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Intro to AI Webinar


0:00 Introduction: AI and IP
4:57 Importance of Intellectual Property in Associations
15:04 The Impact of AI on Inventions
29:28 Copyright and Patent Issues With AI
42:41 Future of AI in Association Services
51:55 Building Moats With Intellectual Property
59:28 Strategic IP Protection in Association Innovation



In this episode, Amith and Mallory sit down with Robert Plotkin, an AI patent attorney and author of "AI Armor." Robert shares his insights on intellectual property (IP) and its evolving landscape in the AI era. He discusses the importance of IP in building competitive advantages and strategies for associations to leverage their assets, such as content and data, to create a "moat" against competitors. The conversation also delves into topics like AI-generated inventions, patentability, and the potential for associations to develop AI co-pilots or assistants leveraging their expertise and brand recognition. 



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More about Your Hosts:

Amith Nagarajan is the Chairman of Blue Cypress (, a family of purpose-driven companies and proud practitioners of Conscious Capitalism. The Blue Cypress companies focus on helping associations, non-profits, and other purpose-driven organizations achieve long-term success. Amith is also an active early-stage investor in B2B SaaS companies. He’s had the good fortune of nearly three decades of success as an entrepreneur and enjoys helping others in their journey.
Follow Amith on LinkedIn.

Mallory Mejias is the Manager at Sidecar, and she's passionate about creating opportunities for association professionals to learn, grow, and better serve their members using artificial intelligence. She enjoys blending creativity and innovation to produce fresh, meaningful content for the association space. Follow Mallory on Linkedin.

Read the Transcript

Disclaimer: This transcript was generated by artificial intelligence using Descript. It may contain errors or inaccuracies.

Mallory Mejias: [00:00:00] Robert, I want to thank you so much for joining us on our podcast today. You know, in previous episodes, Amith and I have talked a little bit about IP, but it's not something we've been able to dive deep on. So we're super excited to have you on the podcast. How are you?

Robert Plotkin: I'm doing great. Thanks, Mallory.

Thanks, Amith. It's really great to be here. Thanks for having me.

Mallory Mejias: For sure. I'm hoping you can share a little bit with our listeners about your background, what you've done in the past, and how you got here.

Robert Plotkin: Yeah, I am an intellectual property attorney. I focus primarily on obtaining patent protection for growing tech companies from the founding stages all the way up through growth and exit.

My background is in computer science. I started programming as a kid back 80s, loved it, went on to study computer science, went, then went on to become a lawyer and been Obtaining primarily software patents [00:01:00] for over 25 years. I enjoy working with founders on their way up, to use IP to bolster their company, to increase value, to generate revenue, and particularly to help them achieve those goals.

Successful exits, because that's what everyone is shooting for. Partnerships, mergers, acquisitions, whatever it happens to be. I enjoy using IP as a strategic business asset. And maybe we can talk a little bit about that today in the context of associations.

Mallory Mejias: Absolutely. And I think we definitely will get into that.

But first, I think we should go back to the building blocks to kind of set the stage for this conversation. What is IP kind of by definition and in your own words, and why is it so important?

Robert Plotkin: Yeah, intellectual property broadly Is a set of legal rights that an individual or an organization or a company owns in their [00:02:00] intellectual creations So that could be a piece of art It could be a blog post it could be a website a video music You On my side of things where I deal with patents most of the time, it can be a physical invention, a car engine, it could be a drug, a new kind of chemical, or what I deal with most of the time, new type of software, new type of algorithm or process implemented in software.

Anything that is new and useful that solves a practical problem can be protected by a patent. So whether it's a copyright in, in a creative or artistic work, uh, or a patent. Or a trade secret in something like a formula. The formula for Coca Cola is very, very famous trade secret. Whether it's any of those types of IP, If you as an individual or organization own it, you have a legal ability to stop others from using that IP without [00:03:00] your permission.

That's why it's usually called intellectual property. It's somewhat analogous to just owning a physical thing like your car, where someone cannot legally drive it without your permission. But IP applies to ideas, information, data, inventions. songs, websites, anything like that, where someone else cannot.

Copy or use reproduce that work without your permission. So it can be a very, very powerful type of a tool or an asset to have for that reason, because in the in the information age, and we're probably moving past even the information age now, increasing number https: otter. ai Intellectual property rather than in physical assets where companies used to have their, their primary competitive advantage, you know, that [00:04:00] machinery or real estate still important, but increasingly increasing percentage of the economy, increasing number of entities have their primary value in these intangible or intellectual assets.

Amith Nagarajan: Robert, one follow up question I have on that opening. Uh, area of discussion is in the association context, there often is a tremendous amount of content and in some cases data like registries or other data that's been collected in a sector that an association may represent. Um, do those elements, uh, do those constitute intellectual property by your definition?

Robert Plotkin: Yeah, they would typically be protected by copyright or trade secret or a combination of both. Uh, the customer lists, any data collected from customers, although it probably would not be copyrightable in most cases by the entity, but it could be maintained as a trade secret. And it can be [00:05:00] extremely valuable.

I mean, we may talk about it more, but as data. Generally, an information and maybe even knowledge becomes more of a commodity. Any entity has to ask what differentiates us, what gives us that extra layer of value that our competitors don't have. And very often it's that private data that can be the basis.

competitive advantage and therefore for valuable intellectual property in the form of trade secrets. I

Amith Nagarajan: know we'll dig into more of this in the near future, but you know, associations, we often discuss with leaders how their brand and their content are in many respects, latent assets that can be leveraged far more greatly in the era of generative AI and AI more broadly.

