Copyright Expectancy Right

Copyright Expectancy Right is an emerging legal concept designed to resolve the dilemma of rights attribution for AI training data. It posits that data contributors, through their 'digital labor,' acquire a right to expect a share in the future economic benefits generated by AI models trained on their data. This provides a flexible value distribution mechanism beyond the traditional 'all-or-nothing' copyright framework. Its legal foundation is linked to labor theory of property and is compatible with the spirit of the Text and Data Mining (TDM) exceptions in the EU's Directive on Copyright in the Digital Single Market (2019/790). In risk management, it sits at the intersection of IP and data governance, aiming to preemptively manage legal risks from unclear data provenance, aligning with principles in frameworks like the NIST AI Risk Management Framework (AI RMF) that call for transparency and fairness.

Enterprises can apply Copyright Expectancy Right through a three-stage governance model. Step 1: Implement Data Provenance Tracking. Use technologies like blockchain to create an immutable record of data sources and usage, which aligns with the record-keeping requirements of ISO/IEC 27701 for data processing activities. Step 2: Design a Fair Value Distribution Model. Employ game-theory models like the Shapley Value to quantify the contribution of each dataset to the AI model's performance and link this to revenue sharing or royalties in data licensing agreements. Step 3: Integrate into Compliance Frameworks. Embed this mechanism into the overall IP management and data protection systems, ensuring compliance with regulations like GDPR's principle of fairness. A global tech firm implemented a similar blockchain-based system for its AI training data, resulting in a 25% reduction in third-party data licensing disputes and improved audit pass rates for data governance.

Taiwanese enterprises face three key challenges. 1. Legal Ambiguity: Taiwan's Copyright Act does not yet recognize this right, creating contractual uncertainty. The solution is to proactively establish these rights through detailed data licensing and revenue-sharing contracts, leveraging the principle of freedom of contract while monitoring legislative developments like the draft AI Basic Act. 2. Technical Complexity: Implementing blockchain and Shapley Value models requires specialized expertise. The mitigation strategy is to start with pilot projects on high-value AI models and partner with expert consultants to leverage mature solutions. 3. Weak Data Governance Culture: Many firms lack granular data source tracking. The solution is to elevate data governance to a strategic priority, initiating a comprehensive data asset inventory and classification project, with clear action items to establish a baseline framework within 6 months.

Winners Consulting specializes in Copyright Expectancy Right for Taiwan enterprises, delivering compliant management systems within 90 days. We have successfully served over 100 local companies. Request a free consultation: https://winners.com.tw/contact