人工智能與不正當(dāng)競爭
——揭開人工智能監(jiān)管領(lǐng)域一個(gè)被低估的基石

斯蒂芬·舒勒（Stefan Scheuerer） 著 / 完全法律人碩士，慕尼黑馬克斯·普朗克創(chuàng)新與競爭研究所初級研究員

黃軍 鞠金琪 譯 / 青島大學(xué)法學(xué)院

一、 引言

長期以來，“人工智能”（簡稱“AI”）一直是知識產(chǎn)權(quán)和競爭法學(xué)者的關(guān)注焦點(diǎn)。然而，與知識產(chǎn)權(quán)和反壟斷不同，1. Although hinting at the Anglo-American legal sphere, the term ‘a(chǎn)ntitrust’ is preferred in this analysis over ‘competition law’ in order to avoid terminological confusion vis-a` -vis ‘unfair competition law’, since (from a European perspective) both regimes can be considered subsets of ‘competition law’, understood as an umbrella term.反不正當(dāng)競爭法（簡稱“UCL”）在人工智能監(jiān)管領(lǐng)域能夠并且應(yīng)當(dāng)發(fā)揮的作用迄今為止在很大程度上被忽視了。2. But see for example WIPO Conversation on Intellectual Property (IP) and Artificial Intelligence (AI), Second Session,‘Revised Issues Paper on Intellectual Property Policy and Artificial Intelligence’ (21 May 2020) para 8: ‘No separate section concerning AI and unfair competition has been added. However, recognizing that IP law and competition law clearly relate,questions have been added in the various sections (...)’.當(dāng)然，反不正當(dāng)競爭法是一個(gè)復(fù)雜的問題——對其本身作為一個(gè)法律領(lǐng)域的理解存有爭議，而在歐盟成員國之間，更不用說在世界范圍內(nèi)，其在法律秩序中的體系定位和設(shè)計(jì)存在較大差異——這一事實(shí)是解釋這一缺陷的一個(gè)因素。更重要的是，這部法律體系的潛力似乎值得引起法律界人士的注意，他們對這部法律的關(guān)注還不夠深入。為了填補(bǔ)前述分析空白，3. Implications of AI for the legal order can be approached either from a ‘legalistic’ viewpoint, ie starting from the doctrinal framework of a specific legal regime, or from a ‘technological’/‘phenomenological’ viewpoint, ie starting from factual problems that arise in an economic, technological or societal context, cf Nicolas Petit, ‘Law and Regulation of Artificial Intelligence and robots: Conceptual Framework and Normative Implications’ (2017) 2 ＜https:/ papers.ssrn.com/sol3/papers.cfm?abstract_id?2931339＞ accessed before 27 November 2020; both approaches are important and complement each other. This articles contributes to the ‘legalistic’ dimension; for a ‘technological’ perspective, see (from an IP angle) Josef Drexl and others,‘Technical Aspects of Artificial Intelligence: An Understanding from an Intellectual Property Law Perspective’ (2019) Max Planck Institute for Innovation & Competition Research Paper No 19-13 ＜https://papers.ssrn.com/sol3/papers.cfm?ab stract_id?3465577＞ accessed before 27 November 2020.本文研究了被廣泛稱為人工智能監(jiān)管的關(guān)鍵支柱和指導(dǎo)范式的一般原則在多大程度上反映在反不正當(dāng)競爭法的特定子對應(yīng)物中，從而闡明了反不正當(dāng)競爭法為其成就作出貢獻(xiàn)的潛力。從分析角度來看，本評估過程中的一個(gè)特別重點(diǎn)在于從反不正當(dāng)競爭法角度考慮人工智能提出的突出問題，這些問題通常在不同法律制度下被討論——以表明這種觀點(diǎn)可能會(huì)補(bǔ)充甚至取代傳統(tǒng)方法。在實(shí)質(zhì)內(nèi)容方面，將著重關(guān)注對反不正當(dāng)競爭法之于人工智能創(chuàng)新生態(tài)系統(tǒng)的作用。最后，從相反的角度，本文將考慮人工智能有可能進(jìn)一步助推反不正當(dāng)競爭法理論體系發(fā)展的潛力，以及它對全球競爭秩序的意義。

二、場景設(shè)置：什么是人工智能，什么是反不正當(dāng)競爭法，后者能對前者監(jiān)管起到什么作用

人工智能與反不正當(dāng)競爭法的共同之處在于，很難說它們到底是什么。人工智能是一個(gè)“包羅萬象”的術(shù)語，指涉的是圍繞大數(shù)據(jù)分析和先進(jìn)算法的某些新技術(shù)，包括“自主”和“自我學(xué)習(xí)”的情形。為了在為本分析的目的揭開技術(shù)術(shù)語的神秘面紗時(shí)，機(jī)器學(xué)習(xí)（作為最重要和最突出的人工智能技術(shù)）將被視為主要參考點(diǎn)。4. For an overview on the technical functioning of ML and its relationship to adjacent AI technologies, see Drexl and others (n 3).反不正當(dāng)競爭法是一個(gè)不那么時(shí)髦但同樣有歧義的現(xiàn)象：它在國際層面首先體現(xiàn)在1803年 《保護(hù)工業(yè)產(chǎn)權(quán)巴黎公約》第十條之二，其歷來被視為在競爭中保護(hù)“倫理”或者“商業(yè)倫理”，依靠“尊貴商人”的理想模式?，F(xiàn)代學(xué)界通過運(yùn)用功能經(jīng)濟(jì)學(xué)的維度來構(gòu)建反不正當(dāng)競爭法，其假定與反壟斷法的最終互補(bǔ)性，并將保護(hù)競爭作為一項(xiàng)制度的中心目標(biāo)。5. cf Reto M Hilty, ‘The Law Against Unfair Competition and its Interfaces’ in Reto M Hilty and Frauke Henning-Bodewig(eds), Law Against Unfair Competition - Towards a New Paradigm in Europe? (Springer 2007) 1; Rupprecht Podszun, ‘Der‘more economic approach’ im Lauterkeitsrecht’ [2009] WRP 509.盡管如此，反不正當(dāng)競爭法規(guī)則的準(zhǔn)確設(shè)計(jì)和理解在歐盟成員國和全世界范圍內(nèi)都有相當(dāng)大的差異：從競爭法的編纂到消費(fèi)者法、公法；從實(shí)質(zhì)上講，在保護(hù)競爭、消費(fèi)者和作為一個(gè)競爭制度之間搖擺不定。6. For an overview, see Frauke Henning-Bodewig, International Handbook Of Unfair Competition (CH Beck/Hart/Nomos 2013);illustrative of the scattered nature, Richard Arnold, ‘English Unfair Competition Law’ (2013) 44 IIC 63, 77: ‘It is still the case that English law does not recognise any general tort of unfair competition. It does not follow, however, that there is no English law of unfair competition’; on the difficulties of determining UCL, see also Frauke Henning-Bodewig and Achim Spengler,‘Conference Report: “Framing - The ‘Hard Core’ of Unfair Competition Law”’ [2016] GRUR Int 911.盡管歐盟通過《不正當(dāng)商業(yè)行為（UCP）指令》對反不正當(dāng)競爭法中的企業(yè)對消費(fèi)者（B2C）層面進(jìn)行了協(xié)調(diào)，7. Directive 2005/29/EC of the European Parliament and of the Council concerning unfair business-to-consumer commercial practices in the internal market.但企業(yè)對企業(yè)（B2B）層面迄今為止尚未被統(tǒng)一。8. As far as the B2C dimension is concerned, this article will focus on European law; as far as the B2B dimension is concerned,on German law as an illustrative and doctrinally advanced example or blueprint.

然而，這種模糊性并不一定是反不正當(dāng)競爭法潛在運(yùn)用于人工智能監(jiān)管領(lǐng)域的不利條件。誠然，鑒于上述分歧，它在協(xié)調(diào)監(jiān)管方面幾乎不會(huì)立即產(chǎn)生效果。然而，首先“監(jiān)管競爭”的理念可能會(huì)帶來收益。尤其是歐盟層面的B2B領(lǐng)域反不正當(dāng)競爭法不協(xié)調(diào)的事實(shí)，從這個(gè)角度來看，其應(yīng)被視為機(jī)遇。人工監(jiān)管領(lǐng)域與其尋求監(jiān)管的技術(shù)同樣是動(dòng)態(tài)的。至于如何對待反不正當(dāng)競爭法視域下的人工智能，各國相互競爭的措施本身可能被視為“監(jiān)管沙箱”：9. On regulatory sandboxes for data sharing, cf Rupprecht Podszun, ‘Datenpools: Ausprobieren statt differenzieren‘[2019] WUW 289.找到的最佳解決方案可以出口到其他司法管轄區(qū)——無論是在立法層面，還是在通過比較法律方法對一般條款進(jìn)行司法解釋的層面。第二，在相關(guān)方面，反不正當(dāng)競爭法固有的特殊靈活性十分契合人工智能領(lǐng)域的動(dòng)態(tài)屬性，它將對全部法律秩序的理解最終進(jìn)行統(tǒng)一。反不正當(dāng)競爭法可以作為一種“后備”機(jī)制發(fā)揮可行的作用，在缺乏具體立法情況下以應(yīng)對新的和不可預(yù)見的競爭風(fēng)險(xiǎn)。這種后備屬性屬于反不正當(dāng)競爭法的傳統(tǒng)特征，它為從理論發(fā)展到后來明確的法典化創(chuàng)造了肥沃的土壤。10. cf Herbert Zech, Information als Schutzgegenstand (Mohr Siebeck 2012) 161 f.它在數(shù)字經(jīng)濟(jì)中獲得了更大的意義。

當(dāng)前人工智能監(jiān)管原則在反不正當(dāng)競爭法范式中的體現(xiàn)程度如何？關(guān)于人工智能監(jiān)管框架的爭論是動(dòng)態(tài)的、持續(xù)的，現(xiàn)在談?wù)撌且粋€(gè)成熟的知識顯然還為時(shí)過早。盡管如此，在學(xué)術(shù)探討和公共及私人機(jī)構(gòu)的眾多政策指南中，可以找到總體上且反復(fù)出現(xiàn)的相關(guān)范式的某種共識。在反復(fù)被援引的原則中，包括全面實(shí)現(xiàn)“道德”、公平、透明、問責(zé)、自主和促進(jìn)創(chuàng)新。11. cf only High-Level Expert Group on Artificial Intelligence, ‘Ethics guidelines for trustworthy AI’ (2019) ＜https://ec.europa.eu/digital-singlemarket/en/news/ethics-guidelines-trustworthy-ai＞ ccessed before 27 November 2020; OECD, ‘Council Recommendation on Artificial Intelligence’ (2019) ＜https://legalinstruments.oecd.org/en/instruments/ OECD-LEGAL-0449＞accessed before 27 November 2020; this list of values is by no means exhaustive, yet these appear to be the most prominent ones.以下考慮事項(xiàng)將闡明，反不正當(dāng)競爭法如何具體有助于實(shí)現(xiàn)這些目標(biāo)。

