29th Annual BTLJ-BCLT Spring Symposium: Copyrightable Subject Matter, Panel 5

Berkeley Center for Law & Technology (BCLT)
Berkeley Center for Law & Technology (BCLT)May 14, 2026

Why It Matters

Understanding the evolving scope of software copyright helps companies safeguard assets and navigate AI‑driven innovation, reducing litigation risk and informing licensing strategies.

Key Takeaways

  • Copyright shields expression, not functionality, per Baker v. Selden.
  • 1980 amendments codified software copyright despite lacking congressional hearings.
  • Abstraction‑filtration test filters ideas, procedures, and methods from protection.
  • Industry moved from physical dongles to licensing and anti‑piracy measures.
  • AI‑generated code revives old copyright debates with new complexities.

Summary

The 29th annual BTLJ‑BCLT Spring Symposium examined what subject matter in software can be copyrighted, opening with a historical overview and segueing into AI‑generated code challenges.

Speakers traced copyright’s roots from the 1880 Baker v. Selden decision, through the 1976 Act’s Section 102(b) language, the 1980 amendment prompted by CONTU, and landmark cases such as Apple v. Franklin, Whelan v. Jaslow, and the Second Circuit’s Altai abstraction‑filtration test that now shape protection of source code, structure, sequence, and organization.

Pam Samuelson highlighted the “functionality exclusion” and quoted Justice Breyer’s early criticism; Jule Sigall illustrated the era with a 1978 CONTU photo and noted Microsoft’s “Manson family” snapshot, while referencing Google v. Oracle’s fair‑use ruling as a modern touchstone.

The discussion underscored that copyright remains a primary revenue tool for software firms, but evolving AI code creation and ambiguous interface protection demand fresh doctrinal guidance, influencing licensing, anti‑piracy tactics, and future legislative reforms.

Original Description

Program occurred April 17, 2026
At the BTLJ Spring Symposium’s panel on software, copyright, and generative AI, scholars and practitioners traced how AI-generated code — likely uncopyrightable under current Copyright Office guidance — threatens to collapse the legal infrastructure underpinning open source software licenses, and how empirical evidence of large language model memorization is forcing courts to reconsider whether a model’s weights may themselves constitute a copy fixed in a tangible medium of expression.
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