Author: Jess Trost
Introduction
Major social media platforms like Instagram and TikTok have introduced “Teen Account” systems that impose heightened privacy defaults, restrict messaging, and limit algorithmic recommendations for minors. These rollouts have arrived as courts confront a growing wave of lawsuits seeking to bypass traditional immunity under Section 230 of the Communications Decency Act (CDA). This wave of litigation has gained momentum with the Third Circuit’s decision in Anderson v. TikTok, where the court held that algorithmic recommendations constitute a platform’s own “first-party speech,” opening a potential pathway around Section 230’s traditional shield. In March 2026, a Los Angeles jury found Meta and Google liable for negligent design of Instagram and YouTube, concluding that platform features were a substantial factor in user harm independent of third-party content.
This blog post argues that Teen Account features do not establish platform liability but instead provide concrete evidence that social media platforms are configurable systems capable of implementing safer designs without eliminating core functionality. Under a design-defect theory, courts routinely consider whether a safer, feasible alternative design was available, as that inquiry bears directly on whether the product could have been made less harmful without sacrificing its core functionality. By already applying these restrictions to users under 18, platforms such as Instagram demonstrate that safer configurations are not merely technically and operationally viable, but also serve as concrete evidence of a feasible alternative design.
Why Teen Accounts Have Appeared Now
Teen Accounts emerged in response to sustained social, political, and legal pressure on the technology industry beginning around 2019. Internal company materials indicate that platforms were aware of potential harms well before implementing design changes. For example, a 2019 Meta study identified a subset of users engaged in “problematic” usage—a designation that applied to approximately 12.5% of users—and concluded that existing research suggested negative effects on well-being.
Internal testing further revealed that recommendation systems could actively connect minors with potentially dangerous adult users. In one internal experiment, Instagram found that accounts engaging in what it termed “groomer-esque behavior” were recommended minors at significantly higher rates than typical users, and that a substantial portion of those recommendations led to attempted contact. Despite these findings, the company did not immediately implement stronger protections for younger users. Internal communications unsealed in recent multidistrict litigation further illustrate this delay. In one 2020 exchange, Instagram engineers acknowledged the platform’s addictive design, likening it to a drug and referring to themselves as “pushers.”
The tipping point for public and political outrage occurred in October 2021, when whistleblower Frances Haugen leaked hundreds of pages of internal documents. Her disclosures showed that Meta knew its platforms negatively impacted teen mental health, but repeatedly subordinated safety interventions to user-growth and retention metrics. This moment triggered widespread political backlash, including congressional hearings and increased legislative attention to youth online safety.
As pressure intensified and litigation exposure grew, platform design choices became legally significant. By 2025, thousands of claims brought by states, school districts, and private plaintiffs had been consolidated into multidistrict litigation alleging that engagement-driven features caused youth harm.
Although platforms introduced incremental safety adjustments following the 2021 disclosures, the more comprehensive Teen Account configurations were implemented and heavily promoted only as litigation intensified. This timing suggests that these features function not only as product changes, but also as strategic evidence, showing that safer configurations were feasible and already within the platforms’ control. In ongoing litigation, platforms have cited these features to argue that they take youth safety seriously, while plaintiffs have characterized the same rollouts as reactive measures that came only after years of internal awareness and external pressure.
Section 230 as the Traditional Barrier: The Shift from Content to Design
Section 230 of the CDA has long served as the central doctrinal hurdle to holding online platforms liable for user injuries. At the heart of that protection is § 230(c)(1), which provides that no provider of an interactive computer service shall be treated as the publisher or speaker of information provided by a third party. In practice, that framework has shielded platforms from traditional publisher liability for the vast volume of user-generated content they host. Courts routinely dismissed early claims seeking to hold platforms liable for recommending or failing to remove harmful posts, categorizing such actions as impermissible attempts to circumvent publisher immunity.
Given the limits of § 230, plaintiffs in recent youth-harm litigation have increasingly targeted platform design instead of content. Features such as algorithmic feeds, infinite scroll, autoplay, and push notifications are not merely neutral tools for displaying speech; plaintiffs increasingly characterize them as design choices that structure user behavior and prolong minors’ exposure to harmful content. By treating social media applications as defectively designed products rather than passive venues for expression, plaintiffs seek to advance claims rooted in negligence and product liability.
Products Liability and Configurability
Once social media platforms are analyzed as products rather than publishers, the governing legal framework shifts. Courts typically apply either the consumer expectations test or the risk-utility test, often referred to as the alternative design test. The more analytically demanding framework is the alternative design test, which requires plaintiffs to demonstrate that a safer, feasible design existed that would have reduced the harm without undermining the product’s core function. Historically, the alternative design requirement has been difficult to satisfy because platforms guard their algorithms as proprietary trade secrets, treating them as “black boxes.” However, unsealed documents reveal that platform developers actively modeled these alternative designs internally. For example, Meta executives rejected a proposal to make teen accounts private by default after internal analyses projected it would cause a 1.9% decrease in total time spent by adolescents over a five-year window. Teen Accounts directly respond to this evidentiary challenge, providing a rare instance in which the defendant has implemented a materially different configuration of the same product.
