Blind Judgement: Agent-Based Supreme Court Modelling With GPT

Hamilton, Sil

doi:10.48550/arxiv.2301.05327

Cited by 7 publications

(7 citation statements)

References 11 publications

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“…Recently, through extensive training on vast amounts of web data, LLMs have demonstrated an impressive capability to generate humanlike behavior. The applications of generative agents powered by LLMs range from replacing human subjects in psychological experiments (Dillion et al, 2023;Hutson, 2023), simulating voting patterns (Argyle et al, 2023), providing support for mental wellbeing (Ma et al, 2023), exploring economic behavior (Horton, 2023), predicting US Supreme Court decisions (Hamilton, 2023), assisting with research design and experiments (Boiko et al, 2023), and encoding clinical knowledge (Singhal et al, 2023). Wang et al (2023) provides a comprehensive review of recent efforts.…”

Section: Realizing the Potential Of Llms In Social Sciencesmentioning

confidence: 99%

Generative agent‐based modeling: an introduction and tutorial

Ghaffarzadegan,

Majumdar,

Williams

et al. 2024

System Dynamics Review

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We discuss the emerging new opportunity for building feedback‐rich computational models of social systems using generative artificial intelligence. Referred to as generative agent‐based models (GABMs), such individual‐level models utilize large language models to represent human decision‐making in social settings. We provide a GABM case in which human behavior can be incorporated into simulation models by coupling a mechanistic model of human interactions with a pre‐trained large language model. This is achieved by introducing a simple GABM of social norm diffusion in an organization. For educational purposes, the model is intentionally kept simple. We examine a wide range of scenarios and the sensitivity of the results to several changes in the prompt. We hope the article and the model serve as a guide for building useful dynamic models of various social systems that include realistic human reasoning and decision‐making. © 2024 System Dynamics Society.

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Section: Realizing the Potential Of Llms In Social Sciencesmentioning

confidence: 99%

Generative agent‐based modeling: an introduction and tutorial

Ghaffarzadegan,

Majumdar,

Williams

et al. 2024

System Dynamics Review

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“…Jurisprudence: LLM-based agent can serve as aids in legal decision-making processes, facilitating judges in rendering more informed judgements [23,56]. Blind Judgement [56] employs several language models to simulate the decision-making processes of multiple judges. It gathers diverse opinions and consolidates the outcomes through a voting mechanism.…”

Section: Social Sciencementioning

confidence: 99%

Genomic Surveillance for SARS-CoV-2 — China, September 26, 2022 to January 29, 2023

Wang¹,

Niu²,

Su³

et al. 2023

China CDC Weekly

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Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated 2,431 variants over the course of its global transmission over the past 3 years. To better evaluate the genomic variation of SARS-CoV-2 before and after the optimization of coronavirus disease 2019 (COVID-19) prevention and control strategies, we analyzed the genetic evolution branch composition and genomic variation of SARS-CoV-2 in both domestic and imported cases in China (the data from Hong Kong and Macau Special Administrativc Regions and Taiwan, China were not included) from September 26, 2022 to January 29, 2023.Methods: Analysis of the number of genome sequences, sampling time, dynamic changes of evolutionary branches, origin, and clinical typing of SARS-CoV-2 variants submitted by 31 provincial-level administrative divisions (PLADs) and Xinjiang Production and Construction Corp (XPCC) was conducted to assess the accuracy and timeliness of SARS-CoV-2 variant surveillance.Results: From September 26, 2022 to January 29, 2023, 20,013 valid genome sequences of domestic cases were reported in China, with 72 evolutionary branches. Additionally, 1,978 valid genome sequences of imported cases were reported, with 169 evolutionary branches. The prevalence of the Omicron variants of SARS-CoV-2 in both domestic and imported cases was consistent with that of international epidemic variants.Conclusions: This study provides an overview of the prevalence of Omicron variants of SARS-CoV-2 in China. After optimizing COVID-19 prevention and control strategies, no novel Omicron variants of SARS-CoV-2 with altered biological characteristics or public health significance have been identified since

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“…In the voting-based cooperation, each agent can freely provide their opinions. The consensus for final decisions can be reached through a voting process [48]. The cooperation can be also reached by assigning different roles to agents through role-based cooperation [20,20,49,49,50], e.g., the UI designer is responsible for designing an interface of an application while the role of engineer is about writing the code of the software.…”

Section: Execution Enginementioning

confidence: 99%

Responsible-AI-by-Design: A Pattern Collection for Designing Responsible Artificial Intelligence Systems

Zhu

et al. 2023

IEEE Softw.

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The release of ChatGPT, Bard, and other large language model (LLM)-based chatbots has drawn huge attention on foundations models worldwide. There is a growing trend that foundation models will serve as the fundamental building blocks for most of the future AI systems. However, incorporating foundation models in AI systems raises significant concerns about responsible AI due to their black box nature and rapidly advancing super-intelligence. Additionally, the foundation model's growing capabilities can eventually absorb the other components of AI systems, introducing the moving boundary and interface evolution challenges in architecture design. To address these challenges, this paper proposes a pattern-oriented responsible-AI-by-design reference architecture for designing foundation model-based AI systems. Specially, the paper first presents an architecture evolution of AI systems in the era of foundation models, from "foundation-model-as-a-connector" to "foundationmodel-as-a-monolithic architecture". The paper then identifies the key design decision points and proposes a pattern-oriented reference architecture to provide reusable responsible-AI-by-design architectural solutions to address the new architecture evolution and responsible AI challenges. The patterns can be embedded as product features of foundation model-based AI systems and can enable organisations to capitalise on the potential of foundation models while minimising associated risks.

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Blind Judgement: Agent-Based Supreme Court Modelling With GPT

Cited by 7 publications

References 11 publications

Generative agent‐based modeling: an introduction and tutorial

Generative agent‐based modeling: an introduction and tutorial

Genomic Surveillance for SARS-CoV-2 — China, September 26, 2022 to January 29, 2023

Responsible-AI-by-Design: A Pattern Collection for Designing Responsible Artificial Intelligence Systems

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