计算机科学

计算机科学 ›› 2023, Vol. 50 ›› Issue (7): 347-354.doi: 10.11896/jsjkx.220900120

• 交叉&前沿 • 上一篇    下一篇

论算法解释权的重构——全算法开发流治理与分级分类解释框架

丛颖男1, 王兆毓2, 朱金清3   

  1. 1 中国政法大学商学院 北京 100088
    2 清华大学法学院 北京 100084
    3 北京字节跳动网络技术有限公司 北京 100043
  • 出版日期:2023-07-15 发布日期:2023-07-05
  • 通讯作者: 朱金清(zhujinqing@bytedance.com)
  • 作者简介:(cyn_2010@163.com)
  • 基金资助:
    北京市教改项目“法商大数据分析创新型人才培养模式研究”(京教函[2020]427号);中国政法大学新兴学科培育建设计划

Reconstructing the Right to Algorithm Explanation －－Full Algorithm Development Flow Governance and Hierarchical Classification Interpretation Framework

CONG Yingnan1, WANG Zhaoyu2, ZHU Jinqing3   

  1. 1 Business School,China University of Political Science and Law,Beijing 100088,China
    2 School of Law,Tsinghua University,Beijing 100084,China
    3 Beijing Bytedance Network Technology Co.,Ltd,Beijing 100043,China
  • Online:2023-07-15 Published:2023-07-05
  • About author:CONG Yingnan,born in 1985,Ph.D,associate professor,master supervisor,is a member of China Computer Federation.His main research interests include big data on business and law,artificial intelligence,blockchain,Fin-tech,Reg-tech and complex system.ZHU Jinqing,born in 1984,postgra-duate,engineer,is a member of China Computer Federation.His main research interests include database systems,content data analysis,artificial intelligence and knowledge graphs.
  • Supported by:
    Beijing Education Reform Project “Research on the Training Mode of Innovative Talents for French Business Big Data Analysis”(Jingjiaohan [2020] No.427) and Cultivation and Construction Plan of Emerging Disciplines of China University of Political Science and Law.

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摘要： 随着人工智能技术的快速发展,自动化决策算法逐渐进入公共领域并越来越多地影响到社会公益与个人权益。而相应的算法风险如算法歧视、算法偏见、算法垄断等不断出现,进而引发了算法治理的切实需求。面对自动化决策使用者与用户之间信息、技术的不对称地位,传统法律资源不敷适用,对自动化决策用户保护之权利的不足成为算法解释权的必要性基础。作为算法治理的重要手段,算法解释权的价值在于对算法的“黑盒”构建“适度透明性”,矫正开发者与用户之间的信息不对称,并且再平衡双方畸形的分配风险负担,成为规制自动化决策使用者、保障用户权益必不可少的制度配置,因此算法解释权研究成为国内外学界与司法实践共同关注的焦点。而在现行法视野下,算法解释权制度存在适格主体过于狭窄,保护范围不够全面,权利内容尚需明确等问题。对此,在解构算法解释权的基础上,从全算法开发流治理与分级分类解释框架的视角对算法解释权制度进行重构。通过全算法开发流治理的建构,对算法解释权的主客体进行适度扩张;通过分级分类解释框架的构筑,结合个案视角明确算法解释权的内容与边界,以此兼顾算法的个性与共性,平衡算法解释的效率与用户权益的保护,全面保障自动化决策中的各方权利主体利益,为数字经济发展赋能。

