{"id":9673,"date":"2026-07-08T10:10:51","date_gmt":"2026-07-08T10:10:41","guid":{"rendered":"https:\/\/www.law.georgetown.edu\/tech-institute\/research-insights\/insights\/new-technical-briefing-digital-fingerprinting-2\/"},"modified":"2026-07-08T16:06:23","modified_gmt":"2026-07-08T16:06:23","slug":"a-response-to-access-to-justice-in-the-age-of-ai","status":"publish","type":"page","link":"https:\/\/www.law.georgetown.edu\/tech-institute\/research-insights\/insights\/a-response-to-access-to-justice-in-the-age-of-ai\/","title":{"rendered":"A Response to Access to Justice in the Age of AI"},"content":{"rendered":"
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A Response to Access to Justice in the Age of AI<\/strong><\/h2>\n<\/div>\n
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Last we spoke, I\u00a0argued<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0that there\u2019s little evidence that justice tech helps people. Now there\u2019s a paper hinting that AI might be helping people get to court without attorneys (and win?)\u2014but that isn\u2019t what the authors conclude. Being that the piece received significant attention, it deserves a closer look.<\/p>\n

I\u2019m referring to a working draft of an academic paper, \u201cAccess to Justice in the Age of AI: Evidence from U.S. Federal Courts<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u201d, by Shah and Levy. A\u00a0New York Times<\/span>(This link opens in a new tab)<\/span><\/span><\/a><\/em>\u00a0article<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0from late May amplified its findings. The paper\u2019s core claim is that the share of federal filings by people without attorneys\u2014so-called self-represented litigants (SRL)\u2014grew from 11% to 17% between 2020 and 2025. AI, the authors conclude, is driving the increase.<\/p>\n

The problem is that the paper can\u2019t prove its conclusion. Are people using AI to write court filings? Of course: everyone is using AI to write everything. The problem is that the paper went further than its data can support. While grabbing AI as the explanation, it ignored historical drivers of SRL litigation, like the economy. It relies on AI-detection software, which is a suspect research method. And what\u2019s worse: in framing SRLs as a burden on courts, it blames people for using the one resource they can afford to help navigate the justice system, while letting corporate culprits off the hook.<\/p>\n

Not Everything is Attributable to AI<\/strong><\/h2>\n
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The data at the center of the paper are 1,600 SRL court filings from before and after the public release of ChatGPT in 2023. They write that \u201cAI-generated text has been rising monotonically [in SRL federal filings] from 1.0% in 2023 to 18.0% in early 2026.\u201d At the same time, SRL filings as a total of federal filings are up 6%. The authors float two \u201cdescriptive\u201d conclusions: AI is creating new litigants who otherwise wouldn\u2019t have sued, or it\u2019s convincing people to drop their lawyers and go at it alone. They treat both as equally plausible without interrogating either.<\/div>\n<\/div>\n<\/div>\n

The upward trend in SRL and represented federal filings started in 2021 after the pandemic dip and two years before ChatGPT\u2019s public launch. While the growth curve gets steeper in 2024 and 2025, the pre-existing trend matters because the period from 2021 onward was one of escalating economic distress for American households. By the end of 2025, total household debt grew to\u00a0$18.8 trillion<\/span>(This link opens in a new tab)<\/span><\/span><\/a>. Credit card balances rose to $1.28 trillion. Delinquency rates on auto loans and credit cards climbed steadily, particularly among\u00a0lower-income borrowers<\/span>(This link opens in a new tab)<\/span><\/span><\/a>. People who are falling behind on debts get sued, and people who can\u2019t pay a $2,000 credit card bill can\u2019t afford a lawyer.<\/p>\n

The paper\u2019s own framing reinforces this point, though the authors don\u2019t draw the connection. Section 3.3 sorts cases into \u201csimple\u201d (consumer debt, civil rights, foreclosure) and \u201ccomplex\u201d (securities fraud, patent infringement). They note that the SRL uptick is concentrated in the simple case categories. The authors treat this as evidence that AI helps with cases that require less lawyer intervention. But they never consider that simple and complex cases, as they define them, impact different demographics. The average salary of a patent holder in the U.S. is\u00a0$256,000<\/span>(This link opens in a new tab)<\/span><\/span><\/a>. Securities ownership is dominated by households earning more than\u00a0$100,000 a year<\/span>(This link opens in a new tab)<\/span><\/span><\/a>. Both groups have access to resources, which buys legal representation. By contrast, we know economic hardship is a driver of litigation. Even the authors\u2019 own data shows a 42% increase in SRL filings in federal court between 2008 and 2012. During that time, SRLs went from 10% of the federal docket to 14% (remember, the authors\u2019 big statistic is that AI caused a 6% jump in SRL filings). This is all to say, the growth in SRL cases is at least as consistent with growing economic hardship as it is with AI adoption.<\/p>\n

