Framing Algorithms – Competition Law and (Other) Regulatory Tools

Picht, Peter Georg; Loderer, Gaspare Tazio

doi:10.2139/ssrn.3275198

Cited by 6 publications

(3 citation statements)

References 26 publications

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“…In the European framework, as far as existing bodies of law are concerned, the capability of the General Data Protection Regulation 1 (GDPR) to provide effective regulation of the data management and processing methods implemented in profiling algorithms has been thoroughly inspected (Dobber et al, 2019;Eskens, 2016;Malgieri, 2021;Wachter, 2018); also, competition law was identified as a potential tool to tackle the structural distortions caused by personalized practices occurring at market level (Ezrachi & Stucke, 2019;Mundt, 2020;Picht & Tazio Loderer, 2019).…”

Section: Preliminary Considerationsmentioning

confidence: 99%

No Consumer Is an Island—Relational Disclosure as a Regulatory Strategy to Advance Consumer Protection Against Microtargeting

2023

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Presently, most business-to-consumer interaction uses consumer profiling to elaborate and deliver personalized products and services. It has been observed that these practices can be welfare-enhancing if properly regulated. At the same time, risks related to their abuses are present and significant, and it is no surprise that in recent times, personalization has found itself at the centre of the scholarly and regulatory debate. Within currently existing and forthcoming regulations, a common perspective can be found: given the capacity of microtargeting to potentially undermine consumers’ autonomy, the success of the regulatory intervention depends primarily on people being aware of the personality dimension being targeted. Yet, existing disclosures are based on an individualized format, focusing solely on the relationship between the professional operator and its counterparty; this approach operates in contrast to sociological studies that consider interaction and observation of peers to be essential components of decision making. A consideration of this “relational dimension” of decision making is missing both in consumer protection and in the debate on personalization. This article defends that consumers’ awareness and understanding of personalization and its consequences could be improved significantly if information was to be offered according to a relational format; accordingly, it reports the results of a study conducted in the streaming service market, showing that when information is presented in a relational format, people’s knowledge and awareness about profiling and microtargeting are significantly increased. The article further claims the potential of relational disclosure as a general paradigm for advancing consumer protection.

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Section: Preliminary Considerationsmentioning

confidence: 99%

No Consumer Is an Island—Relational Disclosure as a Regulatory Strategy to Advance Consumer Protection Against Microtargeting

2023

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“…Regulatory sandboxes are not new (Tsang 2019;Mattli 2018;Picht 2018). They exist in the Fintech industry, where new rules are experimented in controlled environments (thanks to simulations run over big data) before being implemented at large scale.…”

Section: Regulatory Sandboxesmentioning

confidence: 99%

Algorithmic disclosure rules

Porto

2021

Artif Intell Law

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During the past decade, a small but rapidly growing number of Law&Tech scholars have been applying algorithmic methods in their legal research. This Article does it too, for the sake of saving disclosure regulation failure: a normative strategy that has long been considered dead by legal scholars, but conspicuously abused by rule-makers. Existing proposals to revive disclosure duties, however, either focus on the industry policies (e.g. seeking to reduce consumers’ costs of reading) or on rulemaking (e.g. by simplifying linguistic intricacies). But failure may well depend on both. Therefore, this Article develops a `comprehensive approach', suggesting to use computational tools to cope with linguistic and behavioral failures at both the enactment and implementation phases of disclosure duties, thus filling a void in the Law & Tech scholarship. Specifically, it outlines how algorithmic tools can be used in a holistic manner to address the many failures of disclosures from the rulemaking in parliament to consumer screens. It suggests a multi-layered design where lawmakers deploy three tools in order to produce optimal disclosure rules: machine learning, natural language processing, and behavioral experimentation through regulatory sandboxes. To clarify how and why these tasks should be performed, disclosures in the contexts of online contract terms and privacy online are taken as examples. Because algorithmic rulemaking is frequently met with well-justified skepticism, problems of its compatibility with legitimacy, efficacy and proportionality are also discussed.

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“…That, in turn, helps to foster innovation in the Fintech industry. See: ESMA, EBA and EIOPA (2019); Piri (2019); Arner et al (2016), Mattli (2018; Picht and Loderer (2018).…”

Section: Algorithmic Disclosure Co-regulation For Platforms' Business Usersmentioning

confidence: 99%

Co-regulating algorithmic disclosure for digital platforms

Porto¹,

Zuppetta

2020

Policy and Society

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With digital platforms gaining dominant intermediating role and exerting regulatory functions vis-à-vis small and medium-sized enterprises (SMEs) through algorithms, EU institutions have started considering to rely on their analytical capacity to regulate the myriads of market transactions occurring within and through them (so-called platformto-business, or P2B transactions). Most of the time, the EU suggests recurring to light-tough disclosure duties. Hence, the European model falls short in rebalancing information asymmetry and unequal bargaining power plaguing the SMEs. In practice, the EU model consists either in pure delegation of self-regulatory powers (codes of conduct) or nonenforceable co-regulatory schemes (with technical standards established by the platforms themselves). Other models have been suggested that rely on the regulator's access to the platform's data (so called savvy and data-delegated options). These governance models present several limitations, making the platforms' role as regulatory intermediators little credible. In this scenario, the paper purports that a third option should be considered. In particular, to tackle the multifaceted risks associated with algorithmic decisions by digital platforms, while at the same time avoiding stifling innovation, it makes three suggestions: (1) also information disclosures should be done by an algorithm; (2) that is pre-tested in a co-regulatory process, that involves the regulator and stakeholders; and (3) enforced through legal and other empowerment tools, rather than sole fines.

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Framing Algorithms – Competition Law and (Other) Regulatory Tools

Cited by 6 publications

References 26 publications

No Consumer Is an Island—Relational Disclosure as a Regulatory Strategy to Advance Consumer Protection Against Microtargeting

No Consumer Is an Island—Relational Disclosure as a Regulatory Strategy to Advance Consumer Protection Against Microtargeting

Algorithmic disclosure rules

Co-regulating algorithmic disclosure for digital platforms

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