三、“人工智能倫理”和“商業(yè)倫理”：監(jiān)管嵌合體的(非)融合

首先，人們通?？梢运伎迹藗兯鶑V泛宣揚(yáng)的“人工智能倫理”12. cf High-Level Expert Group (n 11); IEEE, ‘Ethically Aligned Design - A Vision for Prioritzing Human Well-being with Autonomous and Intelligent Systems’ (2019) ＜https://standards.ieee.org/content/dam/ieeestandards/standards/web/documents/other/ead1e.pdf?utm_medium? undefined&utm_source?undefined&utm_campaign?undefined&utm_content?undefined&utm_term?undefined＞ accessed before 27 November 2020.的愿景與“商業(yè)倫理”的概念之間是否存在聯(lián)系，這種聯(lián)系通?；蛑辽僭跉v史上與反不正當(dāng)競爭法有關(guān)。這顯然觸及了關(guān)于反不正當(dāng)競爭法到底是什么的爭論內(nèi)核。正如前文所述，在其歷史根源上曾經(jīng)是一個(gè)涉及競爭“倫理”的法律領(lǐng)域。13. It is worth noting, however, that now as before, irrespective of the ‘moral’ rhetoric and underpinnings, the practical application of the law has often followed a functional balancing of interests.盡管這種理解在很大程度上被現(xiàn)代經(jīng)濟(jì)功能方法所取代，但舊的理解碎片仍然滲透在法律、判決和學(xué)術(shù)探討之中，各成員國的側(cè)重點(diǎn)也各不相同。如果有人認(rèn)為“商業(yè)倫理”在法律秩序中仍有一席之地，而該領(lǐng)域就是反不正當(dāng)競爭法，那么將相關(guān)原則與“人工智能倫理”的要求結(jié)合起來似乎并不牽強(qiáng)。然而，本文的立場并非宣揚(yáng)這一主張，而是要指出迫切需要對“倫理”敘事進(jìn)行去神秘化。首先也是最重要的是，如果缺少“法律”的鏡像，就很難有“倫理”價(jià)值觀，尤其是與各自價(jià)值觀有關(guān)的基本權(quán)利或人權(quán)，14. cf High-Level Expert Group (n 11) 37, however, considering fundamental rights a mere sub-realisation of ethics.這使得“倫理”的整個(gè)概念更令人困惑，而不是有助于實(shí)現(xiàn)法學(xué)研究目的。其次，通常被視為“不道德”的行為往往與反競爭行為具有一致性。在任何情況下，顯然只有“人工智能倫理”中與市場和競爭相關(guān)或影響市場和競爭的部分才與反不正當(dāng)競爭法相關(guān)。最后，當(dāng)涉及具體法律運(yùn)作時(shí)，所有這些問題，無論其形而上學(xué)的起源如何，均可歸結(jié)為所有市場參與者合法利益的平衡。這種平衡是反不正當(dāng)競爭法理論的核心。因此，以下考慮將包含法律而非“倫理”反思。

四、公平

人工智能和反不正當(dāng)競爭法最明顯、同時(shí)也是最復(fù)雜的潛在“共同點(diǎn)”是“公平”原則本身。從表面上看，反不正當(dāng)競爭法中的“公平”和人工智能語境中的“公平”可能被認(rèn)為除了術(shù)語之外并無共同之處：人工智能爭論中的“公平”大多被理解為平等原則和禁止“有偏見”的歧視，反不正當(dāng)競爭法中“公平”旨在保護(hù)競爭或至少與競爭相關(guān)的利益。15. Of course, some phenomena of ‘discrimination’ have immediate competitive relevance, for example the prohibition imposed on dominant companies not to apply dissimilar conditions under art 102(c) TFEU; on the connection between anti-discrimination legislation and UCL, see also section VIII.2. below.然而，這兩個(gè)概念不僅具有內(nèi)在的開放性和模糊性。16. cf High-Level Expert Group (n 11) 12: ‘(...) we acknowledge that there are many different interpretations of fairness (...)’.人們也不應(yīng)忽視人工智能的（錯(cuò)誤）使用可能帶來的諸多負(fù)面影響，尤其是對競爭的負(fù)面影響。雖然這主要體現(xiàn)在反壟斷場景中，如“算法共謀”，17. cf only Mark-Oliver Mackenrodt and Francisco Beneke, ‘Artificial Intelligence and Collusion’ (2019) 50 IIC 109.但人工智能影響的領(lǐng)域往往與傳統(tǒng)上的反不正當(dāng)競爭法相關(guān)，尤其是與“消費(fèi)者保護(hù)”的相關(guān)領(lǐng)域。下面將提供示例。盡管禁止“不正當(dāng)”商業(yè)行為的反不正當(dāng)競爭法一般條款的顯著特性固然可以解決新的和不可預(yù)見的競爭風(fēng)險(xiǎn)，但基于邏輯原因，本文沒有對此進(jìn)行進(jìn)一步闡述。

雖然這不是深入探討“公平”的實(shí)質(zhì)意義（或者更確切地說：它所包含的多重維度）的持續(xù)和長期爭論的地方，但反不正當(dāng)競爭法對“公平”市場秩序的一個(gè)非常具體的貢獻(xiàn)值得強(qiáng)調(diào)：它與反壟斷法的監(jiān)管互補(bǔ)性。從實(shí)質(zhì)上講，反不正當(dāng)競爭法可以解決未能達(dá)到市場支配地位反壟斷要求的競爭問題。18. cf Heike Schweitzer and others, ‘Modernisierung der Missbrauchsaufsicht fu¨ r marktma¨ chtige Unternehmen’(2018)107,110＜https://www.bmwi.de/Redaktion/DE/Publikationen/Wirtschaft/modern isierung-der-missbrauchsaufsichtfuer-marktmaechtige-unternehmen. html＞ accessed before 27 November 2020; Peter Picht and Gaspare Loderer, ‘Framing Algorithms - Competition Law and (Other) Regulatory Tools’ (2018) Max Planck Institute for Innovation & Competition Research Paper No 18-24, 33 ＜https://papers.ssrn.com/ sol3/papers.cfm?abstract_id?3275198＞ accessed before 27 November 2020: ‘Although not addressed in detail here, rules against unfair competition are another major element, both as a template for and a tool complementary to the provisions against cartels and abuse of dominance’; on data access as a concrete example where this complementarity becomes relevant, see section IX.1. below.鑒于在數(shù)據(jù)驅(qū)動(dòng)型市場中確定市場力量的難度，其重要性愈加凸顯。19. cf Boris Paal and Moritz Hennemann, ‘Big Data im Recht’ [2017] NJW 1697, 1699.當(dāng)然，考慮到理論的體系性，必須謹(jǐn)慎，不要繞過或破壞反壟斷法的結(jié)論性決定，即非支配主體采取的某些行為在反不正當(dāng)競爭法中并不具有違法性。然而，如果人們依循對反不正當(dāng)競爭法的“現(xiàn)代”理解，將保護(hù)競爭作為一項(xiàng)機(jī)制置于其目的的關(guān)注中心，那么其一般條款可以作為解決反壟斷領(lǐng)域之外人工智能所引致的市場失靈的基石。

五、透明

透明是人工智能監(jiān)管的核心準(zhǔn)則。人們普遍希望人工智能本身的解決（與純?nèi)祟悰Q策相反）和人工智能實(shí)現(xiàn)決策的具體方式（通常被稱為“黑箱”問題，通過努力實(shí)現(xiàn)“可解釋的人工智能”來反映）均是透明的。20. Of course, the feasibility of transparency in the latter regard ultimately depends on the technological state of the art, cf Deven Desai and Joshua Kroll, ‘Trust But Verify - A Guide to Algorithms and the Law’ (2017) 31 Harvard Journal of Law &Technology 1.當(dāng)前透明有多種表現(xiàn)形式，但一個(gè)重要的形式無疑是市場透明度。保護(hù)市場透明度的傳統(tǒng)體系領(lǐng)域是反不正當(dāng)競爭法，其禁止誤導(dǎo)性商業(yè)行為。21. cf Section 1, arts 6 and 7 UCP Directive.在各自理論測試下，最終具有決定性是一項(xiàng)決策的起源是基于算法還是人為的，以及這是否會(huì)影響消費(fèi)者的商業(yè)決策。22. cf Benjamin Raue and Antje von Ungern-Sternberg, ‘Ethische und rechtliche Grundsa¨ tze der Datenverwendung‘[2020]ZRP 49, 52.

1.基于人工智能的個(gè)性化

人工智能應(yīng)用的主要和最具經(jīng)濟(jì)價(jià)值的領(lǐng)域之一是用于個(gè)性化策略，尤其是個(gè)性化定價(jià)和個(gè)性化廣告。23. On personalised advertising see Guido Noto La Diega, ‘Data as Digital Assets. The Case of Targeted Advertising’ in Mor Bakhoum and others (eds), Personal Data in Competition, Consumer Protection and Intellectual Property Law - Towards a Holistic Approach? (Springer 2018) 447. The extent to which such personalisation actually happens in practice remains dubious, cf OECD Secretariat, ‘Personalised Pricing in the Digital Era’ (2018) ＜https://one.oecd.org/document/DAF/COMP/WD(2018)146/en/pdf＞ accessed before 27 November 2020; further empirical research is needed in this area.圍繞是否應(yīng)當(dāng)禁止或限制這種個(gè)性化策略展開了激烈辯論，即使這些策略是提高整體福利的，理據(jù)在于消費(fèi)者普遍認(rèn)為它們是“不正當(dāng)?shù)摹被蛘摺安还摹薄?4. See on this debate Christopher Townley, Eric Morrison and Karen Yeung, ‘Big Data and Personalised Price Discrimination in EU Competition law’ (2017) King’s College London Dickson Poon School of Law Research Paper No 2017-38 ＜https://papers.ssrn.com/sol3/papers. cfm?abstract_id?3048688＞ accessed before 27 November 2020; Gerhard Wagner and Horst Eidenmu¨ ller, ‘Down by Algorithms? Siphoning Rents, Exploiting Biases, and Shaping Preferences: Regulating the Dark Side of Personalized Transactions’ (2019) 86 University Of Chicago Law Review 581, 587.在不深入討論情形下，有一件事似乎是無可爭議的：消費(fèi)者必須知道他或她受制于個(gè)性化策略，而未得到同等對待。25. On the respective regulatory potential of UCL, see Picht and Loderer (n 18) 33; Wagner and Eidenmu¨ ller (n 24) 590; cf also the precontractual information duty on personalised pricing on the basis of automated decision-making according to art 4(4)(a)(ii) Directive (EU) 2019/ 2161.在某種程度上，如果消費(fèi)者不是基于自主和知情的決策行事，個(gè)性化可能因此違反反不正當(dāng)競爭法規(guī)定的透明度規(guī)則。26. cf Helga Zander-Hayat, Lucia Reisch and Christine Steffen, ‘Personalisierte Preise - eine verbraucherpolitische Einordnung’[2016]VuR 407; Franz Hofmann, ‘Der ma?geschneiderte Preis - Dynamische und individuelle Preise aus lauterkeitsrechtlicher Sicht’ [2016] WRP 1080; on the implications for consumer ‘a(chǎn)utonomy’, see section VII. below.尤其是價(jià)格透明度的缺失會(huì)造成信息不對稱，從而消除了對競爭至關(guān)重要的價(jià)格比較可能性，進(jìn)而損害經(jīng)濟(jì)福利。27. cf Zander-Hayat, Reisch and Steffen (n 26) 407 f.當(dāng)然，精確的信息要求也有爭議：為了不引起“信息過載”，必須對其加以平衡，28. In this regard, personalisation offers interesting possibilities: each consumer could get personalised information, exactly suiting his or her capabilities, situation and needs. Ultimately, this is one aspect of what is currently discussed under the vision of ‘personalised law’, cf (critically) Philip Bender, ‘Limits of Personalization of Default Rules - Towards a Normative Theory’(2020) Working Paper of the Max Planck Institute for Tax Law and Public Finance No 2020-02 ＜https://papers.ssrn.com/ sol3/papers.cfm?abstract_id?3544029＞ accessed before 27 November 2020.并且必須根據(jù)在特定社會(huì)或商業(yè)環(huán)境中合理預(yù)期或常見（包括人工智能的使用程度）來解釋，29. According to Hans-Wolfgang Micklitz and Monika Namyslowska, ‘§ 5a UWG’ in Gerhard Spindler and Fabian Schuster(eds), Recht der elektronischen Medien (4th edn, CH Beck 2019), average consumers don’t expect prices to be personalised, and this circumstance may be relevant for their commercial decision. Conversely, should personalised pricing develop to become such common practice that the public generally expects to be subjected to personalised prices as the new digital normal, the misleading character would vanish.以及對于所討論的商業(yè)傳播媒介，哪些履行信息義務(wù)的方式和方法是適當(dāng)?shù)摹?0. Considerations de lege ferenda include a duty to highlight the use of AI via visual symbols, cf Martin Ebers, ‘Ku¨ nstliche Intelligenz und Verbraucherschutz’ [2020] VuR 121.

