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Reel Rights: Copyright’s Collision With Documentaries

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By: Alexander Tranquill

The Rise of Tiger King

Remember the start of the Covid-19 pandemic? Like myself, many Americans turned to TV to find comfort, and, in those first few surreal weeks, many found themselves watching one particularly enthralling, peculiar, and utterly outlandish story: Tiger King. Tiger King is a Netflix documentary series released in March 2020, which details the increasing tensions between rival big cat eccentrics, eventually culminating in Joe Exotic’s arrest in a murder-for-hire plot of rival Carole Baskin. While Tiger King initially generated massive media attention, it has more recently been the subject of intense copyright litigation.

If you are unfamiliar with this story, Joe Exotic was an internet personality long before Tiger King. With a substantial presence on YouTube, the Netflix documentary heavily relied on video footage originally created by Exotic and his employees. The suit now at issue, Whyte Monkee v. Netflix, centers on Netflix’s use of a video that shows Exotic giving an eulogy at his late husband’s funeral. The video was originally shot by Timothy Sepi, an employee and videographer at Exotic’s Gerald Wayne Zoo. However, Sepi now claims he never gave Netflix permission to use his footage, thus forming the basis for his copyright infringement claim.

During litigation, the district court originally found that Netflix’s use of the footage fell under the fair use exception to copyright infringement. This decision was later reversed by the Tenth Circuit, but, after a great deal of consternation and a flurry of amicus briefs, the Tenth Circuit later vacated its ruling and granted a petition for rehearing. Though the final decision is still pending, this case is significant because the decision has  major implications for documentary filmmakers, while also raising important questions about the rights of content creators in our age of smartphones and social media––where personal footage is often reused by others.

Copyright Protections and Fair Use

To understand the legal questions raised in Whyte Monkee, we must explore the interaction between copyright protections and the doctrine of fair use. Overall, copyright is a type of intellectual property that protects original works of authorship (i.e. paintings, photos, writings, movies) against use by others. However, authorship is a fairly low bar, requiring only a minimal level of creativity. If any creativity can be shown, copyright protections immediately attach when the work is fixed (published) in a tangible medium. As a result, recordings, much like Sepi’s home-video, are often considered copyrightable.

The fair use exception to copyright infringement allows a party to use a work without the permission of the creator if the copying is done for a limited or “transformative” purpose. While there are no hard and fast rules, courts will consider four factors in determining fair use: (1) the purpose and character of the use, (2) the nature of the copyrighted work, (3) the amount and substantiality of the portion used, and (4) the effect of the use on the market for the copyrighted work. Recently, courts have taken particular interest in the first factor, considering the significance of any changes made to the original while also assessing the purpose of the work.  

The Supreme Court’s Warhol Decision

Recently, the Supreme Court issued a detailed analysis of this first factor in Warhol v. Goldsmith. Here, Warhol was sued for a series of silkscreen prints he created of Prince, which he based on a copyrighted image captured by Goldsmith. Considering the purpose and character of Warhol’s silkscreens, the Court clarified that it is no longer sufficient for a work to simply add “new expression” to the original; the key question is whether the work serves “a purpose distinct from the original.” While purpose is not necessarily limited, derivative works should comment on, criticize, or provide otherwise unavailable information to the original. Therefore, although Warhol added new artistic expression to the original, his work did not constitute fair use because its purpose and character aligned with Goldsmith’s––both works were licensed to media companies, merely being used “to illustrate a magazine about Prince with a portrait of Prince.” Thus, because Warhol’s work simply used Goldsmith’s image as a template for the same commercial purpose, it failed to seriously comment on, criticize, or add information to the copyrighted image. 

Applying the Warhol Precedent

Following in the footsteps of Warhol, the Tenth Circuit overturned the district court’s decision in Whyte Monkee, relying on the purpose and character of the use. While the district court found Netflix’s use transformative as it incorporated the funeral clip into a broader narrative, the Tenth Circuit, citing Warhol, concluded that fair use requires the derivative work to serve a distinct purpose. Specifically, the court required the derivative work to critically comment “on the substance or style of the original composition.” With this backdrop, the court found that Netflix only used the funeral footage to show Exotic’s purported megalomania and showmanship. Accordingly, Netflix failed to seriously comment on the style of the video clip itself, instead using the video to “target[] a character in the composition.” Therefore, because Netflix used the funeral footage to detail Exotic’s life and not to comment on the style of the footage, the Tenth Circuit found that the first factor weighed against fair use. 

