January 2025

Tomorrow’s Originalism: Would a Time Machine Solve Originalism’s Implementation Problem?

Solomon Park, MJLST Staffer

I. Tomorrow’s Originalism: After Original Public Meaning Originalism & the Implementation Problem

When interpreting the Constitution, the threshold question is what “meaning [did] the text ha[ve] for competent speakers of American English at the time [the relevant] provision of the text was framed and ratified?”[1] This philosophy—known as Public Meaning Originalism (“PMO”)—has become the predominant way judges approach Constitutional questions.[2] But PMO hasn’t always been the majority methodology.[3] Contrary to the prevalence of PMO in the Roberts Court, it was only relatively recently in District of Columbia v. Heller, that PMO really found its footing. As Justice Scalia then wrote: “in interpreting [the Constitution] we are guided by the principle that ‘[t]he constitution was written to be understood by the voters; its words and phrases were used in their normal and ordinary as distinguished from technical meaning.’”[4] This passage in Heller— and subsequent cases involving constitutional challenges—would usher in a new age of originalism and solidify the prevalence of PMO in modern constitutional jurisprudence.[5]

Although today’s originalism has been defined by PMO as the initial starting point, significant debate persists with how originalism should be implemented. Known as the “implementation problem,” legal scholars have critiqued originalism for its inability to “address how practicing judges and attorneys should apply originalist theories.”[6] This concern over implementation—and workability writ large[7]—has proven to be a significant point of contention in recent Supreme Court cases. And no case better exemplifies these challenges than United States v. Rahimi—a Second Amendment case decided just last term. In five separate concurring opinions, and a single dissent, the Justices took originalism to task—engaging with each other to express their support and concerns with PMO.[8]

This current discord preludes tomorrow’s originalism. But unlike the shift from Original Intent to Original Public Meaning, tomorrow’s originalism will likely not be one of substantive form—but rather of content (i.e. not whether PMO is the correct starting point, but rather what tools should be permissible/given more weight to conduct PMO analysis). Foreshadowing the future, we might consider the wealth of literature that surrounds textualism (i.e. rules surrounding semantic/substantive canons, as well as legislative history) as an indicator of the rigor that originalist jurisprudence might eventually arrive at.

This blog post suggests that before we arrive at tomorrow’s originalism, it may be helpful to take a step back. At its core, PMO has a simple premise: competent speakers of American English around ratification had an idea of what the Constitution meant, and it is this meaning that lawyers, judges, and Justices should now strive to locate.

Focusing on the fundamentals, what if we could literally go back in time and ask these speakers of American English? How exactly would we go about doing so? What sort of parameters would shape the questions we ask? Who would we seek out? This very brief blog post, proposes and shows how the following Mondale Time Machine hypothetical could: concretize ongoing discussions about implementation, and provide a way to clarify, and evaluate, existing originalist tools.

II. The Mondale Time Machine (“MTM”) Hypothetical: Core Capabilities & Limitations

The Mondale Time Machine (“MTM”) Hypothetical—Somewhere in the depths of Minnesota Law’s library, there is a time machine…

This very real device has yet to have been activated but can teleport willing “speakers of American English” to the present. The current plan is to then survey these speakers about the Original Public Meaning of a specific provision of the Constitution.

MTM possesses the following initial capabilities, it can teleport any number of people: from anywhere (i.e. geographic area); from anytime (i.e. can limit the search to a specific range of years); and can even teleport people possessing any permutation of specific characteristics or demographics (i.e. of a certain socioeconomic class, race, or gender). Note: this list of capabilities is non-exhaustive and additional capabilities can be added/subtracted by the reader.

MTM requires researchers—meaning the reader—to actually make these decisions. In preparation for the first round of time travel, and in order to best reflect PMO’s objectives, the reader has been asked to provide parameters—and their rationale—to the list of the above capabilities.

III. MTM Raises Two Core Questions/Opportunities:

This hypothetical raises at least two core questions. First, as a procedural matter how much of an issue is the implementation problem—as well as other problems that have been leveled against PMO? Afterall, if we conclude that not even asking a thousand people from the founding era would be sufficient, then the implementation problem is indeed serious. Some of the best arguments for this side could be that: any number of time travelers are probably under inclusive; the selected time travelers would not be representative of the founding era as a population; and evaluation problems could arise when there is disagreement amongst the time travelers.

