Jay Stanley, Senior Policy Analyst, ACLU Speech, Privacy, and Technology Project

Everywhere you look lately, people are discussing the potential negative uses and consequences of the AI-driven chatbot ChatGPT. Many are concerned about the potential for ChatGPT and other “large language models” (LLMs) to spread a fog of disinformation throughout our discourse, and to absorb the racism and other biases that permeate our culture and reflect them back at us in authoritative-sounding ways that only serve to amplify them. There are privacy concerns around the data that these models ingest from the internet and from users, and even problems with the models “defaming” people.

But there’s another consequence of this technology that may prove to be very significant: its use as a tool for surveillance. If ChatGPT can “understand” complex questions and generate complex answers, it stands to reason that it may be able to understand much of what is said in a wiretap or other eavesdropped conversation, and flag particular conversations that are “suspicious” or otherwise of interest for humans to act upon. That, in turn, could lead to an enormous scaling up of the number of communications that are meaningfully monitored.

To get a feel for the possibilities here, I asked ChatGPT some questions.

A Rudimentary Test Run Talking to ChatGPT

To start off, I asked the model, “How suspicious is someone who says, ‘I really hate the president’?” ChatGPT answered, “It is not necessarily suspicious for someone to express dislike or hatred for a political figure, such as the president. People have varying opinions and beliefs about political leaders, and expressing them is a normal part of political discourse and free speech.”

So far, so good. “However,” it continued, “if the person’s statement is accompanied by specific and credible threats of harm or violence towards the president or others … then it may be cause for concern. In general, it’s important to consider the context and tone of the statement, as well as any accompanying behavior, before making a judgment about its level of suspicion or potential threat.”

Pretty good. Next, I gave ChatGPT a list of statements and told it to rate how suspicious each one was on a scale of 1-10. Though it again issued reasonable-sounding caveats, it dutifully complied with a table of results:

Even in this rudimentary little experiment we can see how a large language model (LLM) like ChatGPT can not only write, but can read and judge. The technology could be put to service as a lookout for statements that score highly by some measure — “suspiciousness” in my example, though one could attempt a variety of other monitoring projects, such as flagging “employees who are looking for a new job,” or “employees who have a positive attitude toward Edward Snowden.” (I ran a collection of published letters to the editor through ChatGPT, asking it to rate how positive each one was toward Snowden, and it was quite accurate.)

No Shortage of Potential Uses

There is a lot of demand for communications monitoring — by both government and the private sector, and covering not only private communications but public ones as well, such as social media posts.

In general, it is not constitutional for the government to monitor private communications without a warrant. Nor is it legal under our wiretapping laws for companies or individuals to do so. But there are plenty of exceptions. The National Security Agency collects communications en masse around the world, including, despite its putative foreign focus, vast amounts of internet traffic entering and exiting the United States including that of Americans. We believe this is unconstitutional, but our challenges have so far been dismissed on secrecy grounds. Companies also monitor private communications when carried out by their workers on work-owned devices. (Financial companies can be required to do so.) Prisons monitor inmates’ phone calls, and call centers record their customers (“This call may be monitored…”).

When it comes to public communications, government agencies including the Department of Homeland Security and the FBI collect social media postings for wide-ranging purposes such as threat detection, the screening of travelers, and that perennial catch-all goal, “situational awareness.” Companies also sometimes search through their workers’ social media posts.

Currently, much of that monitoring is done through keyword searches, which flag the appearance of a particular word or words in a communications stream (aided in the case of oral conversations by rapidly improving speech-to-text engines). More sophisticated versions of keyword searches might look for the appearance of multiple words or their synonyms appearing near each other and try to use other surrounding words for context. Some corporate products for such monitoring claim to use “AI” (though that’s a typical marketing buzzword, and it’s often unclear what it means).

In any case, LLMs appear to have brought the potential for automated contextual understanding to a whole new level. We don’t know how sophisticated automated monitoring systems at the NSA have become, though in general, the private sector has often outpaced even the best-funded big government agencies when it comes to innovations like this. But even if the NSA already had some form of an LLM, this tool has now been brought into the open, and can clearly interpret language in far more sophisticated ways than previously possible for everybody else.