2.人工智能相關(guān)營銷的進(jìn)一步示例

除了個(gè)性化，反不正當(dāng)競爭法還可以解決人工智能相關(guān)營銷活動(dòng)的透明度問題。首先，鑒于“人工智能”術(shù)語的模糊性，人們可以考慮在“AI”一個(gè)誤導(dǎo)性實(shí)踐的誘人承諾下，對“正常”計(jì)算機(jī)軟件的營銷行為進(jìn)行討論。其次，企業(yè)越來越多地公布與人工智能相關(guān)的行為準(zhǔn)則，在這些準(zhǔn)則中，其或多或少的具體說明了他們打算如何使用人工智能來造福社會(huì)，并避免歡迎的行為。31. cf Google, ‘AI at Google: our principles’ (7J une 2018) ＜https://www. blog.google/technology/ai/ai-principl es/＞ accessed before 27 November 2020.這些準(zhǔn)則可被視為“企業(yè)數(shù)字責(zé)任”現(xiàn)象的一部分，即“企業(yè)社會(huì)責(zé)任”的數(shù)字化延續(xù)。32. On the latter, see comprehensively Reto M Hilty and Frauke Henning-Bodewig (eds), Corporate Social Responsibility.Verbindliche Standards des Wettbewerbsrechts? (Springer 2014).

如果一家公司違反了該準(zhǔn)則中的聲明，反不正當(dāng)競爭法將在打擊欺騙行為和恢復(fù)市場透明度方面發(fā)揮重要作用。33. cf Frauke Henning-Bodewig, ‘TRIPS and Corporate Social Responsibility: Unethical Equals Unfair Business Practices?’ in Hanns Ullrich and others (eds), TRIPS plus 20 (Springer 2016) 701, 714.因?yàn)椋绻鞠肜盟麄兊摹傲己帽憩F(xiàn)”作為針對重視此種表現(xiàn)的消費(fèi)者的競爭優(yōu)勢，那么唯有在所做的宣傳得到切實(shí)履行的情況下，基于這些理由的競爭才能發(fā)揮作用。在這方面，法律適用的主要問題是許多聲明的模糊性。34. cf ibid.例如，人們很難從諸如以“有益社會(huì)”35. Google (n 31) principle No 1.方式使用人工智能的承諾中得出結(jié)論。

再次，另一組可能越來越具有相關(guān)性的案例來自知識產(chǎn)權(quán)法領(lǐng)域，并且涉及區(qū)分無形商品尤其是在版權(quán)意義上看起來像“作品”的無形商品是由人類創(chuàng)造的，還是在人工智能的大力幫助下創(chuàng)造的必要性。對于“人工智能生成”作品的知識產(chǎn)權(quán)保護(hù)的正當(dāng)性而言，大量的人工指導(dǎo)是否是必要的，這一問題一直且將進(jìn)一步讓知識產(chǎn)權(quán)學(xué)者忙碌。36. cf in more detail section IX.2. below.然而，可以肯定的是，在法律上討論“人類制造”和“人工智能生成”的區(qū)別面臨著一個(gè)現(xiàn)實(shí)挑戰(zhàn)，即必須辨別各自的起源。其中的一個(gè)市場解決方案有賴于消費(fèi)者對于人工生成作品的評價(jià)，而不是人工智能生成的作品，如果實(shí)際上無法區(qū)分彼此，則不起作用。37. On this ‘market solution’, see in more detail Reto M Hilty, Jo¨ rg Hoffmann and Stefan Scheuerer, ‘Intellectual Property Justification for Artificial Intelligence’ (2020) Max Planck Institute for Innovation & Competition Research Paper No 20-02, 11＜https://papers.ssrn.com/ sol3/papers.cfm?abstract_id?3539406＞ accessed before 27 November 2020.如果AI生成的“作品”被當(dāng)作人造產(chǎn)品進(jìn)行營銷，這種營銷無論是主動(dòng)還是被動(dòng)地隱瞞人工智能的來源，都可能構(gòu)成不正當(dāng)競爭行為：一種誤導(dǎo)行為。38. In this regard, it should be noted that the potential non-registrability of subject matter generated ‘a(chǎn)utonomously’ by AI may also lead companies to conceal the use of AI when registering their inventions or designs, cf WIPO (n 2) para (vii); Sven Hetmank and Anne Lauber-Ro¨ nsberg, ‘Ku¨ nstliche Intelligenz - Herausforderungen fu¨ r das Immaterialgu¨ terrecht’ [2018]GRUR 574, 581 therefore suggest that a labelling requirement as to AI involvement could be introduced as a protection criterion for AI-generated products to establish transparency; on deceptive conduct before patent offices and potential remedies, see generally Eugenio Hoss, Deceptive Conducts before the Patent Office (Nomos 2019).

六、責(zé)任

確保企業(yè)對其人工智能造成的“自動(dòng)”損害負(fù)責(zé)是與人工智能相關(guān)的最“經(jīng)典”的法律問題。39. An aspect worth highlighting in this context is the overestimation of the relevance of ‘a(chǎn)utonomy’ notions: in many cases, it is simply decisive whether there has been (in)sufficient guidance of foreseeability of certain AI-induced results ‘on the human side’, irrespective of the ‘a(chǎn)utonomy’ degree ‘on the AI side’.最典型的例子是自動(dòng)駕駛汽車碾壓行人。然而，AI也可能“自主地”損害知識產(chǎn)權(quán)或總體競爭。在反不正當(dāng)競爭法的案例中，關(guān)鍵問題在于確定是由或者在企業(yè)人工智能幫助下實(shí)施的不公平商業(yè)行為的責(zé)任。在近期的學(xué)術(shù)討論之中，人們便強(qiáng)調(diào)了對此類“歸因問題”的整體概念的需要，即將圍繞“次要責(zé)任”等概念的有點(diǎn)支離破碎的理論框架整合到一個(gè)連貫的框架中。40. cf Franz Hofmann, ‘Disziplinarita¨ t, Intradisziplinarita¨ t und Interdisziplinarita¨ t am Beispiel der Grundsa¨ tze “mittelbarer Verantwortlichkeit”’ [2018] JZ 746; on harmonisation possibilities of intermediary liability cf Matthias Leistner, ‘Intermediary Liability in a Global World’ in Tatiana Eleni Synodinou (ed), Pluralism or Universalism in International Copyright Law (Kluwer Law 2019)當(dāng)具體從人工智能角度來構(gòu)建這樣的框架時(shí)，在已有經(jīng)驗(yàn)基礎(chǔ)上構(gòu)建框架，即在不同法律制度的責(zé)任歸因領(lǐng)域已經(jīng)形塑的范例，而不是從零開始創(chuàng)造全新的概念，這種做法似乎是明智的。反不正當(dāng)競爭法可以是這些理論上鼓舞人心的制度之一。

在德國，“競爭中違反注意義務(wù)的責(zé)任”的概念是根據(jù)反不正當(dāng)競爭法一般條款發(fā)展而來的，從而作為知識產(chǎn)權(quán)法“侵權(quán)責(zé)任”的一種替代方案。41. cf German Federal Supreme Court, 12 July 2007, I ZR 18/04 - Jugendgefa¨ hrdende Medien bei ebay.它提供了將反競爭行為歸責(zé)于公司的理論指導(dǎo)，使得公司對未履行其阻止相關(guān)行為的職責(zé)負(fù)責(zé)。該范式特別是在或者為了互聯(lián)網(wǎng)群加以發(fā)展和改進(jìn)，特別需要對相應(yīng)措施的范圍和“合理性”制定標(biāo)準(zhǔn)，包括它們在多大程度上包含防止未來相同或類似侵權(quán)行為的義務(wù)。42. cf Ansgar Ohly, ‘§ 8 UWG’ in Ansgar Ohly and Olaf Sosnitza (eds), Gesetz gegen den unlauteren Wettbewerb (7th edn, CH Beck 2016) para 127.已經(jīng)有人提出將這一概念作為一種潛在的合理模型移轉(zhuǎn)于人工智能情形引發(fā)的違反反壟斷法行為的情形。43. cf Moritz Hennemann, ‘Ku¨ nstliche Intelligenz und Wettbewerbsrecht’ [2018] ZWeR 161, 180 f.它可能為歸因分歧提供有價(jià)值的架構(gòu)、先例和參考因素，提升法律確定性，并在商業(yè)自由和防止損害之間實(shí)現(xiàn)經(jīng)濟(jì)上的合理權(quán)衡。最后，鑒于充分責(zé)任和創(chuàng)新之間的聯(lián)系，這一問題也可以被視為反不正當(dāng)競爭法對促進(jìn)人工智能創(chuàng)新的貢獻(xiàn)，這一目標(biāo)將在下文第九部分進(jìn)一步闡述。

七、自主性

如果我們遵循科幻小說啟發(fā)的概念，人工智能的最終威脅是其取代人類的潛力。然而，保護(hù)人類自主性是人工智能監(jiān)管原則的核心。44. cf only High-Level Expert Group (n 11) 12; OECD (n 11) IV.1.2.a).反不正當(dāng)競爭法建立在并致力于維護(hù)人類經(jīng)濟(jì)的一個(gè)非常重要的子方面：消費(fèi)者作為市場參與者的自主性，他們讓競爭的概念在履行其“仲裁員角色”時(shí)發(fā)揮作用。人工智能在此方面提出了兩方面的問題。

1.供應(yīng)商使用人工智能的自主性威脅

人工智能在供應(yīng)端的使用，尤其是在個(gè)性化策略中的使用，將新產(chǎn)品和廣告完全基于既有偏好，可能會(huì)在“過濾泡沫”中捕獲消費(fèi)者。在這種偏好定制系統(tǒng)的擴(kuò)散過程中，來自各種市場選項(xiàng)的自主性選擇可能會(huì)消減。然而，好消息是，反不正當(dāng)競爭法大體上提供了解決這些威脅的方法：如前所述，透明度要求至少緩解了緊張情形。45. cf section V.1. above; Wagner and Eidenmu¨ ller (n 24) 590 on personalised pricing: ‘An obligation to disclose the application of first-degree price discrimination appears innocuous and potentially effective to leverage consumer autonomy.’消費(fèi)者自愿或非自愿地進(jìn)入或停留在過濾泡沫之中，這是一種自主選擇，盡管自愿喪失自我能力的悖論和危險(xiǎn)人所周知。在這種情形下，反不正當(dāng)競爭法似乎是對抗過度“過濾泡沫”問題的以競爭為導(dǎo)向的子支柱。46. A parallel problem regarding ‘filter bubbles of opinion’ threatening democracy is debated in the media law realm, cf Josef Drexl, ‘Bedrohung der Meinungsvielfalt durch Algorithmen’ [2017] ZUM 529.