So, what is all the uproar about? The amicus briefs suggest that this decision will have a chilling effect on the documentary industry, confining filmmakers to commenting on the composition of footage itself (i.e. lighting, angles, editing). In the en banc rehearing, the court re-examined Netflix’s intent behind including the funeral clip in the documentary, focusing on Netflix’s use of the video to detail Exotic’s callous attitude. Thus, the court’s review likely reflects an effort to broaden the meaning of transformative purpose.

In its initial decision, the Tenth Circuit severely narrowed Warhol’s definition of distinctive purpose, requiring a derivative work to critically comment “on the substance or style of the original composition.” While this was an important factor in Warhol, it is not the only relevant factor in examining the purpose and character of a new work. First, the Court in Warhol explicitly looks to purposes outside critical commentary to determine fair use. For example, the Court found that Warhol and Goldsmith’s works shared the same commercial purpose—both were used to “illustrate a magazine about Prince with a portrait of Prince.” Furthermore, the Court in Warhol notes that the “degree of difference” between the works is relevant in the fair use analysis, being weighed together with purpose to determine whether the derivative work is transformative. Ultimately, the Tenth Circuit seems poised to consider other factors in its analysis of the purpose and character of the use. Such a decision would better support filmmakers by providing them greater access to material as they attempt to capture many of the compelling narratives in our world today. As a result, Netflix should continue to assert that its use of the video serves to illustrate Exotic’s personality—distinct from Sepi’s purpose of simply commemorating the funeral. Further, Netflix should revive its district court arguments, claiming the documentary is substantially different from Sepi’s video because it continually interrupts this video with comments from the deceased’s mother and ties the video into the broader story arc to highlight Exotic’s character. Ultimately, these arguments mirror the Supreme Court’s focus in Warhol, offering the Tenth Circuit a precedential foundation to recognize a broader interpretation of transformative use.

The Art of Deception: Should Art Forgeries Be Met with Litigation or Leniency?

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By: Olivia Bravo

Intro

Art forgery is a crime, but should it be met with such harsh penalties? If some art forgeries are so good that they are never discovered and enjoyed the same as the original work, does this argument deserve a more nuanced approach? More importantly, is the cost of litigation worth the hassle?

Art Forgery Defined   

There are many arguments for and against authenticity in art. Is it the artist that creates a work that gives it its value? Or is a work’s value derived from its innate qualities? Because of the subjectivity of the art world, it has long since been a landmine for conmen and fraudsters to exploit. An art “forgery,” or art “fake” is when an artwork is presented by one artist, despite being created by another. Although used interchangeably, an art fake is a copy or replica made and circulated on the market while the original is hanging in a museum or in a private collection, whereas a forgery is made with the intention to deceive an audience. 

Art forgeries undermine the integrity of the art world, but in order to understand the full scope of the issue, it is important to recognize that a forger’s motivations are often more nuanced. Similarly, while psychological factors drive forgers to create their works, the allure of counterfeit works is not driven by the forger, but by societal demand. This recognition is crucial for transparency and for enforcing authenticity in the art market. 

The Case for Litigation

Art has a universal cultural impact, and as a society, we have placed a high value on the protection and cultivation of art and artists. A harsh reality of today’s art world is that more fakes and forgeries are offered for sale than legitimate works, to the point that 20% of the pieces in the world’s most prestigious museums and galleries could be potential forgeries. Many leading art experts and authenticators are even refusing their services to avoid liability, leaving authentication of works to scientists to use instrumental analysis and imaging to determine age and material composition of works. Art forgeries have had a significant impact on the fine art world: creating an economic burden for private buyers, galleries, and art museums who have the sole responsibility of litigating against forgers. 

Art forgeries also create a significant economic deficit when sold to consumers. It is estimated that counterfeit goods cost the US economy between $200- $250 billion per year. The US government suffers significant tax implications from the presence of counterfeit goods in the marketplace. With respect to art forgeries, an individual buyer suffers economic hardship because they are assumed to have purchased an art piece found to be a forgery at an inflated price, which saturates the art market and affects the valuation of other artist’s price point. 

The United States does not have any federal art forgery laws. Federal prosecutions have been successful under the Racketeer Influence and Corrupt Organizations Act (RICO), and independent federal charges are authorized by the Federal Trade Commission under the FTC Act. Even so, criminal prosecutions are rarely brought due to the high burden of proof, and only pursued in extreme cases. Many states require a high burden of proof of intent to defraud in order to bring criminal charges, and only protect the victims of forgeries through consumer protection statutes. 

