MARC21: Au-delà de la constellation : l’impact de Gemini sur les professions juridiques

Au-delà de la constellation : l’impact de Gemini sur les professions juridiques

This research paper seeks to comprehensively evaluate the impact that Google’s AI system, Gemini, could have on various legal professions, based on a rigorous analysis of its claimed capabilities and limitations. The paper begins by introducing large language models (LLMs) and highlighting their cap...

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Autore principale:	Nizza, Umberto
Natura:	Article ou chapitre numérique
Lingua:	Français
Pubblicazione:	2024
Soggetti:	analyse textuelle assistance juridique Gemini intelligence artificielle modèles de langage (LLM) professions juridiques artificial intelligence Large Language Models (LLM) legal assistance legal professions text analysis
Accesso online:	Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM

id	cairn-RIDE_381_0091
record_format	cairn
language	Français
format	Article ou chapitre numérique
building	0/Bibliothèque numérique/ 1/Bibliothèque numérique/Cairn/
topic	analyse textuelle assistance juridique Gemini intelligence artificielle modèles de langage (LLM) professions juridiques artificial intelligence Gemini Large Language Models (LLM) legal assistance legal professions text analysis
spellingShingle	analyse textuelle assistance juridique Gemini intelligence artificielle modèles de langage (LLM) professions juridiques artificial intelligence Gemini Large Language Models (LLM) legal assistance legal professions text analysis Nizza, Umberto Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
topic_facet	analyse textuelle assistance juridique Gemini intelligence artificielle modèles de langage (LLM) professions juridiques artificial intelligence Gemini Large Language Models (LLM) legal assistance legal professions text analysis
description	This research paper seeks to comprehensively evaluate the impact that Google’s AI system, Gemini, could have on various legal professions, based on a rigorous analysis of its claimed capabilities and limitations. The paper begins by introducing large language models (LLMs) and highlighting their capacity to answer diverse questions through simple interactions with users. LLMs excel at processing massive amounts of textual data, enabling them to generate human-like text and translate languages. While recent misuse of LLMs in the legal world exists, a scenario where AI assists rather than replaces professionals is equally plausible. Concerns exist regarding their potential for factual errors (“hallucinations”) due to biases in training data. Among LLMs, Gemini is described as having some advantages over other generative models through ongoing learning, allowing real-time adaptation. However, the literature also outlines concerns with potential biases from training data and hallucinations when generating novel responses. To empirically test Gemini’s performance, a series of analytical experiments are conducted. Simulated interactions with Gemini through Poe (a platform for querying AI) are used to verify its advertised capabilities in assisting judges, lawyers, and in-house counsel. Initial findings suggest Gemini’s effectiveness in supporting legal professionals with repetitive and analytical tasks. Based on preliminary observations, Gemini can be a valuable tool for research, summarization, analysis, translation, and even case simulation. In particular, Gemini demonstrates the ability to summarize complex supreme court rulings within seconds, accurately identifying key issues and legal principles applied. Additionally, Gemini’s ability to provide insights beyond human imagination can enhance understanding and improve strategic decision-making in legal contexts. The findings in this paper suggest that Gemini excels at analyzing complex legal texts and extracting valuable information. However, concerns regarding potential hallucinations remain, particularly in the generative aspect where legal solutions are envisioned. While Gemini offers solutions and prompts for reflection, it may not yet be fully adept at complex legal reasoning. Some limitations emerge in generative capabilities when asked to predict court decisions based on given facts. While Gemini can motivate divergent views rationally, outcomes sometimes differ from realities, revealing an inability to deduce like humans. Additional testing on risk assessment documents finds Gemini can provide risk matrices and categorize/summarize issues swiftly. Nevertheless, it also identifies some risks differently than human experts. Furthermore, document management capabilities appear limited through online interactions alone versus integrated software. Overall, the research determines Gemini shows promise in assisting with repetitive legal analysis but faces restrictions replacing humans requiring independent legal judgment or decision-making. For entrepreneurial lawyers and in-house counsel, Gemini can be a valuable assistant in routine tasks, boosting overall productivity. However, the use of AI in judicial roles raises concerns about overfitting, omitted variables, and paradoxes due to limitations in legal data availability. In these cases, the paper suggests that artificial intelligence should serve as an assistant to human judges, not a substitute. While progressing technically, the manuscript argues that humans will continue outperforming AI, requiring nuanced legal understanding beyond factual analysis. Careful, informed use as assistants over substitutes could maximize productivity, especially for business/non-public roles. However, fuller capability realization depends on ongoing model development overcoming hallucination flaws. Concerns also remain around data confidentiality if directly offered to private companies without guarantees. While progress on technical advances may still occur, the paper argues humans will continue surpassing AI, requiring nuanced legal judgments based on human experience and wisdom beyond factual reasoning alone.
author	Nizza, Umberto
author_facet	Nizza, Umberto
author_sort	Nizza, Umberto
title	Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
title_short	Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
title_full	Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
title_fullStr	Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