And as we get into the conversation, I just wanted to put that out there because it's the backdrop for, uh, some of the thinking that I know many of our listeners will be pondering, which is, you know, how does this apply to me? How do I protect my assets? [00:06:00] How do I leverage my assets? And in this sector, there are some groups that have software to protect, uh, or software to leverage, but, and I think there's an opportunity for a lot more of that because generative AI makes it so much easier to create novel software, which is a whole nother level.

I think interesting conversation, but I just wanted to put that out there, uh, to contextualize some of this for our typical listener.

Robert Plotkin: Well, you mentioned brand and, you know, I, I didn't mention trademarks, which is the other major type of intellectual property and you're right for, for associations, very often that's going to be an important, valuable piece of the picture.

A trademark is anything like a product name, a slogan, a logo. often a phrase that's associated with a product or a service, uh, that identifies its source. I'll use Coca Cola again, one of the most famous brands out there. You might say, well, there's lots of sodas that taste similar to Coke. Why does it [00:07:00] maintain such a huge market share?

The brand is a huge part of it. People associate quality and taste and enjoyment and good experiences and all of these things and reliability that they know whenever they buy a can of coke, it's going to taste the same in the way they expected. They associate that with the brand. So that brand in the law is protected using trademarks, and that's a very, very valuable asset for a company to have, particularly in industries or contexts where there isn't a lot of differentiation based on what inventions you have or technology or maybe even information.

It's the brand that could be the real distinguishing feature.

Amith Nagarajan: And in an era, as you mentioned, where even knowledge is potentially going to be commoditized, even in a highly vertical, narrow domain, like a specialty area of law, for example, there is an opportunity for the association with oftentimes a [00:08:00] very strong brand in that particular discipline or a particular geography to leverage that brand to do some really interesting things.

So we'll get into that more.

Robert Plotkin: Yeah. I mean, and you know much more about this than me, but I can only guess one way in which that's relevant is if you have an association that's been around for a long time, you know, there might be a double edged sword where it, it may have trouble keeping up with new innovative, uh, upstart organizations, but it's got that old, well known brand that's trusted.

And that could be the thing that's really, you know, useful in its corner.

Amith Nagarajan: Well, as an IP attorney, I'm sure the answer to this question is yes, because there's an association for everything, but I'm assuming there's an association for intellectual property attorneys, or I'm Perhaps even patent attorneys and groups like that and perhaps exactly what you just mentioned They may have been around a while and so they have uh trust and credibility But perhaps they're not necessarily on the cutting edge in terms of how they deliver Or disseminate information or how they connect [00:09:00] people and there's you know there's both kind of the risk piece and also the opportunity if a brand like one of those associations were to AI and reduce friction and improve engagement, um, in the ways that we talk about a lot here.

Robert Plotkin: Absolutely. Before

Mallory Mejias: we chat about the AI landscape now, I want to go back a little bit with you, Robert. You seemed to be interested in AI before it was cool, quote unquote. I'll say you wrote a book called Genie and the Machine all the way back in 2009 about AI generated inventions. I'm curious, what inspired you at that time to be interested in AI?

Thanks for having me.

Robert Plotkin: Yeah, in fact, it goes back even further. I said I was programming when I was a kid. Uh, I entered a science fair in high school must have been 1987 or so with a piece of software. I wrote that. used a pretty primitive form of machine learning to learn how to play tic tac toe. [00:10:00] And it was based on a project in the 60s.

Someone named Mitchie who did this in a physical computer using matchboxes that were labeled with different tic tac toe boards and he had different numbers of beads in them to represent the weights for those of you in the audience who know about machine learning. So he trained a machine learning model in a, in a physical computer.

Anyway, uh, I remember, uh, learning a lot from that science fair experiment, uh, early type of machine learning in the eighties, but going to the book, the genie in the machine, which was about, uh, how AI back in the nineties and early two thousands was being used to automate the inventive process. And the implications of that for patent law.

For example, I address things like, can a invention that was invented by or using AI be patented? Uh, Would it qualify for patent [00:11:00] protection if the invention was designed primarily by a piece of software, for example? And I got motivated, uh, to write about that because I was seeing it happen. I was seeing it happen again, back in the 90s, even in the early 2000s.

Uh, of course, the technology then was not nearly as widespread or advanced as it is now, both because of all of the orders of magnitude of improvements in hardware and also software. I mean, I wrote the book before deep learning. Uh, was around, you know, there's been a few really major algorithmic and software advances since that time, but when I wrote the book, there were already a few patents that had been granted on what you might call computer generated inventions.

I had an example of a team at NASA that designed an antenna using a type of AI called the generic genetic algorithm, and that antenna went on a NASA space station. Uh, I interviewed, uh, a, uh, Inventor who helped oral be create the first version [00:12:00] of the cross action toothbrush using a neural network based A.I. So it was real. But I'll say that the book didn't get a whole lot of attention back then, because I think people thought this isn't real or they just couldn't connect to it. And then, of course, ever since around 2019 2020. This has gotten more attention. And then ever since chat GPT came out, the topic has got just just launched into space.

But it's been very edifying and very satisfying for me to see people pay attention to this. And now the U. S. Patent Office patent offices around the world have all been grappling with this question of what's now being called a I assisted inventions. I like that term because there's always humans involved.