An arguably more effective means of litigation, through the application of intellectual property laws, would protect artists rights and fill gaps left by criminal and civil protections due to the lower standard of proof needed to bring an infringement claim. Copyright and trademark law can be advantageous in litigating art forgery, assuming the work is not in the public domain and the copyright has been registered. Both have limited reach due to their specific authorship and publication requirements, but can be attached to federal criminal laws to be more effective. However, overall stricter regulation and harsher punishments in the U.S. and globally might better confront the circulation of fake art and deter future perpetrators.

Is There a Case For Leniency?

Art forgers are the talented creators of their art and own copyright protection to their original works. Should this be considered in the art forgery debate? For example, there is a psychological effect on how we perceive art that is disrupted by the knowledge that a work is a forgery. When the monetary value of a work is assigned according to the art market based on “fair market value,” but that value is tied to the artist and the perceived knowledge of their innate talent, what are we really valuing? Is it the art or the artist?  

Substantial resources are being invested into the prevention of art forgeries to the extent that art experts, authenticators, and foundations—dedicated to preserving the legacy of great artists—are becoming extinct for fear of litigation. This burden of authenticity has led to a situation where prosecution is the only recourse once a forger has already been found guilty. But lawsuits are so expensive that there might be room for a nuanced approach that either includes more protections for all parties involved or for a rethinking of art forgery litigation. 

So, what is the solution to a problem that clearly has many ethical and theoretical considerations? Should forgers be met with harsh punishments that will further shape the legal landscape of art fraud prosecution? Or is there a case for potential leniency depending on the intent of the artist and the subsequent impact their forgery has on the viewer and the world? Authenticity remains an elusive judicial concept, and as courts evaluate how to assign losses for victims as well as fair sentences for art forgers, a critical rethinking on how we view art and art litigation might be in order.

Sorry Grandma . . . ChatGPT says You’re Healthy: The Growing Prevalence of AI in Insurance Claim Denials

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By: Joseph Valcazar

As of 2024, 32.8 million Americans received health insurance through a Medicare Advantage plan. This accounts for over half of all Medicare recipients. Covering some of the most vulnerable members of the populace. Including senior citizens aged 65 and older, individuals with disabilities, and those with end stage renal disease. It should come as no surprise that these groups are reliant on insurance to cover necessary treatments that would otherwise be too costly. Even with coverage, 13.6% of a Medicare family’s total expenses are health-related. In contrast, for non-Medicare families this figure is 6.5%. Now, health insurance carriers are integrating AI driven predictive models to calculate care plans, which is raising concerns among medical professionals that patients are being denied necessary care, leading to legal action.

What is Medicare Advantage?

Traditional Medicare encompasses inpatient treatment through Medicare Part A, and outpatient treatment through Medicare Part B. Eligible recipients of Medicare are automatically enrolled to receive coverage under part A. Part B coverage is voluntary. Users who choose to participate in Part B pay a monthly premium, determined by an individual’s household income.

In 1997, Congress passed the Balanced Budget Act (BBA) which introduced Medicare Part C, later named Medicare Advantage (MA). The BBA permitted the Center for Medicare & Medicaid Services (CMS) to contract with private health insurance carriers to provide health insurance plans to eligible Medicare recipients. In turn, MA participants would receive full Part A and Part B coverage, just as they would under traditional Medicare, but through a private insurance carrier (think UnitedHealthcare, Blue Cross Blue Shield, etc.). In addition, MA plans could offer supplemental benefits not offered under traditional Medicare, such as dental and vision coverage or gym memberships. 

However, under Medicare Advantage, these private companies control all MA related claims, determining how much of received or expected care is covered. This is where the controversial nH Predict model enters the picture. 

The nH Predict Model. 

Created by NaviHealth (now owned by UnitedHealth Group), the nH Predict model is designed to predict post-acute care needs. Post-acute care refers to treatment for a severe injury, illness, or surgery, typically caused by trauma. The most common post-acute treatments involve visits to  skilled nursing facilities (SNF), and home health agencies (HHA). 

Investigations of the nH predict model have indicated the model has become “increasingly influential in decisions about patient care and coverage.” While the specifics of the model are unknown, the nH predict model functions by utilizing databases containing millions of medical records, evaluating demographic information such as age, preexisting health conditions, and other factors to determine custom care plans, including duration of treatments.

