shiny object of AI and misses the opportunity to strengthen law around the underlying issues. The FEC needs more authority to regulate campaign spending on false or misleading media generated by any means and published to any outlet. Meanwhile, the FEC’s own Inspector General continues to warn Congress that the agency is stressed by flat budgets that don’t allow it to keep pace with ballooning campaign spending.
It is intolerable for such a patchwork of commissions to be left to wonder which, if any of them, has jurisdiction to act in the digital space. Congress should legislate to make clear that there are guardrails on political speech and to better draw the boundaries between the FCC, FEC, and FTC’s roles in governing political speech. While the Supreme Court cannot be relied upon to uphold common sense regulations on campaigning, there are strategies for strengthening regulation under the First Amendment. And Congress should allocate more funding for enforcement.
The FEC has asked Congress to expand its jurisdiction, but no action is forthcoming. The present Senate Republican leadership is seen as an ironclad barrier to expanding the Commission’s regulatory authority. Senate Majority Leader Mitch McConnell has a decades-long history of being at the forefront of the movement to deregulate American elections and constrain the FEC. In 2003, he brought the unsuccessful Supreme Court case against the McCain-Feingold campaign finance reform act (the one that failed before the Citizens United case succeeded).
The most impactful regulatory requirement would be to require disclosure of interactive applications of AI for campaigns—and this should fall under the remit of the FCC. If a neighbor texts me and urges me to vote for a candidate, I might find that meaningful. If a bot does it under the instruction of a campaign, I definitely won’t. But I might find a conversation with the bot—knowing it is a bot—useful to learn about the candidate’s platform and positions, as long as I can be confident it is going to give me trustworthy information.
The FCC should enter rulemaking to expand its authority for regulating peer-to-peer (P2P) communications to explicitly encompass interactive AI systems. And Congress should pass enabling legislation to back it up, giving it authority to act not only on the SMS text messaging platform, but also over the wider Internet, where AI chatbots can be accessed over the web and through apps.
And the media has a role. We can still rely on the media to report out what videos, images, and audio recordings are real or fake. Perhaps deepfake technology makes it impossible to verify the truth of what is said in private conversations, but this was always unstable territory.
What is your role? Those who share these concerns could submit a comment to the FEC’s open public comment process before October 16, urging it to use its available authority. We all know government moves slowly, but a show of public interest is necessary to get the wheels moving.
Ultimately, all these policy changes serve the purpose of looking beyond the shiny distraction of AI to create the authority to counter bad behavior by humans. Remember: behind every AI is a human who should be held accountable.
This essay was written with Nathan Sanders, and was previously published on the Ash Center website.
AI Risks
There is no shortage of researchers and industry titans willing to warn us about the potential destructive power of artificial intelligence. Reading the headlines, one would hope that the rapid gains in AI technology have also brought forth a unifying realization of the risks—and the steps we need to take to mitigate them.
The reality, unfortunately, is quite different. Beneath almost all of the testimony, the manifestoes, the blog posts, and the public declarations issued about AI are battles among deeply divided factions. Some are concerned about far-future risks that sound like science fiction. Some are genuinely alarmed by the practical problems that chatbots and deepfake video generators are creating right now. Some are motivated by potential business revenue, others by national security concerns.
The result is a cacophony of coded language, contradictory views, and provocative policy demands that are undermining our ability to grapple with a technology destined to drive the future of politics, our economy, and even our daily lives.
These factions are in dialogue not only with the public but also with one another. Sometimes, they trade letters, opinion essays, or social threads outlining their positions and attacking others’ in public view. More often, they tout their viewpoints without acknowledging alternatives, leaving the impression that their enlightened perspective is the inevitable lens through which to view AI But if lawmakers and the public fail to recognize the subtext of their arguments, they risk missing the real consequences of our possible regulatory and cultural paths forward.
To understand the fight and the impact it may have on our shared future, look past the immediate claims and actions of the players to the greater implications of their points of view. When you do, you’ll realize this isn’t really a debate only about AI. It’s also a contest about control and power, about how resources should be distributed and who should be held accountable.