Uh, can those be patented? What should the rules be? Even Should the A. I. B. Named as an inventor or a co inventor? Uh, all of these issues are being addressed by patent offices and courts around the [00:13:00] world. Uh, and it's only going to become a more prominent topic.

Amith Nagarajan: I think it's super interesting, you know, for our companies here at our family of businesses are always building new software and leveraging A. I. More and more. And so it's Uh, you know, thinking about that from a software company perspective, I think it's just a fascinating discussion and thought process of what is protectable, what is fundamentally the idea of invention when the machine is able to create such a large percentage of it.

I know authors are thinking about that in the context of writing books, uh, with copyright protection or the lack thereof in some cases. Uh, when we wrote our AI book for associations, Ascend, last year, we heavily used AI, knowing full well that there's a very high likelihood that there's no copyright protection available for that particular title.

And in fact, for us, we didn't care because we intended to freely distribute the product and make it available to everyone in the world. And our goal was to disseminate the information and not to profit from the book itself. very much. Um, but [00:14:00] to, you know, share that content. So for us, it was a perfect use case, and we weren't too concerned about it.

Plus, I tend to, you know, shoot first and ask questions later in the way I build companies anyway, and it's just kind of the nature of entrepreneurship. Um, but for associations who are thinking actively about this exact topic, You know, for example, do they use AI to help them author a journal article? Uh, will they have copyright protection or not?

Um, what's the, is there a framework for thinking about that that you could share? I'm sure that people are at this point in the pod anxious to hear a little bit of a decision tree maybe on what might help them decide what maintains protection and what prevents them from getting protection.

Robert Plotkin: Sure, and you know, I am, I am primarily a patent attorney so it might be a little dangerous for me to veer too far into copyright.

But the, I think the most important guideline for people to keep in mind, even as the law evolves on this question of what is and isn't copyrightable when you use AI to help you do something like, like write a book is [00:15:00] to ask, what was the human contribution to this? Uh, I think it, if something is entirely a hundred percent, uh, AI generated, uh, it may not be copyright, uh, protected, protectable by copyright, right?

Maybe in some places and not others, but the more that you as a human contribute, the more The more easy it will be for you to obtain copyright protection. And to be honest, it's probably going to be better for you from a business or organizational perspective anyway, uh, to be more involved as I'm sure you saw from, from writing the book.

You said it was heavily, you know, relied heavily on the use of AI, but I'm sure that it reflects your personality and your ideas and your expertise, you brought all that to bear on it as well.

Amith Nagarajan: Very much so. Our process for the book was we got a group of people together who contributed to it. We built a very detailed outline, largely without AI support to generate the topics, and then each contributor [00:16:00] basically wrote or spoke to a transcription tool to generate raw content.

And then we use the AI essentially to distill that content down, in some cases to summarize it, in some cases to clean it up, and then to stitch it together. The other thing we had the AI do that was really interesting. This is the early days of GPT 4. This was last spring. We fed the AI the non fiction element, and then we asked the AI to develop a narrative for a fictional, um, plot that would go across multiple chapters.

The idea being it's something along the lines of a business fable, right? Where we are able to share a story about an association leader and what happened to them over time. It was actually quite remarkable how good the AI was at that creative task, even compared to the other pieces. Uh, so all the ideas were definitely ours, but we heavily used AI to create the copy and to refine the copy.

We're right now just kicking off the second edition, um, the, the really meat of that work, uh, to update the book. We plan to update it at [00:17:00] least once a year, and we're actually a little bit overdue for the update, um, but, uh, we'll once again be using, heavily using AI. But the ideas are certainly coming from us and from, You know, our audience of people who provide feedbacks.

There's a lot of human input.

Robert Plotkin: I mean, it's interesting. The process you described is exactly the kind of process I both was observing and was suggesting in the genie in the machine in the inventive context, which is that a I by becoming increasingly able to fill in the details of a goal or an idea or written work or an invention would enable people to To focus on the higher level ideation, defining the problem they want to solve, defining the goal they want to achieve, and then leaving it to the A.I. To fill in more of the low level details, the equivalent in the inventive context of writing the outline, so to speak, and then letting the A. I. Fill in the details. It's very much analogous to what you do as a [00:18:00] manager, uh, when you have people who are working for you or with you or when you're collaborating.

So in that sense, it's not, you know, any different. And the process you described is one that I think takes gets the best of both worlds. It enables you the work to reflect, as you said, your ideas. Uh, not be bland or generic to reflect your insights to provide value to the reader that other people wouldn't have been able to provide, but it saves you time and effort in writing it.

And maybe, as you said, in the in the context of coming up with a creative story comes up with something you couldn't have. I did something similar last year. I was writing a an article about Whether AI could be named as an inventor on a patent. So I wrote an essay. My mind tends to work in sort of essay like style.

And I asked ChatGPT to write a story, a fictional story, illustrating that concept. And it did, as [00:19:00] you said, a surprisingly good job. It imagined, A science fair or an inventor's fair in which there were multiple entries with different inventions, one of which was created by an A. I. And the human inventor was afraid that it was going to lose to the A.I. But in the end, the judges awarded. And it had a moral to the story and it was quite good. So I ended up publishing my essay along with the chat GPT story. This is before I saw your book using the same sort of general approach. But if you can learn what the AI is good at. You can couple it with what you're good at, just as when you build a team or work together with a team of people, right?