2.消費(fèi)者使用人工智能的自主性威脅

（甚至）更成問題的是，消費(fèi)者使用人工智能的鏡像維度，特別是在依賴物聯(lián)網(wǎng)（以下簡稱“IoT”）應(yīng)用時(shí)，“算法消費(fèi)者”一詞已經(jīng)被創(chuàng)造出來。47. Niva Elkin-Koren and Michal Gal, ‘Algorithmic Consumers’ (2017) 30 Harvard Journal of Law & Technology 309.一個(gè)例子是“智能家居”中的“自動(dòng)冰箱”，它可以在沒有人類消費(fèi)者（主動(dòng)）參與的情況下（根據(jù)先前的偏好）訂購新的食物。一方面，這種使用可能構(gòu)成一種受歡迎的“以牙還牙”對抗策略，以對抗企業(yè)對人工智能的損害，恢復(fù)技術(shù)和信息的平衡，同時(shí)，從人類學(xué)的角度來看，它可能會(huì)剝奪消費(fèi)者作為理性市場代理人的能力，因?yàn)樗麄兊乃袥Q策均由人工智能工具來完成。48. cf the concerns articulated by Josef Drexl at the ‘Consumer Law Days 2019’ conference, reported by Jure Globocnik and Stefan Scheuerer, ‘Datenzugang, Verbraucherinteressen und Gemeinwohl - Bericht u¨ ber die Verbraucherrechtstage 2019 des Bundesministeriums der Justiz und fu¨ r Verbraucherschutz in Berlin’ (2020) 11 JIPITEC 228, 229.

關(guān)于反不正當(dāng)競爭法應(yīng)對自身基礎(chǔ)威脅的潛在解決方案，在理論上接受并調(diào)整“算法消費(fèi)者”，尤其是“一般消費(fèi)者”標(biāo)準(zhǔn)的構(gòu)建似乎是必要的，49. The ‘a(chǎn)verage consumer’ standard, against which misleading practices are judged, is not only challenged by personalisation phenomena that question the very concept of ‘a(chǎn)verage’ (cf Peter Rott, ‘Der “Durchschnittsverbraucher” - ein Auslaufmodell angesichts personalisierten Marketings?’ [2015] VuR 163). Also, with a view to ‘a(chǎn)lgorithmic consumers’, a ‘technicised’reconstruction of this hypothetical figure as ‘a(chǎn)verage algorithmic consumer’ may become necessary.但不足以解決自主性問題。相反，如同其他法律領(lǐng)域一樣，很可能有必要“讓人參與其中”。例如，冰箱可能會(huì)被迫不時(shí)查看消費(fèi)者，詢問他們的偏好是否發(fā)生了變化，或者是否對新的報(bào)價(jià)感興趣。這樣的義務(wù)通常必須在反不正當(dāng)競爭法之外實(shí)現(xiàn)。

盡管如此，反不正當(dāng)競爭法借助其在消費(fèi)者選擇模式方面的豐富經(jīng)驗(yàn)，可以為決策者提供理論指導(dǎo)，以評估有多少?zèng)Q策權(quán)可以委托給“算法消費(fèi)者”，以及有多少?zèng)Q策權(quán)不能委托給“算法消費(fèi)者”，而不破壞市場秩序本身的功能。尤其是，反不正當(dāng)競爭法理論可以在此方面影響關(guān)于通過設(shè)計(jì)實(shí)現(xiàn)各自規(guī)范的爭論。50. cf IEEE (n 12).

八、反不正當(dāng)競爭法作為與人工智能相關(guān)的特別反不正當(dāng)競爭法市場行為規(guī)則的實(shí)施工具

（一）在執(zhí)法環(huán)境中定位反不正當(dāng)競爭法

反不正當(dāng)競爭法可以作為反不正當(dāng)競爭法以外各類市場行為規(guī)則的（額外）執(zhí)行支柱，違反這些規(guī)則會(huì)通過“違反法定義務(wù)”這一原則對競爭產(chǎn)生負(fù)面影響。在程序方面，這一選擇通過競爭對手和消費(fèi)者協(xié)會(huì)釋放了執(zhí)法的可能性，許多法律秩序有賴于反不正當(dāng)競爭法，從而在與反壟斷法相關(guān)的國家當(dāng)局之外提供了一種制度性補(bǔ)充。冗長的行政程序相比，這種執(zhí)法方式速度更快、更靈活，因此顯示出特別適合人工智能和數(shù)字經(jīng)濟(jì)的特征。從實(shí)質(zhì)上講，“違反法定義務(wù)”似乎是一個(gè)恰當(dāng)?shù)睦碚摴ぞ?，可以將正在進(jìn)行的有關(guān)數(shù)字經(jīng)濟(jì)中保護(hù)消費(fèi)者利益的法律領(lǐng)域日益趨同的討論付諸實(shí)施。在這些機(jī)制下可能受到制裁的眾多違法行為中，有三種似乎與人工智能背景尤為相關(guān)：歧視、個(gè)人數(shù)據(jù)保護(hù)和網(wǎng)絡(luò)安全。51. The phenomena of discrimination and personal data protection can be seen in conjunction with the personalisation problem outlined above, as personalisation can be based on data gathering in violation of data protection rules, and if the personalisation relies on traits protected by anti-discrimination laws, it may also violate the latter.

（二）市場相關(guān)環(huán)境下基于人工智能的歧視

反歧視立法是從法律上判斷“人工智能偏見”問題的標(biāo)準(zhǔn)。盡管反歧視規(guī)則不是與市場行為相關(guān)的規(guī)則，但在反不正當(dāng)競爭法范域內(nèi)，它們可以在某些情況下適用。一個(gè)明顯的例子是上述商業(yè)環(huán)境中的個(gè)性化策略，即如果個(gè)性化是基于反歧視法禁止提及的特征，如種族或性別。盡管這些方面在一開始就以非經(jīng)濟(jì)價(jià)值為基礎(chǔ)，如人的尊嚴(yán)和個(gè)性，但它們?nèi)匀挥绊懞拖拗浦髽I(yè)在市場上的行為表現(xiàn)。

（三）競爭與隱私：是敵是友?

AI對社會(huì)造成的最基本與最具體52. As opposed to the more far-reaching sci-fi dystopias circling around the discourse.的威脅在于它有能力建立全方位的監(jiān)控，包括國家和私營企業(yè)的監(jiān)控。53. cf Marc Amstutz, ‘Dateneigentum’ (2018) 218 AcP 438, 520, diagnosing the threat of ‘a(chǎn)lgorithmic governmentality’ based on big data gathering (although not considering data protection laws the correct or sufficient remedy).因此，將強(qiáng)有力的數(shù)據(jù)保護(hù)規(guī)則與競爭規(guī)則所追求的以市場和福利為導(dǎo)向的經(jīng)濟(jì)目標(biāo)保持一致至關(guān)重要。54. In this regard it is worth highlighting that both welfare and data protection are collective societal interests, cf Indra Spiecker genannt Do¨ hmann at the Consumer Law Days 2019 (n 48) 233.德國競爭主管機(jī)構(gòu)聯(lián)邦反壟斷局對Facebook的調(diào)查引發(fā)了關(guān)于競爭法和數(shù)據(jù)保護(hù)法之間關(guān)系的激烈辯論，該機(jī)構(gòu)將濫用主要基于支配地位的行為視為違反數(shù)據(jù)保護(hù)規(guī)則。55. Bundeskartellamt, 6 February 2019, B6-22/16; German Federal Supreme Court, 23 June 2020, KVR 69/19 - Facebook II; see on the respective discussion Marco Botta and Klaus Wiedemann, ‘The Interaction of EU Competition, Consumer, and Data Protection Law in the Digital Economy: The Regulatory Dilemma in the Facebook Odyssey’ (2019) 64 The Antitrust Bulletin 428; Klaus Wiedemann, ‘A Matter of Choice: The German Federal Supreme Court’s Interim Decision in the AbuseofDominance Proceedings Bundeskartellamt v. Facebook (Case KVR 69/ 19)’ (2020) 51 IIC 1168.與此同時(shí)，還有一種討論是關(guān)于違反數(shù)據(jù)保護(hù)是否可以作為違反反不正當(dāng)競爭法的法定義務(wù)予以制裁。56. cf Ansgar Ohly, ‘UWG-Rechtsschutz bei Versto¨ ?en gegen die Datenschutz-Grundverordnung?’ [2019] GRUR 686.如果人們遵循上述反壟斷法和反不正當(dāng)競爭法之間目的互補(bǔ)的觀點(diǎn)，認(rèn)可兩部法律本質(zhì)上均是為了保護(hù)有效競爭（或最大化福利）的同一目標(biāo)，然后將這兩條討論進(jìn)路聯(lián)系并結(jié)合起來似乎至關(guān)重要。57. cf Torsten Ko¨ rber, ‘Die Facebook-Entscheidung des Bundeskartellamtes’ [2019] NZKart 187, considering the Facebook proceedings an antitrust equivalent to UCL’s breach of statutory duty doctrine.從反壟斷的角度來看，檢驗(yàn)的是違反數(shù)據(jù)保護(hù)規(guī)則的行為是否可以被視為屬于市場主導(dǎo)行為人“利用”客戶或“阻礙”競爭對手的既定類別；在反不正當(dāng)競爭法語境下，需要違反市場行為規(guī)則，并對市場參與者的（與競爭相關(guān)的）利益產(chǎn)生相當(dāng)大的影響。然而，這兩個(gè)方面的共同問題似乎是，數(shù)據(jù)保護(hù)規(guī)則在多大程度上與競爭有內(nèi)在聯(lián)系，或者因違反數(shù)據(jù)保護(hù)法而對競爭造成損害需要哪些特定于競爭的“額外條件”。58. As regards breach of statutory duty in the EU, the discussion is overlapped by the systematic issue of whether the GDPR sanction regime is conclusive and thus prevents relying on additional enforcement mechanisms. This question is out of the scope of this paper, as it gives no guidance on the substantive relationship between data protection law and competition law.

這個(gè)問題的答案很復(fù)雜，而且反思仍在繼續(xù)。然而，本文希望強(qiáng)調(diào)一些理論指引：首先，將“隱私”理解為一種經(jīng)濟(jì)商品并將其納入經(jīng)濟(jì)福利理論的努力需要進(jìn)一步追求和推進(jìn)。59. Welfare theory is ultimately about the (pareto-)optimal allocation of goods: if privacy can be understood as a good that has to be optimally allocated, it may well be included in an overall welfare doctrine spanning both competition and data protection law; on the economics of privacy, see Alessandro Acquisti, Curtis Taylor and Liad Wagman, ‘The Economics of Privacy’ (2016)54 Journal of Economic Literature 442; pessimistic, Bertin Martens at the Consumer Law Days 2019 (n 48) 231, considering the economic value of privacy still being insufficiently understood and economics thus being of little help for balancing welfare with data protection interests; optimistic, Ryan Calo, ‘Privacy and Markets: A Love Story’ (2016) 91 Notre Dame Law Review 649.這樣，隱私作為數(shù)字經(jīng)濟(jì)的核心消費(fèi)者利益，最終可能會(huì)被視為“消費(fèi)者福利”的組成部分。遵循一種普遍思路，這是競爭法應(yīng)當(dāng)追求的規(guī)范性標(biāo)準(zhǔn)，同時(shí)也被認(rèn)為是需要重構(gòu)和適應(yīng)數(shù)字時(shí)代的標(biāo)準(zhǔn)。60. cf European Data Protection Supervisor, ‘Preliminary Opinion: Privacy and competitiveness in the age of big data: The interplay between data protection, competition law and consumer protection in the Digital Economy’ (March 2014) para 71＜https://edps.europa.eu/sites/edp/files/ publication/14-03-26_competitition_law_big_data_en.pdf＞ accessed before 27 November 2020: ‘Given the reach and dynamic growth in online services, it may therefore be necessary to develop a concept of consumer harm, particularly through violation of rights to data protection, for competition enforcement in digital sectors of the economy’.其次，關(guān)于隱私/人格61. There are complex differentiations regarding the concepts of ‘privacy’ and ‘personality’ and their interrelation. Elaborating on these lies beyond the scope of this article.和知識產(chǎn)權(quán)概念上重疊的理論知識應(yīng)納入討論：盡管這兩種制度的側(cè)重點(diǎn)不同，但都作為無形標(biāo)的物權(quán)利的基礎(chǔ)被納入了基于經(jīng)濟(jì)和人格本位的理由中，同時(shí)針對知識產(chǎn)權(quán)與競爭法之間關(guān)系的理解似乎遠(yuǎn)比隱私與競爭法之間更為進(jìn)步。62. On the relationship between privacy and intellectual property, cf Diana Liebenau, ‘What Intellectual Property Can Learn from Informational Privacy, and Vice Versa’ (2016) 30 Harvard Journal of Law and Technology 285; on a historical side note,it seems illustrative to recall that the influential German scholar Josef Kohler once considered the whole body of (B2B) UCL as protecting the ‘personality interests’ of companies, cf Josef Kohler, Der unlautere Wettbewerb (Rothschild 1914) 17 ff; one can still reflect on whether to locate in particular trade secrecy interests purely in the realm of economics, to view them from an IP angle, or to theorise them in conjunction with privacy and ‘corporate personality’ paradigms.第三，無論如何，這種反思的結(jié)果很可能是數(shù)據(jù)保護(hù)規(guī)則的混合屬性，包括一些可以適用于經(jīng)濟(jì)范式的要素和其他不能適用于經(jīng)濟(jì)范式的要素。63. cf the differentiation by Francisco Costa-Cabral and Orla Lynskey, ‘The Internal and External Constraints of Data Protection on Competition Law in the EU’ (2015) LSE Working Papers 25/2015, 3, assuming that ‘EU data protection norms may impose both an internal and an external constraint on the application of competition law’.第四，也是最后一點(diǎn)，盡管存在目的多元化和重疊性，但必須注意一條基本的系統(tǒng)分界線：在不損害競爭情況下，數(shù)據(jù)保護(hù)不能也不應(yīng)通過競爭機(jī)制純粹以“執(zhí)法協(xié)助”為由來實(shí)施。64. Against an expansionist use of breach of statutory duty in non-market related contexts, see generally Ansgar Ohly, ‘§3a UWG’ in Ansgar Ohly and Olaf Sosnitza (n 42) para 21; anyway, the rather strong enforcement regime of the GDPR has mitigated the need of externally assisting the formerly ‘toothless tiger’ data protection law.

