Query: artificial intellegence ip law

title: Pheromone based artificial life routing system for IP networks
abstract: Pheromone based ant routing is a distributed routing algorithm with good scalability and robustness. A 2 D cellular automata (CA) model of the computer network is presented in this paper, by means of which the algorithm is analyzed. It is discovered that the procedure of establishing a stable route is self organized towards the attractive peculiar state, and the duration of time for the routing establishment is power law distributed. A practical protocol over IP network is also presented in this paper. Two simulations were done to compare the performance dynamic and the load balancing performance between this protocol and OSPF protocol, the result of which shows that the ant routing out performs OSPF in these categories.

title: Intellectual Contract and Intellectual Law
abstract: Technological change is altering the nature of contract toward a greater focus on intangible assets. The direction of technological change toward greater connectivity, interoperability, mobile communications, the Internet of Things (IoT) artificial intelligence (AI) virtual inventions, and cooperative research and development (R&D) has profound implications. This article develops a new framework that I refer to as "Intellectual Law" to address this shift. The article introduces the concept of "Intellectual Contract" (IC) to characterize agreements for invention, innovation, and technology adoption. The article also introduces the concept of "Intellectual Tort" (IT) to describe liability including but not limited to misappropriation of trade secrets and infringement of patents, trademarks, and copyrights. Intellectual Law provides a consistent framework for IC, IT and Intellectual Property (IP) The article observes that legal protections for inventors cannot rely solely on what has proven to be a flawed combination of IT and IP. The article argues that greater emphasis on IC would improve both IT and IP. Because IC protects expectation interests it is essential for creating, developing, sharing, and applying intangible assets. IC generates gains from trade that enhance the benefits of inventors, innovators and adopters beyond what can be achieved by IT and IP alone.

title: Protectability and Enforceability of AI Generated Inventions
abstract: Artificial intelligence (AI) leads to disruptive innovations in every aspect of life. This technology not only changes the rules of all data related fields, it also either has or will soon reach the point where it generates innovation without human input. As its economic relevance increases, the question of protectability and enforceability of AI generated inventions naturally arises. After evaluating the nature of AI driven innovation, this chapter assesses the possibilities and restrictions of such protectability and enforceability. As will be shown, the legal system already provides instruments for IP protection, particularly patent protection. However, this technological progress poses challenges to the legal framework and to the common understanding of IP protection. Notably, current law does not allow patent protection of autonomously AI generated inventions that were created without human contribution.