Teen Accounts as Evidence of Configurability
The emergence of Teen Accounts directly alters this evidentiary landscape. Social media platforms have now deployed youth-specific configurations that impose heightened privacy defaults, restrict messaging, and limit algorithmic amplification. These features are not hypothetical proposals; they are operational systems implemented at scale. Under the alternative design framework, plaintiffs are no longer required to rely solely on speculative expert testimony. Instead, they can point to the platforms’ own implemented designs as concrete evidence that safer configurations were both technologically and practically achievable.
Evidence of configurability allows plaintiffs to argue not only that a safer alternative design was feasible, but that the platform actively selected a less restrictive configuration for general users despite possessing the capability to implement greater safeguards. This inference is reinforced by internal research showing that platforms possessed extensive, granular data detailing how their algorithmic designs influenced user behavior and exposure patterns.
The Weaponization of Configurability
The configurability of these platforms is not merely theoretical; it is reflected in how platforms adjust content delivery. Independent algorithmic audits demonstrate that platforms already possess actionable knowledge of a user’s age and mental vulnerability. One study revealed that YouTube, Instagram, and TikTok algorithms could rapidly detect when an account behaved like a “struggling” adolescent, subsequently amplifying their exposure to distressing and problematic content. This suggests that platforms have the exact technological capacity to identify and protect vulnerable youth but actively configure their algorithms to prioritize engagement over protective interventions. Trial testimony and unsealed documents explicitly confirm this economic tradeoff.
Why Demonstrated Capability Does Not Resolve Liability
Although these settings demonstrate configurability, this technological capability alone is insufficient to establish liability. In ongoing social media litigation, connecting a particular design choice to a particular adolescent’s psychological injury remains a difficult evidentiary task. Because mental health outcomes are inherently multi-causal, defendants routinely highlight confounding variables—such as offline stressors, family dynamics, and preexisting vulnerabilities—to contest allegations of proximate causation, underscoring that even a feasible alternative design may not fully account for the alleged harm.
Even if plaintiffs succeed in moving their claims into a product-design framework, substantial constitutional defenses remain. To bypass Section 230, plaintiffs rely on recent precedent like the Third Circuit’s decision in Anderson v. TikTok, which held that a platform’s algorithmic recommendations constitute its own “first-party speech.” However, in classifying algorithms as first-party speech to defeat Section 230, courts inadvertently arm platforms with a formidable First Amendment defense. Platforms increasingly argue that altering their algorithms to restrict content curation infringes upon their constitutionally protected editorial discretion. Accordingly, while feasibility and configurability reshape the product liability inquiry, they do not displace the broader constitutional constraints that continue to govern platform liability.
Implications for Future Litigation
Teen Accounts do not determine liability, but they change how cases are argued. Historically, plaintiffs seeking to prove a feasible alternative design often had to rely on theoretical models of what a less harmful platform might look like. By operationalizing heightened privacy defaults and algorithmic restrictions, the platforms have supplied plaintiffs with a concrete evidentiary baseline. Future litigation may therefore focus less on abstract debates over technological possibilities and more on comparisons between a platform’s earlier configuration and the safeguards it later adopted.
In ongoing multidistrict litigation, for example, discovery has already unearthed internal communications demonstrating that platform executives explicitly suppressed safety interventions that threatened user retention metrics, signaling how aggressively plaintiffs will pursue internal testing data in future actions. As more design-based claims survive early dismissal, the prospect of deeper factual development may also affect settlement incentives. This pressure is already materializing in practice; facing the imminent prospect of a Los Angeles jury trial, both TikTok and Snapchat opted to execute confidential settlements rather than defend their algorithmic architectures in open court.
Conclusion
Teen Accounts do not resolve the hardest questions in social media tort litigation. They do not independently establish duty, causation, defect, or constitutional permissibility. Instead, by proving that major platforms can build materially different environments for minors, they narrow the gap between hypothetical safety proposals and implemented software architecture. This shift reframes how courts evaluate platform responsibility. As design-defect litigation matures, the central inquiry shifts from whether safeguards are possible to why platforms chose not to implement them.
Introduction
Financial Technology (FinTech) has increasingly made finance and banking accessible for millions of people globally. While FinTech has largely had positive effects, it has also drawn criticism. Examples of this include, but are not limited to, financial surveillance and controversial financial products, such as cryptocurrencies, non-fungible tokens, and buy-now-pay-later.
Another controversial byproduct of FinTech is the proliferation of prediction markets, which has raised numerous legal questions. Prediction markets are platforms that allow users to speculate on the outcome of real-world events. Some of the current major legal issues surrounding the prediction markets are (i) whether states or the federal government have authority over “event contracts”, (ii) market manipulation and insider trading, (iii) what constitutes a gaming event, (iv) liability for third-party services, and (v) consumer protection questions. This blog post will summarize the current status of the first three points.
The lack of clear and defined terms in the prediction market presents an opportunity for legislation to protect consumers and regulate the industry. By becoming well-versed in the intricacies of these legal questions, attorneys and law firms can offer additional value to clients.
What Is a Prediction Market?