（四）網(wǎng)絡(luò)安全

網(wǎng)絡(luò)安全對于人工智能和物聯(lián)網(wǎng)生態(tài)系統(tǒng)的運(yùn)行和信譽(yù)至關(guān)重要。需要防止黑客入侵的“自動(dòng)駕駛汽車”再次提供了一個(gè)例證。雖然網(wǎng)絡(luò)安全的法律理論仍處于起步階段，但其作為一套市場行為規(guī)則的性質(zhì)似乎是無可爭議的。65. For a comparative law overview on the legal framework, cf DennisKenji Kipker and Sven Mueller, ‘International Regulation of Cybersecurity - Legal and Technical Requirements’ [2019] MMRAktuell 414291.如果違反此類規(guī)則，反不正當(dāng)競爭法規(guī)定的責(zé)任可以作為（額外）誘因，促使企業(yè)充分維護(hù)各自的標(biāo)準(zhǔn)。66. cf Thomas Riehm and Stanislaus Meier, ‘Rechtliche Durchsetzung von Anforderungen an die IT-Sicherheit’ [2020] MMR 571, 574 f.

九、反不正當(dāng)競爭法對促進(jìn)人工智能創(chuàng)新監(jiān)管框架的貢獻(xiàn)

人工智能的另一個(gè)關(guān)鍵承諾是促進(jìn)創(chuàng)新。反不正當(dāng)競爭法至少可在三個(gè)方面為促進(jìn)創(chuàng)新法律框架作出貢獻(xiàn)，以下概述之。

（一）反不正當(dāng)競爭法背景下的數(shù)據(jù)訪問

數(shù)據(jù)訪問是人工智能創(chuàng)新的關(guān)鍵之所在。特別是“機(jī)器學(xué)習(xí)”嚴(yán)重依賴數(shù)據(jù)。過去幾年里，關(guān)于獲取這些數(shù)據(jù)的爭論已經(jīng)取得了很大進(jìn)展。67. Numerous possible doctrinal foundations de lege lata and de lege ferenda have been invoked for granting such access; for a comprehensive overview, cf Federal Ministry of Justice and Consumer Protection and Max Planck Institute for Innovation and Competition (eds), Data Access, Consumer Interests and Public Welfare (Conference Volume on the Consumer Law Days 2019)(forthcoming).然而，在討論中很少考慮從反不正當(dāng)競爭法領(lǐng)域推斷數(shù)據(jù)訪問機(jī)制的選項(xiàng)。68. See the proposal of Drexl at the Consumer Law Days 2019 (n 48) 237 and 238; in detail, Josef Drexl, ‘Connected Devices- An Unfair Competition Law Approach to Data Access Rights of Users’ (2020) Max Planck Institute for Innovation and Competition Research Paper No 20- 22 ＜https://papers.ssrn.com/sol3/papers.cfm?abstract_id?3746163＞ accessed before 31 December 2020.如果數(shù)據(jù)訪問利益可以定位于傳統(tǒng)上與反不正當(dāng)競爭法的相關(guān)領(lǐng)域，那么出于體系一致性的原因，它們應(yīng)該位于那里而非其他領(lǐng)域。69. On the value and necessity of locating claims in the fitting legal regime, see the discussion at the Consumer Law Days 2019(n 48) 238; from the perspective of applicable law, Drexl (n 68) 42.然而除此之外，還應(yīng)探究反不正當(dāng)競爭法作為競爭相關(guān)問題的創(chuàng)新“蓄水池”的潛力，對于這些問題，其他任何系統(tǒng)領(lǐng)域都不是直觀的、顯眼的或在眼前的。70. On this feature of UCL, see section II. above.反不正當(dāng)競爭法進(jìn)路可以解決與B2B和B2C維度相關(guān)的訪問問題，而且似乎不需要明確的法律提案，71. But see in this vein Drexl (n 48) 237.盡管這肯定利于法律的明確性。相反，就目前而言，反不正當(dāng)競爭法一般條款可以勝任此項(xiàng)任務(wù)。

首先，橫向請求可能導(dǎo)致“故意阻礙競爭對手”的后果，德國反不正當(dāng)競爭法針對B2B行為設(shè)置了“小一般條款”，其基于整體利益平衡，認(rèn)定B2B行為是不正當(dāng)?shù)摹?2. § 4 No 4 UWG (‘gezielte Behinderung’); this doctrinal option was first brought to my attention by an oral statement of Matthias Leistner.作為這樣一種利益，根據(jù)反不正當(dāng)競爭法的基本原理，人們可以突出整個(gè)市場的運(yùn)行和競爭。其優(yōu)勢尤其在于，在反壟斷法意義上沒有主導(dǎo)地位的情況下，市場失靈可以得到補(bǔ)救。73. On the antitrust framework for data access, cf Josef Drexl, ‘Designing Competitive Markets for Industrial Data’ (2017) 8 JIPITEC 257, 280 ff; under a UCL approach, it is also conceivable to draw on the antitrust criteria the CJEU has established in its ‘essential facility’ doctrine (cf Case C-418/01 IMS Health ECLI:EU:C:2004:257) as a starting point and then develop them further, duly heeding differences and specificities; on FRAND principles as a potential role model for data access, cf Heiko Richter and Peter R Slowinski, ‘The Data Sharing Economy: On the Emergence of New Intermediaries’ (2019) 50 IIC 4; in any case, aligning the ‘fairness’ element of FRAND with a claim based on unfair competition law appears apt at least on the terminological surface.在獲取數(shù)據(jù)方面，市場失靈是多方面的，不僅限于濫用壟斷權(quán)力的情形。74. For an overview of potential market failures relating to data access, see Bertin Martens, ‘Data Access, Consumer Interests and Social Welfare: An Economic Perspective’ (2020) ＜https://papers.ssrn.com/sol3/papers. cfm?abstract_id?3605383＞accessed before 27 November 2020.這也應(yīng)該放在源于德國反壟斷法（《反限制競爭法》第20條）“輸出”的“相對市場支配地位”概念背景下進(jìn)行看待，盡管在歐洲層面上缺乏類似規(guī)定，但其在規(guī)范數(shù)字經(jīng)濟(jì)方面具有相當(dāng)大的潛在意義。75. cf Heike Schweitzer at the Consumer Law Days 2019 (n 48) 231; Drexl (n 68) 33, 36, 41.

在反壟斷中，其他司法管轄區(qū)考慮采用這樣的考量因素，似乎并不令人信服； 相反，一個(gè)有效的選擇是將它們解釋為反不正當(dāng)競爭法中的體系混合現(xiàn)象。從實(shí)質(zhì)上講，某種權(quán)力不對稱（但低于支配閾值）可能會(huì)（共同）決定干預(yù)的衡量標(biāo)準(zhǔn)。76. cf Martin Peitz and Heike Schweitzer, ‘Ein neuer europa¨ischer Ordnungsrahmen fu¨ r Datenma¨ rkte?’ [2018] NJW 275,280, encouraging the development of case groups of ‘data-related exclusionary conduct’ in B2B relationships beyond market dominance constellations.

其次，尤其是在消費(fèi)者的訪問意愿方面，反不正當(dāng)競爭法似乎是理想的體系空間，因?yàn)槠銪2C維度通常被歸類為“消費(fèi)者保護(hù)法”領(lǐng)域。77. See Drexl (n 48) 237, arguing that the constellation resembles the rules of advertising, a traditional key realm of UCL;comprehensively, Drexl (n 68) 40 ff; see also Jo¨ rg Hoffmann and Begonia Gonzalez Otero, ‘Demystifying the Role of Data Interoperability in the Access and Sharing Debate’ (2020) Max Planck Institute for Innovation & Competition Research Paper No 20-16, 20 ＜https://papers.ssrn.com/sol3/papers.cfm? abstract_id?3705217＞ accessed before 27 November 2020.在某種程度上，訪問與可移轉(zhuǎn)性相對應(yīng)，基于反不正當(dāng)競爭法的可移轉(zhuǎn)性機(jī)制可與通用數(shù)據(jù)保護(hù)條例（GDPR）的第20條的行為范式結(jié)合，在數(shù)字消費(fèi)者福利的共同愿景下進(jìn)行理論化。關(guān)于授予此類訪問權(quán)的實(shí)質(zhì)性標(biāo)準(zhǔn)，有人建議，為了最佳使用連接設(shè)備，必須使用某些數(shù)據(jù)，并將該聲明構(gòu)造為“連接性聲明”，甚至超出了可移轉(zhuǎn)性。78. According to Drexl (n 48) 238, it appears ‘fair’ to grant data access to consumers who need such access in order to use their device in an economically sound manner; on consumer access needs in the IoT, cf also Drexl (n 68); Josef Drexl, ‘Data access and control in the era of connected devices’ (2019) ＜https://www.beuc.eu/publications/beuc-x-2018-121_ data_access_and_control_in_the_area_of_connected_devices.pdf＞ accessed before 27 November 2020.