Everyone has their own strengths and weaknesses. And when you build a good team, you take people and you, you, you leverage the best from everybody. And you, you, the team can be better than every individual individually, right?

Amith Nagarajan: We talk a lot about this, uh, you know, [00:20:00] the concept of an explosion of opportunity coming from the availability of more creativity.

And then we talk about this a lot in our content here on the pod, but also in our courses and in our blog articles and so forth. And a part of what we're referring to is when you open up a modality of expression that is previously unavailable due to a lack of skill. So in my case, I'm not a fiction writer.

I was never good at that. And so that whole idea for the book wouldn't have been possible without the aid of AI, other than, you know, hiring a person to do it. And then we probably wouldn't have done it because of costs and time and all those things. So, uh, and then a similar thing recently is that I don't know if you've had a chance to play with a tool called suno ai, but we talked about it last week's pod. Uh, but it's a music generator and I've been using it ever since I discovered that tool, I've been playing with it almost every day because it's so much fun. Uh, but I'm sending people songs like my brother in law had a 50th birthday last week and I, I had it singing the song and, and like French jazzy vocals and stuff like that [00:21:00] and, and throw in some funny stuff from a trip that me and my wife and, and they did recently and it's just awesome because it's like this creative expression that you didn't previously have available.

I have no musical talent whatsoever. Um, and first of all, he didn't know it was AI. And secondly, didn't even pick up on like kind of a little, um, Easter egg lyrics that were in there until we pointed it out to him and he's like, man, this is crazy. So, uh, I think that's an opportunity for business communication.

Obviously we come back to in this context of, uh, opening up creative doors where previously, you know, they, they didn't exist. So that gets to a really exciting, um,

Robert Plotkin: I, I wonder, you know, cause I, I'll say something else that I, I use in the legal context. And I wonder how it applies with associations, which is that, you know, lawyers are known for speaking in jargon.

Uh, we have our own language essentially, and that can create a barrier for communication with clients or even sometimes with other lawyers. I'm in patent law, which has its own terminology and I do my best to make sure. I think I'm [00:22:00] pretty good at speaking in plain English to people, but it can be challenging.

And that's one way in which I've used AI. To take something that I write in my own words and translate it to be more understandable to somebody else. And I suspect when you deal with associations, particularly ones working in a very narrow field, Or maybe just from being in the non profit world. Maybe there's a certain lingo or jargon that people use that may make it difficult for them to communicate with either their members, or funders, or other people.

Does that resonate at all?

Amith Nagarajan: 100 percent You know, the opportunity to reach more people, to reach them where they are at in a form that they can comprehend and absorb. Whether it's a different modality like taking text and converting it to audio for people who don't read written words well, or it's just preferred for them to listen.

Uh, or perhaps from one natural language to another from English to French to Spanish or from one level of expertise to another. So you might take a medical domain where a doctor is speaking to another [00:23:00] doctor. They might speak differently to someone outside of their field and certainly differently, at least hopefully so, to someone that's a patient or the family member of a patient.

And so there's an opportunity around content. Where you have an asset, like, you know, take a particular branch of medicine, well, there's an association for that, and they might have some of the best content on the planet in that particular vertical, uh, domain. And so the opport and usually it's deeply technical, because it's related to the people who are the practitioners of that discipline.

And so being able to translate that in an accurate way, but still in a in a different levels, right, depending on the educational level or the context, I think is a really powerful modality. These are all different modalities of communication in my mind. Uh, and that's part of what's so exciting about this is we've unlocked language and unlocked communication effectively more broadly.

And so for associations, at their core, they're communications machines. So it's, it's super relevant to them in my mind.

Mallory Mejias: Going back to copyright of AI generated content, [00:24:00] Robert, I just want to dig into that a little bit more. I know your expertise is with patents, but just to kind of have this conversation and explore it with you, you said the key question to consider was, What was the human contribution in this piece of work?

And in my mind, I'm thinking this is a really great area, right? Is it a percent of human contribution? Is it yes or no? Was there contribution? Was there not? Could you argue that even just giving an AI model a prompt is significant enough human contribution? So I'm guessing this is a question that the courts will need to answer within the next few years for sure.

But have you seen any of these questions answered particularly with patents already?

Robert Plotkin: Yeah, you know, so far the, the question has been answered somewhat differently in the patent context than in the copyright context. Uh, I believe that the current answer from the U. S. Copyright Office, uh, is that you need to identify, like, which part of your, the work was AI generated and which part was human generated, which I think is a really [00:25:00] unfortunate, uh, solution.

One, as a practical matter, it's, it may be impossible to separate. And secondly, I don't think that's really the right answer from a public policy perspective to say, uh, these words were written by an AI. It also doesn't encourage people to make the best uses of AI and writing, which is to focus on what Amith said.

Come up with your unique ideas. Who I would say if, if we want to get the resulting work out to the public and as widespread away as quickly as possible, why should we penalize someone if 90 percent of the words that came out were quote generated by AI? As long as there was a person who put their unique, uh, thoughts and, and spirit and personality in at the front.

And as you said, Mallory, perhaps even if it was just or primarily by putting in a prompt, I think that's the [00:26:00] wrong way to go. And I hope that things change on the copyright side on the patent side. Uh, you know, so far it really hasn't been answered. By the patent office so much, or even by the courts, it's really being decided on a case by case basis, primarily based on the, the patent laws requirement of what's called non obviousness, which is a little tricky to decide.