The prediction market is a part of the broader scheme of FinTech, also known as Financial Technology, which refers to the use of technology and innovation to provide financial products and services. FinTech has historically been praised for its democratization of financial services and increased access to the finance industry. FinTech provides infrastructure, data analytics, and leverages regulatory matrices that enable the adoption of prediction markets into the mainstream and allow them to function like traditional derivative exchange platforms. Derivatives are financial contracts whose values are derived from the performance of underlying market factors, such as interest rates, currency exchange rates, etc. Prediction markets are platforms that allow users to speculate on the outcome of real-world events across popular culture, weather, sports, economics, politics, and other areas of interest. They function similarly to futures markets for commodities or other financial assets. Some familiar prediction markets are Kalshi, Polymarket, Robinhood, and sportsbooks, such as FanDuel and DraftKings.
According to Forbes, the total volume for the prediction market reached $44 billion in 2025. Sports dominate prediction markets by volume driving flow, meaning it accounts for short-term and high frequency transactions; while politics and economics gain capital commitment, where people hold positions for longer periods of time. Although prediction markets often include sports-related event contracts, they are not subject to the same rules as sportsbooks and, therefore, avoid state regulation and taxes. Prediction markets differentiate themselves from bookmakers and sportsbooks because they only monetize transaction fees, rather than charging a vigorish or betting against the user.
The aforementioned regulatory loopholes have increased scrutiny and visibility on these financial instruments.
The Law on the Issues
State vs. Federal Authority
As it presently stands, the Commodity Futures Trade Commission (CFTC) has authority over event contracts under the Commodity Exchange Act (CEA). An event contract is a derivative contract whose payoff is based on a specified event, occurrence, or value. As of February 2026, the CFTC’s authority has been challenged by more than 36 states, citing public policy reasons. States posit that event contracts are not derivatives, but gambling and therefore should be state-regulated. The CFTC is diametrically opposed to patchwork legislation by the states because, in their opinion, event contracts are derivatives and are already regulated at the federal level. On April 6, 2026, the U.S. Court of Appeals for the Third Circuit affirmed enjoinment against the New Jersey Division of Gaming Enforcement from enforcing a state law against Kalshi’s sports-related event contracts, strengthening the CFTC’s claim that the CEA preempts state law.
There are roughly 20 federal lawsuits where Kalshi is a party. Approximately eight of the lawsuits are from state gambling commissions and Indian tribes accusing the prediction market of operating as an unlicensed sports gambling platform; six of the suits are offensive, where Kalshi is the plaintiff; and the remaining complaints were filed by individuals who argue Kalshi is an illegal service that is worsening gambling addiction. Maryland, Ohio, Nevada, and Massachusetts have proven successful against Kalshi as of early April 2026. Further, the CFTC has sued Arizona, Connecticut and Illinois, seeking to block what it insinuates are unlawful state efforts to regulate the prediction markets.
Market Manipulation and Insider Trading
Market manipulation and insider trading may pose a threat to the prediction markets. Event contracts are not securities in the traditional sense, and therefore are not subject to the anti-fraud provisions of the Securities Exchange Act of 1934, which prohibits trading based on material, non-public information. However, the CFTC has its own anti-manipulation and anti-fraud provisions promulgated under CEA Section 6(c).
In 2025, a Republican gubernatorial candidate for California posted a video of him placing a bet on Kalshi on his own candidacy. Kalshi’s compliance department flagged the transaction, and the candidate acknowledged that he knew the trade was improper and violated the platform’s rules. Kalshi imposed a financial penalty and a five-year suspension. The violation stemmed from his influence over the outcome and his possession of confidential information that enabled him to act in breach of a pre-existing duty of trust and confidence.
Wash selling is another concern. A wash sale occurs when a security is sold at a loss and followed by a repurchase of the same or substantially identical security within 30 days. In prediction markets, wash selling resembles executing trades to falsify volume or manipulate prices, which violates the CFTC’s exchange rules. Wash sales are particularly relevant to tax attorneys because wash selling has important tax implications. However, losses from sales or trades of commodity futures contracts do not apply. This is another example that emphasizes the importance of guidance that clarifies the classification of these financial instruments to more accurately assess the implications of trades and sales.
What Constitutes a Gaming Event
Event contracts are generally types of derivatives that are structured as binary options based on the outcome of events. The existing rules on event contracts are outlined in § 5 of the CEA and CFTC Rule 40.11. These rules explicitly prohibit event contracts that involve enumerated activities, such as terrorism, assassination, war, gaming, and any activity that is unlawful under State or Federal Law (TAWGA). However, gaming is not defined, which is an area of contention as it concerns sports on prediction market platforms. Many states have taken the position that if it looks like sports betting or gambling, then it should not be considered an event contract. The CFTC has proposed to define “gaming” in the new § 40.11(b)(1), and the definition would be consistent with its interpretation of the term in the Nadex Order and the Kalshi Order.
Whether contracts on weather, sports, or politics should be considered event contracts is a topic of considerable debate. The American Gaming Association posed the question pertaining to sports, and the results revealed that four out of five Americans believe that sports-related contracts on prediction markets should be subjected to gambling regulations. In terms of weather and other random topics, the argument is that it serves no public good and that the lack of regulation is contributing to the rise in gambling addiction.