title: IP Collaborative Agreements in the Creative Industries: Interim Report
abstract: The AHRC Creative Industries Clusters Programme (CICP) is a radical departure from traditional research funding. Research is understood in the context of R&D collaborations that are conceived to lead to new products and services, and ultimately to increased productivity and economic growth. These are ambitious, perhaps unprecedented goals for arts and humanities funding. The experimental nature of creative R&D collaborations between Universities and industry, the subject matter of this report, requires new and innovative collaborative models and considerable cultural adaptation. We cannot know what works best at the outset. But consortium leaders and collaborators need to know the state of the art: what is the orthodox approach to managing and exploiting intellectual property (IP) (where IP is seen as a 'thing to be sold' as well as, more fluid iterative interactions (where IP may be viewed as an enabler and catalyst to achieve wider goals, such as increasing capacity and developing an ecosystem) This report does not aim to provide a set of IP exploitation templates. It is designed to instigate discussion and draw attention to recent research and resources that make it possible to develop bespoke solutions. The aim is to achieve a better understanding of the environment and to enable collaborators on the Creative Industries Clusters Programme to make informed decisions. The report is structured in 5 sections. Section 1 provides a brief introduction to different forms of intellectual property (including patents, trade marks, design rights, copyright confidentiality) As copyright regulates much of the creative industry's output, the report includes a crash course on copyright law, drawing on the resources of CopyrightUser.org, a guidance portal developed by CREATe research. Different types of copyright works are explained, the criteria for protection, the difference between authorship and ownership, how there are economic (linked to owner) and moral (linked to author) imperatives in the copyright system, and, finally, how licensing is used to exploit copyright works. Section 2 focuses on the resurgence of creative reuse that appears to be a function of the digital environment. It is rare that new products or services do not touch on, be inspired by or adapt existing creative productions. There are opportunities within copyright law, due to the availability of public domain materials and limitations placed by law on the scope of copyright protection, but there are also real risks where exploitation becomes impossible without a careful understanding of joint creation and the need to obtain permissions. Section 3 explains the current practice of collaborative agreements between the University sector and industry, focussing on the so called Lambert approach, a toolkit of model agreements that has wide currency in science and technology collaborations. An important difficulty of the Lambert approach is the complexity and formality of the language used that seeks to provide legal clarity for future scenarios before the market potential of the collaboration can be assessed. In the creative industries, it is often necessary to revisit agreements at a later stage, typically once scalability becomes viable. Tying too many knots at the outset may provide legal assurance but also stifle the growth potential of the collaboration. Without concrete examples, it is difficult to envisage how IP arising from collaborative projects is translated into the real world. Section 4 shares 4 case studies, each from a different creative sector and using a different RD secondly, a more mixed approach of using copyright material for audio visual production with overlapping layers of different licences for different subject matter is explained; thirdly taking cues from a rapidly developing technology sector, product development over open source licensed artificial intelligence (AI) platforms is explored; and finally a case study from the galleries, libraries, archives and museums sector contrast different attitudes to the use of public domain materials. The report concludes with Section 5 entitled 'pitfalls and challenges' This suggests a number of issues that decision makers should reflect on when seeking to manage IP in collaborative agreements: the difficulty of distinguishing background and foreground IP in creative projects, especially under conditions of iterative production involving users; the importance of trust in creative relationships and the need to devise contractual ownership agreements rather than relying on joint authorship provisions of the law; the 'nobody knows' characteristic of cultural production, where prediction of future success is elusive but potential windfalls are high (due to the 'winner take all' tendency of creative markets) the need to understand the use of options to collaborate under conditions of uncertainty, and the advantages of building future freedoms to operate into the RD clarification of IP issues in augmented and virtual reality (AR/VR) which usually contain a wide range of potential subject matter, including technology and third party cultural materials; the temptation of micro enterprises and SMEs in the creative sector to avoid engaging with IP, due to time, knowledge and financial pressures; an understanding of the 'negative space' under copyright law, where it may be difficult to draw the line between ideas and expressions, and where alternatives to enforcement may be needed, such as brand identity and first mover advantages; open access obligations that cover research outputs in the context of the UK Research Excellence Framework (REF) navigating and challenging the established culture of University technology transfer offices, shaped by a culture that often results in risk averse processes of managing and exploiting IP. The radical nature of new R&D collaborations in the creative industries will require new approaches. There is a need for policy buy in at the highest level from both research funders and collaborating Universities. Experimental collaborative models will not come risk free. Innovative and adaptive approaches, open and closed, exclusive and non exclusive need to be encouraged. There can be no hiding in walled gardens.

title: Rethinking Software Protection
abstract: The core of artificial intelligence (AI) applications is software of one sort or another. Of course, if software were a mere ingredient, we may have had AI applications already decades ago. After all, it was Allen Touring who in the 1950s developed the first test for AI and concepts surrounding it. But while available data and computing power are important for the recent quantum leap in AI, there would not be any AI without computer programs or software. Therefore, the rise in importance of AI forces us to take once again a closer look at software protection through intellectual property (IP) rights, but it also offers us a chance to rethink this protection, and while perhaps not undoing the mistakes of the past, to at least adapt the protection so as not to increase the dysfunctionality that we have come to see in this area of law for the past decades. To be able to establish the best possible way to protect or not to protect the software in AI applications, this chapter starts with a short technical description of what AI is, and readers are referred to other chapters in this book for a deeper analysis (1) It continues by identifying those parts of AI applications that constitute software to which legal software protection regimes may be applicable (2) before outlining those protection regimes, namely copyright and patents (3) The core part of the chapter analyses potential issues regarding software protection with respect to AI using specific examples from the fields of evolutionary algorithms and of machine learning (4) Finally, the chapter draws some conclusions regarding the future development of IP regimes with respect to AI (5)

title: The Impact of ICT Advances on Education: A Case Study
abstract: ICT advances in the pace of Moore's law as well as Gilder's Law. The introduction of ICT into education has resulted astounding effects in learning. This paper presents a case study of the establishment of National Engineering Research Center for E learning, as part of education informationized effort in China. There are four stages of China's integration of ICT with education: start up phase, application phase, integration phase, and innovation phase. The four phases are well in line with the ICT evolutions from standalone computer, to all IP network, to all cloud infrastructure, and to today's all AI, which utilizes full spectrum of ICT including emerging technology advances in big data and artificial intelligence. The role of ICT in education has gone far beyond as an assisting tool in learning; it led to reconsider the traditional classroom centric teaching architecturally, as well as represented a paradigm shift in education including the roles of classroom teaching, the way of learning, the learning period systematically. Interactive and exploratory learning have become the mantra and education as a service is inevitable. At the same time, like any other technologies, ICT used in education can backfire if not carefully planned. This paper proposes a systematical engineering approach that integrates multiple tooling and activities around the learning of a particular subject with the purpose that engages learners through an intuitive, game like environment where students learn through exploration and discovery.