Second, the hypothetical provides an opportunity to clarify and evaluate desirable features in current/future originalist tools. For example, if we conclude that teleporting an expert linguist from the founding era would be sufficient—then tools like dictionaries (which reflect the opinion of a small but highly educated group of people) should also receive an elevated status. Answering the hypothetical provides a clear platonic ideal for originalism. For example, if we decide that the time machine should transport people possessing various demographics, then the tools we use for originalist analysis should also reflect this ideal. For this reason, a tool which fails to capture these perspectives lacks a signature quality—perhaps even a necessary one—which should demote the persuasive weight given to the tool.

IV. Conclusion: Would a Time Machine Solve Originalism’s Implementation Problem?

 “Discerning what the original meaning of the Constitution requires in this or that case may sometimes be difficult… Faithful adherence to the Constitution’s original meaning may be an imperfect guide, but I can think of no more perfect one for us to follow.”—Justice Gorsuch, United States v. Rahimi[9]

This passage from Justice Gorsuch’s concurrence in Rahimi captures two simultaneous truths. Originalism is, and likely will remain, the “imperfect guide” used to interpret the Constitution. But at the same time, originalism has challenging flaws which arise out of its implementation.

Ultimately, my hypothetical highlights these two realities. On the one hand, a gut feeling tells us that a time machine should be able to solve the implementation problem. Afterall, if not even a thousand people from the founding era could resolve the issue, then what could? On the other hand, working through the hypothetical shows the line drawing problems created by the implementation critique. In the face of that difficulty—and as Justice Gorsuch reminds us—that doesn’t mean the inquiry is over.

I hope this blog post presents an interesting, and entertaining, thought experiment. My answer to the hypothetical would take too many words to write. However, I do think that the hypothetical probably strengthens tools that are capable of more holistically representing communities—such as Corpus Linguistics.

 

 

Notes:

[1] Lawrence B. Solum, The Public Meaning Thesis: An Originalist Theory of Constitutional Meaning, 101 B. U. L. Rev. 1953, 1957 (2022).

[2] See, e.g., Lawrence B. Solum, Original Public Meaning, 807 Mich. St. L. Rev. 897, 810 n. 5-7 (2024) (providing an in-depth analysis of the use of PMO in: the Supreme Court, various federal courts of appeal, and state supreme courts); John O. McGinnis & Michael B. Rappaport, Original Methods Originalism: a New Theory of Interpretation and the Case Against Construction, 103 Nw. U. L. Rev. 751, 761 (2009) (“Original public meaning is now the predominant originalist theory”); see also William Baude, Is Originalism Our law?, 115 Colum L. Rev. 2349, 2391 (2015) (concluding that “originalism seems to best describe our law”). But see Justice Stephen Breyer, Pragmatism or Textualism, 138 Harv. L. Rev. 718, 722 (2025) (“While the Court may well be in the midst of a paradigm shift toward textualism and originalism, the unworkability of these approaches in practice will push the Court back toward the traditional approach — gradually and with time”).

[3] See generally Keith E. Whittington, The New Originalism, 2 Geo. J. L. & Pub. Pol’y 599, 599-613 (2004) (describing and explaining the shift from Original Intent Originalism to Original Public Meaning Originalism).

[4] District of Columbia v. Heller, 554 U.S. 570, 570 (2008).

[5] See, e.g., Saul Cornell, Heller, New Originalism, and Law Office History: “Meet the New Boss, Same as the Old Boss,” 56 UCLA L. Rev.  1095, 1095 (2009) (“District of Columbia v. Heller has been hailed by its supporters as a model of ‘new originalism,’ a methodology that focuses on original public meaning and eschews any concern for original intent.”).

[6] Michael L. Smith and Alexander S. Hiland, Originalism’s Implementation Problem, 30 Wm & Mary Bill of Rts. J. 1063, 1064 (2022).

[7] See generally Kurt Eggret et al., Chapman Law Review Debate: Does Originalism Work?, 26 CHAP. L. REV. 237, 244 (2023) (manuscript of a debate between Professor Kurt Eggert and Professor Lee Strang over Originalism’s workability issue); see also Justice Stephen Breyer, supra note 2, at 722.

[8] Compare United States v. Rahimi, 602 U.S. 680, 692 (2024) (“the appropriate analysis involves considering whether the challenged regulation is consistent with the principles that underpin our regulatory tradition) (citing N.Y. ST. Rifle and Pistol Ass’n., Inc v. Bruen, 597 U.S. 1, 26-31 (2022), with Rahimi, 602 U.S. at 702-703 (Sotomayor, J. & Kagan, J. concurring) (critiquing the dissent as being “so exacting as to be useless”), with id. at 711-712 (Gorsuch, J. concurring) (writing to emphasize the importance of originalism. “Faithful adherence to the Constitution’s original meaning may be an imperfect guide, but I can think of no more perfect one for us to follow”), with id. at 714, 719, 719-731 (Kavanaugh, J. concurring) (clearly supporting original public meaning originalism, and examining the role of “pre-ratification history, post-ratification history, and precedent when analyzing vague constitutional text”), with id. at 737-738, 739-740 (Barrett, J. concurring) (explaining the “basic premises of originalism,” and explaining the problem of “level[s] of generality”), with id. at 744, 745-747 (Jackson, J. concurring) (explaining that Bruen’s test has led to serious workability issues for lower courts, and that significant questions remain with originalism’s scope), with id. at 753-763 (Thomas, J. dissenting) (explaining why “[t]he Government does not offer a single historical regulation that is relevantly similar to [the applicable statute]”).