Beneath this roiling discord is a true fight over the future of society. Should we focus on avoiding the dystopia of mass unemployment, a world where China is the dominant superpower or a society where the worst prejudices of humanity are embodied in opaque algorithms that control our lives? Should we listen to wealthy futurists who discount the importance of climate change because they’re already thinking ahead to colonies on Mars? It is critical that we begin to recognize the ideologies driving what we are being told. Resolving the fracas requires us to see through the specter of AI to stay true to the humanity of our values.
One way to decode the motives behind the various declarations is through their language. Because language itself is part of their battleground, the different AI camps tend not to use the same words to describe their positions. One faction describes the dangers posed by AI through the framework of safety, another through ethics or integrity, yet another through security, and others through economics. By decoding who is speaking and how AI is being described, we can explore where these groups differ and what drives their views.
The Doomsayers
The loudest perspective is a frightening, dystopian vision in which AI poses an existential risk to humankind, capable of wiping out all life on Earth. AI, in this vision, emerges as a godlike, superintelligent, ungovernable entity capable of controlling everything. AI could destroy humanity or pose a risk on par with nukes. If we’re not careful, it could kill everyone or enslave humanity. It’s likened to monsters like the Lovecraftian shoggoths, artificial servants that rebelled against their creators, or paper clip maximizers that consume all of Earth’s resources in a single-minded pursuit of their programmed goal. It sounds like science fiction, but these people are serious, and they mean the words they use.
These are the AI safety people, and their ranks include the “Godfathers of AI,” Geoff Hinton and Yoshua Bengio. For many years, these leading lights battled critics who doubted that a computer could ever mimic capabilities of the human mind. Having steamrollered the public conversation by creating large language models like ChatGPT and other AI tools capable of increasingly impressive feats, they appear deeply invested in the idea that there is no limit to what their creations will be able to accomplish.
This doomsaying is boosted by a class of tech elite that has enormous power to shape the conversation. And some in this group are animated by the radical effective altruism movement and the associated cause of long-term-ism, which tend to focus on the most extreme catastrophic risks and emphasize the far-future consequences of our actions. These philosophies are hot among the cryptocurrency crowd, like the disgraced former billionaire Sam Bankman-Fried, who at one time possessed sudden wealth in search of a cause.
Reasonable sounding on their face, these ideas can become dangerous if stretched to their logical extremes. A dogmatic long-termer would willingly sacrifice the well-being of people today to stave off a prophesied extinction event like AI enslavement.
Many doomsayers say they are acting rationally, but their hype about hypothetical existential risks amounts to making a misguided bet with our future. In the name of long-term-ism, Elon Musk reportedly believes that our society needs to encourage reproduction among those with the greatest culture and intelligence (namely, his ultrarich buddies). And he wants to go further, such as limiting the right to vote to parents and even populating Mars. It’s widely believed that Jaan Tallinn, the wealthy long-termer who co-founded the most prominent centers for the study of AI safety, has made dismissive noises about climate change because he thinks that it pales in comparison with far-future unknown unknowns like risks from AI. The technology historian David C. Brock calls these fears “wishful worries”—that is, “problems that it would be nice to have, in contrast to the actual agonies of the present.”
More practically, many of the researchers in this group are proceeding full steam ahead in developing AI, demonstrating how unrealistic it is to simply hit pause on technological development. But the roboticist Rodney Brooks has pointed out that we will see the existential risks coming—the dangers will not be sudden and we will have time to change course. While we shouldn’t dismiss the Hollywood nightmare scenarios out of hand, we must balance them with the potential benefits of AI and, most important, not allow them to strategically distract from more immediate concerns. Let’s not let apocalyptic prognostications overwhelm us and smother the momentum we need to develop critical guardrails.
The Reformers
While the doomsayer faction focuses on the far-off future, its most prominent opponents are focused on the here and now. We agree with this group that there’s plenty already happening to cause concern: Racist policing and legal systems that disproportionately arrest and punish people of color. Sexist labor systems that rate feminine-coded résumés lower. Superpower nations automating military interventions as tools of imperialism and, someday, killer robots.