But basically what it means is you submit. A patent application for a new mousetrap. You have to demonstrate not only that that's new, that no mousetrap like that has existed before, but that there was some ingenuity, uh, required my, my patent lawyer friends would not like me using that term, uh, but that there, there was some, uh, uh, Uh, degree of skill required that went beyond the norm to create that mousetrap, or [00:27:00] perhaps that the mousetrap would be surp if you showed it to a person who norm a mousetrap engineer who normally invents mousetraps.

If you showed it to that person, they would be surprised by how it works. That that would be one indication that the invention is what we call non-obvious and therefore patentable. So if you. Apply this to the context of AI, uh, one example would be if, let's say you have a new drug with a chemical structure, uh, you might ask, could someone have just taken an existing description of the function they wanted the drug to perform and put that into an off the shelf AI product and get that chemical structure out without any additional effort?

If so, It might be that that chemical structure is considered obvious and not patentable. Said a different way. Uh, you, I, you generally are going to have to [00:28:00] prove to get a patent that you couldn't create the invention you're trying to patent just by putting a sort of obvious or trivial prompt into a system like a chat GPT and get an answer out.

That's going to be.

Amith Nagarajan: Sorry to interrupt, I was just going to be a very interesting test to continue to apply as these AIs become radically smarter over time.

Robert Plotkin: It's going to be, yeah, and I identified this in the book years ago, uh, it's very hard even to apply practically because how is a patent examiner going to work backwards?

Essentially, uh, think about it that again, a let's use the example of a mousetrap. If you submit a patent application for a mousetrap and you say my mousetrap has a spring and a lever and, uh, all these different components, uh, yeah. Really, the patent examiner should ask, is that the kind of thing that anyone?

Uh, with, with what we call ordinary skill could have designed with [00:29:00] the push of a button using some off the shelf AI software. How is the patent examiner really going to do that? Are they going to need to sit at their desk with some AI design software and try putting some descriptions into it that are, that are trivial and see if they get out the invention that you're trying to patent.

It's going to be quite hard. It's going to be quite hard, but I'm not sure that there really is a better Way to do it. But I think at a high level, the question is for a new invention. Uh, is it something that could have just easily been generated by by off the shelf AI using a well known or trivial kind of a prompt or or other type of an input?

If so, not, I think not patentable. And you could say, That that's going to actually raise the bar for patentability as AI increasingly helps augment the inventive skill of people. It's going to raise the bar for patentability, but it's going to do something else at the [00:30:00] same time, which is it's going to make people more skilled inventors.

So it's going to be boosting people's skill as it's also leveling the playing field. And it's unclear how those two things are going to play out with each other. It's the same in all fields, you know, outside of the patent field, right? Whenever I hear people say, well, AI is going to make writers obsolete because it's raising the bar, and it's enabling almost anyone to become an average writer.

Yeah, but then skilled writers are going to use it and leverage it to become even more skilled. Both of those things are happening at the same time as each other,

Amith Nagarajan: you know, and I guess an interesting way to look at it. And, you know, we often talk about how the people. You know, people are concerned about job loss, and at the moment it appears as though, what I'm about to say is true, and it might change over time, but that people are unlikely to be replaced by AI alone, but they're very likely to be replaced by people who know how to use AI really well, to your point.

One, this is perhaps a little bit off the track, but I'm just curious, because I think there [00:31:00] is a relation to associations and the work they do, but you know, the U. S. Patent and Trademark Office, and similar agencies around the world. Uh, do you know, by chance, if they're embracing the use of AI to aid their work and thinking about the mountain of, uh, patent and trademark and, and copyright related issues or whatever else there, other kind of matters they're, they have coming through.

I know it's historically been a long backlog, even we do trademark work all the time and it takes months or years to get feedback. Do you think there's an embrace of the technology to help them? Because to answer the question you asked, I could think, Hey, let's take this patent application, take it to chat GPT and ask if it was not, not obvious.

Robert Plotkin: I know of at least two things that the two ways in which the U. S. Patent Office has been embracing AI. The first is to classify patent applications. So when patent application comes in, they have to decide what technology is this for. Is it for mousetrap technology? Is it for antivirus software? Is it a drug?

And then they assign it to the relevant patent examiner based on the classification about a year [00:32:00] ago, they announced they had developed. They had trained their own model internally for doing patent application classifications. I don't know if it's 100 percent automated. There's probably some human review after the fact.

But that's one way in which they're using AI internally. And then the tools for doing patent searching have been AI infused increasingly. They're getting better all the time, primarily for doing natural language searching. You can imagine traditionally, uh, there has, when, when the patent office gets a patent application, it gets assigned to a patent examiner.

I'll use the mousetrap example again. They have to decide. Is this a new type of mousetrap? How do they do that? They search for previous patents. They see if they find any that are for the same mousetrap that they're examining now. So to do that, they have to come up with a set of queries in a database.

There's an intermediate step of, of, of doing that. Designing the queries. And as we know that that takes a lot of skill when you're using a [00:33:00] traditional database, particularly if you have to use a query language like sequel or some other God awful language, you know, but now increasingly that middle step is being eliminated.

You can just take the patent application that's been submitted and use it as if it's a query. It's the query, right? Maybe you do something else, but things are heading in that direction and it's eliminating the need to have this special querying or searching skill or at least reducing the importance of that.