What’s a Safe Bet on Prediction Markets?
The lack of clear and precise oversight and regulatory procedures surrounding prediction markets has resulted in legal pandemonium. Several politicians are proposing legislation to provide guardrails on prediction markets. This includes the “Public Integrity in Financial Prediction Markets Act of 2026,” “Prediction Markets Are Gambling Act,” and the “Event Contract Enforcement Act.” Forbes suggests that some implications of prediction markets on FinTech are: (a) the narrowing of regulatory arbitrage; (b) the value of data and analytics; and (c) the vitality of governance and oversight. The regulatory arbitrage is the biggest source of contention.
The “Public Integrity in Financial Prediction Markets Act of 2026” is a federal bill introduced to prohibit government officials and employees from engaging in “insider trading” on prediction markets. Representatives Blake Moore (R-UT) and Salud Carbajal (D-CA) introduced bipartisan legislation, “The Event Contract Enforcement Act”, to ensure event contracts can continue to serve legitimate business interests while protecting Americans from the safety and national security risks of dangerous or otherwise problematic event contracts. The purpose of the act is to require the CFTC to prohibit event contracts involving TAWGA, echoing the prohibited enumerated activities outlined in Rule 40.11. Another goal is to allow states to opt out of the gaming contract prohibition, which is at the center of the gambling controversy and federal lawsuits. Senators John Curtis (R-UT) and Adam Schiff (D-CA) introduced the “Prediction Markets Are Gambling Act” to prohibit CFTC-registered entities from listing any contract that resembles a sports bet or casino-style game. The bill aims to remove any ambiguity in the CEA that warrants sports betting as an event contract to more closely align with what the senators believe was Congress’ intent.
The future of prediction markets may be in dire straits. There is bipartisan support for stricter oversight of prediction markets. Kalshi is currently facing a class action suit for failure to pay out $54 million in relation to the death of Ayatollah Ali Khamenei, a TAWGA class activity that should have been prohibited. The growth of prediction markets has been fueled by regulatory arbitrage, raising several legal questions. These questions have garnered attention not only from average citizens, but from the executive branch and legislators. Becoming an expert in the issues surrounding prediction markets allows law firms and business entities to remain compliant and presents opportunities for business development.
Introduction
In the United States, courts have commonly rejected arguments to protect an artist’s “style” under copyright law. This treatment stems from the idea-expression distinction, which provides copyright protection for fixed expressions, but not abstract ideas. The copyright law regime treats style as an unprotectable idea. This means that multiple people may paint a tree with leaves, but the size, color, and shape of the tree in a particular painting is a distinctive expression that is protected. The emergence of generative artificial intelligence (AI) raises new questions and avenues to explore the limits of copyright law as it stands. The ability of AI models to produce new images “in the style of” specific artists increases the potential scope and magnitude of harm to said artists through the exploitation of their creativity, skill, and time.
The use of AI in artistic and creative contexts is impactful because it calls into question the foundational reasoning underlying the idea-expression distinction. Mark Lemley, a leading intellectual property scholar, theorizes that “increasingly, the things humans contribute in a collaboration with generative AI will be ideas and high-level concepts” and “AI will contribute the expression.” In other words, the ability of AI to take creative ideas prompted by individuals and express them in something tangible flips the idea-expression distinction on its head, disrupting the entire copyright law regime. This theory emphasizes the transformative potential of AI to challenge current law and demonstrates how drastic challenges to copyright law can open the door for reconsiderations of the protectability of an artist’s style.
While it has always been possible for individuals to copy the style of another artist’s work, the capacity for harm to artists increases exponentially due to the capabilities of AI. It is now as simple as typing a short prompt into an AI model to create an image that can be commercially marketed. Even without naming the original artist, individuals in the market may recognize their style. This scenario creates potential economic harm if the demand for original works by the artist whose style is being appropriated declines because similar works are widely available on the market. There are additional reputational implications if the subjects being depicted do not align with the artist’s individual values. Even if the artist disapproves of the image, the market will nonetheless associate the image with the artist. The artist’s lack of control over AI-created works reduces the incentive for innovation and new creation, hindering the constitutional goal of copyright to promote original works.
This blog post focuses on style in the context of visual art and takes two approaches to frame how style can be incorporated into protectable expression. First, it analogizes artistic style to the protection of architectural works in 17 U.S.C. § 102(8). Second, it outlines a theory-based route through the right of publicity that can serve as the foundation for protecting style.
Architectural Works Analogy
The adoption of architectural works as a category of copyrightable subject matter by Congress offers an interesting analogy to evaluate and understand how elements of an artist’s style are and are not protected under current copyright law. The United States Code defines an “architectural work” as a tangible design that “includes the overall form as well as the arrangement and composition of spaces and elements in the design, but does not include individual standard features.” In other words, designers may retain a copyright in the original combination of elements that give a building a distinctive character, but may not receive protection for broader features of a building. Significantly, Congress prevents protection of architectural style categories, such as art deco, midcentury modern, or neoclassical. This means that while design features such as arches and columns are not protectable, the unique combination of such features in an original manner can produce a protectable architectural work. The statute makes clear that Congress elected to specifically protect the overall form and arrangement of an architectural design, even if broader and standard features are used.