（二）反不正當(dāng)競爭法與“人工智能與知識產(chǎn)權(quán)”對話，第1部分：市場敏感型投資保護(hù)

雖然整個(gè)學(xué)界似乎均在討論人工智能及其輸出的傳統(tǒng)知識產(chǎn)權(quán)，尤其是版權(quán)和專利保護(hù)，79. cf Jyh-An Lee, Kung-Chung Liu and Reto M Hilty (eds), Artificial Intelligence and Intellectual Property (OUP 2021)(forthcoming); Ryan Abbott, ‘I Think Therefore I Invent’ (2016) 57 Boston College Law Review 1079; Ana Ramalho, ‘Will robots rule the (artistic) world?’ (2017) 21 Journal of Internet Law 15; Annemarie Bridy, ‘Coding Creativity’ (2012) 5 Stanford Technology Law Review 1.但立足反不正當(dāng)競爭法對相關(guān)主題的保護(hù)卻鮮有受到學(xué)界關(guān)注。80. But see Tim W Dornis, ‘Artificial Creativity: Emergent Works and the Void in Current Copyright Doctrine’ (2020) 22 Yale Journal of Law and Technology 1, 25 ff; Tim W Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ [2019]GRUR 1252, 1256 f; Daniel Gervais, ‘Exploring the Interfaces between Big Data and Intellectual Property Law’ (2019) 10 JIPITEC 3, 19 para 84; Drexl (n 73) 270 para 62.是填補(bǔ)這一空白的時(shí)候了。81. Trade secret protection as a hybrid regime between IP and UCL will be considered separately in section IX.3. below.

1.通過反不正當(dāng)競爭法保護(hù)人工智能創(chuàng)新：實(shí)踐風(fēng)險(xiǎn)和理論視野

一個(gè)長期而有爭議的討論圍繞著在多大程度上可以根據(jù)反不正當(dāng)競爭法同時(shí)或在既有的知識產(chǎn)權(quán)法之外授予對模仿無形主體的保護(hù)。這些理論的具體設(shè)計(jì)在歐盟成員國和國際上各不相同。82. In the Anglo-American sphere, they appear as ‘misappropriation doctrine’, which is to some extent comparable to continental European UCL approaches, but very narrowly construed, cf Tim W Dornis, ‘Artificial Creativity’ (n 80) 26 ff.除了反不正當(dāng)競爭法特定情形（如欺騙模仿）之外，鑒于傳統(tǒng)理論禁止基于“道德”理由的“照搬式”或“寄生式”模仿，83. This ‘moral’ rhetoric still resonates in the French terminology of ‘parasitisme’.無論是市場效應(yīng)，還是事實(shí)上不斷擴(kuò)大的知識產(chǎn)權(quán)保護(hù)范圍，現(xiàn)代理論強(qiáng)調(diào)了反不正當(dāng)競爭法作為靈活且對市場敏感的保護(hù)機(jī)制的潛力。84. See Hilty (n 5); Ansgar Ohly, ‘A Fairness-Based Approach to Economic Rights’ in Bernt Hugenholtz (ed), Copyright Reconstructed (Wolters Kluwer 2018) 83; Annette Kur, ‘What to Protect, and How? Unfair Competition, Intellectual Property,or Protection Sui Generis’ in Nari Lee and others (eds), Intellectual property, unfair competition and publicity: convergences and development (Edward Elgar 2014) 11, 27 f; Ansgar Ohly, ‘The Freedom of Imitation and Its Limits - A European Perspective’(2010) 41 IIC 506, 522.認(rèn)識到這一區(qū)別是以下考慮的關(guān)鍵: 然而在實(shí)踐中，反不正當(dāng)競爭法的現(xiàn)有形式——如法院所適用的，仍部分地沿用著舊的道德原則——造成了過度保護(hù)公共領(lǐng)域事項(xiàng)的危險(xiǎn)，85. See on this danger Drexl (n 73) 270 para 63.現(xiàn)代的、市場敏感型的經(jīng)濟(jì)觀點(diǎn)具有相當(dāng)大的潛力。這種潛力可能體現(xiàn)在三個(gè)方面：首先，在一個(gè)抽象的法律理論闡釋中，它象征著一種為數(shù)據(jù)經(jīng)濟(jì)量身定制的無形商品保護(hù)方法的總體監(jiān)管范式，即靈活性；其次，在不確定情況下，作為引入新的權(quán)利的替代方案，從中提取且與應(yīng)然法相關(guān)的考量因素；第三，考慮到人工智能可能會(huì)從根本上改變知識產(chǎn)權(quán)格局，并相應(yīng)地重塑與反不正當(dāng)競爭法的互動(dòng)局面，這是一個(gè)經(jīng)典而又錯(cuò)綜復(fù)雜的闡釋，與知識產(chǎn)權(quán)實(shí)然法的補(bǔ)充保護(hù)功能相關(guān)。雖然這三個(gè)維度顯然緊密聯(lián)系，但下面的分析將把它們作為一個(gè)寬泛的三重結(jié)構(gòu)予以建構(gòu)起來。

2.靈活的經(jīng)濟(jì)功能侵權(quán)評估

從現(xiàn)代意義上反不正當(dāng)競爭法的總體法律理論特性開始，這些似乎使其成為人工智能創(chuàng)新監(jiān)管的完美匹配。簡言之，反不正當(dāng)競爭法的保護(hù)是基于行為，而非主體導(dǎo)向;86. cf Drexl (n 73) 278 para 112: ‘This however questions the very appropriateness of a property approach to regulating that economy. IP systems are largely based on the paradigm of protecting intangible assets, such as technologies in particular, that play a role as input in the production of physical goods. Such a paradigm does not seem to fit a world in which customers have to rely on real-time and accurate information as an input.’它是高度靈活的，而不是依賴于標(biāo)準(zhǔn)化、預(yù)先確定的標(biāo)準(zhǔn)；它對福利經(jīng)濟(jì)觀點(diǎn)很敏感，即在必要的程度內(nèi)補(bǔ)救市場失靈——無論這種市場失靈是由知識產(chǎn)權(quán)領(lǐng)域的過度保護(hù)，還是保護(hù)不足造成的。不利的一面是缺乏法律確定性，經(jīng)濟(jì)學(xué)知識的眾多不足之處以及實(shí)際應(yīng)用的復(fù)雜性。87. cf Rupprecht Podszun, ‘Der ,,more economic approach“im Lauterkeitsrecht’ [2009] WRP 509, 517.在靈活性特點(diǎn)中值得注意的是，反不正當(dāng)競爭法未有預(yù)先確定的條款：因此，從理論上講，它具有持續(xù)投資攤銷所需時(shí)間的潛力，88. See Markus Deck, ‘§ 17 Wettbewerblicher Nachahmungsschutz (§ 4 Nr. 3 UWG)’ in Gordian Hasselblatt (ed), MAH Gewerblicher Rechtsschutz (5th edn, CH Beck 2017) para 164, on the duration of protection for traditional computer programs under UCL.而正式保護(hù)期限與實(shí)際保護(hù)需要之間的差距長期以來一直被認(rèn)為是知識產(chǎn)權(quán)法的一個(gè)危及福利的問題。89. cf Reto M Hilty and Thomas Jaeger, ‘Gesamtanalyse und Erkenntnisse’ in Reto M Hilty and Thomas Jaeger (eds),Europa¨isches Immaterialgu¨ terrecht - Funktionen und Perspektiven (Springer 2018) 665, 675.這在人工智能背景下變得更加重要，人工智能的特征具有十分動(dòng)態(tài)的生產(chǎn)周期，難以與抽象的保護(hù)條款保持一致。90. See Hilty, Hoffmann and Scheuerer (n 37) 20; Drexl (n 73) 278 para 112: ‘In an environment where it is key to capture the moment and where being late leads to wrong decisions, asking the question of how long data should be protected will simply miss the needs of this economy.’此外，保護(hù)可以根據(jù)特定的行業(yè)需要進(jìn)行調(diào)整，以因應(yīng)人工智能行業(yè)特定的變化。91. In a way, contemplating sector-specific protection constitutes the mirror image of the current debate on sector-specific data access regimes.

關(guān)于行為依賴的特征，人工智能和物聯(lián)網(wǎng)領(lǐng)域的一個(gè)常見問題是難以界定92. This relates in particular to the dynamism of subject matter such as self-learning or ‘evolutionary’ algorithms.和定位93. This is reflected in the prominent debate on who should own the rights in ‘AI-generated’ output; on a more visionary note,a general blurring of ‘a(chǎn)ctors’ within global informational networks has been diagnosed, with the proposal of responding by ultimately holding ‘conduct itself’ liable, cf Gunther Teubner, ‘Digitale Rechtssubjekte?’(2018) 218 AcP 155, 202.保護(hù)對象。在這種可疑情形下，它似乎是一種可行的“解決方法”，而不是關(guān)注行為的福利效應(yīng)，從而將問題從技術(shù)領(lǐng)域轉(zhuǎn)移到經(jīng)濟(jì)領(lǐng)域。94. Comparable proposals have been made as to the reconstruction of copyright law: namely, instead of technically looking at ‘reproductions’, undertaking a ‘principle-based assessment’ inspired by modern trademark infringement doctrine, cf Taina Pihlajarinne, ‘Should We Bury the Concept of Reproduction - Towards Principle-Based Assessment in Copyright Law?’ (2017)48 IIC 953.此外，反不正當(dāng)競爭法的經(jīng)濟(jì)功能屬性似乎特別適合保護(hù)“人工智能生成的”無形物。法學(xué)界爭論中所關(guān)注的問題案例的特點(diǎn)是缺乏顯著的人力努力或指導(dǎo)。95. For a critical assessment of the technological state of the art vis-a` -vis scholarly ‘a(chǎn)utonomy’ assumptions, see, however,Daria Kim, ‘AIGenerated Inventions: Time to Get the Record Straight?’ [2020] GRUR International 443.因此，反不正當(dāng)競爭法的市場焦點(diǎn)似乎是一個(gè)特別合適的監(jiān)管選擇。保護(hù)人類“創(chuàng)造者”（從廣義上理解，不限于版權(quán)）的人格和利益一直是授予知識產(chǎn)權(quán)的一個(gè)關(guān)鍵理由。96. See Hilty, Hoffmann and Scheuerer (n 37) 4 ff.然而，在沒有人的情況下，他們的利益必須在平衡工作中得到重視，“發(fā)明家”被“投資者”所取代，97. See Herbert Zech, ‘Artificial Intelligence: Impact of Current Developments in IT on Intellectual Property’ [2019] GRUR Int 1145, 1147: ‘Ultimately, AI generated innovations will only be protected or protectable by investment protection rights. The inventor (author) will be replaced by an investor using AI.’基于反不正當(dāng)競爭法理論上合理的理由，對其采取“更多”而非“純粹經(jīng)濟(jì)的方法”似乎是一個(gè)適當(dāng)?shù)目蚣堋?8. Robert Yu, ‘The Machine Author’ (2017) 165 University of Pennsylvania Law Review 1245, 1266 ff suggests using the ‘hot news misappropriation doctrine’, a ‘quasi-property-fairness-standard’, for handling AI creations.在每種情況下，均必須調(diào)查誰進(jìn)行了相關(guān)投資，以及他們的補(bǔ)償是否因搭便車而受到威脅。從法律理論角度來看，一方面可以堅(jiān)持區(qū)分歐洲大陸版權(quán)傳統(tǒng)中以人類為中心建立起的“經(jīng)典”知識產(chǎn)權(quán)法，另一方面是人工智能的純粹經(jīng)濟(jì)市場機(jī)制。99. Of course, this goes with the caveat that the ‘romantic’, anthropocentric understanding of IP has to a certain extent been overridden by industry-determined market realities, see Hilty, Hoffmann and Scheuerer (n 37) 27.