The utilization of predictive models has garnered concerns from medical professionals and patients alike, who are concerned that an increasing reliance on such models fail to account for the unique individual factors that contribute to a patient’s recovery, leading to inaccurate results. An ongoing class action lawsuit claims the nH predict model has a 90% error rate. The lawsuit also accuses UnitedHealthcare of having knowledge of this error rate and still using the model to override treating physicians’ determinations.

Class Action Lawsuits

Since its creation, multiple health insurance providers have integrated the error-prone nH predict model into their claims process. Many MA patients have filed federal class action lawsuits against major health insurance companies, including UnitedHealthcare and Humana, alleging breach of contract, breach of implied covenant of good faith and fair dealing, and unjust enrichment. The plaintiffs claim that by using the faulty nH predict model, these companies have unfairly denied claims which have directly and proximately caused their damages.

In one claim against UnitedHealthcare, Dale Henry Tezletoff, a 74 year old MA recipient suffered a stroke that required hospital admission. Mr. Tezletoff’s doctor recommended he seek post-acute treatment at a SNF for 100 days. After 20 days of treatment at an SNF, he was informed by UnitedHealthcare that any future treatment would not be covered. It required two separate appeals before a UnitedHealthcare doctor reviewed Mr. Tezletoff’s medical records and concluded additional recovery time was needed. Yet, after 20 more days at the SNF, Mr. Tezletoff was again informed that any future post-acute care had been denied. And this time, even with an opposing opinion from Mr. Tezletoff’s doctor, UnitedHealthcare refused to overrule its decision. As a result, Mr. Tezletoff was required to pay out-of-pocket expenses totalling $70,000 to receive the necessary treatment.

These lawsuits shine a spotlight on the ethical and legal ambiguities of AI in its current state. The legal system is not well equipped to respond on the whim to new complex technological advancements. When a court has the opportunity to hear a case on an emerging issue, it is placed in a position to serve as a voice of authority. A ruling in the plaintiff’s favor would act as a deterrent to similar future conduct. Providing the legislature an additional buffer as they tackle the unenviable task of regulating this new technology.

The fact is, Mr. Tezletoff’s story is not unique, and the implications of these lawsuits are apparent; people’s quality of life is on the line. The outcome of these lawsuits, and the response from the government, will help shape how AI is integrated into the healthcare industry and others like it.

The Government’s Initial Reactions

The federal government has begun to respond to these concerns. On January 1, 2024, the Department of Health and Human Services enacted new rules requiring specialized health care professionals to review any denial involving a determination of a service’s medical necessity. A change that is viewed as fixing “a big hole” in managing the use of AI predictive models.

More recently, on September 28, 2024, California passed SB 1120, requiring health care service plans utilizing AI to determine necessary medical treatments to meet and comply with specific requirements. The objective of this new legislation is to increase the transparency of these models, prevent discrimination, and limit supplantation of health care providers decision making.

The introduction of AI in the healthcare industry is novel, and further reactions from governments on a state and federal level are likely to follow.

Conclusion

Proponents of AI predictive models believe that these systems will speed up the claims process, detect unusual billing patterns, and allow health insurance companies to make more accurate risk assessments. In turn, this will allow these companies to utilize their resources more efficiently and offer better treatment plans. But at what cost to the insured? If AI proves to be as reliable as its proponents believe, then perhaps a future exists where predictive models are commonplace, and serve to benefit not only the insurance companies, but those covered as well. However, many of these models are in their infancy. Currently relying on the outputs of these models, especially when it involves the health and wellbeing of individuals, is a slippery slope that can, and has harmed people physically and financially. 

A Comparative Analysis of AI Governance Frameworks

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By Audrey Zhang Yang

Introduction

The advent of artificial intelligence (AI) has prompted nations around the globe to develop governance frameworks to ensure the ethical, secure, and beneficial deployment of AI technologies. This paper presents a comparative analysis of AI governance frameworks across five key regions: the European Union, the United Kingdom, the United States, China, and Singapore. Each region has adopted a unique approach, reflecting its cultural values, legal traditions, and strategic priorities. By examining these frameworks, we can discern the varying priorities and methods of regulation that influence the global AI landscape.

European Union

The EU stands at the forefront of AI regulation with its Artificial Intelligence Act (AI Act), a pioneering legislative effort to categorize and manage AI systems based on their risk levels. The Act delineates four categories of risk: unacceptable, high, medium, and low, with prohibitions on certain AI applications deemed contrary to EU values, such as social scoring and manipulative practices. This regulatory framework is complemented by existing product liability directives, technical standards, and conventions addressing AI’s impact on human rights. Collectively, these measures embody the EU’s commitment to a human-centric AI that aligns with its democratic values and social norms.