The alternative to the end-of-the-world, existential risk narrative is a distressingly familiar vision of dystopia: a society in which humanity’s worst instincts are encoded into and enforced by machines. The doomsayers think AI enslavement looks like the Matrix; the reformers point to modern-day contractors doing traumatic work at low pay for OpenAI in Kenya.
Propagators of these AI ethics concerns—like Meredith Broussard, Safiya Umoja Noble, Rumman Chowdhury, and Cathy O’Neil—have been raising the alarm on inequities coded into AI for years. Although we don’t have a census, it’s noticeable that many leaders in this cohort are people of color, women, and people who identify as LGBTQ. They are often motivated by insight into what it feels like to be on the wrong end of algorithmic oppression and by a connection to the communities most vulnerable to the misuse of new technology. Many in this group take an explicitly social perspective: When Joy Buolamwini founded an organization to fight for equitable AI, she called it the Algorithmic Justice League. Ruha Benjamin called her organization the Ida B. Wells Just Data Lab.
Others frame efforts to reform AI in terms of integrity, calling for Big Tech to adhere to an oath to consider the benefit of the broader public alongside—or even above—their self-interest. They point to social media companies’ failure to control hate speech or how online misinformation can undermine democratic elections. Adding urgency for this group is that the very companies driving the AI revolution have, at times, been eliminating safeguards. A signal moment came when Timnit Gebru, a co-leader of Google’s AI ethics team, was dismissed for pointing out the risks of developing ever-larger AI language models.
While doomsayers and reformers share the concern that AI must align with human interests, reformers tend to push back hard against the doomsayers’ focus on the distant future. They want to wrestle the attention of regulators and advocates back toward present-day harms that are exacerbated by AI misinformation, surveillance, and inequity. Integrity experts call for the development of responsible AI, for civic education to ensure AI literacy and for keeping humans front and center in AI systems.
This group’s concerns are well documented and urgent—and far older than modern AI technologies. Surely, we are a civilization big enough to tackle more than one problem at a time; even those worried that AI might kill us in the future should still demand that it not profile and exploit us in the present.
The Warriors
Other groups of prognosticators cast the rise of AI through the language of competitiveness and national security. One version has a post-9/11 ring to it—a world where terrorists, criminals, and psychopaths have unfettered access to technologies of mass destruction. Another version is a Cold War narrative of the United States losing an AI arms race with China and its surveillance-rich society.
Some arguing from this perspective are acting on genuine national security concerns, and others have a simple motivation: money. These perspectives serve the interests of American tech tycoons as well as the government agencies and defense contractors they are intertwined with.
OpenAI’s Sam Altman and Meta’s Mark Zuckerberg, both of whom lead dominant AI companies, are pushing for AI regulations that they say will protect us from criminals and terrorists. Such regulations would be expensive to comply with and are likely to preserve the market position of leading AI companies while restricting competition from start-ups. In the lobbying battles over Europe’s trailblazing AI regulatory framework, US megacompanies pleaded to exempt their general-purpose AI from the tightest regulations, and whether and how to apply high-risk compliance expectations on noncorporate open-source models emerged as a key point of debate. All the while, some of the moguls investing in upstart companies are fighting the regulatory tide. The Inflection AI co-founder Reid Hoffman argued, “The answer to our challenges is not to slow down technology but to accelerate it.”
Any technology critical to national defense usually has an easier time avoiding oversight, regulation, and limitations on profit. Any readiness gap in our military demands urgent budget increases and funds distributed to the military branches and their contractors, because we may soon be called upon to fight. Tech moguls like Google’s former chief executive Eric Schmidt, who has the ear of many lawmakers, signal to American policymakers about the Chinese threat even as they invest in US national security concerns.
The warriors’ narrative seems to misrepresent that science and engineering are different from what they were during the mid-twentieth century. AI research is fundamentally international; no one country will win a monopoly. And while national security is important to consider, we must also be mindful of self-interest of those positioned to benefit financially.
As the science-fiction author Ted Chiang has said, fears about the existential risks of AI are really fears about the threat of uncontrolled capitalism, and dystopias like the paper clip maximizer are just caricatures of every start-up’s business plan. Cosma Shalizi and Henry Farrell further argue that “we’ve lived among shoggoths for centuries, tending to them as though they were our masters” as monopolistic platforms devour and exploit the totality of humanity’s labor and ingenuity for their own interests. This dread applies as much to our future with AI as it does to our past and present with corporations.