The statute’s treatment of architectural works can be expanded and applied to other artistic works if an artist’s style is viewed as a form of expressive arrangement of techniques and aesthetic decisions. For example, while Vincent Van Gogh could not have claimed protection over post-impressionism, swirled brushstrokes, or vibrant color palettes, the combination and arrangement of these elements can be analogized to an architect’s expression of standard features. Under this view, style may be seen less as an abstract idea and more as a fixed expression made up of defined features.
With this more defined approach to viewing unique artists and their style, it is clear why generative AI poses a risk. As the AI is learning how to replicate an artist’s style, it identifies the unique combination and arrangement of elements and creates the equivalent of an artistic profile. When generating a new image “in the style of” an artist, AI has the explicit goal of making the image in the artist’s recognizable style, utilizing the combination of elements in the works it was trained on. This means that AI is creating new works based on the expressive arrangement and combination of elements that makes an artist’s style distinct, which would be protectable if the image was an architectural work. This analogous relationship and the strong theoretical argument for protecting artistic style in the context of generative AI provides one logical route toward advocating for the protection of style.
Right of Publicity Perspective
The right of publicity is a state-level right intended to prevent “unauthorized uses of a person’s identity.” The theory underlying this right offers a foundation for recognizing artistic style as part of an individual’s identity. The ability of an AI model to associate a specific style with a specific artist to create new images indicates a merging of the two concepts, with style becoming a proxy for artistic identity. It is often an individual’s unique artistic identity that the market values. If style is viewed as part of an artist’s identity, the right of publicity provides a strong mechanism for protecting it. The rationale underlying the right of publicity is “preserving the commercial value of their identity” and “protecting the autonomy of their personality.” These underlying rationales align closely with the specific harms that generative AI can have on artists through unauthorized appropriation of their styles, namely economic and reputational harms.
California legislature and courts lead in granting publicity protections and provide the strongest outline for a federally regulated and protected right of publicity. Not only does the California Civil Code § 3344 provide legislative protections for the “name, voice, signature, photograph, or likeness” of an individual, but state common law also provides broader protections. The scope of the right of publicity doctrine is further articulated through case law, which protects elements of identity and can serve as the blueprint for protecting style as an element of identity. In Midler v. Ford Motor Co., the Ninth Circuit held that the imitation of actress and comedian Bette Midler’s voice constituted misappropriation even though neither her name nor her image was associated with the advertisement. The Court stated that “[t]o impersonate her voice is to pirate her identity.” The scope of this statute was expanded in White v. Samsung Electronics, where the Ninth Circuit held that a robot dressed to resemble Vanna White and positioned to turn letters as is done on the Wheel of Fortune game show infringed on her right of publicity. The court noted that the right of publicity protects more than “a laundry list of specific means of appropriating identity” and “name and likeness” do not need to be used to infringe the right of publicity. Symbolic references emulating the attire and behavior of an individual are enough to violate one’s identity. These cases illustrate how a broad and nonliteral conception of identity is recognized under the right of publicity.
This expansive approach by the Ninth Circuit implicates the incorporation of artistic style, which is simply the combination and arrangement of elements that the public associates with an artist, as part of that artist’s identity. The Ninth Circuit has demonstrated a willingness to grant protection under a broad conception of likeness; an artist’s stylistic signature, like Midler’s vocal tone and White’s television persona, could constitute an element of identity protectable under the right of publicity. This argument is particularly powerful in the context of generative AI, which extracts patterns from an artist’s work and produces a new image intended to be closely associated with that artist, even if the artist’s name is not used. The assumption underlying the right of publicity is that the individuals whose identities are being appropriated are commercially valuable. Similarly, artists that are appropriated for their artistic style are likely to have value. Thus, the exploitation of an artist’s recognizable and imitable style resembles the type of appropriation that the Ninth Circuit sought to prevent. Given the relevant precedent of the California legislature and Ninth Circuit, the right of publicity provides a foundation for protecting an artist’s style.
Conclusion
The traditional arguments for not protecting an artist’s style are being challenged due to the monumental impact that generative AI has on artists. If the idea-expression distinction, a core foundation of copyright law, does not function as intended due to widespread growth of expression but lack of ideas, the copyright regime should reevaluate whether style is protectable. The two foundations outlined in this paper, architectural works and right to publicity, provide starting points for policymakers and legislators to consider in evaluating the protectability of style.
Introduction
Patent law was created to incentivize innovation by granting inventors limited monopolies in exchange for public disclosure of their discoveries. In theory, this should promote competition and technological progress. In practice, however, patent law has paradoxically become a barrier to creativity in the video game industry.
In recent years, there has been a trend of game publishers, including major names like Nintendo, increasingly seeking patents on gameplay mechanics and systems. For example, Nintendo has filed 31 patents alone for the game The Legend of Zelda: Tears of the Kingdom and has received criticism from fans and experts alike regarding the validity of their patents. These developments highlight a longstanding tension within patent law. While some critics argue for protection for software innovations, others say that patents on video game mechanics are often overly broad. This article argues that overly broad video game mechanic patents undermine patent law’s core purposes by chilling creative development and disproportionately burdening smaller studios. Patent law should not prevent other developers from building upon design ideas; instead, it should bolster competition by protecting only concrete, novel implementations that meaningfully advance video game technologies.