United Kingdom

The UK’s AI governance is articulated through five guiding principles that emphasize safety, transparency, fairness, accountability, and the right to redress. Regulatory oversight is distributed among existing agencies, with the Information Commissioner’s Office overseeing data privacy and the Competition and Markets Authority addressing competition-related issues. The UK’s approach integrates AI governance within the existing legal and regulatory framework, ensuring that AI systems are developed and used in a manner consistent with established norms and standards.

United States 

In contrast, the US has adopted a more decentralized and sector-specific approach to AI governance. The recent executive order by President Biden sets forth a national strategy, delegating responsibilities to various federal agencies. The Department of Commerce’s National Institute of Standards and Technology (NIST), Bureau of Industry and Security (BIS), National Telecommunications and Information Administration (NTIA), and U.S. Patent and Trademark Office (USPTO) play pivotal roles in this strategy. The Federal Trade Commission (FTC) has been active in addressing the misuse of biometric data, while the U.S. Securities and Exchange Commission (SEC) and Consumer Financial Protection Bureau (CFPB) have focused on the implications of AI in their respective domains. United States Department of Health and Human Services’ (HHS) regulations on AI in healthcare mark a significant step in sector-specific governance. At the state level, legislation such as Illinois’ Biometric Information Privacy Act (BIPA), California Consumer Privacy Act (CCPA), and California Privacy Rights Act (CPRA) demonstrate a proactive stance on privacy and consumer rights. The US model is characterized by a patchwork of laws and regulations that, together with court precedents and other governance frameworks, shape the AI regulatory environment.

China

China’s approach to AI governance is tightly linked to its broader data security and privacy regime. The Cybersecurity Law, Data Security Law, and Personal Information Protection Law form the backbone of AI regulation, with additional policy documents guiding the AI industry’s development. The Interim Measures for the Management of Generative Artificial Intelligence Services represent a targeted regulatory effort to oversee AI-generated content. China’s strategy reflects its centralized governance model and its ambition to become a leader in AI while maintaining strict control over data and technology.

Singapore

Singapore’s AI governance framework is characterized by its non-mandatory nature, focusing on guidelines, testing frameworks, and toolkits to promote best practices in AI adoption. This approach has created a business-friendly environment that encourages innovation and attracts companies seeking a more flexible regulatory landscape. Singapore’s model demonstrates a balance between fostering AI development and ensuring responsible use through voluntary compliance with government-endorsed guidelines.

Conclusion

The comparative analysis of AI governance frameworks across the EU, UK, US, China, and Singapore underscores the multifaceted nature of AI regulation and the diverse philosophies underpinning it. The EU’s Artificial Intelligence Act represents a step towards a comprehensive, risk-based regulatory regime, setting a precedent for future legislation with its categorization of AI applications and emphasis on fundamental rights and values. This contrasts with the US’s decentralized, sector-specific approach, which relies on a mosaic of federal and state regulations, agency guidelines, and industry standards to govern the AI landscape. The US system’s flexibility allows for rapid adaptation to technological advancements but may result in a less cohesive regulatory environment.

China’s centralized governance model integrates AI regulation within its broader data security framework, reflecting its strategic intent to harness AI’s potential while enforcing stringent data control measures. This approach facilitates a coordinated and consistent policy environment but may also impose rigid constraints on AI innovation and usage. Singapore, on the other hand, has crafted a non-mandatory, guidelines-based framework that prioritizes industry growth and agility. By promoting voluntary adherence to best practices, Singapore positions itself as a hub for AI development, though this flexibility might pose challenges in ensuring accountability and ethical compliance.

The UK’s governance framework, guided by principles of safety, transparency, and fairness, seeks to embed AI regulation within its existing legal and regulatory structures. This principle-driven approach aims to ensure that AI development aligns with societal norms and provides mechanisms for redress, yet it may require continuous updates to keep pace with the rapid evolution of AI technologies.

In conclusion, the examination of these diverse governance frameworks reveals that there is no one-size-fits-all approach to AI regulation. Each model reflects the region’s cultural, legal, and strategic priorities, and each comes with its own set of trade-offs. As AI technologies continue to advance and permeate various aspects of society, these governance frameworks will need to evolve, balancing the promotion of innovation with the protection of public interests. The ongoing dialogue of suitable practices among these regions will be crucial in shaping a global AI governance landscape that is both dynamic and responsible.

