The EU Needs to Reform the GDPR To Remain Competitive in the Algorithmic Economy
Europe’s success in the global algorithmic economy requires a regulatory environment that is fit for AI but does not reduce consumer protections.
Since the mid-1990s, the digital economy has been evolving in three phases: the “Internet economy” transformed into the “data-driven economy,” which in turn is transforming into the “algorithmic economy,” in which the ability to use artificial intelligence (AI) is proving critical to firms’ success.
AI promises significant social and economic benefits. However, those benefits can be diminished by poor regulations, especially those related to data processing, as data lies at the heart of AI. In particular, the General Data Protection Regulation (GDPR), while establishing a needed EU-wide privacy framework, will unfortunately inhibit the development and use of AI in Europe, putting firms in the EU at a competitive disadvantage to their North American and Asian competitors. The GDPR’s requirement for organizations to obtain user consent to process data, while perhaps being viable, yet expensive, for the Internet economy, and a growing drag on the data-driven economy, will prove exceptionally detrimental to the emerging algorithmic economy.
To address these limitations in the GDPR, several European countries have pursued strategies to facilitate access to personal data by companies in specific industries. These isolated efforts are important but will not be sufficient to fully leverage the value of data and capture growth in the long term. The GDPR, in its current form, puts Europe’s future competitiveness at risk. Europe’s success in the global algorithmic economy requires a regulatory environment that is fit for AI but does not reduce consumer protections.
If the EU wants to thrive in the algorithmic economy, it needs to reform the GDPR, such as by expanding authorized uses of AI in the public interest, allowing repurposing of data that poses only minimal risk, not penalizing automated decision-making, permitting basic explanations of automated decisions, and making fines proportional to harm.