关键词: 算法解释权, 算法治理, 自动化决策, 个人信息保护

Abstract: With the rapid development of artificial intelligence,automated decision-making algorithms(ADM) have gradually entered the public domain and increasingly affected social welfare and individual interests.Meanwhile,emerging risks of ADM,such as algorithmic discrimination,algorithmic bias,and algorithm monopoly have raised the demand of governance to algorithm.Faced with information and technology asymmetry among parties involved,traditional legal resources fall short in protecting the rights of users in ADM,which justifies the right to explanation.In addition,the right to algorithm explanation,serving as an important means of algorithm governance,is conductive to making the black box of algorithm moderately transparent,correcting information asymmetry,and balancing the risk burden between the deployer and the user.It has thus become a necessity in regulating ADM deployers and safeguarding the interests of its users.Therefore,the right to explanation has become the focus in both academic and practical realms from home and abroad.However,the right to algorithm explanation in China is faced with the problem of limited eligible parties,insufficient protection scope,and inexplicit content of rights.In this regard,this paper advocates decons-tructing the right to explanation and further reconstructing it from the perspective of machine learning workflow with a hierarchical classification framework.Introducing the concept of machine learning workflow can reasonably extend the scope of the subject and object of the right,while establishing the framework of hierarchical classification can clarify the content and boundary of the right,which considers both individuality and generality of algorithms and balances the efficiency of explanation and the protection of users’ rights.In this way,all parties in ADM can be fully protected,and the development of digital economy can be empo-wered.

Key words: Right to explanation, Algorithm governance, Automated decision making, Protection of personal data

中图分类号: 