Beyond the economy, national politics and federal priorities also deserve consideration. The single largest year-on-year jump in SRL filings is in 2025. The\u00a0Times<\/em>\u00a0article quotes a federal court staff attorney in Minnesota saying he\u2019d seen a \u201c50 percent uptick in filings from non-prisoners starting around March 2025.\u201d By then, we were two months into an administration abusing the public and dismantling the federal agencies that traditionally filed suits in court on behalf of people who can\u2019t afford to. By October 2025, the Trump-led Consumer Financial Protection Bureau had\u00a0dismissed or rolled back 42 enforcement actions<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0and gutted its consumer complaint program. The DOJ\u2019s Civil Rights Division\u00a0froze all new litigation<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0and lost an estimated\u00a070 percent of its attorney staff<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u2014a fraction of the\u00a0over 10,000 attorneys<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0that have left federal service in the last 18 months.<\/p>\n

When federal enforcement retreats, bad actors face fewer consequences, harmful practices increase, and individuals are left to fend for themselves. The paper simply doesn\u2019t consider the economic and political forces that have driven people into court without counsel for decades.<\/p>\n

AI Detection Isn\u2019t<\/strong><\/h2>\n

Setting aside alternative explanations, the paper\u2019s methodology deserves scrutiny.<\/p>\n

The study relies on Pangram, a proprietary black-box algorithm, to determine whether a filing contains AI-generated text. The authors cite one\u00a0working paper<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0that benchmarks Pangram\u2019s accuracy. It\u2019s a thin foundation, and the problems compound from there.<\/p>\n

There is little published research on Pangram specifically, but AI detection tools have well-documented defects.\u00a0Researchers out of Dublin<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0concluded that benchmark accuracy is not a reliable measure of AI detection tools’ real-world efficacy. These tools are benchmarked on domain-specific data, and accuracy drops when the tools are pointed at different subject matter. The benchmark cited by the authors wasn\u2019t tested on legal text, a significant gap for a paper about court filings.<\/p>\n

Another red flag is that false positives are a chronic problem.\u00a0Stanford researchers<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0found that non-native English speakers\u2019 writing is disproportionately flagged as AI-generated. A finding with obvious implications for the demographics that make up SRL litigants. False negatives are equally concerning. When AI text is paraphrased, detection accuracy dropped from 70.3% to 4.6% in one\u00a0study<\/span>(This link opens in a new tab)<\/span><\/span><\/a>.\u00a0Other research<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0found that hybrid texts\u2014documents mixing human and machine-generated writing\u2014also cause accuracy to drop.<\/p>\n

Taken as a whole, these tools offer a limited signal, not a verdict. These weaknesses in the methodology are particularly important to call out because the authors\u2019 first recommendation is to replicate this study on state court data. State court dockets are where the access-to-justice crisis is most acute, and replicating this methodology would misidentify who is filing and why. Building policy on top of such a weak foundation would do real harm to the most disadvantaged people trying to navigate our justice system.<\/p>\n

Stop Blaming the Poor<\/strong><\/h2>\n

Even if the methodology were stronger, the paper\u2019s framing raises a separate concern: it blames people without attorneys as the source of court strain.<\/p>\n

Starting in the abstract and running throughout, the authors frame increased SRL filings as a \u201cburden\u201d on the courts. However, they do not show that an increase in AI use has led to weaker cases. Well before AI, SRLs had a bad track record winning in court. However, the authors\u2019 own data says SRLs are losing 6% less than before ChatGPT went public and getting settlements 3% more of the time. Whether these changes are attributable to AI is unclear, however, they deserve more attention. But, if SRL outcomes are improving, the \u201cburden\u201d argument gets harder to make.<\/p>\n

Second, the paper glosses over its own data showing that filings by represented parties are up nearly 8% over the 2020-2025 period. Other studies provide evidence from state courts that AI is being used by corporate filers, particularly in America\u2019s fastest-growing docket:\u00a0debt collection<\/span>(This link opens in a new tab)<\/span><\/span><\/a>. A\u00a0handful of companies<\/span>(This link opens in a new tab)<\/span><\/span><\/a>\u00a0drive the majority of predatory debt litigation that looks to win by default, not on the merits of the claim. If AI-powered bulk filing is left unchecked, it\u00a0will<\/em>\u00a0create systemic burdens and supercharge courts into a platform for wealth redistribution going the wrong direction. But that\u2019s due to corporate greed, not poor folks.<\/p>\n

American justice is already out of reach for lower and increasingly middle-class people. Publishing and elevating research that obscures this systemic problem by blaming the disadvantaged isn\u2019t just wrong, it\u2019s harmful. The crisis isn\u2019t that people have found a tool that helps them get to court, iit\u2019s that they had no other choice.<\/p>\n

\u00a0<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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