大数据和新兴竞争担忧

IF 3.1 2区社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence and Law Pub Date : 2021-07-14 DOI:10.2139/ssrn.3884350

Aaqib Javeed

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引用次数: 0

摘要

本文认为，获取大数据是在线平台成功和发展的重要因素之一。通过大数据，企业可以跟踪市场趋势，并以以前不可能的方式使用目标广告服务。这些数据可以通过一些基于人工智能的进步来增加市场力量，从而增加进入相关市场的门槛。占主导地位的网络平台可以利用大数据进行价格歧视等反竞争行为，也可以拒绝获取数据，从而提高相关市场的进入壁垒。因此，本文试图考察上述竞争问题及其在竞争法下可能的补救措施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Big Data and Emerging Competition Concerns

This paper identifies access to Big Data as one of the important factors for the success and growth of online platforms. Through Big Data, businesses can track market trends and use target advertising services in ways that were previously impossible. The data can be leveraged to increase market power through a number of artificial intelligence-based advances, thereby increases barriers to entry in the relevant market. Dominant online platforms can use Big Data to enter into certain anti-competitive acts such as price discrimination as well as refuse access to data which can enhance barriers to entry in the relevant market. Hence, this paper seeks to examine the above-mentioned competition concerns and their possible remedies under competition law.

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来源期刊

Artificial Intelligence and Law Multiple-

CiteScore

9.50

自引率

26.80%

发文量

期刊介绍： Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.