This Contribution examines whether an artist can claim copyright protection over art they created with the assistance of an artificial intelligence program. Naomi Perla (’21) argues that such works satisfy the “original work of authorship” requirement pursuant to 17 U.S.C. § 102(a), thereby granting copyright protection to the artist. The requirements of both authorship and originality are satisfied due to the artist’s creative choices that are largely reflected in the finished pieces. Moreover, the Copyright Act is meant to expand to include new works of art so that artists are consistently incentivized to create for the benefit of the public.
Despite decades of Federal Circuit precedent, a clear definiteness rubric for functional patent claims covering software inventions remains evasive. Questions persist on what constitutes sufficient structure to absolve these claims of means-plus-function treatment. The level of algorithmic specificity required to ensure definiteness for claims that are drafted in means-plus-function form is similarly abstruse. In this Contribution, Zachary Hadd (’21) argues that even software-specific “structure” is best interpreted under the means-plus-function framework and that according definiteness to anything less than step-by-step algorithmic de-tail is not only unjustified, but ultimately inconsistent with Federal Circuit precedent.