And I know the U. S. Patent Office is using AI, sort of AI infused. As you know, it's hard to define AI. You could just say it's based on natural language processing or, uh, more natural language based searching for prior art. Uh, but I'll say this, and, you know, I may need to be tactful, but it is somewhat related to associations.

There's a big association within the Patent Office, which is the Patent Examiner's Union. And often there is a tension to say the least, uh, between the [00:34:00] union and the development and adoption of new technology, at least in part because of the reason you mentioned fear of job loss, uh, concern about that needing to be retrained, change how things are done.

So, uh, I don't know a lot about the details of how that's played out within the patent office, but I know that it's a perennial issue there. Uh, that, uh, That there is the I'm not making an anti union statement. Actually, I'm just saying that that is a fact. And sometimes that comes into play.

Amith Nagarajan: Well, I think there's a natural tension amongst any number of people or groups that have, you know, aligned misalignment essentially in terms of what they're naturally thinking about.

And so I think there's there's opportunity for unions to be incredibly Uh, forward looking with a I and help train their legions of workers in their fields on a I to be more competitive and more productive. And there's obviously the other side of it as well. So I think it's gonna be interesting to see how that particular Sub segment of the world we live in and [00:35:00] associations, uh, you know moves moves ahead I appreciate you going down that quick path because they're super Those processes those two examples of augmentation within the patent office are super relevant to associations They're both examples where they've taken existing processes.

They have not automated the processes, but they've augmented Human labor with A. I. Tools to eliminate perhaps some of the least interesting parts of the work that classification element takes a certain level of skill to do it correctly and to route it down the right path. So it's not, you know, if it's in the backlog of someone's cues, a software expert and it was a drug application or something for a drug patent and it got there, Now it's got to go to the back of the queue for the drug person.

So I think that's a really important process, yet one that is obviously very relatively low hanging fruit for an AI perspective. Similarly for associations. Many associations deal with high volumes of applications for content, where if they run a scholarly journal or if they run a large conference, they have submissions of proposals for speaking, proposals [00:36:00] for journal articles, et cetera, and they have to go through a very long process and a very complex process.

So similar opportunities exist in this realm. So, but, uh, thanks. Thanks for going on that path. I

Robert Plotkin: wonder if it raises another point that's common to my world and your world, which is that this demonstrates that the kind of fixed mindset, you know, is, is, um, is a mistake. That there's probably a lot of applications in the context you talked about.

Maybe that people don't submit because they know it's going to take so long. Let's not even bother. And then by speeding things up, you could expand the number. There are many ways in which a I actually can create increased demand or supply and having this fixed mindset that Oh, if we reduce the amount of labor, there's required per task.

That means there's going to be less total work to do, I think, is a mistake. It may [00:37:00] be true in some cases, but it's not always true. I mean, in the legal context by using a I think to provide legal services, it may create An increased demand for either new services or the ability for people to purchase existing services at a lower price that they wouldn't have even bought before.

There's all kinds of ways in which the demand is elastic, in a sense, is what I'm saying from an economic point of view that people sometimes overlook. In their fixation on this. Oh, the A. I. Is going to take away work and thereby decrease demand for human labor.

Amith Nagarajan: That's a great segue into something we wanted to talk about.

Um, in that, you know, when we think about patent and patent, both filing a patent and eventually potentially protecting, Um, you know, you typically think of, uh, large budgets, you know, it's expensive to get patents and you talk about, um, your world of doing this work for organizations of various sizes, you know, so this, all this gender of AI is likely to make, uh, you know, at least [00:38:00] certain portions of your workflow, um, simpler, easier, faster, more scalable.

And so. You know, if there was a fixed number of patents that could be created in the world, um, then, of course, you know, you might have, uh, an existential threat to your fundamental business. Uh, but if, if the theory is, you know, upheld and has so far throughout recorded economic history has been true, the demand is essentially insatiable and correlates to, you know, lower cost driving increased demand when, when there's a product or service that's novel, right?

So you have this happening over and over throughout time as. Technology disruptions have occurred. Um, you're going to have more companies essentially coming to you, more associations maybe coming to you saying, Hey Robert, can you help me with a patent? It'll cost now maybe a third of what it might have cost you know, 10 years ago or something like that and maybe there's more opportunity to get patents.

So, have you seen any evidence of that in your own practice or in other practices kind of adjacent to yours?

Robert Plotkin: Yeah, I mean, I'm start just starting to see it. It's really at the very early [00:39:00] stages. And I would say that that we are already, uh, working on modifying how we perform services, offering new types of services.

We're exploring all of the different ways in which AI can help us to evolve how we provide to make them more readily available. It's it's it's early days, but I just want to I want to I always like using a couple of examples of what you talked about when you say through economic history and how easy it is to fall into this trap of thinking that there's fixed fixed demand.

You know, Bill Gates very famously said it might have been in the 80s. No one would. Why would anyone ever need a computer with more than 640 K of memory? And so for people out there don't I mean, that is what a, uh, uh, is it a millionth of what most computers have now? It's a tiny, tiny fraction, right? Uh, and so it's, and he's a smart guy, you know, and yet he somehow fell into this trap of [00:40:00] thinking, how could we possibly expand?

I mean, when I was growing up, we had a handful of television networks and I, and then cable came along and you had what, a hundred channels. And I think many people thought, why would anyone ever need more than that? Well, all of us now have the equivalent of what, millions of channels through the internet television.