[9] United States v. Rahimi, 602 U.S. 680, 711 (2024) (Gorsuch, J. concurring).


How Workers Can Respond to Increased Use of Generative Artificial Intelligence

Yessenia Gutierrez, MJLST Staffer

Recent advances in generative Artificial Intelligence (AI) have generated a media buzz and revived worries about the future of work: How many jobs are at risk of being eliminated? Can workers be retrained to work new jobs that did not exist before, or new versions of their now technologically-augmented jobs? What happens to those workers who cannot be retrained? What if not enough jobs are created to compensate for those lost?

It is hard to calculate the pace, extent, and distribution of job displacement due to technological advancements.[1] However, there is general agreement among business leaders that there will be significant job losses due to AI.[2] Professions spanning the education and income spectrum may be impacted, from surgeons to investment bankers to voice actors.[3]

Nevertheless, the jobs predicted to be most impacted are lower-paid jobs such as bank tellers, postal service clerks, cashiers, data entry clerks, and secretaries.[4]

Proponents of rapid AI adoption emphasize its potential for creating “a productivity boost for non-displaced workers” and a resultant “labor productivity boom.”[5] While that will likely be true, what remains uncertain is who will reap the majority of the benefits stemming from this boom — employers or their now more productive workers.

One of the main concerns about increasing use of AI in the workplace is that entire job classifications will be eliminated, leaving large swaths of workers unemployed. There is no consensus over whether technology has created or eliminated more jobs.[6] However, even assuming technological advances have created more jobs than those rendered obsolete, the process of large numbers of workers switching from one type of job to another (perhaps previously nonexistent) job still creates serious challenges.

For one, this process adds stress on an already economically- and emotionally-stressed population.[7] The Center for Disease Control credits “fears about limited employment opportunities, perceptions of job insecurity, and anxiety about the need to acquire new skills” as contributing to “public health crises such as widespread increases in depression, suicide, and alcohol and drug abuse (including opioid-related deaths).”[8] Those workers able to keep their jobs have less bargaining power, as they fear speaking up about possible health, safety, and other concerns for fear of losing their job.[9]

To assist in this transition, some argue that more government intervention is necessary.[10] In fact, several states have enacted legislation regulating the use of AI in employment matters, including protections against discrimination in employment decisions made using AI.[11] Some states are also experimenting with AI training for high school seniors and state employees, sometimes with encouragement from major employers.[12] Federal politicians are also considering legislation, although none has passed.[13]

Some commentators argue that workers themselves have a responsibility to learn skills to remain competitive in the labor market.[14] Still others argue that employers should take up the task of retraining employees, with benefits for employers including ensuring an adequate supply of skilled labor, reducing hiring costs, and increasing employee loyalty, morale, and productivity.[15] One subset of this approach are partnerships between employers and labor unions, such as that between Microsoft Corp. and the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO).[16] Announced in December of 2023, the partnership lists its goals as (1) sharing information about AI trends with unions and workers, (2) integrating worker feedback into AI development, and 3) influencing public policy in support of affected workers.

Others point to the need for strong worker organizations that are capable of bargaining about and achieving protections related to AI and other technology in the workplace.

Collective Bargaining

The Economic Policy Institute, a think-tank aligned with labor unions, argues that the “best ‘AI policy’ that [policymakers] can provide is boosting workers’ power by improving social insurance systems, removing barriers to organizing unions, and sustaining lower rates of unemployment.”[17] Union officials agree on the importance of unions protecting their members from technological displacements, and have started pushing for “requirements that companies must notify and negotiate with worker representatives before deploying new automation technologies.”[18]

The above-mentioned partnership between the AFL-CIO and Microsoft includes a “neutrality framework” which “confirms a joint commitment to respect the right of employees to form or join unions, to develop positive and cooperative labor-management relationships, and to negotiate collective bargaining agreements that will support workers in an era of rapid technological change.”[19] Ideally, this means that Microsoft would not attempt to dissuade any employees that try to unionize, including through common “union avoidance” measures.[20] Employer neutrality can provide more favorable conditions for unionizing, which provides a formal mechanism for workers to collectively bargain for technology policies calibrated to their particular industry and tasks.