History of Video Games & Patent Law
To understand how this problem emerged, it is crucial to examine how a system designed to promote innovation through protection has, over time, come to restrict creative expression in video games.
At first, the video game industry was “indifferent to potential patent rights.” Inventor and game developer Ralph Baer filed the first patent for a tennis-like video game in 1968. His creation led to the Magnavox Odyssey, the first home video console and subsequent blueprint for the industry. Baer’s ingenuity inspired other companies including Atari, whose arcade game Pong (and later home consoles) achieved the commercial success that Magnavox struggled to obtain. As other companies rushed to emulate Atari’s success, Magnavox filed suits claiming these game companies were infringing on Baer’s patents. Through the 1970s, patents remained less central than copyrights as the distinction between hardware and software developed. Still, this marked the beginning of a legal shift that foreshadowed the modern trend of using patents to protect not only tangible inventions, but also abstract gameplay ideas.
Section 101, Abstract Ideas and Game Mechanic Patentability
35 U.S.C. § 101 governs patentability, allowing patents to be granted to “whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter.” While straightforward theoretically, its interpretation has been far from simple. There has been a struggle to draw a distinct line between an unpatentable, abstract idea and a patentable implementation in software; video game technology amplifies this ambiguity because of its complexities.
Following the Supreme Court’s decision in Diamond v. Diehr—which upheld a patent for a rubber-curing process that used a computer algorithm to calculate optimal cure times—courts began interpreting 35 U.S.C. § 101 more liberally, allowing patents for software and abstract algorithms. Scholars have pointed out that lower courts have misapplied Diehr by granting protections to abstract processes that patent law was never meant to cover. In Bilski v. Kappos, the Supreme Court confirmed that abstract ideas cannot become patent-eligible simply by being implemented on a computer.
Alice Corp v. CLS Bank attempted to clarify how to interpret § 101 by requiring a two-step analysis of patent infringement claims: (1) is the claim directed to an abstract idea, and if so, (2) is there an “inventive concept” that transforms the idea into a patentable application? The second step of Alice has been inconsistently applied, which has led to unpredictable outcomes such as the issuing of broad patents.
For example, in DDR Holdings, the court upheld an e-commerce software patent because “the claimed solution is necessarily rooted in computer technology to overcome a problem specifically arising in the realm of computer networks.” Within the gaming sector, this poses a very tangible threat. The varied application of the abstract-idea doctrine has led to the proliferation of overly broad video game mechanic patents. This causes legal uncertainty for developers and inventors, creating a chilling effect on innovation, as the court’s stance remains unclear.
Drafting Around the Abstract Idea Doctrine
The “rules of a game” are generally not patentable, falling under the abstract idea exception to 35 U.S.C. § 101. This exception can serve as a hurdle to patenting certain kinds of games. To overcome this obstacle, applicants draft game mechanic patents using highly specific, technical language that outlines the software implementation rather than the underlying rules. Although this filing method often satisfies the formal requirements of the Patent Act, it enables patent holders to claim broad ownership over fundamental gameplay interactions that could be implemented in innumerable ways. This drafting strategy is especially visible in recent filings by major publishers, such as Nintendo’s patent filings for The Legend of Zelda: Tears of the Kingdom.
The Legend of Zelda’s patents describe the meticulous calculations for object interactions, user interface elements such as the loading screen, and particular character abilities, yet expand to cover the broader concept of combining objects in virtual environments to solve puzzles. This is the type of mechanic other developers might independently create using entirely different lines of code and visual designs. By cloaking abstract gaming ideas in technical specifications, these patents effectively form a conceptual wall around common game design methods and patterns.
As a result, indie developers are placed in a precarious position. Small studios often lack the resources to conduct comprehensive searches of prior art before they develop games; even if they identify potentially conflicting patents, they may not have the means to design around them. The threat of litigation from major publishers may force indie developers to abandon promising projects or avoid entire genres, regardless of whether the implementation would differ, as video game “development is a capital-intensive endeavor” that “requir[es] substantial financial resources.”
Inter Partes Review: A Potential Solution
The America Invents Act provides a mechanism to challenge questionable patents. Inter Partes Review (IPR) allows third parties to petition the Patent Trial and Appeal Board to reexamine a patent’s validity based on prior art at a fraction of the potential litigation costs. IPR also has a lower burden of proof because there is no presumption of patent validity. IPR provides a comparatively accessible forum for challengers and serves as a crucial tool for invalidating broad patents that were potentially granted erroneously.
However, IPR has limitations. The process requires significant legal expertise and can cost, on average, $300,000—more affordable than a multi-million-dollar trial, but beyond reach for many indie studios. Additionally, with IPR, patents can only be challenged on specific grounds, not on the abstract idea doctrine that often applies to game mechanics. Further, “IPR practitioners will no longer be able to use general knowledge to bridge evidentiary gaps and instead rely on the four corners of prior art or printed publications,” which can provide an evidentiary advantage for patent owners. Despite these constraints, Inter Partes Review, even if unsuccessful, can serve as a procedural leveling mechanism by introducing administrative scrutiny and litigation risk even where substantive invalidation is unlikely.
Game Mechanics as Legal Property
Patent law’s reach has expanded far beyond hardware and physical devices as games have become increasingly software-based, encouraging developers to protect algorithms, interfaces, and in-game systems that shape player experiences. However, scholars have noted that software patents often fail to provide clear notice to potential innovators, as their scope can be difficult to identify and interpret before litigation.
A controversial example of this trend is Warner Bros. Interactive Entertainment’s patent on the ‘Nemesis System’ from the game Middle-earth: Shadow of Mordor, which grants them exclusive rights over dynamic enemies that are “promoted to a bigger threat” upon defeating players. This system was meant to tailor player experience by crafting miniature bosses that were “tailored to…specific playthrough[s]” that remember the character and can develop a vendetta against them. Many of these patents are considered overly broad because they fail to meaningfully limit claims to specific technological processes and instead seek protection over high-level gameplay concepts and functional outcomes. By monopolizing such mechanics, these companies have sparked widespread concern among fans and experts.
The threat of potential litigation, rather than actual enforcement, can discourage developers from engaging in iterative, experimental design, effectively serving as a barrier to entry. A small studio developing a memory-based enemy system, for instance, might scrap the feature entirely rather than risk resembling Warner Bros.’ patent. As a result, patent law risks promoting the very stagnation it was meant to prevent.
Conclusion
From law journals to consumer outcry, the backlash against overly broad video game patents has become impossible to ignore. As courts continue to grapple with the boundaries of patentable subject matter under § 101, the video game industry illustrates what happens when patent protection extends too far. When abstract gameplay concepts are treated as proprietary rights, innovation suffers. If patent law is meant to promote progress, it must allow developers to build upon and refine existing concepts without sacrificing creative freedom. Meaningful reform requires limiting patents to specific technical solutions while keeping core gameplay concepts in the public domain—available for all developers to iterate upon and improve.
Over the past decade, schools across the United States have increasingly turned to digital surveillance technologies to monitor students’ online behavior in the name of safety. Among these technologies, Gaggle has emerged as one of the most widely adopted platforms, serving more than 5.8 million students at over 1,500 school districts across the United States. Gaggle’s tasks performed include scanning millions of students’ emails, documents, chats, and images for signs of self-harm, violence, or bullying. Supporters claim that Gaggle helps schools prevent tragedies and identify students in crisis, while critics warn that Gaggle’s constant monitoring compromises student privacy and autonomy and is a risk to equality for all students. This blog post examines Gaggle’s role in K–12 education by analyzing how Gaggle operates, assessing its effectiveness, weighing its benefits against its harms, and considering the adequacy of existing legal protections. Although the platform is promoted as a tool for students’ well-being, its pervasive monitoring raises serious ethical and constitutional concerns that outweigh its purported benefits.
Gaggle integrates with Google Workspace and Microsoft 365 to scan student emails, documents, and images associated with school accounts for language indicating self-harm, usage or possession of drugs, or risks of violence. Because schools can grant Gaggle access to student accounts, surveillance extends beyond school hours and onto students’ personal devices whenever and wherever they log in. Even social media notifications tied to school emails can be monitored. To identify potentially harmful material, Gaggle employs an in-house, AI-powered filtering system that compares scanned content against a proprietary “blocked-word list” containing profanity and references to self-harm, violence, bullying, or drugs. Content flagged by Gaggle’s AI system is reviewed by human moderators, who may escalate “incidents” to administrators or, in severe cases, to law enforcement. Gaggle divides flagged content into three tiers: “violations,” “questionable content,” and “possible student situations.” The last category involves imminent threats such as suicide or possible violence and triggers immediate contact with school officials. While the company claims to have helped save thousands of lives, its data are self-reported and unverifiable. Critics highlight the lack of independent evaluation and the questionable reliability of low-paid contract reviewers expected to process hundreds of incidents per hour. Despite these concerns, many educators view Gaggle as a useful tool for early intervention. However, existing evidence does not conclusively show that Gaggle reduces suicide, self-harm, or violence, suggesting that its promise may rest more on perception than on measurable results.
Proponents argue that Gaggle responds to a growing mental health crisis amongst youths. Rising rates of depression and anxiety—especially among LGBTQ+ and transgender students—make it difficult for schools to identify struggling students. Supporters claim that Gaggle helps detect warning signs, allowing earlier counseling or intervention. They also cite the platform’s ability to address cyberbullying and fulfill legal mandates under state anti-bullying laws. Additionally, given the growing fear of school shootings, administrators see Gaggle as a supplement to limited counseling resources, capable of flagging threats before violence occurs. From this perspective, Gaggle provides schools with a sense of control and readiness, offering reassurance that no cry for help will go unnoticed. Yet, this reassurance often obscures the dark side to Gaggle’s constant surveillance: the erosion of students’ fundamental right to privacy and their ability to learn freely and to express themselves without constant scrutiny.
Continuous surveillance discourages students from expressing themselves freely. Developmental psychologists emphasize that adolescence is a key period for cultivating creativity, independence, and critical thought. When students know they are constantly monitored, they self-censor and conform. This undermines what privacy scholars call “intellectual privacy”—the ability to think and communicate without fear of observation. Research shows that over half of monitored students refrain from sharing their true thoughts online, confirming that Gaggle’s presence suppresses open exploration. In effect, the system teaches young people that safety and obedience take precedence over curiosity and trust. Such lessons, internalized at a formative stage, may have lasting consequences for democratic participation and creative confidence.
Gaggle’s algorithmic bias and access patterns also disproportionately harm disadvantaged students. AI systems often reflect racial and linguistic bias, flagging language used by students of color or LGBTQ+ youth as “offensive.” Low-income students, who rely on school-issued devices, are more heavily surveilled because, for financial reasons, they cannot separate school and personal accounts. Gaggle accesses information through students’ school accounts—regardless of whether they log in from personal or school-provided devices—and can also capture notifications from social media when those accounts are used for registration. Without access to private electronic devices, these students have little choice but to rely on school accounts for all purposes, making it difficult to maintain privacy or segregate personal activity from school monitoring. Moreover, Gaggle has blocked LGBTQ+ websites and flagged terms like “gay” or “queer,” deterring students from seeking support. In some cases, its monitoring has even exposed students’ sexual orientation without consent, placing them at risk of harm at home. These harms compound preexisting inequities in education, as marginalized students already face higher rates of disciplinary action. When surveillance is piled on top of these disparities, it amplifies rather than alleviates injustice. The result is a system that treats vulnerability as suspicious and equates being different to being dangerous.
By extending monitoring to all hours and authorizing contact with law enforcement, Gaggle risks feeding into the school-to-prison pipeline. The “school-to-prison pipeline” describes the phenomenon in which heightened discipline, surveillance, and law enforcement involvement in schools push students, especially the most at-risk ones, out of educational environments and into the juvenile or criminal justice systems. Although the company claims its system is not disciplinary, its reports can reach police if administrators are unavailable. This increases criminalization, especially for minority students already subject to harsher discipline. In the post-Dobbs era, where abortion and gender-affirming care are criminalized in some states, Gaggle’s stored data could be used against students seeking medical information, raising severe privacy concerns. Students and parents rarely receive meaningful notice or the ability to opt out of the surveillance. Unlike some competitors, Gaggle operates in the background without visible indicators. While the company recommends schools notify families, many do not, leaving parents unaware that surveillance occurs. Additionally, opting out effectively bars students from using essential educational technology, mandating surveillance by default. This lack of transparency undermines informed consent and contradicts principles of digital autonomy. As a result, millions of students are subjected to 24/7 surveillance without ever being asked for permission, creating a generation of learners for whom privacy is not a right but a privilege.
Existing federal laws inadequately address the scope of student surveillance. The Children’s Internet Protection Act (CIPA) requires schools receiving federal funds to monitor minors’ online activity and block obscene content. However, it was intended to restrict access to harmful material—not to justify constant behavioral surveillance. Gaggle’s around-the-clock monitoring exceeds what CIPA envisions, and its overbroad filters have restricted legitimate LGBTQ+ educational resources. The Family Educational Rights and Privacy Act (FERPA) restricts disclosure of student records but includes a “school-official exception” allowing data sharing with third-party contractors. This loophole permits schools to grant Gaggle broad access without parental consent, undermining FERPA’s original purpose of safeguarding student records. The Children’s Online Privacy Protection Act (COPPA) governs the collection of children’s data under age thirteen. Because schools can consent on parents’ behalf, Gaggle is not required to obtain direct parental consent. Moreover, COPPA does not apply to students over thirteen, leaving middle and high schoolers unprotected. Fourth Amendment implications remain uncertain. Under New Jersey v. T.L.O., searches must be justified and reasonable in scope, but courts have split on how this applies to digital monitoring. In State v. Gaul, scanning emails on school servers was upheld since students were notified, but R.S. v. Minnewaska recognized privacy rights in personal social media messages. Gaggle’s continuous off-campus surveillance may therefore raise constitutional concerns, particularly where students lack meaningful notice or the opportunity to avoid monitoring.
Gaggle’s promise of safety comes at the expense of student privacy, equity, and trust. To ensure a fair balance, policymakers should commission independent research to evaluate effectiveness; require transparency and parental notice; mandate audits for algorithmic bias; limit surveillance to school hours and on-campus use; and update CIPA, FERPA, and COPPA to reflect modern digital realities. Schools must also consider alternatives that emphasize human connection rather than algorithmic control, such as increasing access to counseling, peer support programs, and teacher training in mental health awareness. Ultimately, while technology can support student well-being, it must not erode the freedom to think, explore, and learn without fear of being watched. Gaggle’s 24/7 surveillance, though possibly well-intentioned, risks transforming schools into digital panopticons where privacy and creativity give way to control. The task before educators and lawmakers is not to abandon safety, but to redefine it—a task that protects both students’ lives and their liberty to live as autonomous thinkers in a democratic society.