Regulatory solutions do not need to reinvent the wheel. Instead, we need to double down on the rules that we know limit corporate power. We need to get more serious about establishing good and effective governance on all the issues we lost track of while we were becoming obsessed with AI, China, and the fights picked among robber barons.
By analogy to the healthcare sector, we need an AI public option to truly keep AI companies in check. A publicly directed AI development project would serve to counterbalance for-profit corporate AI and help ensure an even playing field for access to the twenty-first century’s key technology while offering a platform for the ethical development and use of AI.
Also, we should embrace the humanity behind AI. We can hold founders and corporations accountable by mandating greater AI transparency in the development stage, in addition to applying legal standards for actions associated with AI. Remarkably, this is something that both the left and the right can agree on.
Ultimately, we need to make sure the network of laws and regulations that govern our collective behavior is knit more strongly, with fewer gaps and greater ability to hold the powerful accountable, particularly in those areas most sensitive to our democracy and environment. As those with power and privilege seem poised to harness AI to accumulate much more or pursue extreme ideologies, let’s think about how we can constrain their influence in the public square rather than cede our attention to their most bombastic nightmare visions for the future.
This essay was written with Nathan Sanders, and previously appeared in the New York Times.
Deepfake Election Interference in Slovakia
Well designed and well timed deepfake or two Slovakian politicians discussing how to rig the election:
Šimečka and Denník N immediately denounced the audio as fake. The fact-checking department of news agency AFP said the audio showed signs of being manipulated using AI. But the recording was posted during a 48-hour moratorium ahead of the polls opening, during which media outlets and politicians are supposed to stay silent. That meant, under Slovakia’s election rules, the post was difficult to widely debunk. And, because the post was audio, it exploited a loophole in Meta’s manipulated-media policy, which dictates only faked videos—where a person has been edited to say words they never said—go against its rules.
I just wrote about this. Countries like Russia and China tend to test their attacks out on smaller countries before unleashing them on larger ones. Consider this a preview to their actions in the US next year.
Political Disinformation and AI
Elections around the world are facing an evolving threat from foreign actors, one that involves artificial intelligence.
Countries trying to influence each other’s elections entered a new era in 2016, when the Russians launched a series of social media disinformation campaigns targeting the US presidential election. Over the next seven years, a number of countries—most prominently China and Iran—used social media to influence foreign elections, both in the US and elsewhere in the world. There’s no reason to expect 2023 and 2024 to be any different.
But there is a new element: generative AI and large language models. These have the ability to quickly and easily produce endless reams of text on any topic in any tone from any perspective. As a security expert, I believe it’s a tool uniquely suited to Internet-era propaganda.
This is all very new. ChatGPT was introduced in November 2022. The more powerful GPT-4 was released in March 2023. Other language and image production AIs are around the same age. It’s not clear how these technologies will change disinformation, how effective they will be or what effects they will have. But we are about to find out.
Election season will soon be in full swing in much of the democratic world. Seventy-one percent of people living in democracies will vote in a national election between now and the end of next year. Among them: Argentina and Poland in October, Taiwan in January, Indonesia in February, India in April, the European Union and Mexico in June, and the US in November. Nine African democracies, including South Africa, will have elections in 2024. Australia and the UK don’t have fixed dates, but elections are likely to occur in 2024.
Many of those elections matter a lot to the countries that have run social media influence operations in the past. China cares a great deal about Taiwan, Indonesia, India, and many African countries. Russia cares about the UK, Poland, Germany, and the EU in general. Everyone cares about the United States.
And that’s only considering the largest players. Every US national election from 2016 has brought with it an additional country attempting to influence the outcome. First it was just Russia, then Russia and China, and most recently those two plus Iran. As the financial cost of foreign influence decreases, more countries can get in on the action. Tools like ChatGPT significantly reduce the price of producing and distributing propaganda, bringing that capability within the budget of many more countries.
