1,720,963 research outputs found
SUMMONING A NEW ARTIFICIAL INTELLIGENCE PATENT MODEL: IN THE AGE OF CRISIS
Get PDFAs the world is seeking the exit strategy from the pandemic while
still combating the fast-moving spread of the virus in many countries,
we need an equally speedy and powerful tool to combat the
pandemic’s implications. On the forefront against COVID-19,
artificial intelligence (AI) technology has become a digital armament
in the development of new drugs, vaccines, diagnostic methods, and
forecasting programs. Patenting these new, nonobvious, and efficient
technological solutions is a critical step in fostering the research and
development, huge investments as well as commercial processes. This
Article considers the challenges of the current patent law as they apply
to AI inventions in general and especially in the age of a global
pandemic. The Article proposes a novel solution to the hurdles of
patenting AI technology by establishing a new patent track model for
AI inventions (including the inventions that are made by AI systems
and creative AI systems themselves). Unlike other publications
promoting either complete abandonment of AI related patents, or
advocating to maintain current patent laws, or recommending minor
adjustment to patent laws, this Article suggests a novel model of
separate patent venue solely targeting AI inventions. The argument of
this Article is based on four pillars: the difficulty of having a patenteligible
subject matter, the hurdle of the “blackbox” conundrum, the
confusion of who is “a person of ordinary skills in the art” (POSITA),
and the criticality of establishing a new AI patent track model,
especially during a global epidemic
Generating Rembrandt: Artificial Intelligence, Accountability and Copyright - The Human-Like Workers Are Already Here - A New Model
No full text“Equality and Privacy by Design”: A New Model of Artificial Intelligence Data Transparency via Auditing, Certification, and Safe Harbor Regimes
Get PDFCopyrightability of Artworks Produced by Creative Robots, Driven by Artificial Intelligence Systems and the Concept of Originality: The Formality - Objective Model
No full textGenerating Rembrandt: Artificial Intelligence, Copyright, and Accountability in the 3A Era--The Human-like Authors are Already Here- A New Model
Get PDFArtificial 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
When Artificial Intelligence Systems Produce Inventions: The 3A Era and an Alternative Model for Patent Law
No full textGender Biases in Cyberspace: A Two-Stage Model, the New Arena of Wikipedia and Other Websites
Get PDFIncreasingly, there has been a focus on creating democratic standards and norms in order to best facilitate open exchange of information and communication online―a goal that fits neatly within the feminist aim to democratize content creation and community. Collaborative websites, such as blogs, social networks, and, as focused on in this Article, Wikipedia, represent both a cyberspace community entirely outside the strictures of the traditional (intellectual) proprietary paradigm and one that professes to truly embody the philosophy of a completely open, free, and democratic resource for all. In theory, collaborative websites are the solution for which social activists, intellectual property opponents, and feminist theorists have been waiting. Unfortunately, we are now realizing that this utopian dream does not exist as anticipated: the Internet is neither neutral nor open to everyone. More importantly, these websites are not egalitarian; rather, they facilitate new ways to exclude and subordinate women. This Article innovatively argues that the virtual world excludes women in two stages: first, by controlling websites and filtering out women; and second, by exposing women who survived the first stage to a hostile environment. Wikipedia, as well as other cyber-space environments, demonstrates the execution of the model, which results in the exclusion of women from the virtual sphere with all the implications thereof
Melodies Manipulated: Intellectual Property & The Music Industry
Get PDFMarilyn Mosby, Founder and Managing Partner of Mahogany Elite Consulting, opened the IPLJ Symposium with her Keynote Address which focused on the cultural, political, and social context surrounding the use of rap lyrics as evidence in criminal prosecutions.
The opening panel, “Do You Get Déjà Vu?,” comprised of Gary Adelman, Partner, Adelman Matz PC; Linna Chen, Senior Legal Counsel, Litigation & Copyright, Spotify; and Ilene Farkas, Partner, Pryor Cashman, and was moderated by Sarah Matz, Partner, Adelman Matz PC, and Adjunct Professor at Fordham University School of Law. The panel discussed recent copyright cases, specifically Williams v. Gaye (the “Blurred Lines Case”) and Griffin v. Sheeran and deliberated about what these decisions mean for artists involved in copyright infringement suits.
The second panel, Robotic Rhapsody, explored the effects of AI-generated music on the music industry and its implications for music copyright law. The panel included Paul Fakler, Partner, Mayer Brown; Alex Mitchell, Co-Founder and CEO of Boomy Music (a Generative AI Music platform); and Marc Ostrow, Senior Counsel, Romano Law. The panel was moderated by Fordham Law Visiting Professor Shlomit Yanisky-Ravid.
The last panel of the day, Rhyme & Punishment, circled back to the use of rap lyrics as evidence in criminal trials and the blatantly racist nature of this practice. Panelists included Erik Nielson, University of Richmond Liberal Arts Professor and Department Chair and Co-Author of the award-winning book Rap on Trial: Race, Lyrics, and Guilt in America; Amber Baylor, Columbia Law School Professor and Criminal Defense Clinic Director; Emerson Sykes, Senior Staff Attorney, American Civil Liberties Union (“ACLU”); and Kenan Kurt, Chief of Staff and Counsel for New York State Senator Brad Hoylman-Sigal. The panel was moderated by Fordham Law Professor Bennett Capers
Melodies Manipulated: Intellectual Property & The Music Industry
No full textMarilyn Mosby, Founder and Managing Partner of Mahogany Elite Consulting, opened the IPLJ Symposium with her Keynote Address which focused on the cultural, political, and social context surrounding the use of rap lyrics as evidence in criminal prosecutions.
The opening panel, “Do You Get Déjà Vu?,” comprised of Gary Adelman, Partner, Adelman Matz PC; Linna Chen, Senior Legal Counsel, Litigation & Copyright, Spotify; and Ilene Farkas, Partner, Pryor Cashman, and was moderated by Sarah Matz, Partner, Adelman Matz PC, and Adjunct Professor at Fordham University School of Law. The panel discussed recent copyright cases, specifically Williams v. Gaye (the “Blurred Lines Case”) and Griffin v. Sheeran and deliberated about what these decisions mean for artists involved in copyright infringement suits.
The second panel, Robotic Rhapsody, explored the effects of AI-generated music on the music industry and its implications for music copyright law. The panel included Paul Fakler, Partner, Mayer Brown; Alex Mitchell, Co-Founder and CEO of Boomy Music (a Generative AI Music platform); and Marc Ostrow, Senior Counsel, Romano Law. The panel was moderated by Fordham Law Visiting Professor Shlomit Yanisky-Ravid.
The last panel of the day, Rhyme & Punishment, circled back to the use of rap lyrics as evidence in criminal trials and the blatantly racist nature of this practice. Panelists included Erik Nielson, University of Richmond Liberal Arts Professor and Department Chair and Co-Author of the award-winning book Rap on Trial: Race, Lyrics, and Guilt in America; Amber Baylor, Columbia Law School Professor and Criminal Defense Clinic Director; Emerson Sykes, Senior Staff Attorney, American Civil Liberties Union (“ACLU”); and Kenan Kurt, Chief of Staff and Counsel for New York State Senator Brad Hoylman-Sigal. The panel was moderated by Fordham Law Professor Bennett Capers
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