  • TP182
[1]YANOFSKY N S.Towards a Definition of an Algorithm [J].Journal of Logic and Computation,2011,21(2):253-286.
[2]STEINER C,DIXON W.Automate this:How Algorithms Came to Rule Our World[M].Portfolio/Penguin,2012.
[3]DIETERICH W,MENDOZA C,BRENNAN T.COMPAS Risk Scales:Demonstrating Accuracy Equity and Predictive Parity [R].Northpointe Inc,2016.
[4]ZELEZNIKOW J.An Australian Perspective on Research and Development Required for the Construction of Applied Legal Decision Support Systems [J].Artificial Intelligence and Law,2002,10(4):237-260.
[5]MCPEAK A.Disruptive Technology and the Ethical Lawyer[J].The University of Toledo Law Review,2018,50:457.
[6]PASQUALE F.The Black Box Society:The Secret Algorithm that Control Money and Information[M].Harvard University Press,2015.
[7]ZHENG Z H.The Ethical Crisis and Legal Regulation of theArtificial Intelligence Algorithm[J].Science of Law(Journal of Northwest University of Political Science and Law),2021,39(1):14-26.
[8]LI J.The Construction of the Right of Algorithmic Interpretation in Public Services[J].Seeking Truth,2021,48(3):110-120.
[9]LV B B.On the Algorithm Explanation Obligation of Personal Information Processors[J].Modern Law Science,2021,43(4):89-101.
[10]ZHANG L H.Regulation of Algorithms in the Age of Artificial Intelligence[M].Shanghai:Shanghai People’s Publishing House,2021.
[11]BRENNAN T,DIETERICH W,EHRET B.Evaluating the Predictive Validity of the COMPAS Risk and Needs Assessment System [J].Criminal Justice and Behavior,2009,36(1):21-40.
[12]BLOCH-WEHBA H.Access to Algorithms[J].Fordham Law Review,2019,88:1265.
[13]CITRON D K,PASQUALE F.The Scored Society:Due Process for Automated Predictions [J].Washington Law Review,2014,89:1.
[14]HARARI Y N.21 Lessons for the 21st Century[M].Random House,2018.
[15]ZHOU W.Algorithmic Conspiracy of Antitrust Regulations[J].Law Science,2020(1):40-59.
[16]JIA K.Artificial Intelligence and Algorithm Governance Re-search[J].Chinese Public Administration,2019(1):17-22.
[17]ZHENG Z H,XU Z X.Legal Regulation and Judicial Review of Algorithmic Discrimination in the Age of Big Data:Take Legal Practice in the U.S.as an Example[J].Journal of Comparative Law,2019(4):111-122.
[18]XIE Z S.Regulating Algorithmic Decision:Focusing on theRight to Explanation of Algorithm[J].Modern Law Science,2020,42(1):179-193.
[19]ZHANG L H.Research on Algorithmic Interpretation Power of Business Automation Decision-making[J].Science of Law(Journal of Northwest University of Political Science and Law),2018,36(3):65-74.
[20]JIA Z F.The Right of Algorithm Interpretation is not a Legal Right－Comment on Article 25 of Personal Information Protection Law(Draft)[J].Electronics Intellectual Property,2020(12):49-61.
[21]SHAO G S,HUANG Q.Algorithmic Harms and the Right to Explanation[J].Chinese Journal of Journalism & Communication,2019,41(12):27-43.
[22]WACHTER S,MITTELSTADT B,FLORIDI L.Why a Right to Explanation of Automated Decision-making Does not Exist in the General Data Protection Regulation [J].International Data Privacy Law,2017,7(2):76-99.
[23]XU K.Taming Algorithms:Historical Evolution and Contemporary System of Algorithm Governance[J].ECUPL Journal,2022,25(1):99-113.
[24]ZHANG L H.The Iteration and Innovation of Algorithm Regulation[J].Legal Forum,2019,34(2):16-26.
[25]ZHANG E D.Background,Logic and Structure of the Right to Explanation of Algorithmic Decision-making in the Age of Big Data[J].Legal Forum,2019,34(4):152-160.
[26]AMERSHI S,BEGEL A,BIRD C,et al.Software Engineering for Machine Learning:A Case Study[C]//2019 IEEE/ACM 41st International Conference on Software Engineering:Software Engineering in Practice(ICSE-SEIP).IEEE,2019:291-300.
[27]Microsoft.The Team Data Science Process[EB/OL].(2022-03-03) [2022-04-26].https://docs.microsoft.com/en-us/azure/architecture/data-science-process/overview.
[28]FAYYAD U,PIATETSKY-SHAPIRO G,SMYTH P.TheKDD Process for Extracting Useful Knowledge from Volumes of Data [J].Communications of the ACM,1996,39(11):27-34.
[29]WIRTH R,HIPP J.CRISP-DM:Towards a Standard ProcessModel for Data Mining[C]//Proceedings of the 4th Interna-tional Conference on the Practical Applications of Knowledge Discovery and Data Mining.2000:29-40.
[30]PAN S J,YANG Q.A Survey on Transfer Learning [J].IEEE Transactions on Knowledge and Data Engineering,2009,22(10):1345-1359.
[31]HOGAN B.The Presentation of Self in the Age of Social Media:Distinguishing Performances and Exhibitions Online [J].Bulletin of Science,Technology & Society,2010,30(6):377-386.
[32]CONG Y N,WANG Z Y,ZHU J Q.Insights into Dataset and Algorithm Related Problems in Artificial Intelligence for Law[J].Computer Science,2022,49(4):74-79.
[33]ISARAN E T.When an Algorithm Helps Send You to Prison[EB/OL].(2017-10-26) [2022-04-26].https://www.nytimes.com/2017/10/26/opinion/algorithm-compas-sentencing-bias.html.
[34]ZUO W M.Will the Era of AI Judges Come－Based on the Comparison and Outlook of Judicial Artificial Intelligence Between China and Foreign Countries[J].Tribune of Political Science and Law,2021,39(5):3-13.
[35]SHEN W X.On the Construction and Systematization of thePersonal Information Right[J].Journal of Comparative Law,2021(5):1-13.
[36]WEN Y.The Nature and Prospect of Algorithmic Rights－The Theoretical Separation and Functional Compatibility Based on Algorithmic Rights and Personal Information Rights[J].Journal of Huazhong University of Science and Technology(Social Science Edition),2022,36(1):54-63.
[37]RAVEN B H.Social influence and power[R].California University Los Angeles,1964.
[38]ZHANG L H.Function and Realization of the Algorithm Interpretation Rights in Business Automated Decisions[J].Journal of Soochow University(Philosophy & Social Science Edition),2020,41(2):51-60.
[39]GUNNING D,STEFIK M,CHOI J,et al.XAI—ExplainableArtificial Intelligence [J].Science Robotics,2019,4(37):eaay7120.
[40]VLADECK D C.Machines without Principals:Liability Rulesand Artificial Intelligence [J].Washington Law Review,2014,89(1):117.
[41]SU Y.An Interpretation and Specification of the Obligations of Optimizing the Explainability and Transparency of Algorithm[J].Science of Law(Journal of Northwest University of Political Science and Law),2022,40(1):133-141.
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