3.在市場失靈的不確定情況下替代新的知識產(chǎn)權(quán)

談及反不正當(dāng)競爭法的應(yīng)然法的考量因素時(shí)，反不正當(dāng)競爭法傳統(tǒng)上被視為“標(biāo)兵職能”，這意味著在相關(guān)理論最終成為完整的知識產(chǎn)權(quán)之前，可以基于反不正當(dāng)競爭法的理由給予保護(hù)。100. On the ‘pacesetter function’ of UCL vis-a` -vis introducing new intellectual property rights, see Zech (n 10) 161 f; Ohly (n 84) 522 f; Kur (n 84) calls UCL an ‘incubator’ for new IP rights; emphasising the ‘interim’ character of a UCL solution in the AI context, Dornis, ‘Artificial Creativity’ (n 80) 44; Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ (n 80)1252.在考慮潛在的新保護(hù)機(jī)制時(shí)，尤其是對于計(jì)算機(jī)生成的“作品”，以及數(shù)據(jù)或ML模型，應(yīng)該記住這一屬性。101. cf Ce′line Castets-Renard, ‘The Intersection between AI and IP: Conflict or Complementarity?’ (2020) 51 IIC 141,142: ‘(...) the lawmaker may be led to consider that a sui generis system of IP rights for AIgenerated inventions should be raised to adjust innovation incentives for AI’; in favour of new IP regimes, Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ (n 80) 1257 and 1264.只要不清楚引入此類權(quán)利是否有經(jīng)濟(jì)需要，即是否存在需要補(bǔ)救的市場失靈，102. Outlining the context-dependency of market failure regarding AI outputs as opposed to not identifying market failure regarding AI tools, Hilty, Hoffmann and Scheuerer (n 37) 15 ff; considering market failure possible regarding training data,Philipp Hacker, ‘Immaterialgu¨ terrechtlicher Schutz von KI-Trainingsdaten’ [2020] GRUR 1025, 1033; assuming an economic need for protection, Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ (n 80) 1264; yet all authors acknowledge the lack of clear empirical evidence. Absent such evidence, the whole market failure standard ultimately comes down to an allocation of the burden of proof or burden of justification, with the option of either the status quo or the freedom principle as a starting point.相反，人們可以全面監(jiān)控事物的發(fā)展，收集經(jīng)濟(jì)證據(jù)和見解，靈活地根據(jù)反不正當(dāng)競爭法的理據(jù)給予保護(hù)，并在持續(xù)地保護(hù)需求實(shí)現(xiàn)后，將相關(guān)領(lǐng)域中確定的規(guī)則法典化。103. Critical on the introduction of new IP rights for trained AI, Zech (n 97) 1146: ‘Any reaction of IP law beyond jurisprudence and interpretative guidance has to be handled with care. New investment protection rights should only be introduced if otherwise a clear market failure is to be expected. In the area of artificial intelligence, this seems not to be the case’; on the sufficiency of(inter alia) UCL with regard to protection of AI data, cf also Peter R Slowinski, ‘Rethinking Software Protection’ (2020) Max Planck Institute for Innovation & Competition Research Paper No 20-17, 18 ＜https://papers.ssrn.com/sol3/papers.cfm?abstract_id?3708110＞ accessed before 27 November 2020.當(dāng)然，基于不確定背景下潛在的功能失調(diào)的市場干預(yù)經(jīng)濟(jì)成本，104. Dysfunctional effects of IP in the data economy are especially identified as regards the database sui generis right, see Matthias Leistner, ‘The Existing European IP Rights System and the Data Economy - An Overview With Particular Focus on Data Access and Portability’ (2020) 13 ff ＜https://papers.ssrn.com/sol3/papers.cfm?abstract_id?3625712＞ accessed before 27 November 2020.必須與在沒有明確定義權(quán)利105. Highlighting the problem of legal uncertainty when relying on UCL protection, Hacker (n 102) 1032; criticising UCL as‘rather shaky ground for the protection of industrial data’, Andreas Wiebe, ‘Protection of industrial data - a new property right for the digital economy?’ [2016] GRUR Int 877, 879; considering UCL ‘patchy at best’, Dornis, ‘Artificial Creativity’ (n 80) 59.的情況下的法律不確定性成本，以及與B2B領(lǐng)域的反不正當(dāng)競爭法缺乏協(xié)調(diào)相關(guān)的成本進(jìn)行權(quán)衡。106. Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht‘(n 80) 1260; Wiebe (n 105) 879.

4.需要根據(jù)數(shù)字經(jīng)濟(jì)的需要對理論要求進(jìn)行微調(diào)

最后，關(guān)于反不正當(dāng)競爭法保護(hù)的具體應(yīng)用，應(yīng)強(qiáng)調(diào)微調(diào)評估理論要求的必要性。法律秩序中常見的具體標(biāo)準(zhǔn)可分為兩類：首先，從歷史和體系角度來看，它們是與反不正當(dāng)競爭法的其他傳統(tǒng)范式相一致的“特定不正當(dāng)性”規(guī)范，尤其是對來源的混淆，即市場透明度問題，或者與違反商業(yè)秘密有關(guān)的知識收集；107. In Germany, for example, such criteria are codified in an explicit norm of the German Act against Unfair Competition (§4 No 3 UWG), while there is a long-standing discussion on under which circumstances further protection can be granted on the grounds of the general clause (cf Ansgar Ohly, ‘Hartplatzhelden.de oder: Wohin mit dem unmittelbaren Leistungsschutz?’ [2010]GRUR 487); Dornis, ‘Artificial Creativity’ (n 80) 27 considers ‘deceptive and goodwill-appropriating conduct’ as lying at the heart of misappropriation prevention in European and civil-law UCL.其次，它們可以作為知識產(chǎn)權(quán)保護(hù)閾值的功能等價(jià)物，如德國理論要求標(biāo)的物呈現(xiàn)“競爭屬性”。這一標(biāo)準(zhǔn)一直存在疑問，而且，由于它依賴于視覺范式，其適用性也受到了數(shù)字化背景的新挑戰(zhàn)。108. cf Maximilian Becker, ‘Lauterkeitsrechtlicher Leistungsschutz fu¨ r Daten‘ [2017] GRUR 346, 347 f.然而，在法律方法的范圍內(nèi)，此類標(biāo)準(zhǔn)通?？梢杂煞ㄔ汉蛯W(xué)界靈活制定，因此，應(yīng)根據(jù)數(shù)字經(jīng)濟(jì)的需要和特點(diǎn)制定相應(yīng)的標(biāo)準(zhǔn)。109. On the difficulties of applying ‘competitive originality’ to non-visual contexts, see Maximilian Becker, ‘§ 64 Lauterkeitsrechtlicher Leistungsschutz fu¨ r Daten’ in Wolfgang Gloy, Michael Loschelder and Rolf Danckwerts (eds),Handbuch des Wettbewerbsrechts (5th edn, CH Beck 2019) 47 ff.最終，他們的目標(biāo)必須是在更具體的抽象層面上，為法院進(jìn)行市場失靈評估提供指導(dǎo)。在此情形下，如果將基于反不正當(dāng)競爭法的數(shù)據(jù)訪問機(jī)制的概念（見上文第IX.1節(jié)）與數(shù)據(jù)保護(hù)機(jī)制相結(jié)合，則綜合的反不正當(dāng)競爭法方式具有逐步促進(jìn)在訪問和保護(hù)之間找到廣泛尋求的最佳平衡的潛力。反不正當(dāng)競爭法可以為從頭開始考慮的全新方法提供有利空間。一個(gè)具體的相關(guān)領(lǐng)域似乎正在推動(dòng)特殊數(shù)據(jù)庫保護(hù)權(quán)的革新：要求進(jìn)行這種改革的呼聲愈演愈烈，110. cf Leistner (n 104) 17 f; Drexl (n 68) 45.其中包括在形成一個(gè)新的和適當(dāng)?shù)臋C(jī)制時(shí)，需要將數(shù)據(jù)保護(hù)和數(shù)據(jù)訪問結(jié)合起來看待。

（三）反不正當(dāng)競爭法與“人工智能與知識產(chǎn)權(quán)”對話，第2部分：人工智能組件的應(yīng)用

當(dāng)將這些考慮因素具體應(yīng)用于人工智能時(shí)，它似乎傾向于按照機(jī)器學(xué)習(xí)過程的步驟來構(gòu)建評估，即訓(xùn)練數(shù)據(jù)、學(xué)習(xí)過程和輸出。111. This structure is inspired by Drexl and others (n 3).對這些現(xiàn)象的市場失靈的實(shí)質(zhì)性評估超出了本文的范圍。112. For some literature cf n 102.相反，本文旨在闡明一些抽象的理論范式，以應(yīng)對潛在的市場失靈。

1.訓(xùn)練數(shù)據(jù)

從訓(xùn)練數(shù)據(jù)開始，將反不正當(dāng)競爭法保護(hù)應(yīng)用于數(shù)據(jù)113. On the basic premise of what ‘data’ actually is, cf Zech (n 10) 32 f.總體上已經(jīng)討論了很長一段時(shí)間，特別是作為一種替代方法或者反對在數(shù)據(jù)中引入新產(chǎn)權(quán)的論點(diǎn)。114. cf Josef Drexl and others, ‘Data Ownership and Access to Data - Position Statement of the Max Planck Institute for Innovation and Competition of 16 August 2016 on the Current European Debate’ (2016) Max Planck Institute for Innovation& Competition Research Paper No 16-10, para 18 ＜https://papers.ssrn.com/sol3/papers.cfm?ab stract_id?2833165＞ accessed before 27 November 2020; Drexl (n 73) 270; it is worth noting that although a purely economic perspective on the data property issue has in general rightfully been criticised as too short-sighted (cf Amstutz (n 53) 441), in the concrete doctrinal context of UCL as a competition-oriented regime, the standard must be an economic one; on data as subject matter of UCL protection, see generally Becker (n 108) 346; theoretically open towards applying the UCL general clause to data, Ansgar Ohly, ‘Anmerkung zu BGH, Unlauteres Verhalten als Voraussetzung fu¨ r wettbewerbsrechtlichen Nachahmungsschutz - Segmentstruktur’ [2017]GRUR 79, 92; Rupprecht Podszun, ‘§ 3 UWG’ in Henning Harte-Bavendamm and Frauke Henning-Bodewig (eds), UWG (4th edn, CH Beck 2016) para 178.如此一來，反不正當(dāng)競爭法還可以構(gòu)成一種防止數(shù)據(jù)的特定子現(xiàn)象（即人工智能訓(xùn)練數(shù)據(jù)）被盜用的保護(hù)手段，這意味著防止通過使用與競爭對手相同的訓(xùn)練數(shù)據(jù)創(chuàng)建另一個(gè)人工智能模型。115. cf Hacker (n 102) 1031, himself critical as to the sufficiency of such an approach.時(shí)間動(dòng)態(tài)性的特點(diǎn)促使學(xué)者們對進(jìn)行了數(shù)據(jù)的比較，并相應(yīng)地考慮了在反不正當(dāng)競爭法下對時(shí)尚的動(dòng)態(tài)法律保護(hù)。假設(shè)兩者均具有很高的價(jià)值，但是短暫的，因此至少注冊的知識產(chǎn)權(quán)似乎不適合對其進(jìn)行最佳保護(hù)。116. On protection regimes for fashion, see Kal Raustiala and Christopher Sprigman, ‘The Piracy Paradox: Innovation and Intellectual Property in Fashion Design’ (2006) 92 Virginia Law Review 1687, 1692; a further role model could be financial information for stock market transactions, cf Gervais (n 80) 9 para 30; for applying old misappropriation doctrines to new data contexts, cf also Victoria Ekstrand and Christopher Roush, ‘From “Hot News” to “Hot Data”: The Rise of FinTech, the Ownership of Big Data, and the Future of the Hot News Doctrine’ (2017) 35 Cardozo Arts & Entertainment LJ 303.無論人們認(rèn)為這些相似是否令人信服，在任何（和每種）情況下，都必須考慮人工智能培訓(xùn)數(shù)據(jù)的特定經(jīng)濟(jì)特質(zhì)，尤其是生成或獲取這些數(shù)據(jù)所需的投資。117. On the need to differentiate between personal data, industrial raw data and AI training data, cf Hacker (n 102) 1025.至于評估進(jìn)一步取決于上述相應(yīng)法律秩序的理論要求，118. According to Hacker (n 102) 1031, an example for UCL-specific ‘unfair conduct’ would be that employees take training data with them when changing their workplace to a competitor.特別是數(shù)據(jù)是否表現(xiàn)出“競爭性原創(chuàng)性”存在爭議，并且假設(shè)在大多數(shù)情況下它們沒有。119. Dismissive, Christoph Zieger and Nikolas Smirra, ‘Fallstricke bei Big Data-Anwendungen’ [2013] MMR 418, 421; very critical also Hacker (n 102) 1032.

