Attribution of authorship

Attribution of authorship refers to the process of determining the creator of a work under copyright law. This is critical in the age of generative AI, where the line between human creativity and machine output is blurred. According to international standards like ISO 42001:2023, AI governance requires clear attribution protocols to manage risks. In the US, the Copyright Office has maintained that purely AI-generated works lack human authorship, while the UK's CDPA Section 9(3) provides a unique framework for computer-generated works. For enterprises, this means establishing a clear legal nexus between human input and AI output to secure copyrightable assets. This distinction is vital for trade secret protection, as AI-generated insights could be classified as proprietary intelligence if properly attributed to the enterprise. Failure to do so risks losing control over AI-derived innovations and competitive advantages.

Practical application involves three key steps: Classification, Documentation, and Contractual Protection. First, enterprises must classify AI outputs into 'human-centric,' 'hybrid,' and 'AI-centric' categories to apply appropriate legal standards. Second, a technical provenance system—utilizing metadata, version control, and usage logs—must be implemented to track the creative process. Third, employee contracts and vendor agreements must explicitly define the ownership of AI-generated outputs. For example, a Taiwan-based manufacturing firm implemented a 'human-in-the-loop' verification process for AI-optimized designs, ensuring each AI-assisted design had a human engineer's sign-off. This practice reduced copyright invalidation risks by 35% and increased the success rate of patent applications by 20% within the first year of implementation. These steps ensure that AI-generated assets are legally defensible assets rather than liabilities.

Taiwan enterprises face three primary challenges: Regulatory ambiguity, technical-legal gaps, and employee awareness. The first challenge is that Taiwan's Copyright Act does not explicitly define AI authorship, creating uncertainty in court. To overcome this, companies should adopt the 'human-centric contribution' principle, ensuring significant human creative input is documented for every AI-assisted work. The second challenge is the lack of technical tools for provenance tracking; enterprises should invest in AI-specific version control systems or blockchain-based attribution logs. The third challenge is the risk of trade secret leakage through employee use of public AI tools. This can be mitigated by implementing strict AI Governance Policies (AGP) and conducting regular compliance audits. A phased approach—starting with policy-making in month one, tool-selection in month two, and employee training in month three—is recommended for effective implementation.

Winners Consulting Services Co., Ltd. specializes in Attribution of authorship for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact