Open Content in Open Context

This article presents the challenges and rewards of sharing research content through a discussion of Open Context, a new open access data publication system for field sciences and museum collections. Open Context is the first data repository of its kind, allowing self-publication of research data, community commentary through tagging, and clear citation and stable hyperlinks, and Creative Commons licenses that make reusing content legal and easy.The Nov-Dec 2007 issue of Educational Technology magazine is an entire special issue dedicated to "Opening Educational Resources." A series of articles in this issue highlight open educational models, including OpenCourseWare, Connexions and this piece on Open Context, co-authored by Sarah Whitcher Kansa and Eric Kansa

Generating Rembrandt: Artificial Intelligence, Copyright, and Accountability in the 3A Era--The Human-like Authors are Already Here- A New Model

Artificial intelligence (AI) systems are creative, unpredictable, independent, autonomous, rational, evolving, capable of data collection, communicative, efficient, accurate, and have free choice among alternatives. Similar to humans, AI systems can autonomously create and generate creative works. The use of AI systems in the production of works, either for personal or manufacturing purposes, has become common in the 3A era of automated, autonomous, and advanced technology. Despite this progress, there is a deep and common concern in modern society that AI technology will become uncontrollable. There is therefore a call for social and legal tools for controlling AI systems’ functions and outcomes. This Article addresses the questions of the copyrightability of artworks generated by AI systems: ownership and accountability. The Article debates who should enjoy the benefits of copyright protection and who should be responsible for the infringement of rights and damages caused by AI systems that independently produce creative works. Subsequently, this Article presents the AI Multi- Player paradigm, arguing against the imposition of these rights and responsibilities on the AI systems themselves or on the different stakeholders, mainly the programmers who develop such systems. Most importantly, this Article proposes the adoption of a new model of accountability for works generated by AI systems: the AI Work Made for Hire (WMFH) model, which views the AI system as a creative employee or independent contractor of the user. Under this proposed model, ownership, control, and responsibility would be imposed on the humans or legal entities that use AI systems and enjoy its benefits. This model accurately reflects the human-like features of AI systems; it is justified by the theories behind copyright protection; and it serves as a practical solution to assuage the fears behind AI systems. In addition, this model unveils the powers behind the operation of AI systems; hence, it efficiently imposes accountability on clearly identifiable persons or legal entities. Since AI systems are copyrightable algorithms, this Article reflects on the accountability for AI systems in other legal regimes, such as tort or criminal law and in various industries using these systems

Copyright

Copyright is the branch of Intellectual Property Law that governs works of expression such as books, paintings and songs, and the expressive aspects of computer programs. Intellectual products such as these have a partially public goods character: they are largely inexhaustible and nonexcludable. Intellectual Property Law responds to inexcludability by giving producers legal rights to exclude nonpayers from certain usages of their intellectual products. The goal is to provide incentives for new production at fairly low transaction costs. However, the copyright owner will charge a price above marginal cost and this, coupled with the inexhaustibility of most copyrighted products, creates deadweight loss. Various copyright doctrines (such as the idea/expression dichotomy, the limited duration of the copyright ownership term and the doctrine of ‘fair use’) work to reduce deadweight loss and other costs within a larger structure that creates incentives. Copyright Law, unlike Patent Law, gives owners rights only against those who actually copy the work. This limitation, too, may serve to reduce both transaction costs and deadweight loss. Empirically it is unclear how successful copyright has been in creating incentives for production, reducing transaction costs and keeping deadweight costs low

Creativity and craft

I revisit the distinction between intangible works of authorship and tangible objects, which is a fundamental proposition of modern copyright law. I suggest that reconsidering that distinction, at least in part, may expand the range of possibilities for aligning modern copyright as an economic construct with the historical roots of copyright and with ethical claims about authorial expression. Revisiting that distinction also may provide contemporary lawyers and policymakers with a much-needed tool for managing challenges posed by digital technology

Lawful Personal Use

Whenever someone makes a copy of a copyrighted work, that copy is either authorized by the copyright owner, permitted by some express provision of the copyright statute (such as the ephemeral copy provision in section 112 or the fair use provision in section 107), or infringing. That\u27s what we tell our colleagues and what we teach our students. But most of us don\u27t actually believe it, and this article argues that that understanding of the copyright law is wrong. I make this argument by examining the copyright law through the lens of personal use. Unlike many other jurisdictions, the United States has not troubled itself to nail down the lawfulness of personal copying and other personal uses. The statute prohibits infringement actions “based on the noncommercial use by a consumer” of “a digital audio recording device, a digital audio recording medium, an analog recording device, or an analog recording medium,” but is otherwise silent on the topic of personal uses. We have been comfortable with considerable uncertainty about the scope of lawful personal use because enforcing copyrights against personal uses seemed, until recently, unthinkable. Two related developments have spurred a reexamination of the lawfulness of personal uses. First, in the last three years, record labels and motion picture studios have sued thousands of individuals for copyright infringement. Second, the Supreme Court in the Grokster case adopted a standard for contributory copyright liability for distributors of technology that turns on whether the uses that the distributors encouraged their customers to engage in are lawful or unlawful. In this article, I argue that people\u27s reading, listening, viewing, watching, playing and using copyrighted works is at the core of the copyright system. I revisit copyright cases that have attracted criticism for their stingy construction of copyright owners\u27 property rights, and suggest that the narrow reading of copyright rights was motivated, at least in part, by courts\u27 solicitude for the interests of readers and listeners. I then articulate a definition of personal use. Armed with that definition, I look at the range of personal uses that are uncontroversially non-infringing under current law. I focus in particular on personal uses that seem to fall within the literal terms of copyright owners\u27 exclusive rights, and seem to be excused by no statutory limitation, but which are nonetheless generally considered to be lawful. I proceed to offer an alternative test for assessing the lawfulness of personal uses. Finally, I return to the conventional paradigm of copyright statutory interpretation, under which all unlicensed uses are infringing unless excused. I suggest that that rubric is not only inaccurate, but potentially destructive of copyright\u27s historic liberties

Equitable Resale Royalties

A “resale royalty right” is a legal right that gives certain artists the right to claim a percentage of the resale price of the artworks they created. Many countries have created a resale royalty right, but the United States has not, and a federal court recently held that a resale royalty right created by California was preempted by federal law. Commentators disagree about the justification of the resale royalty right. Supporters argue that equity entitles artists to a resale royalty right, which also encourages the production of artwork and protects artists from exploitation. Opponents argue that the resale royalty right is both inequitable and inefficient, because it benefits successful artists at the expense of unsuccessful artists by lowering prices on the primary market, and cannot provide a salient incentive for economically rational artists to produce more artwork. This Article assumes that the purpose of the resale royalty right is to increase the equity and efficiency of the art market, and asks how to create an equitable and efficient resale royalty system. It considers several different potential models for the collection and distribution of resale royalties, including a private right of action, resale royalty organizations, and federal taxation. It concludes that the most equitable and efficient model would be a “resale royalty tax,” distributed either to the National Endowment for the Arts (NEA) or on a progressive basis to unsuccessful artists

"Beyond copyright": law, conflicts and the quest for practical solutions

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AI & IP Innovation & Creativity in an Age of Accelerated Change, 52 Akron L. Rev. 813 (2018)

From a glimmer in the eye of a Victorian woman ahead of her time, AI has become a cornerstone of innovation that “will be the defining technology of our time.” Around 2016, the convergence of computing power, funding, data, and open-source platforms tipped us into an AIdriven 4IR. AI can make a difference in accelerating disruptive innovation by bringing a data-driven approach to invention and creation. To do so, the law must embrace change and innovation as an imperative in a journey towards an ever-shifting horizon. In the creative arts, the work for hire doctrine provides a pragmatic legal vehicle for interests to vest and negotiated by the commercial interests best placed to encourage investment in both the technology and its downstream uses. Like humangenerated work, AI-generated work is an amalgam of mimicry mined from our own learning and experience. The training data it draws upon, both for expressive and non-expressive sues, are merely grist for AI’s mill. Consequently, fair use must be liberally applied to prevent holdup by copyright owners and stifle transformative uses enabled by AI. AI can also be used to decipher complex copyright infringement cases such as those involving musical compositions. In the technological arts, the controversy will revolve around who owns innovative breakthroughs primarily or totally attributed to AI. How should these breakthroughs affect the regard for the notion of PHOSITA? How does AI change the equation when it comes to infringement? And how can AI help save the patent system from obsolescence? In these, AI both enables and challenges how we reward individuals whose ingenuity, industry, and determination overcame the frailty of the human condition to offer us inventions that make our lives more efficient and pleasurable. It will take a clear-eyed view to ensure that copyright and patent laws do not impede the very progress they were designed to promote