在区块链支持的社会信用体系上构建可信和安全的社区
Constructing Trustworthy and Safe Communities on a Blockchain-Enabled Social Credits System
摘要：
大数据和人工智能（AI）技术的出现正在重塑世界。技术革命在提高我们生活质量的同时，也引发了新的担忧。超人的能力使人工智能在许多数据和/或计算密集型任务中优于人类工作者。此外，数字超级大国对个人表现出傲慢，这侵蚀了社会的信任基础。在这份立场文件中，我们建议基于区块链启用的社会信用系统（BLESS）构建值得信赖和安全的社区，该系统奖励参与社会有益活动的居民。人的真正价值在于为他人服务。BLESS系统被认为是一种有效的方法，以促进价值和尊严，致力于加强我们的社区和规范商业和私人行为。BLESS系统利用区块链网络的去中心化架构，不仅允许草根个人参与社会信用系统（SCS）的评级过程，还可以在无信任的网络环境中提供交易数据的防篡改。区块链记录中的匿名性也可以保护个人在与强大企业的斗争中成为目标。启用智能合约的身份验证和授权策略可防止任何未经授权的实体访问信用系统。BLESS方案有望提供安全、透明和分散的SCS。
英文摘要：
The emergence of big data and Artificial Intelligence (AI) technology is reshaping the world. While the technological revolution improves the quality of our life, new concerns are triggered. The superhuman capability enables AI to outperform human workers in many data- and/or computing-intensive tasks. Also, digital superpowers are showing arrogance towards individuals, which erodes the trust foundation of the society. In this position paper, we suggest to construct trustworthy and safe communities based on a BLockchain-Enabled Social credits System (BLESS) that rewards the residents who commit in socially beneficial activities. Human being's true value lies in serving other people. The BLESS system is considered as an efficient approach to promote the value and dignity in efforts focused on enhancing our communities and regulating business and private behaviors. The BLESS system leverages the decentralized architecture of the blockchain network, which not only allows grassroots individuals to participate rating process of a social credit system (SCS), but also provides tamper proof of transaction data in the trustless network environment. The anonymity in blockchain records also protects individuals from being targeted in the fight against powerful enterprises. Smart contract enabled authentication and authorization strategy prevents any unauthorized entity from accessing the credit system. The BLESS scheme is promising to offer a secure, transparent and decentralized SCS.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