2.算法和模型

關(guān)于人工智能算法的保護(hù)，必須在技術(shù)上和法律上加以區(qū)分：在訓(xùn)練模型的基礎(chǔ)上，優(yōu)化算法基本上由經(jīng)典軟件組成，它們某種程度上是用計(jì)算機(jī)代碼編寫的，120. cf Zech (n 97) 1146.而此類算法永遠(yuǎn)不受知識產(chǎn)權(quán)保護(hù)。因此，它們不僅在著作權(quán)法和專利法下的待遇與經(jīng)典軟件相同，121. ibid.而且也適用反不正當(dāng)競爭法對軟件保護(hù)的一般范式。122. In this context, it should be noted that the correct doctrinal realm for locating software protection has always been debated and the introduction of a ‘sui generis’ right been discussed as an alternative, cf Reto M Hilty and Christophe Geiger, ‘Patenting Software? A Judicial and SocioEconomic Analysis’ (2005) 36 IIC 615, 643 f; Slowinski (n 103) 9 ff; thus, when rethinking the respective paradigms against the backdrop of AI, UCL appears a valuable option to be taken into consideration in discourses on the apt systematic location of protection.在這方面，值得一提的是，上述關(guān)于計(jì)算機(jī)程序的流行觀點(diǎn)也是如此。123. On the comparability of fashion and (traditional) computer programs under UCL, see Deck (n 88) para 163.這些通?？梢允艿椒床徽?dāng)競爭法的保護(hù)，124. As with data, the established requirements of the doctrinal acquis, at least under German law, may pose some problems.As far as ‘competitive originality’ is understood as an indication of origin, it is doubtful to what extent computer programs in general and AI models in particular can be considered to display such character. Also, the traditional visual element associated with this notion hardly fits computer programs, cf Deck (n 88) para 159.然而必須注意著作權(quán)法和專利法關(guān)于它們（非）保護(hù)范圍的結(jié)論性決定，鑒于對這些現(xiàn)象特定的知識產(chǎn)權(quán)保護(hù)，反不正當(dāng)競爭法的現(xiàn)實(shí)相關(guān)性幾乎缺失。這個(gè)案例更為復(fù)雜，比如訓(xùn)練有素的人工智能模型，即實(shí)際的人工智能工具：這些模型，包括它們所構(gòu)成的“權(quán)重”，是否或在多大程度上受版權(quán)法和專利法的保護(hù)存在爭議，125. cf Slowinski (n 103) 16 ff; Bego～na Gonzalez Otero, ‘Machine Learning Models Under the Copyright Microscope: Is EU Copyright Fit for Purpose?’ (2020) Max Planck Institute for Innovation & Competition Research Paper No 21-02 ＜https://ssrn.com/abstract? 3749233＞ accessed before 31 December 2020; Patrick Ehinger and Oliver Stiemerling, ‘Die urheberrechtliche Schutzfa¨higkeit von Ku¨ nstlicher Intelligenz am Beispiel von Neuronalen Netzen’ [2018] CR 2018 761.尤其是它們的動(dòng)態(tài)、不斷變化的性質(zhì)可能會(huì)改變傳統(tǒng)的知識產(chǎn)權(quán)范式。126. cf Zech (n 97) 1146, pointing at the possibility of UCL protection for trained AI.因此，一方面，與優(yōu)化算法相比，可以認(rèn)為反不正當(dāng)競爭法的相關(guān)性更大，因?yàn)槠浠谛袨榈撵`活性，將反不正當(dāng)競爭法應(yīng)用于訓(xùn)練有素的ML模型可以靈活地解決這些不確定環(huán)境下的市場失靈。 另一方面，如果模型不受知識產(chǎn)權(quán)軟件保護(hù)，則此決定通常不應(yīng)被反不正當(dāng)競爭法保護(hù)所規(guī)避或者推翻。

3.生成物

對于人工智能生成的產(chǎn)物，遵循知識產(chǎn)權(quán)法的系統(tǒng)決策必須再次成為適用反不正當(dāng)競爭法的關(guān)鍵指引。如前所述，它的潛在相關(guān)性尤其體現(xiàn)于由于缺乏人類作者、發(fā)明家或設(shè)計(jì)師而無法為人工智能生成物提供知識產(chǎn)權(quán)保護(hù)的情形下。127. cf Zech (n 97) 1146; Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ (n 80) 1256 f.然而，無論這種缺失是系統(tǒng)性的故意還是偶然的仍然模棱兩可：“人工智能生成物”在相關(guān)法律頒布時(shí)根本無法想象，這一論點(diǎn)可以轉(zhuǎn)向一個(gè)或者另一個(gè)方向。128. Dornis, ‘Der Schutz ku¨ nstlicher Kreativita¨ t im Immaterialgu¨ terrecht’ (n 80) 1257 identifies a ‘gap’ of IP law regarding this issue.無論如何，與人工智能生成的無形物品相關(guān)的兩項(xiàng)進(jìn)展需要密切監(jiān)測：第一，對市場結(jié)構(gòu)的經(jīng)驗(yàn)經(jīng)濟(jì)學(xué)洞察，以確定市場失靈或其缺失；第二，關(guān)于缺乏人參與可能對“公共領(lǐng)域”的知識產(chǎn)權(quán)范式產(chǎn)生的影響的法律理論討論。129. cf Mauritz Kop, ‘AI & Intellectual Property: Towards an Articulated Public Domain’ (2020) 29 Texas Intellectual Property Law Journal ＜https://papers.ssrn.com/sol3/papers.cfm?abstract_id?3409715＞ accessed before 27 November 2020.

（四）商業(yè)秘密保護(hù)的反不正當(dāng)競爭法維度

最后，商業(yè)秘密保護(hù)的反不正當(dāng)競爭法維度可以作為監(jiān)管人工智能經(jīng)濟(jì)的法律理論基石。在歐盟，商業(yè)秘密保護(hù)同一時(shí)期已被編纂為一項(xiàng)獨(dú)立的法律。130. Directive (EU) 2016/943 on the protection of undisclosed knowhow and business information (trade secrets) against their unlawful acquisition, use and disclosure.然而，它仍然植根于并援引反不正當(dāng)競爭法，特別是當(dāng)它依賴（不）正當(dāng)標(biāo)準(zhǔn)作為侵權(quán)法的附屬一般條款時(shí)。131. cf Drexl (n 78) 97: ‘Here, the Directive integrates EU trade secrets protection into a broader unfair competition law framework.’商業(yè)秘密保護(hù)是人工智能/知識產(chǎn)權(quán)保護(hù)領(lǐng)域的一個(gè)重要組成部分。132. Josef Drexl and others, ‘Comments of the Max Planck Institute for Innovation and Competition of 11 February 2020 on the Draft Issues Paper of the World Intellectual Property Organization on Intellectual Property Policy and Artificial Intelligence’(2020) 9 ＜https://pure.mpg. de/rest/items/item_3193085_2/component/file_3193086/content＞ accessed before 27 November 2020.數(shù)據(jù)、算法、模型和生成物均可作為商業(yè)秘密進(jìn)行保護(hù)。133. cf Tanya Aplin, ‘Trading Data in the Digital Economy: Trade Secrets Perspective’ in Sebastian Lohsse, Reiner Schulze and Dirk Staudenmayer (eds), Trading Data in the Digital Economy: Legal Concepts and Tools (Nomos 2017); specifically on trade secret protection for AI training data, Hacker (n 102) 1032.盡管存在某些福利主義的模糊性，134. The effects of trade secret protection on AI innovation are ambivalent insofar as on the one hand, the regime provides some extent of exclusivity, thereby protecting investments and safeguarding innovation incentives, while on the other hand, it also creates obstacles vis-a` -vis third parties that want to use e.g. certain data to train their ML models.但歐洲商業(yè)秘密制度作為一個(gè)平衡且充分的制度在排他性和獲取性之間實(shí)現(xiàn)最佳權(quán)衡而被廣泛贊譽(yù)。135. Leistner (n 104) 18 ff.這主要?dú)w功于它采取了受到反不正當(dāng)競爭法啟發(fā)的、靈活的、基于行為的方法。136. Drexl (n 73) 269 para 56: ‘(...) such further limited protection can be considered as better suited to serve the purposes of the data economy, by focussing on the particular way in which a third party has specifically acquired access to the data instead of granting exclusive protection against the use of data’.該制度不是一個(gè)成熟的財(cái)產(chǎn)角度，137. ibid 291, para 182: ‘Rather than recognising exclusive control over any use of protected information, as would be typical for intellectualproperty regimes, EU trade secrets law implements a tort law approach that bans specific conduct related to the acquisition, dissemination and use of trade secrets that can be considered unfair.’而是作為知識產(chǎn)權(quán)和反不正當(dāng)競爭法的理論混合體構(gòu)建的，將彼此的優(yōu)點(diǎn)結(jié)合起來。138. On the advantages of legal hybrids, see Ohly (n 84) 86 ff.根據(jù)這些優(yōu)點(diǎn)，商業(yè)秘密指令可被視為上述反不正當(dāng)競爭法方法的整體法律理論特征的具體化。不僅是為了法律的一致性，商業(yè)秘密保護(hù)和反不正當(dāng)競爭法不應(yīng)被視為兩個(gè)獨(dú)立的領(lǐng)域，而是應(yīng)當(dāng)（仍然）以相互的觀點(diǎn)理解和解釋。畢竟，TS指令對反不正當(dāng)競爭法標(biāo)準(zhǔn)的明確依賴性，也有可能使反不正當(dāng)競爭法作為一個(gè)利益和重要領(lǐng)域重新煥發(fā)活力，并在其B2B維度上重新推動(dòng)歐洲的協(xié)調(diào)對話。

十、結(jié)論與展望

事實(shí)證明，在日漸由人工智能決定的市場秩序方面，反不正當(dāng)競爭法將發(fā)揮切實(shí)可行的作用。它可以在許多方面促進(jìn)中央監(jiān)管模式的落實(shí)，旨在為了社會(huì)利益最佳的利用這一新技術(shù)。因此，反不正當(dāng)競爭法能夠而且不應(yīng)該只是被動(dòng)地因應(yīng)和調(diào)整其既有標(biāo)準(zhǔn)，而是應(yīng)憑借其理論靈活性，積極參與制定應(yīng)對人工智能所提出的多種挑戰(zhàn)所需的新標(biāo)準(zhǔn)。與此同時(shí)，人工智能所引發(fā)的法律問題為進(jìn)一步反思和完善反不正當(dāng)競爭法的本質(zhì)和核心提供了契機(jī)，反不正當(dāng)競爭法是一個(gè)仍未有得到充分理解的法律體系。由于其特有的靈活性，反不正當(dāng)競爭法對社會(huì)、經(jīng)濟(jì)和技術(shù)變革表現(xiàn)出高度的依賴性和回應(yīng)性。這些變化目前和今后一段時(shí)間均是由人工智能推動(dòng)的。反不正當(dāng)競爭法可能會(huì)以這種方式被重塑與改進(jìn)，成為調(diào)整數(shù)字經(jīng)濟(jì)、競爭秩序和社會(huì)的真正基石。

致謝

感謝弗諾克·亨寧·博德維希教授、約爾格·霍夫曼和克勞斯·維德教授提供的有益意見。