A couple of months ago, I attended a conference with representatives from all of the cybersecurity agencies in the US. They talked about their expectations regarding election interference in 2024. They expected the usual players—Russia, China, and Iran—and a significant new one: “domestic actors.” That is a direct result of this reduced cost.
Of course, there’s a lot more to running a disinformation campaign than generating content. The hard part is distribution. A propagandist needs a series of fake accounts on which to post, and others to boost it into the mainstream where it can go viral. Companies like Meta have gotten much better at identifying these accounts and taking them down. Just last month, Meta announced that it had removed 7,704 Facebook accounts, 954 Facebook pages, 15 Facebook groups, and 15 Instagram accounts associated with a Chinese influence campaign, and identified hundreds more accounts on TikTok, X (formerly Twitter), LiveJournal, and Blogspot. But that was a campaign that began four years ago, producing pre-AI disinformation.
Disinformation is an arms race. Both the attackers and defenders have improved, but also the world of social media is different. Four years ago, Twitter was a direct line to the media, and propaganda on that platform was a way to tilt the political narrative. A Columbia Journalism Review study found that most major news outlets used Russian tweets as sources for partisan opinion. That Twitter, with virtually every news editor reading it and everyone who was anyone posting there, is no more.
Many propaganda outlets moved from Facebook to messaging platforms such as Telegram and WhatsApp, which makes them harder to identify and remove. TikTok is a newer platform that is controlled by China and more suitable for short, provocative videos—ones that AI makes much easier to produce. And the current crop of generative AIs are being connected to tools that will make content distribution easier as well.
Generative AI tools also allow for new techniques of production and distribution, such as low-level propaganda at scale. Imagine a new AI-powered personal account on social media. For the most part, it behaves normally. It posts about its fake everyday life, joins interest groups and comments on others’ posts, and generally behaves like a normal user. And once in a while, not very often, it says—or amplifies—something political. These persona bots, as computer scientist Latanya Sweeney calls them, have negligible influence on their own. But replicated by the thousands or millions, they would have a lot more.
That’s just one scenario. The military officers in Russia, China, and elsewhere in charge of election interference are likely to have their best people thinking of others. And their tactics are likely to be much more sophisticated than they were in 2016.
Countries like Russia and China have a history of testing both cyberattacks and information operations on smaller countries before rolling them out at scale. When that happens, it’s important to be able to fingerprint these tactics. Countering new disinformation campaigns requires being able to recognize them, and recognizing them requires looking for and cataloging them now.
In the computer security world, researchers recognize that sharing methods of attack and their effectiveness is the only way to build strong defensive systems. The same kind of thinking also applies to these information campaigns: The more that researchers study what techniques are being employed in distant countries, the better they can defend their own countries.
Disinformation campaigns in the AI era are likely to be much more sophisticated than they were in 2016. I believe the US needs to have efforts in place to fingerprint and identify AI-produced propaganda in Taiwan, where a presidential candidate claims a deepfake audio recording has defamed him, and other places. Otherwise, we’re not going to see them when they arrive here. Unfortunately, researchers are instead being targeted and harassed.
Maybe this will all turn out okay. There have been some important democratic elections in the generative AI era with no significant disinformation issues: primaries in Argentina, first-round elections in Ecuador, and national elections in Thailand, Turkey, Spain, and Greece. But the sooner we know what to expect, the better we can deal with what comes.
This essay previously appeared in The Conversation.
Malicious Ads in Bing Chat
Malicious ads are creeping into chatbots.
NSA AI Security Center
The NSA is starting a new artificial intelligence security center:
The AI security center’s establishment follows an NSA study that identified securing AI models from theft and sabotage as a major national security challenge, especially as generative AI technologies emerge with immense transformative potential for both good and evil.
Nakasone said it would become “NSA’s focal point for leveraging foreign intelligence insights, contributing to the development of best practices guidelines, principles, evaluation, methodology and risk frameworks” for both AI security and the goal of promoting the secure development and adoption of AI within “our national security systems and our defense industrial base.”
He said it would work closely with U.S. industry, national labs, academia and the Department of Defense as well as international partners.
Sidebar photo of Bruce Schneier by Joe MacInnis.