The United States Court of Appeals for the Federal Circuit was created in 1982 to unify and clarify patent law, inter alia. It was built from political compromise after the Hruska Commission, which studied the caseload crisis in the federal appellate courts in the 1970s, initially recommended creation of a new National Court of Appeals that would exist between the regional federal appellate circuits and the Supreme Court. The Federal Circuit judges admirably implemented these functions for four decades.

In patent law, “unenforceability” can have immense consequences. At least five equitable doctrines make up the defense of “unenforceability” as it was codified into the Patent Act in 1952: laches; estoppel; unclean hands; patent misuse; and according to some, inequitable conduct. Yet in the seventy years since incorporation of equitable defenses into the patent statute, the Supreme Court has not clarified their reach. Indeed, twice in the last four years, the Supreme Court avoided giving complete guidance on the crucial questions of whether, and when, such equitable defenses are available to bar damages in cases brought at law.

When do new technologies require their own law? Judge Easterbrook argued in 1996 that there is no more need for a “Law of Cyberspace” than there ever was for a “Law of the Horse.” Rather, existing laws spanning multiple fields often are sufficient to cover niche factual applications and even new technological change. The same is true now of “The Law of Blockchain.” Nonetheless, blockchain marketplace participants lack any cohesive analysis to turn to that is neutral as to outcome and performs a comprehensive analysis spanning the multitude of laws affecting the whole ecosystem. We might not need a “Law of Blockchain,” yet this article hopes to shed light on the wide scope of existing laws that apply to this new technological era.

Inauthentic media depictions can harm a person’s privacy and reputation and pose a risk to broader society, as well. “Deepfake” technology allows the creation of a type of inauthentic media using “deep machine learning” techniques, using a computer to quickly swap or simulate faces, voices, and movements.