arXiv subjects

Nicholas J. Restrepo

Publications and source records attributed to Nicholas J. Restrepo.

6 recordsLinked to original sources

arXiv2026

When AI output tips to bad but nobody notices: Legal implications of AI's mistakes

The adoption of generative AI across commercial and legal professions offers dramatic efficiency gains -- yet for law in particular, it introduces a perilous failure mode in which the AI fabricates fictitious case law, statutes, and judicial holdings that appear entirely authentic. Attorneys who unknowingly file such fabrications face professional sanctions, malpractice exposure, and reputational harm, while courts confront a novel threat to the integrity of the adversarial process. This failure mode is commonly dismissed as random `hallucination', but recent physics-based analysis of the Transformer's core mechanism reveals a deterministic component: the AI's internal state can cross a calculable threshold, causing its output to flip from reliable legal reasoning to authoritative-sounding fabrication. Here we present this science in a legal-industry setting, walking through a simulated brief-drafting scenario. Our analysis suggests that fabrication risk is not an anomalous glitch but a foreseeable consequence of the technology's design, with direct implications for the evolving duty of technological competence. We propose that legal professionals, courts, and regulators replace the outdated `black box' mental model with verification protocols based on how these systems actually fail.

cs.AI↗

arXiv2025

Long-term resilience of online battle over vaccines and beyond

What has been the impact of the enormous amounts of time, effort and money spent promoting pro-vaccine science from pre-COVID-19 to now? We answer this using a unique mapping of online competition between pro- and anti-vaccination views among ~100M Facebook Page members, tracking 1,356 interconnected communities through platform interventions. Remarkably, the network's fundamental architecture shows no change: the isolation of established expertise and the symbiosis of anti and mainstream neutral communities persist. This means that even if the same time, effort and money continue to be spent, nothing will likely change. The reason for this resilience lies in "glocal" evolution: Communities blend multiple topics while bridging neighborhood-level to international scales, creating redundant pathways that transcend categorical targeting. The solution going forward is to focus on the system's network. We show how network engineering approaches can achieve opinion moderation without content removal, representing a paradigm shift from suppression towards structural interventions.

cs.SI↗

arXiv2025

City riots fed by transnational and trans-topic web-of-influence

The sudden emergence of large-scale riots in otherwise unconnected cities across the UK in summer 2024 came as a shock for both government officials and citizens. Irrespective of these riots' specific trigger, a key question is how the capacity for such widespread city rioting might be foreseen through some precursor behavior that flags an emerging appetite for such rioting at scale. Here we show evidence that points toward particular online behavior which developed at scale well ahead of the riots, across the multi-platform landscape of hate/extremist communities. Our analysis of detailed multi-platform data reveals a web-of-influence that existed well before the riots, involving online hate and extremism communities locally, nationally, and globally. This web-of-influence fed would-be rioters in each city mainly through video platforms. This web-of-influence has a persistent resilience -- and hence still represents a significant local, national, and international threat in the future -- because of its feedback across regional-national-international scales and across topics such as immigration; and its use of multiple lesser-known platforms that put it beyond any single government or platform's reach. Going forward, our findings mean that if city administrators coordinate with each other across local-national-international divides, they can map this threat as we have done here and initiate deliberation programs that might then soften such pre-existing extremes at scale, perhaps using automated AI-based technology.

physics.soc-ph↗

arXiv2023

Complexity of the Online Distrust Ecosystem and its Evolution

Collective human distrust (and its associated mis-disinformation) is one of the most complex phenomena of our time. e.g. distrust of medical expertise, or climate change science, or democratic election outcomes, and even distrust of fact-checked events in the current Israel-Hamas and Ukraine-Russia conflicts. So what makes the online distrust ecosystem so resilient? How has it evolved during and since the pandemic? And how well have Facebook mitigation policies worked during this time period? We analyze a Facebook network of interconnected in-built communities (Facebook pages) totaling roughly 100 million users who pre-pandemic were just focused on distrust of vaccines. Mapping out this dynamical network from 2019 to 2023, we show that it has quickly self-healed in the wake of Facebook's mitigation campaigns which include shutdowns. This confirms and extends our earlier finding that Facebook's ramp-ups during COVID were ineffective (e.g. November 2020). Our findings show that future interventions must be chosen to resonate across multiple topics and across multiple geographical scales. Unlike many recent studies, our findings do not rely on third-party black-box tools whose accuracy for rigorous scientific research is unproven, hence raising doubts about such studies' conclusions, nor is our network built using fleeting hyperlink mentions which have questionable relevance.

cs.SI↗

arXiv2023

Adaptive link dynamics drive online hate networks and their mainstream influence

Online hate is dynamic, adaptive -- and is now surging armed with AI/GPT tools. Its consequences include personal traumas, child sex abuse and violent mass attacks. Overcoming it will require knowing how it operates at scale. Here we present this missing science and show that it contradicts current thinking. Waves of adaptive links connect the hate user base over time across a sea of smaller platforms, allowing hate networks to steadily strengthen, bypass mitigations, and increase their direct influence on the massive neighboring mainstream. The data suggests 1 in 10 of the global population have recently been exposed, including children. We provide governing dynamical equations derived from first principles. A tipping-point condition predicts more frequent future surges in content transmission. Using the U.S. Capitol attack and a 2023 mass shooting as illustrations, we show our findings provide abiding insights and quantitative predictions down to the hourly scale. The expected impacts of proposed mitigations can now be reliably predicted for the first time.

physics.soc-ph↗

arXiv2023

Rise of post-pandemic resilience across the distrust ecosystem

Why is distrust (e.g. of medical expertise) now flourishing online despite the surge in mitigation schemes being implemented? We analyze the changing discourse in the Facebook ecosystem of approximately 100 million users who pre-pandemic were focused on (dis)trust of vaccines. We find that post-pandemic, their discourse strongly entangles multiple non-vaccine topics and geographic scales both within and across communities. This gives the current distrust ecosystem a unique system-level resistance to mitigations that target a specific topic and geographic scale -- which is the case of many current schemes due to their funding focus, e.g. local health not national elections. Backed up by detailed numerical simulations, our results reveal the following counterintuitive solutions for implementing more effective mitigation schemes at scale: shift to 'glocal' messaging by (1) blending particular sets of distinct topics (e.g. combine messaging about specific diseases with climate change) and (2) blending geographic scales.

physics.soc-ph↗