CoCoMo:生成和伦理人工智能的计算意识建模

Edward Y. Chang
{"title":"CoCoMo:生成和伦理人工智能的计算意识建模","authors":"Edward Y. Chang","doi":"arxiv-2304.02438","DOIUrl":null,"url":null,"abstract":"The CoCoMo model proposes a computational solution to the challenge of\nincorporating ethical and emotional intelligence considerations into AI\nsystems, with the aim of creating AI agents that combine knowledge with\ncompassion. To achieve this goal, CoCoMo prioritizes fairness, beneficence,\nnon-maleficence, empathy, adaptability, transparency, and critical and\nexploratory thinking abilities. The model employs consciousness modeling,\nreinforcement learning, and prompt template formulation to support these\ndesired traits. By incorporating ethical and emotional intelligence\nconsiderations, a generative AI model can potentially lead to improved\nfairness, reduced toxicity, and increased reliability.","PeriodicalId":501310,"journal":{"name":"arXiv - CS - Other Computer Science","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CoCoMo: Computational Consciousness Modeling for Generative and Ethical AI\",\"authors\":\"Edward Y. Chang\",\"doi\":\"arxiv-2304.02438\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The CoCoMo model proposes a computational solution to the challenge of\\nincorporating ethical and emotional intelligence considerations into AI\\nsystems, with the aim of creating AI agents that combine knowledge with\\ncompassion. To achieve this goal, CoCoMo prioritizes fairness, beneficence,\\nnon-maleficence, empathy, adaptability, transparency, and critical and\\nexploratory thinking abilities. The model employs consciousness modeling,\\nreinforcement learning, and prompt template formulation to support these\\ndesired traits. By incorporating ethical and emotional intelligence\\nconsiderations, a generative AI model can potentially lead to improved\\nfairness, reduced toxicity, and increased reliability.\",\"PeriodicalId\":501310,\"journal\":{\"name\":\"arXiv - CS - Other Computer Science\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Other Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2304.02438\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Other Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2304.02438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

CoCoMo模型提出了一种计算解决方案,以应对将道德和情商因素纳入系统的挑战,其目的是创造将知识与同情心结合起来的人工智能代理。为了实现这一目标,CoCoMo优先考虑公平、慈善、无害、同理心、适应性、透明度以及批判性和探索性思维能力。该模型采用意识建模、强化学习和提示模板制定来支持这些期望的特征。通过结合伦理和情商方面的考虑,生成式人工智能模型可能会提高公平性,减少毒性,提高可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CoCoMo: Computational Consciousness Modeling for Generative and Ethical AI
The CoCoMo model proposes a computational solution to the challenge of incorporating ethical and emotional intelligence considerations into AI systems, with the aim of creating AI agents that combine knowledge with compassion. To achieve this goal, CoCoMo prioritizes fairness, beneficence, non-maleficence, empathy, adaptability, transparency, and critical and exploratory thinking abilities. The model employs consciousness modeling, reinforcement learning, and prompt template formulation to support these desired traits. By incorporating ethical and emotional intelligence considerations, a generative AI model can potentially lead to improved fairness, reduced toxicity, and increased reliability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Artificial Intelligence-based Smart Port Logistics Metaverse for Enhancing Productivity, Environment, and Safety in Port Logistics: A Case Study of Busan Port Evaluating the Usability of Qualified Electronic Signatures: Systematized Use Cases and Design Paradigms A Brief Discussion on the Philosophical Principles and Development Directions of Data Circulation Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach A Match Made in Semantics: Physics-infused Digital Twins for Smart Building Automation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1