Unfortunately, achieving these measures, whether through legislation or Collective Bargaining Agreements (CBAs), will likely require applying tremendous pressure on employers.

For example, in 2023, the Screen Actors Guild – American Federation of Television and Radio Artists (SAG-AFTRA) union and the Writers Guild of America (WGA) simultaneously went on strike for the first time in sixty years.[21] One of the main demands for both unions was protections against AI use. Both achieved partial concessions after 118 days and 148 days out on strike, respectively.[22]

SAG-AFTRA and WGA enjoyed considerable leverage that other workers likely will not have. As Politico reported, Hollywood serves as a “key base for wealthy Democratic donors” which is especially important in California, where much of the industry is based.[23] Entertainment workers occupy an important place in many of our daily lives and support an economically important industry.[24] Unlike healthcare workers or state employees, withholding their labor cannot be portrayed as dangerous, a characterization that seeks to undermine public support for some striking workers.[25]

The resolve and strategic action of both unions charts a path for other unions to ensure worker input into the use of technology in the workplace, while revealing how difficult this path will be.

Conclusion

Although the exact effects of increased AI-adoption by employers are still unknown, there are clear reasons to take their potential effects on workers seriously, today. Workers across the income spectrum are already feeling the pressure of job losses, job displacements, the need to retrain for a new job, and the economic and emotional stress these cause. Bolstering retraining programs, whether run by the government, employers, or through joint efforts are a step towards meeting the demands of tomorrow. However, to truly assuage employee fears of displacement, workers must have meaningful input into their working conditions, including the introduction of new technology to their workplace. Unions hold an important role in achieving this goal.

 

 

Notes:

[1] Chia-Chia Chang et al., The Role of Technological Job Displacement in the Future of Work, CDC’s NIOSH Science Blog (Feb. 15, 2022), https://blogs.cdc.gov/niosh-science-blog/2022/02/15/tjd-fow/.

[2] See e.g., Jack Kelly, Goldman Sachs Predicts 300 Million Jobs Will be Lost or Degraded by Artificial Intelligence, Forbes (Mar. 31, 2023), https://www.forbes.com/sites/jackkelly/2023/03/31/goldman-sachs-predicts-300-million-jobs-will-be-lost-or-degraded-by-artificial-intelligence/; G Krishna Kumar, AI-led Job Loss is Real, Govt Must Intervene, Deccan Herald (July 21, 2024), https://www.deccanherald.com/opinion/ai-led-job-loss-is-real-govt-must-intervene-3115077.

[3] Kelly, supra note 2.

[4] Ian Shine & Kate Whiting, These Are the Jobs Most Likely to be Lost – And Created – Because of AI, World Economic Forum (May 4, 2023), https://www.weforum.org/stories/2023/05/jobs-lost-created-ai-gpt/.

[5] Kelly, supra note 2.

[6] See e.g., Peter Dizikes, Does Technology Help or Hurt Employment?, MIT News (Apr. 1, 2024), https://news.mit.edu/2024/does-technology-help-or-hurt-employment-0401.

[7] See e.g., Hillary Hoffower, Financial Stress is Making Us Mentally and Physically Ill. Here’s How to Cope, Fortune (May 10, 2024), https://fortune.com/well/article/financial-stress-mental-health-physical-illness/; Majority of Americans Feeling Financially Stressed and Living Paycheck to Paycheck According to CNBC Your Money Survey, CNBC News Releases (Sept. 7, 2023), https://www.cnbc.com/2023/09/07/majority-of-americans-feeling-financially-stressed-and-living-paycheck-to-paycheck-according-to-cnbc-your-money-survey.html.

[8] Chang et al., supra note 1.

[9] Id.

[10] See e.g., Chris Marr, AI Poses Job Threats While State Lawmakers Move With Caution, Bloomberg Law (Aug. 13, 2024), https://news.bloomberglaw.com/daily-labor-report/ai-poses-job-threats-while-state-lawmakers-move-with-caution.

[11] Sanam Hooshidary et al., Artificial Intelligence in the Workplace: The Federal and State Legislative Landscape, National Conference of State Legislatures (updated Oct. 23, 2024), https://www.ncsl.org/state-federal/artificial-intelligence-in-the-workplace-the-federal-and-state-legislative-landscape.