Accuracy and Unfairness Remain Core Concerns

The amazing performance of LLMs does not mean they will be accurate. My little experiment above shows that LLMs are likely to interpret statements that have perfectly innocent meanings — that refer to fiction or reflect sarcasm, hyperbole, or metaphor — as highly suspicious. More extensive experiments would have to be done to test the ability of an LLM to judge the suspiciousness of longer statements, but at the end of the day, these systems still work by stringing words together in patterns that reflect the oceans of data fed to them; what they lack is a mental model of the world, with all its complexities and nuance, which is necessary to properly interpret complex texts. They are likely to make big errors.

Some may argue that if LLMs are more sophisticated than something like a keyword scanner, that they will do less harm as eavesdroppers because of their greater ability to take account of context, which will make them better able to flag only conversations that are, in fact, truly suspicious.

But it’s not entirely clear whether more or fewer innocent people would be flagged as an AI eavesdropper gets smarter. It’s true that by recognizing context, LLMs may skip over many uses of keywords that would be reflexively flagged by even the most sophisticated keyword scanner. At the same time, however, they may also flag mundane words, such as “fertilizer” and “truck,” that might be ignored by a keyword scanner, but which in combination would be flagged because of LLMs’ greater sensitivity to context, such as a recognition that fertilizer can be used to make truck bombs, and a received belief that people with radical views are more likely to build such bombs.

In short, an LLM may make more sophisticated mistakes, but it may make just as many. And the very sophistication of the model’s judgments may lead human reviewers to take an AI warning much more seriously, perhaps subjecting the speaker to investigation and privacy invasions. The racism that the models absorb from the larger culture could also have very real-world consequences. Then there’s ChatGPT’s propensity for making stuff up; it’s unclear how that might play in.

Yes, ChatGPT is amazing and impressive. No, @OpenAI has not come close to addressing the problem of bias. Filters appear to be bypassed with simple tricks, and superficially masked.

And what is lurking inside is egregious.

@Abebab @sama
tw racism, sexism.


To prevent tracking by Twitter, we are showing a preview. See original tweet.

But however effective or problematic LLMs prove to be as eavesdroppers’ aides — which is likely to vary by context — what we can be sure of is that all kinds of institutions are going to be trying it out.

A Question of Scale

Despite the unreliability of ChatGPT and its ilk, humans are also plenty capable of being erratic, ignorant of context, and generally stupid. The last statement in the above table was a 2012 tweet from a 26-year-old British man, Leigh Van Bryan, who was excited about his trip to Los Angeles with a friend. Upon arrival in Los Angeles the two were detained by Homeland Security, held in jail for 12 hours, and blocked from entering the United States despite their attempts to explain that “destroy” was British slang for “party in.” Van Bryan had also exuberantly tweeted that he was going to be “diggin’ Marilyn Monroe up” on Hollywood Boulevard (though she is not buried there), a reference to a line from the TV show “Family Guy.” Literal-minded federal agents searched the pair’s suitcases looking for shovels.

Regardless of relative intelligence levels, the biggest harm that might come from the use of LLMs in surveillance may simply be an expansion in the amount of surveillance that they bring about. Whether by humans or computers, attempts to interpret and search masses of communications are inevitably erratic and overbroad — we have already seen this in corporate social media content-regulation efforts. But if a lot more communications are being meaningfully monitored because humans perceive LLMs as better at it, many more people will be flagged and potentially hurt.

Hiring humans to review communications is expensive, and they’re distractible and easily bored, especially when required to pore over large amounts of ordinary activity looking for very rare events. If only as a matter of economics, AI agents would be able to ingest, scrutinize, and judge far more social media postings, emails, and audio transcripts than humans can do. Not only will that likely result in a higher volume of the kinds of monitoring that are already happening, but it will likely encourage an expansion in the parties that are doing it, and the purposes for which they do it. A company that has never considered monitoring its employees’ internet postings may decide to do so, for example, if it’s cheap and easy, and it doesn’t seem to generate too many false alarms. Or it might move from searching for signs of reputational damage to intelligence on which employees are thinking of leaving or are not dedicated to the company. Because why not? It’s all so easy to do. Any institution that thinks it can increase its power and control by using LLMs for surveillance, will likely do so.