And there's no sign of the demand. As you said, it's insatiable. It's insatiable. So what people now are looking at AI and saying, Oh no, this is going to eliminate the need for people. I'll just put it in context of, of invention and patents, which is that this is my belief. It is backed up by history. I can't prove it going forward.

forward that there there is no limit to the number of new problems we will find to solve and tackle as we solve old ones. So even if I gets really good at solving our existing level of problems, you know, people are really not just ingenious, but motivated. To try to tackle the next higher level problem, [00:41:00] and then they'll, they'll sit on the back of a I to help boost them up to do that.

And I don't think there's ever going to be an end to that

Amith Nagarajan: to build on your Bill Gates story. You know, in addition to the his famous quote of, you know, 64 K should be enough for anyone or something along those lines, which is kind of crazy to look back upon. He's also, I believe, that out of the between him and Paul Allen, he was the one who said, Are B hag is going to be a computer on every desk and every home.

Um, And that beehive seemed totally outlandish at the time. So the reason I bring that up is because you can both be extraordinarily visionary and have blinders on at the same time. And we all have those issues. We all have these biases that lead us down these paths. And, you know, that's one of the things I think I can help us do is to tell us if we're missing something right to give us feedback on the work that we do.

That's one of my favorite use cases is work that I've done. I'll feed it to the AI and say, criticize this. Give me a critique of this piece of software or this, you know, writing or whatever the case may be. Um, you know, one of the other things I wanted to [00:42:00] quickly mention is in the talk that I give on AI, I start off with economic history and over the last thousand plus years, when we look at the growth of global GDP on an inflation adjusted basis, it took basically all of recorded human history to get to, uh, to through 1700 or so to get to one trillion.

And Global GDP. And then it took about 250 years from 1700 roughly to 1950 ish to get from 1 trillion to 10 trillion in global GDP. So, you know, basically infinity time of our species then compared to 250 years for the next 10x increase. But what's even more striking that is from 1950 through now, which is, you know, 65 plus, 70 plus years, We went from 10 trillion to 100 plus trillion in global GDP again on an inflation adjusted basis.

So the next 10x order, order of magnitude increase happened in 65 ish years compared to 250. So what's it going to take for the next 10x increase, right? And that's highly speculative to say, as you just pointed out, we can't write the future the way we can look at the past. But it's, there's a pretty good trend [00:43:00] line there.

And with AI being an accelerator for creativity and opportunity, Uh, demand is likely to drive that because that's a story of demand. It's not a story of anything else. It's showing that 130 plus trillion global GDP, um, compared to one trillion, not that many years ago, um, is a story of demand being insatiable, really saying the same thing you just said.

Robert Plotkin: Yeah. I mean, I would. I think that for a lot of associations, uh, you tell me, particularly nonprofits, one of the things that they struggle with is there's people out there who could benefit from their services who can't get access to it, right? For geographic reasons, for economic reasons, for all kinds of reasons.

And so, you know, to the, anything you can do to expand the ability to serve those people, uh, and, and legal services, you know, it's usually talked about in the context of, you People not being able to get their basic legal needs met for criminal defense or domestic relations or getting a will drawn up or anything like that.

But there's so many [00:44:00] legal needs where people can't access them because it's out of their mostly economic reach. In some cases, there's not a lawyer locally who they can access. Obviously, the Internet has helped a lot with that. But There's so many opportunities to be able to expand the reach of, of services in law.

And I would assume for a lot of associations as well.

Amith Nagarajan: A hundred percent. I think you've actually identified one of the core opportunity areas for associations to grow, which is to do a better job of connecting supply and demand in their verticals. So if you take the legal profession, you say, Hey, think about the bar associations that exist all over the country and all over the world, whether their specialty around, you You know practice area or their geographic based One of the functions they serve is a lawyer referral service, which exists also in very various medical domains And these things are very very traditional, you know Sometimes there you call up a phone number and someone from xyz bar association answers talks to you Asks you about the matter at hand and tries [00:45:00] to connect you with the right member Um, or you have an online version of that, which is very much like click from a series of drop downs, you kind of have to know the topics and then you may or may not find someone.

It's kind of like a Google search where, you know, if I'm in Boston, I'm looking for an IP attorney, I might find 600 people, right? Or whatever the number is. Um, and you and I, Robert met 20 years ago or whatever it was because a friend of a mutual friend of ours had worked with you And he said, Hey, you got to talk to Robert about some software patent.

I was interested in it, and that was just by happenstance. And you helped me with some software patents at my prior company, and that's how we got to know each other. But you know that that's very random in a way, right? It's it's it's this network. And can we take that juice right that made that connection valuable and scale that right?

And that's an opportunity for associations because they're at that nexus of the way. Both sides of the, of, uh, of that micro economy. So there's an opportunity there to create an AI powered, you know, professional networking resource that goes way, way deeper than like, Oh, Robert's been in practice for 25 years and has a CS degree and blah, blah, blah, [00:46:00] blah, blah.

That's cool. But what's his personality like? What kinds of cases is he best at working at? You know, who does he like to work with? Right. And how does that fit with the potential clients? And that choke point exists in a lot of associations, I know, in their various, uh, domains. Uh, so that's just one opportunity category, and there's so many like that, because associations can act as this, you know, superhero intermediary, if you will, uh, to bring the quality of service higher and to lower the cost of getting to these people.

