Patent Examination of Artificial Intelligence-related Inventions

2021 ◽  
pp. 245-265
Author(s):  
Jianchen Liu ◽  
Ming Liu
Keyword(s):  
Artificial Intelligence ◽  
Patent Law ◽  
Patent Rights ◽  
Patent Examination ◽  
Applications Of Ai ◽  
The Way

To date, artificial intelligence (AI) has caused fundamental changes in inventing processes, and many issues are arising therefrom, especially whether and in what way inventions implemented by AI are patent-eligible under the current patent regime. To deal with the issue of patentability, some countries have adjusted their patent regime to AI-related inventions. As a major economy with a world-leading AI industry, China has accumulated abundant experience in examining applications with respect to AI-related inventions. This chapter focuses on China’s experience in the examination of AI-related inventions and its latest regulatory movements in this regard. More specifically, it revolves around China’s practice of modifying its Guidelines for Patent Examination (‘Guidelines’) to clear the way for AI-generated inventions in April 2017, reaching consensus on applying the Patent Law, Implementing Rules of the Patent Law, and the Guidelines to examining the applications of AI-generated inventions, and further revising the Guidelines in December 2019 to make them more suitable for AI-related inventions. This chapter argues that these experiences can be a useful benchmark for other jurisdictions to grant patent rights to AI-related inventions.

scholarly journals Fence Posts or Sign Posts: Rethinking Patent Claim Construction

2016 ◽  
Author(s):  
Mark Lemley
Keyword(s):  
Twentieth Century ◽  
Patent Law ◽  
Patent Claim ◽  
Patent Rights ◽  
Late Twentieth ◽  
Late Twentieth Century ◽  
Patent Claim Construction ◽  
The Way

Patent law is bogged down in the minutia of claims construction. Claimconstruction is central to every patent dispute, but it has not providedthe hoped-for certainty or notice to competitors. Quite the contrary:disputes about the importance of inventions and the scope of patents havebeen replaced by labyrinthine wrangling over words written by lawyers. Theflaws of claim construction result largely from the problems attending"peripheral claims," that is, claims that purport to set the outermostboundaries of patent rights. In this paper, we argue that the way for thepatent system to move ahead may be by looking behind, to the practice of"central claiming" that was prevalent before 1870, and which was used inmany countries through the late twentieth century. Rather than relying onthe illusion of peripheral "fence posts," patent law may do better to onceagain look to stability of central "sign posts." We examine the failure ofperipheral claiming, the benefits of central claiming, and several hybridmeasures that might be adopted, either in the process of moving fromfence-posting to sign-posting, or as improvements over the current systemthat still stop short of fully adopting central claiming.

scholarly journals Artificial Intelligence and its Application in Various Fields

2020 ◽  
Vol 9 (5) ◽  
pp. 1336-1339
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Cyber Security ◽  
Main Idea ◽  
Human Beings ◽  
Military Planning ◽  
Actual Meaning ◽  
And Robotics ◽  
Applications Of Ai ◽  
The Way

The term ‘AI’ is not a new term but the actual meaning of ai is still hidden. Artificial intelligence is a branch of computer science that aims to create machines which are as intelligent as human beings. AI mainly focus on some questions like knowledge required while thinking, the way knowledge can be presented and the way knowledge can be used in other field’s viz. Robotics. Scope of AI is much wider than our thinking. It is not limited to only one or two areas rather in coming future everything will be directly or indirectly linked to AI. Much research has been done on artificial intelligence which has shown that by the end of 2020 many works which was not possible by human beings will be efficiently and accurately can be carried out by the help of robots. Robotics is a branch of engineering that deals with formation, designing, manufacturing, operation of robots. Artificial intelligence is being applied to many areas which are capable to solve many problems like in robotics, e-commerce, domestic chores, medical treatment, gaming, mathematics, military planning etc. The main idea behind the merging of artificial intelligence and robotics is to optimize the level of autonomy through learning. In the coming future we can surely overcome the disadvantages of robots like misuse of it with the help of facial recognition. Or we can use AI in other fields like in cyber security to prevent the systems from being hacked. The applications of AI and how we can implement other applications in coming time are discussed adding to it how we can overcome the disadvantages of using robots in regular life are also discussed.