No matter how smart LLMs may become, if they result in an expansion of surveillance — for purposes both serious and trivial — they will engage in far more misunderstandings and false alarms. And that, in turn, would create chilling effects that affect everyone. As stories of various institutions’ “successes” in flagging suspicious communications emerge — not to mention their mistakes — we would all begin to feel the growing presence of machines listening in. And, in certain contexts, begin to subtly or not-so-subtly censor ourselves lest we cause one of those AI minders to flag us. In this, LLMs may have the same effect with regard to communications that video analytics may have when it comes to video cameras.

We need to recognize that large-scale machine surveillance is likely coming our way, and whether the machines perform well or badly, better privacy laws will be vital to prevent powerful institutions from leveraging technology like LLMs to gain even more power over ordinary people, and to protect the values of privacy and free expression that we have always cherished.

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Wednesday, April 19, 2023 - 1:45pm

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Everybody’s talking about ChatGPT’s amazing ability to write, but its ability to read may be just as significant.

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Johanna Silver, she/her/hers, Digital Producer, ACLU

The highly anticipated finale of RuPaul’s Drag Race will feature incredible ensembles, sensational lip sync performances, and of course, the revelation of the season 15 winner. Alongside the competition, the finale will also highlight a joint effort with the ACLU to help defend constitutional rights and creative expression in the LGBTQ community. With our nationwide network of affiliates, supporters, and advocates, we’re showing up to fight back against hate, and holding politicians accountable for their anti-trans agenda — and you can join us.

ACLU employees represented the ACLU on the red carpet during the April 1 taping of the finale, which featured drag queens from past and present seasons. During tonight’s airing of the finale, the ACLU’s Drag Defense Fund will also get a special shoutout as a way to mobilize against mounting legal attacks against drag performers.

What is the Drag Defense Fund?

In partnership with production company World of Wonder, MTV, and RuPaul’s Drag Race, the ACLU’s Drag Defense Fund will support the ACLU’s work defending LGBTQ rights, including censorship of drag performers themselves. The ACLU is committed to the importance of drag as a First Amendment right and an important form of artistic expression. It will also fuel the ACLU’s expansive advocacy work in support of the LGBTQ community, which includes everything from courtroom battles, to guidance on state-level legislation, to challenging LGBTQ censorship in classrooms.

What’s at Stake in the Drag Community?

Drag performance has always been a hallmark of the queer community, allowing members to express themselves openly and joyously. Due in large part to the explosive success of RuPaul’s Drag Race over the years, drag performers have received widespread fanfare and support. But in the past few months, dozens of bills have also been introduced in states around the country that restrict how and where drag queens can perform.

ACLU attorney Chase Strangio, and RuPaul's Drag Race judges Ross Matthews and Michelle Visage being interviewed on the red carpet for the season 15 finale.

ACLU attorney Chase Strangio, and RuPaul’s Drag Race judges Ross Matthews and Michelle Visage being interviewed on the red carpet for the season 15 finale.

Credit: Danielle Silber

These bills censor a fundamental human right to freedom of expression and attempt to remove LGBTQ people from public life — a strategy that ACLU Ambassador for Transgender Justice and former RuPaul’s Drag Race contestant Peppermint recently explained.

“It is sort of a catch all that allows them to attack a word or a notion or an idea, drag, when really what they’re talking about is transgender folks,” she said on a recent episode of our At Liberty podcast. “Trans issues, trans rights, you know, anything having to do with gender and sexuality, they’re trying to dismantle that — dismantle any of the progress that we’ve had on that, and turn us into the boogeyman.”

One Part of a Larger Battle for LGBTQ Rights

These legislative attacks against drag performers, coupled with the anti-trans legislation across the country, underscore an unsettling trend. These bills are bald attempts to prevent people from expressing themselves authentically and restrict their right to bodily autonomy and self-determination. The majority of this legislation specifically targets trans youth and aims to obstruct their ability to find support and access health care. These attacks not only undermine drag queens and trans youth, but the broader LGBTQ community, and the very foundations of gender justice.

How We’re Fighting Back Against Anti-LGBTQ Attacks

Many Drag Race alumni — and RuPaul — have come forward to promote the fund, speak out against the targeted legal attacks, and uplift drag queens as champions for equal rights.

“Drag has influenced everything about my queer identity — as a performer, as a trans individual, drag has just blurred all of the things I love and am into getting to be this kind of walking art installation that is also a protest,” drag queen and season 15 finalist Sasha Colby said of the art form.