title: A Humanless World: The Progressive Artificial Intelligence and its Impact on Intellectual Property
abstract: With recent leaps in the field of robotics and artificial intelligence, the boundary between science fiction and reality is blurring constantly, with computers performing actions previously thought to be unique only to man. Though challenged by traversal of the physical realm, their capabilities to mimic human problem solving and creativity is growing exponentially. In discovering this potential lies the possibility of a cultural and scientific enrichment the likes of which will dwarf both the Renaissance and the Industrial Revolution, respectively. Naturally this is accompanied by countless inventions and artistic expressions from which society will inevitably benefit. However, due to their originators likely being at least in part or wholly computers, the question will arise as to who will be their true owners or authors from a legal standpoint. This article will examine the extent to which human and machine intelligence can be compared and will attempt to ascertain the ways in which the latter could pose a threat to the system of Intellectual Property laws in place to protect the rights of inventors/creators. Where possible, the piece will also attempt to propose potential remedies and pre emptive actions to alleviate the dangers such a synthetic revolution could cause to IP's legal framework.

title: Interspecific relationship of patchiness to occupancy and abundance, as exemplified by seagrass macrobenthos
abstract: The macroecological abundance occupancy relationship is well known; not so the potential one of patchiness with either or both. Following earlier work on the intertidal seagrass Zostera capensis in South Africa, interspecific macrofaunal patchiness occupancy and patchiness abundance relationships were investigated within each of a number of other seagrass systems (intertidal Cymodocea serratula, Halodule uninervis, Halophila ovalis, Zostera muelleri and Z. noltei, and subtidal Z. capensis) where faunal assemblages were markedly different in their overall abundance and species richness, and where the beds differed in their latitude, longitude, and other variables, including one in an artificial canal in a residential marina. Notwithstanding these differences, in all cases the more abundant and widespread the macrobenthic species, the less was its Lloyd's Ip patchiness, the more clearly so in respect of occupancy than of abundance. Correlation of Ip and mean crowding (Ic) values was relatively poor, and often not significant. This suggests that patchiness of a species is more influenced by unoccupancy levels than by even marked variation in abundance at occupied sites (e.g. Ic values of 380) Indeed, values of Ip were closely correlated with the expression [a.unoccupancy (1 a).Ic] where a is >0.80. In all cases, component macrofaunal species displayed a significant or near significant negative patchiness occupancy relationship in the form of a power law with a mean scaling coefficient across sites of 0.76, although data points appeared highly scattered. There was little uniformity amongst the component species in the life style of the most patchy, most widespread or most abundant.

title: Policy strategies for personalising medicine "in the data moment"
abstract: Data' is relevant in evolving value based healthcare that involves machine learning and artificial intelligence based technologies which are increasingly changing the landscape of personalised medicine (PM) However, a lack in adequate data for decision making may lead to new forms of health inequalities spite of the advancement in the technological front. There exists a dearth in alignment between incentive structures for innovation and policy measures for collective action and data transparency. Against this background, this article identifies the legal challenges for a data driven PM in Europe. Transparency, data protection and Intellectual property rights (IP) are major legal challenges for data oriented personalised research in Europe. Consequently, there is a need for restructuring public policy strategies in the interest of patients.  Legal dogmatic analysis of structural inefficiencies within interrelated legal paradigm over data that limits a functional development of a data driven PM.  Engaging in the data movement in personalised health care calls for special attention to strategic tools such as co regulation and self regulation that bridge the gap in law and practice.

title: Spam Detection Using Artificial Neural Networks Perceptron Learning Rule
abstract: Spam is email sent in bulk where there is no direct agreement in place between the recipient and the sender to receive email solicitation. To prevent the delivery of this so called spam, an automated tool called a spam filter is used to recognize spam. The circular nature of these definitions along with their appeal to the intent of sender and recipient make them difficult to formalize. The spam problem seems to persist and the current state of the art techniques in fighting this problem seems not to provide full proof. There are several approaches which try to stop or reduce the huge amount of spam on individuals. These approaches include legislative measures such as anti spam laws over world wide. Other techniques are known as Origin Based filters which are based on using network information and IP addresses in order to detect whether a message is spam or not. The most common techniques are the filtering techniques attempting to identify whether a message is spam or not based on the content and other characteristics of the message. In this paper, we present a technique to spam filtering using Artificial Neural Networks, and the perceptron learning rule.