Luddites No Longer: Adopting the Technology Tutorial at the Supreme Court*
Bibliographic record
Abstract
I. IntroductionThe average Supreme Court Justice appointed to the Court at age fifty-three.1 Modern Justices remain at the Court significantly longer than their ancestors did, retiring at an average age just short of seventy-nine.2 A Justice appointed today will enjoy a potential tenure that fifty percent longer than that of their typical eighteenth- and nineteenth-century predecessors.3 To put it bluntly, the Court old, and it isn't getting any younger.4Many of the legal issues before the Court are much younger.5 Justice Elena Kagan, the youngest member of the current Court, has seen the rise (and fall) of the compact disc and the VCR, the evolution of video games from Pong to World of Warcraft, and the invention of both cell phones and the Internet. Technological progress challenges the Court by forcing it to adapt the law to fit new, often unique situations. impact of the new on substantive law really quite significant, Chief Justice John Roberts quipped in 2011.6This Note argues that the Supreme Court ill-equipped to meet the challenges presented by rapidly changing technologies. Part II chronicles some of the Court's recent technological troubles, and explains how the current system fails to bridge the Court's technological gap. Part III illuminates how the Court's often Luddite existence damages the law as well as the Court itself. Part IV proposes a solution: the Supreme Court should implement a form of the technology tutorial, a highly malleable process used in patent litigation to educate generalist judges about complex technologies. Through the use of tutorials, the Justices could enhance their understanding of the technologies underlying many difficult cases, resulting in more accurate, defensible, and responsible decisions while simultaneously boosting the Court's legitimacy. Part V briefly concludes.II. The Supreme Court's Technological TroublesThe Supreme Court has never been accused of being ahead of the technological curve. It was not until the mid-1990s that the Court's oral arguments could be heard outside the courtroom, and even then access was still extremely limited.7 Audio recordings of arguments were still zealously guarded into the early 2000s.8 The Court's first website launched in 2000,9 years after the popular growth of the World Wide Web.10 Carbon paper draftopinions circulated between the Justices through the 1960s.11The modern Court still clings to vestiges of the past. Chief Justice Roberts is known to write out his opinions in long hand with pen and paper instead of a computer.12 Justice Stephen Breyer recently confessed that he couldn't even understand the Oscar-winning film The Social Network, which chronicles the rise of social networking behemoth Facebook from creator Mark Zuckerberg's Harvard dorm room.13 In a similar vein, Justice Antonin Scalia explained to a congressional subcommittee, I don't even know what [Twitter] . . . . But, you know, my wife calls me 'Mr. Clueless.'14The Justices' technological ignorance often spills over into the courtroom, and even into the Court's written opinions. The following three cases-Reno v. ACLU,15 City of Ontario v. Quon,16 and Brown v. Entertainment Merchants Ass'n17-provide numerous examples of how a low-tech Court takes on high-tech cases, with troubling results.A. Case Examples1. Reno v. ACLU.-The 1997 case Reno v. ACLU was the Supreme Court's first hands-on encounter with the Internet.18 At issue in the case were First Amendment challenges to two provisions of the Communications Decency Act of 1996 (CDA), which prohibited the transmission of indecent material and the display of patently offensive messages to children.19 The fledgling Internet's capabilities and limitations were crucial to the Court's legal analysis,20 and the Court noted its reliance upon the extraordinary amount of fact-finding performed by the district court. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".