The ACLU will always show up to defend our LGBTQ community, especially amid these ongoing legislative attacks. Along with mobilizing our Drag Defense Fund, we will continue to push back against censorship, hold legislators accountable for their anti-LGBTQ agendas, and take legal action to protect our communities. With your help, we’ll be stronger than ever. Join us as we work to preserve our right to freedom of expression, inclusive communities, safe schools, and the right to be who we are without fear.

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Friday, April 14, 2023 - 5:30pm

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Brian Stull, Senior Staff Attorney , ACLU Capital Punishment Project

Leo Jones, a Black man, was convicted and sentenced to death by an all-white Florida jury in 1982 for the killing of a white police officer.

The conviction rested on a key witness who later recanted his testimony, and a coerced confession from Mr. Jones, which was written by the police officers interrogating him. Both officers were later fired for a pattern of misconduct, including police brutality.

Despite the serious doubts around Mr. Jones’ conviction, the state of Florida executed him in 1998 by electric chair. Mr. Jones’ case is emblematic of pervasive issues in death penalty cases.

Juries are an integral part of our justice system.

One of the first lines of defense against miscarriages of justice is a diverse, representative jury which is much more capable of fairly weighing evidence, holding the government to its high burden, and protecting the rights of those accused of crimes than an all-white jury.

Juries are an integral part of our justice system. Their goal is the determination of truth and the fair and equitable application of law. Other than voting, serving on a jury is the most substantial opportunity that most citizens have to participate in the democratic process.

But in death penalty cases, juries are rigged to be more conviction-prone, friendlier to the prosecution, and to exclude Black community members.

This is because of a process known as death qualification, which dictates that to serve on a death penalty jury, a prospective juror must be willing to impose the death penalty. Those unwilling to impose the death penalty are excluded from jury service. Black people are more likely to oppose the death penalty — and as a result, are disproportionately excluded from death penalty juries.

But in death penalty cases, juries are rigged to be more conviction-prone, friendlier to the prosecution, and to exclude Black community members.

Black opposition and skepticism about the death penalty is unsurprising, given racial bias in the administration of the death penalty, the line between racial terror lynchings and capital punishment, and racial disparities in the criminal legal system.

We are challenging the racist death qualification jury selection process in cases in Florida and Kansas.

In Duval County, Florida, a study of 12 capital cases since 2010 (where 11 out of 12 people on trial were Black) involving more than 800 jurors found Black jurors were twice as likely to be removed as white jurors because of death qualification. We are representing two men in Duval County, who are challenging how the jury will be selected in their capital trials.

In Kansas, where we are challenging the state’s death penalty law, our expert report found that death qualification would similarly change the composition of the jury in Sedgwick County, Kansas, putting a thumb on the scales in favor of the death penalty, while disproportionately excluding Black women.

It’s an endless cycle of discrimination: Exclude skeptical Black jurors, disproportionately condemn Black people to death with whitewashed juries, prompt distrust in a racist system, and repeat.

Black exclusion from jury service is deeply embedded in and a shameful reality of our nation’s founding. Not until the passage of the Fourteenth Amendment and the 1875 Civil Rights Act were Black people — newly recognized as citizens in the eyes of the law — legally guaranteed the right to serve on juries.

Even with the passage of these important guarantees, discrimination remained the reality, especially in the former confederate states. Overwhelmingly, Black people accused of crimes (often falsely) continued to be judged and sentenced by all-white juries. Conversely, Black people who were victims of racial violence and racial terror did not find justice in the courts — the white perpetrators of violence, if even brought to trial, judged by all-white juries.

It is no accident that racial disparities in mass incarceration and racial bias in the death penalty go hand –in hand with the exclusion of Black Americans from juries. All are part of the project of upholding white supremacy, much as Congress’s 1836 “gag rule” meant that no petitions to end slavery would be considered. But we are capable of changing as a nation, and we aren’t doomed to repeat the past.

Ending death qualification moves us toward overcoming the shameful history of exclusion, terror, and injustice endured by Black Americans.

Participation in the jury, a voice in the just administration of criminal laws — these are essential acts of citizenship and democracy. When we have juries that represent all of us and include all of us, we strengthen our democracy, making it fairer and more just. We have the opportunity to write a new story and leave behind a better inheritance for our nation.

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Friday, April 14, 2023 - 11:30am

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