Sports Medicine and Artificial Intelligence: A Primer

2021 ◽  
pp. 036354652110086
Author(s):  
Prem N. Ramkumar ◽  
Bryan C. Luu ◽  
Heather S. Haeberle ◽  
Jaret M. Karnuta ◽  
Benedict U. Nwachukwu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sports Medicine ◽  
Injury Risk ◽  
Industrial Revolution ◽  
Improve Patient Care ◽  
Great Promise ◽  
Patient Reported ◽  
Athlete Injury ◽  
Improve Patient ◽  
Applications Of Ai

Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

scholarly journals Explainable AI: A Review of Machine Learning Interpretability Methods

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 18
Author(s):  
Pantelis Linardatos ◽  
Vasilis Papastefanopoulos ◽  
Sotiris Kotsiantis
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Black Box ◽  
Learning Systems ◽  
Model Complexity ◽  
Learning Models ◽  
New Methods ◽  
Industrial Adoption ◽  
Machine Learning Models ◽  
The Way

Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption, with machine learning systems demonstrating superhuman performance in a significant number of tasks. However, this surge in performance, has often been achieved through increased model complexity, turning such systems into “black box” approaches and causing uncertainty regarding the way they operate and, ultimately, the way that they come to decisions. This ambiguity has made it problematic for machine learning systems to be adopted in sensitive yet critical domains, where their value could be immense, such as healthcare. As a result, scientific interest in the field of Explainable Artificial Intelligence (XAI), a field that is concerned with the development of new methods that explain and interpret machine learning models, has been tremendously reignited over recent years. This study focuses on machine learning interpretability methods; more specifically, a literature review and taxonomy of these methods are presented, as well as links to their programming implementations, in the hope that this survey would serve as a reference point for both theorists and practitioners.

“There is Nothing New in Cyberspace” a Motion for Debate

1992 ◽  
Vol 36 (14) ◽  
pp. 1049-1049 ◽  
Author(s):  
Maxwell J. Wells
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Virtual Reality ◽  
Human Computer Interaction ◽  
Cold Fusion ◽  
Major Advance ◽  
Junk Bonds ◽  
Exciting Development ◽  
Computer Interaction ◽  
The Way

Cyberspace is the environment created during the experience of virtual reality. Therefore, to assert that there is nothing new in cyberspace alludes to there being nothing new about virtual reality. Is this assertion correct? Is virtual reality an exciting development in human-computer interaction, or is it simply another example of effective simulation? Does current media interest herald a major advance in information technology, or will virtual reality go the way of artificial intelligence, cold fusion and junk bonds? Is virtual reality the best thing since sliced bread, or is it last week's buns in a new wrapper?

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence

2020 ◽  
Vol 24 (01) ◽  
pp. 38-49 ◽  
Author(s):  
Natalia Gorelik ◽  
Jaron Chong ◽  
Dana J. Lin
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Bone Tumors ◽  
Image Interpretation ◽  
Bone Age ◽  
Musculoskeletal Imaging ◽  
Radiology Workflow ◽  
Disease Response ◽  
Osseous Metastases ◽  
Applications Of Ai

AbstractArtificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have been studied, including the diagnosis of bone tumors, detection of osseous metastases, assessment of bone age, identification of fractures, and detection and grading of osteoarthritis. This article explores the applications of AI for image interpretation of MSK pathologies.

Ten Assumptions About Artificial Intelligence That Can Mislead Patent Law Analysis

2021 ◽  
Author(s):  
Daria Kim ◽  
Maximilian Alber ◽  
Man Wai Kwok ◽  
Jelena Mitrovic ◽  
Cristian Ramirez-Atencia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Patent Law

scholarly journals Software Testing: Issues and Challenges of Artificial Intelligence & Machine Learning

2021 ◽  
Vol 12 (1) ◽  
pp. 101-112
Author(s):  
Kishore Sugali ◽  
Chris Sprunger ◽  
Venkata N Inukollu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Software Testing ◽  
Future Research ◽  
Critical Component ◽  
Development Methodology ◽  
Testing Strategies ◽  
History Of ◽  
Shed Light ◽  
The Way

The history of Artificial Intelligence and Machine Learning dates back to 1950’s. In recent years, there has been an increase in popularity for applications that implement AI and ML technology. As with traditional development, software testing is a critical component of an efficient AI/ML application. However, the approach to development methodology used in AI/ML varies significantly from traditional development. Owing to these variations, numerous software testing challenges occur. This paper aims to recognize and to explain some of the biggest challenges that software testers face in dealing with AI/ML applications. For future research, this study has key implications. Each of the challenges outlined in this paper is ideal for further investigation and has great potential to shed light on the way to more productive software testing strategies and methodologies that can be applied to AI/ML applications.

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