Strategies for Protecting Artificial Intelligence and Machine Learning post-Alice
Artificial Intelligence (AI) and Machine Learning (ML) innovations are transforming industries. But AI and ML are a very broad terms, and development of the algorithms necessary to implement these innovations can include many stages. Potential uses of these technologies spans across nearly all industries.
The Alice/Mayo framework for determining patent eligibility has made it much more difficult to obtain patents in a variety of technology fields, but initially the futuristic area of artificial intelligence and machine learning was largely spared from dealing with the most difficult of these rejections. As the result of an August 2016 decision by the Federal Circuit in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016) patent eligibility rejections for inventions claiming advances directed to artificial intelligence became as common as 101 rejections of business method applications, for example.
Revised Patent Eligibility Guidance from the United States Patent and Trademark Office issued in January 2019 seems to have turned the tide and has made easier for innovations directed to artificial intelligence and machine learning to be patented, but will the Federal Circuit agree?
Given the variability of what falls within the meaning of AI or ML, and when within a development cycle an such innovation occurs, what are the possible and most valuable intellectual-property strategies to protect these important innovations in a post-Alice era?
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- Artificial Intelligence Technologies Facing Heavy Scrutiny at the USPTO
- Revised Patent Eligibility Guidance Effectively Defines What is an Abstract Idea
- Latest CAFC Ruling in Cleveland Clinic Case Confirms That USPTO’s 101 Guidance Holds Little Weight
- Patent Trends: Artificial Intelligence
- Prospects for Computer-Related Applications Continue to Improve Post-Guidance
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