Your Squishmallow Isn’t Who You Think It Is: Setting The Bounds Of The Soft Toy Market 

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By: Caroline Dolan

Squishmallows were introduced in 2017 and went viral on TikTok and Instagram during the Covid-19 pandemic in 2021. People fell in love with these affordable and huggable plushies that are available in more than 3,000 different characters. Their unique sizes and colors provide comfort and joy for all ages and even serve a niche of Squishmallow collectors. 

Trade Dress: The Look and Feel

Trademarks are “words, names, symbols, or devices” that are distinct, functional, and used in commerce to identify the source of a good. The Lanham Act provides federal protection over the good-will of such artistic creations from infringement, dilution, cybersquatting, and false advertising. It also protects consumers from being deceived by knock-off products. The Lanham Act also protects a product’s trade dress, which is “the commercial look and feel of a product or service that identifies and distinguishes the source of the product or service.” Similar to trademarks, trade dress can receive protection even without formal registration with the U.S. Patent and Trademark Office.  

To assert a trade dress infringement claim, a plaintiff must demonstrate that their product’s trade dress  (1) is distinctive; (2) is owned by the plaintiff; (3) is nonfunctional; and (4) that the defendant used the trade dress without consent in a way that is likely to confuse the ordinary consumer as to the source, sponsorship, or affiliation of the product. The Ninth Circuit has held that a trade dress that fails to be inherently distinctive may still be protected if it possesses a secondary meaning. To show a secondary meaning, a plaintiff must prove “a mental recognition in buyers’ and potential buyers’ minds that products connected with the [trade dress] are associated with the same source.” 

Build-A-Bear vs. Squishmallow

Warren Buffet’s investment company, Berkshire Hathaway, owns Alleghany Corporation which is the parent company of Jazwares LLC. Jazwares oversees Kelly Toys which is a leading toy manufacturer and the creator of Squishmallows. Squishmallows have seen its sales boom since 2021 and can be purchased in a variety of spaces, including in bulk at your local Costco. However, in January 2024, to offer “optimal hugging benefits” in light of Valentine’s Day, Build-A-Bear launched its Skoosherz line—a variety of collectible plush pillow-like toys. 

Once the Sckoosherz line was released, Kelly Toys promptly filed a lawsuit in the Central District of California claiming that Build-A-Bear’s Skoosherz line infringes on Squishmallow’s trade dress because Skoosherz imitate Squishmallows’ “shape, face style, coloring and fabric.” Kelly Toys’ complaint alleges that Skoosherz “have the same distinctive trade dress as the popular Squishmallows, including: shaped fanciful renditions of animals/characters; simplified Asian style Kawaii faces; embroidered facial features; distinctive and nonmonochrome coloring; and velvety velour-like textured exterior.” It asserts that these similarities seek to “trick consumers” and has harmed the Squishmallows brand by “divert[ing] sales and profits from Kelly Toys to Build-A-Bear.” Kelly Toys is seeking unspecified damages and an injunction to stop the sale of Skoosherz. In Kelly Toys’ view, Build-A-Bear is intentionally copying the distinct physical characteristics and exterior appearance of Squishmallows to capitalize on Squishmallows’ international success.

Build-A-Bear has responded by filing its own complaint in the Eastern District of Missouri asserting that its Skoosherz line is merely an extension of its already existing line of animal toys. In Build-A-Bear’s view, Skoosherz merely imitates the popular plushies that Build-a-Bear has previously sold. For instance, Build-A-Bear claims that the Skoosherz Pink Axåolotl is merely an imitation of its original Pink Axolotl toy. The company is seeking a declaratory judgment stating that Skoosherz do not infringe on the Squishmallow trade dress and furthermore, that the Squishmallow trade dress is not even protectable under the Lanham Act. Build-A-Bear asserts that the Squishmallow trade dress lacks a consistent look and feel and shares characteristics with toys already present in the market. According to its complaint, “[i]f each aspect of the claimed trade dress were in fact protected trade dress, it would be virtually impossible for competitors to create alternative designs.”

Bearing a Squishy Future

Trade dress is a critical element of trademark law and serves to safeguard the goodwill of creators, the protection of consumers, and a competitive market. Although this dispute resides in the market of soft toys, it highlights a new perspective of trade dress law and application. If a jury trial is granted, Kelly Toys will likely rely on side-by-side comparisons to highlight the visual similarities between Squishmallows and Skoosherz as well as present consumer comments that have been made on Build-a-Bear’s social media account dubbing Skoosherz as “knockoff Squishmallows.” Although such evidence can support Kelly Toys’ infringement claims, it will still have the initial burden of proving that its trade dress is protectable.