title_full_unstemmed	Au-delà de la constellation : l’impact de Gemini sur les professions juridiques
title_sort	au-delà de la constellation : l’impact de gemini sur les professions juridiques
publishDate	2024
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url	https://ezproxy.univ-orleans.fr/login?url=https://droit.cairn.info/revue-internationale-de-droit-economique-2024-1-page-91?lang=fr https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.3917/ride.381.0091
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spelling	cairn-RIDE_381_0091RIDERevue internationale de droit économique https://droit.cairn.info/revue-internationale-de-droit-economique-2024-1-page-91?lang=fr https://doi.org/10.3917/ride.381.0091 Au-delà de la constellation : l’impact de Gemini sur les professions juridiques Nizza, Umberto2024 analyse textuelleassistance juridiqueGeminiintelligence artificiellemodèles de langage (LLM)professions juridiquesartificial intelligenceGeminiLarge Language Models (LLM)legal assistancelegal professionstext analysisfre Revue internationale de droit économique \| t. XXXVIII \| 1 \| 2024-09-17 \| p. 91-112 \| 1010-8831 RIDE_38143 This research paper seeks to comprehensively evaluate the impact that Google’s AI system, Gemini, could have on various legal professions, based on a rigorous analysis of its claimed capabilities and limitations. The paper begins by introducing large language models (LLMs) and highlighting their capacity to answer diverse questions through simple interactions with users. LLMs excel at processing massive amounts of textual data, enabling them to generate human-like text and translate languages. While recent misuse of LLMs in the legal world exists, a scenario where AI assists rather than replaces professionals is equally plausible. Concerns exist regarding their potential for factual errors (“hallucinations”) due to biases in training data. Among LLMs, Gemini is described as having some advantages over other generative models through ongoing learning, allowing real-time adaptation. However, the literature also outlines concerns with potential biases from training data and hallucinations when generating novel responses. To empirically test Gemini’s performance, a series of analytical experiments are conducted. Simulated interactions with Gemini through Poe (a platform for querying AI) are used to verify its advertised capabilities in assisting judges, lawyers, and in-house counsel. Initial findings suggest Gemini’s effectiveness in supporting legal professionals with repetitive and analytical tasks. Based on preliminary observations, Gemini can be a valuable tool for research, summarization, analysis, translation, and even case simulation. In particular, Gemini demonstrates the ability to summarize complex supreme court rulings within seconds, accurately identifying key issues and legal principles applied. Additionally, Gemini’s ability to provide insights beyond human imagination can enhance understanding and improve strategic decision-making in legal contexts. The findings in this paper suggest that Gemini excels at analyzing complex legal texts and extracting valuable information. However, concerns regarding potential hallucinations remain, particularly in the generative aspect where legal solutions are envisioned. While Gemini offers solutions and prompts for reflection, it may not yet be fully adept at complex legal reasoning. Some limitations emerge in generative capabilities when asked to predict court decisions based on given facts. While Gemini can motivate divergent views rationally, outcomes sometimes differ from realities, revealing an inability to deduce like humans. Additional testing on risk assessment documents finds Gemini can provide risk matrices and categorize/summarize issues swiftly. Nevertheless, it also identifies some risks differently than human experts. Furthermore, document management capabilities appear limited through online interactions alone versus integrated software. Overall, the research determines Gemini shows promise in assisting with repetitive legal analysis but faces restrictions replacing humans requiring independent legal judgment or decision-making. For entrepreneurial lawyers and in-house counsel, Gemini can be a valuable assistant in routine tasks, boosting overall productivity. However, the use of AI in judicial roles raises concerns about overfitting, omitted variables, and paradoxes due to limitations in legal data availability. In these cases, the paper suggests that artificial intelligence should serve as an assistant to human judges, not a substitute. While progressing technically, the manuscript argues that humans will continue outperforming AI, requiring nuanced legal understanding beyond factual analysis. Careful, informed use as assistants over substitutes could maximize productivity, especially for business/non-public roles. However, fuller capability realization depends on ongoing model development overcoming hallucination flaws. Concerns also remain around data confidentiality if directly offered to private companies without guarantees. While progress on technical advances may still occur, the paper argues humans will continue surpassing AI, requiring nuanced legal judgments based on human experience and wisdom beyond factual reasoning alone.Cet article évalue l’impact potentiel du système d’IA Gemini développé par Google sur les professions juridiques. Après avoir présenté Gemini comme un modèle de langage largement entraîné capable de répondre à diverses questions, l’auteur interroge directement Gemini sur ses forces présumées pour les juges, les avocats et les juristes d’entreprise. Des tests sont ensuite réalisés pour vérifier les affirmations de Gemini. Bien qu’il démontre d’impressionnantes compétences analytiques en résumant des textes juridiques complexes en quelques secondes, ses capacités génératives semblent plus limitées. De plus, Gemini identifie certains risques différemment des experts humains. Le document conclut que Gemini montre un grand potentiel d’assistance pour les tâches juridiques répétitives grâce à une analyse textuelle rapide et précise, mais il ne peut pas remplacer entièrement les professionnels lorsque des jugements fins sur la loi sont requis.Cairn restricted access

Au-delà de la constellation : l’impact de Gemini sur les professions juridiques

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