[12] Kaela Roeder, High School Seniors in Maryland Are Getting Daily AI Training, Technical.ly (Nov. 8, 2024), https://technical.ly/workforce-development/high-school-ai-training-howard-county-maryland/; Maryland to Offer Free AI Training to State Employees, Government Technology (Sept. 25, 2024), https://www.govtech.com/artificial-intelligence/maryland-to-offer-free-ai-training-to-state-employees; Marr, supra note 10 (“A coalition of major tech companies is urging state lawmakers to focus their efforts on retraining workers for newly emerging jobs in the industry.”).

[13] Marr, supra note 10.

[14] Rachel Curry, Recent Data Shows AI Job Losses Are Rising, But the Numbers Don’t Tell the Full Story, CNBC (Dec. 16, 2023), https://www.cnbc.com/2023/12/16/ai-job-losses-are-rising-but-the-numbers-dont-tell-the-full-story.html.

[15] See John Hall, Why Upskilling and Reskilling Are Essential in 2023, Forbes (Feb. 24, 2023), https://www.forbes.com/sites/johnhall/2023/02/24/why-upskilling-and-reskilling-are-essential-in-2023/; The 2020s Will be a Decade of Upskilling. Employers Should Take Notice, World Economic Forum (Jan. 10, 2024), https://www.weforum.org/stories/2024/01/the-2020s-will-be-a-decade-of-upskilling-employers-should-take-notice/.

[16] Press Release, AFL-CIO and Microsoft Announce New Tech-Labor Partnership on AI and the Future of the Workforce, AFL-CIO (Dec. 11, 2023), https://aflcio.org/press/releases/afl-cio-and-microsoft-announce-new-tech-labor-partnership-ai-and-future-workforce.

[17] Josh Bivens & Ben Zipperer, Unbalanced Labor Market Power is What Makes Technologu–Including AI–Threatening to Workers, Economic Policy Institute (Mar. 28, 2024), https://www.epi.org/publication/ai-unbalanced-labor-markets/.

[18] Marr, supra note 10.

[19] Press Release, supra note 16.

[20] See e.g., Roy E. Bahat & Thomas A. Kochan, How Businesses Should (and Shouldn’t) Respond to Union Organizing, Harvard Business Review (Jan. 6, 2023), https://hbr.org/2023/01/how-businesses-should-and-shouldnt-respond-to-union-organizing; Ben Bodzy, Best Practices for Union Avoidance, Baker Donelson (last visited Nov. 18, 2024), https://www.bakerdonelson.com/files/Uploads/Documents/Breakfast_Briefing_11-17-11_Union_Avoidance.pdf; Carta H. Robison, Steps for Employers to Preserve a Union Free Workplace, Barett McNagny (last visited Nov. 18, 2024), https://www.barrettlaw.com/blog/labor-and-employment-law/union-avoidance-steps-for-employers.

[21] Chelsey Sanchez, Everything to Know About the SAG Strike That Shut Down Hollywood, Harpers Bazaar (Nov. 9, 2023), https://www.harpersbazaar.com/culture/politics/a44506329/sag-aftra-actors-strike-hollywood-explained/#what-is-sag-aftra.

[22] Jake Coyle, In Hollywood Writers’ Battle Against AI, Humans Win (For Now), AP News (Sept. 27, 2023), https://apnews.com/article/hollywood-ai-strike-wga-artificial-intelligence-39ab72582c3a15f77510c9c30a45ffc8; Bryan Alexander, SAG-AFTRA President Fran Drescher: AI Protection Was A ‘Deal Breaker’ In Actors Strike, USA Today (Nov. 10, 2023), https://www.usatoday.com/story/entertainment/tv/2023/11/10/sag-aftra-deal-ai-safeguards/71535785007/.

[23] Lara Korte & Jeremy B. White, Newsom Signs Laws to Protect Hollywood from Fake AI Actors, Politico (Sept. 17, 2024), https://www.politico.com/news/2024/09/17/newsom-signs-law-hollywood-ai-actors-00179553; Party Control of California State Government, Ballotpedia, https://ballotpedia.org/Party_control_of_California_state_government (last visited Nov. 18, 2024).

[24] Advocacy: Driving Local Economies, Motion Picture Ass’n, https://www.motionpictures.org/advocacy/driving-local-economies/ (last visited Jan. 17, 2025).

[25] See, e.g., Ryan Essex & Sharon Marie Weldon, The Justification For Strike Action In Healthcare: A Systematic Critical Interpretive Synthesis, 29:5 Nursing Ethics 1152 (2022) https://doi.org/10.1177/09697330211022411; Nina Chamlou, How Nursing Strikes Impact Patient Care, NurseJournal (Oct. 10, 2023), https://nursejournal.org/articles/how-nursing-strikes-impact-patient-care/.