'Regulatory Issues of Data and Algorithms for the Data-Driven Economy' by Kung-Chung Liu in (2023) GRUR International comments
Data and algorithms are the lifeblood of the data-driven economy. Big data and big algo are bringing new challenges and legal issues to the fore. This article deals with some aspects of these issues and tries to put forward an analytical framework for typifying, securing access to and use of data, and ultimately maximizing the generation and flow of data. This article then deals with algorithms and endeavours to propose six principles for auditing algorithms and a brand new international governance framework for algorithms and their auditing via a treaty and relevant mechanisms. ...
With the ubiquitous take-up of digital technology and the digitization of products, services, and business processes, we find ourselves in a data-driven economy whose two pillars are data and algorithms. Data and especially big data generated and collected by netizens and machines (devices) connected via the internet of things (IoT) are essential elements of the development of new products or services, business models and competition. Another even more important pillar of the data-driven economy is algorithms, as they decide the collection, compilation and analysis of data, and shape the final decision-making of artificial intelligence (AI). Controversies are on the rise about algorithms being biased or even designed to distort competition and harm consumers, whether algorithm-driven market interactions call traditional economic models of competition law into question (explicit versus tacit collusion1), and whether and how new regulations for algorithms must be developed. How can we best regulate data and algorithms to boost the data-driven economy? How can we overcome the intellectual property (IP) hurdles, copyright and trade secrets in particular, of data and algorithms that might hinder the data-driven economy?
This article is dedicated to the clarification of some of the regulatory issues of data and algorithms ‒ no solution can be offered as it is not targeted at one specific national legal regime – with the concerns for the data-driven economy. It will first focus on data by discussing its typology (identifying three types of data), protection, access and use. The second focal point of this article deals with algorithms and their auditing, and endeavours to propose six principles for auditing algorithms and a new treaty and mechanisms to tackle these issues from the perspectives of global governance.
