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11th Annual Corporate IP Counsel Forum

Macedo, a physicist by training, litigates in all areas of intellectual property law, including patent, trademark and copyright law, with a special emphasis in complex litigation and appellate work.

Fluent in technical jargon spoken by inventors and clients, patentese spoken at the PTO, legalese spoken by courts and attorneys, business jargon spoken by management, and plain English, he seeks to translate complex subject matter into terms all can understand.

Mr. Macedo also has enforced and defended against trademark assertions and/or opposition proceedings for financial service providers, casinos and resorts, non-profit organizations, celebrities;

Clients ranging from international banks, broker dealers and new business ventures call on Mr. Macedo to develop patent strategies, prepare patents, assert rights and defend against infringement claims.

His work includes developing and implementing patent strategies associated with such cutting edge financial innovations like bitcoins and other synthetic currency or math-based assets.

His experience includes successfully defending the Discover Card division of Morgan Stanley from one of the earliest business method patent assertions, and leading the team to implement and enforce the deposit sweep patent portfolio for Island Intellectual Property LLC.

As Co-Chair of the Amicus Committee of the New York Intellectual Property Law Association, Mr. Macedo has been principal counsel or additional counsel on amicus briefs in some of the leading patent cases of recent years, including Cuozzo (at Federal Circuit en banc petition, Supreme Court petition for certiorari and merits brief stage), Highmark and Octane (at the Supreme Court), Kimble v.

Podcast: Artificial Intelligence and Intellectual Property Considerations

Artificial intelligence technology is driving a new wave of innovation, presenting unique challenges and opportunities for intellectual property law and policy.

In this podcast, IP litigation partners Matt Rizzolo and Leslie Spencer, and IP transactions partner Regina Sam Penti, discuss factors impacting patenting AI technologies, determining infringement liability, protecting training data and attributing inventorship or authorship to AI-generated solutions and creations.

In today’s podcast, we’re going to talk about artificial intelligence technology and how it’s driving a new wave of innovation, presenting unique challenges and opportunities for intellectual property law and policy.

So another way to think about AI is by reference to systems that change behaviors without being explicitly programmed to do so, and they can change behaviors based on data collected, usage analysis and other observations.

AI uses larger data sets, so in a sense, the revolution and explosion of AI has really been allowed and enabled by the explosion of data, and the fact that were creating now so much data that we’re practically swimming in it, and we’ve managed to harness this data at a fraction of the cost, using relatively simple everyday devices like cell phones and laptops.

Dr. Thaler has claimed that the Creativity Machine mimics the human brain using two artificial neuron networks and is therefore capable of producing creative outputs to new scenarios without human input.

The law is very much struggling to catch up in this area, so it’s certainly worth exploring the specific rules in the country or jurisdiction where protection is sought, but just have an awareness that these issues are evolving and the law is going to change quickly in these areas.

And if the deal falls apart, can you un-train the AI if it’s your data that’s kind of improved the AI, or is one party left with basically internal relationships and their data being trapped, extracted and exposed in the other parties’

And given that the law is very much struggling to catch up with the technology, you have to consider as a transactional attorney the very real possibility that future regulations may render illegal whatever it is that your AI robot is trained to do today.

For example, claims may be drafted to recite novel technologies for extracting crucial information from a data set, or improving the algorithms such that they make the computer on which they are running process data more quickly, or use less energy.

Regina Sam Penti:Alright,so just chiming in to add that some jurisdictions, Europe for example, may be somewhat more welcoming of AI-based innovations than others, or at least may provide more clarity than we have seen in the U.S. So for instance, The European Patent Office recently unveiled guidelines that make it clear that while AI-innovations that focus on mathematical functions will face an uphill battle in securing patent protection, those innovations that focus on the technological applications of those algorithms might do better.

especially considering that two years ago Congress passed the Defend Trade Secrets Act, which provides a federal cause of action and strong remedies for trade secret misappropriation, and we know several states also have their own statutes.

think of the structure and components of neural networks, think of sort of the training sets, test data, source code and other algorithms that drive the system.

In one context involving AI-driven online chat engagement systems, the Northern District of California recently held that XML data that’s generated by the chat platform analytics could constitute a trade secret under New York law, as it reflected the application of the Plaintiff’s rules and models to test real world situations.

And of course, to the extent AI is implemented in software, that software can be protected using copyright law, but that protection would not extend to functionality, so it is a bit more limited, but it’s certainly something worth thinking about.

And then there’s the complicated issue of whether the liability is for direct infringement alone—the actual making/using of a patented invention—or for indirect infringement—inducing a third party to infringe, or contributing to some third party’s infringement.

So what if you have an AI program that had many different and non-infringing uses at the time it was created, but over time it learned to become exclusively infringing, probably based on data that told it that approach was particularly profitable?

since the ultimate goal of an AI system is for it to learn and developon its own,would it be fair to ever really hold a developer or seller of such a system to be liable for inducing infringement that occurs many weeks, months or years down the road after they have programmed their system?

Even if these questions are unsettled in the law, we always have to consider whether the parties who are at a negotiation table can bring more certainty to some of these arrangements and allocate risks using contractual provisions that hopefully will reduce the likelihood of conflicts down the road.

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