Because that transaction cost is a big reason why people actually have so much overhead in their business, is because they have to spend so much time with the wrong kind of intake. And associations stand to benefit from that themselves if they do a good job with it.

Mallory Mejias: Robert, I know you recently wrote a book. I think at the time of this recording it's available for pre order, but perhaps by the release of this episode it will be fully available. It's called AI Armor. Can you share kind of a high level overview of that book and maybe some insights that might be most relevant for our [00:47:00] nonprofit and association listeners?

Robert Plotkin: Yeah, the book is Uh, a strategy guide to using intellectual property to protect A. I. Innovations. So the audience is primarily companies and other organizations that are developing new types of A. I. Technology. Uh, the types of companies that would be my clients who want to obtain patent or trade secret protection, leverage that to, to raise funds, to, uh, to grow their businesses, to secure a successful exit.

Uh, one thing I'll say is that one of the motivations for the book, was to address and bust some myths about patents and intellectual property, which, which some, which, which often cause innovative companies to not pursue intellectual property protection because they, they hold these myths. One of them is that you only obtain patents if you're planning to use them to sue your competitors to stop them from competing with [00:48:00] you.

And I deal with a lot of companies and they say, Oh, we, we don't need a patent. We're not planning to sue you. Sue anybody. We don't want to sue our competitor. And I say, well, 99 percent of my clients never do that either. Most of what patents are used for is to one signal to potential investors or partners or to the public or to your customers that you're an innovative forward thinking company.

It can also signal to investors that you have, Amith, I know you mentioned, you use this term in your book, that you have a moat. Meaning when an investor says, before I pump some money into you, what kind of reasonable assurance, not a guarantee, but what reasonable assurance do I have? That another company, particularly some tech giant of the world, is not going to see what you're doing, say, that looks good, let's copy that, put it into our product, and run you out of business overnight.

Now, there's a lot of different moats. Intellectual property is one of them. There are, there are others, you know, there's, there's first mover [00:49:00] advantage. There are network effects. There's all kinds of economic mechanisms that can be moats. We talked about data. Before your trade secret, proprietary data, your customer list, your, your brand, uh, those can all be moats, but patents serve that really valuable purpose.

They also are assets. They can be sold. They can be licensed fairly freely compared to things like trademarks, which you can only assign when you, when you sell the business for the most part. But I have quite a few clients who have obtained patents and then licensed them to other companies, meaning. Uh, charge a fee for the ability to use that technology.

And then they also become really val valuable in valuation of a company, uh, particularly when you're looking to get acquired, uh, go public or have some other form of exit. So that myth that intellectual property is only valuable if you're gonna use it to sue, and if you're not looking to sue, you don't need it or wouldn't benefit from intellectual [00:50:00] property is, is one of the motivations I had.

Uh, for that book. But I think the way it would relate, you said, you know, what would your listeners get out of it? I think it's the higher level concept of a moat, even though I think the moat I'm focused on in the book is primarily relevant to tech companies that are developing new forms of technology.

The concept is applicable. And I mean, I say here's where my book and your book are aligned. It's relevant to any business. Any business, really any individual has to ask, Uh, you could call it, it goes by so many names, unique value proposition, uh, as an individual maybe, or what, what gives me my competitive advantage?

What's going, what is it that was going to draw customers or members or funders to me rather than my competitors? Why am I not a commodity? And if I'm not a commodity now, why won't I be a commodity in a few years as a result of [00:51:00] AI, right? How can I maintain that moat, that distinctive, competitive advantage over an extended, sustainable period of time?

I think that's, that's where what I write about and what Amith you write and talk about and work about, uh, overlap with each other.

Amith Nagarajan: Uh, I agree completely and I think the idea of IP generally as an opportunity to build and strengthen, emote is a really critical concept and intersection of, of our content areas.

And when, when I think about associations and their opportunities looking ahead. I think about the types of services that their fields will ask of them or will ask of the world, the things, the unmet potential demand that's out there. Um, so for example, in a particular professional area, uh, instead of just providing, you know, once a year conferences or multiple times per year conferences or fairly static educational courses, there's a need for a much more dynamic, [00:52:00] interactive, Almost copilot, if you will, for that sector where the association has an opportunity to potentially publish a copilot for that's for that field and assistant for that field and they have the brand they have trust and credibility in the space.

Oftentimes in that particular discipline, they have deep content, deeper content, uh, Then most others would have. But the combination of the brand integrity they have in the field coupled with expertise, um, you know, could be very interesting. And so we think about, like, imagine the top 100 smartest members you have and their collective make, you know, brains being merged together and then being available as an A.I. Assistant for your entire field that elevates the entire profession, whatever that profession is. And so my question, and this is a very common discussion, right? This is a common idea that people in the association market are thinking about. Um, there's the customer service side of it, which I find much, it's, it's interesting in terms of the value it creates, lowers friction, etc.

But it's much less interesting than professional knowledge assistant. [00:53:00] Um, when you hear about that idea, do you think about, um, potential patent protection or there are other forms of IP protection that could help an association establish a moat if they built that kind of a co pilot or assistant around their professional expertise?

Robert Plotkin: There could be something patentable in there, and I have been working with some clients on it. I say could be because. If the method you use to produce the copilot is generic, what I say, you've got some core, let's say chat GPT, and you've got a bunch of you use a process where you gather up your unique Knowledge you and you build the, you build the product, the copilot in a conventional way, then that's probably not going to be patentable.

But the fact that you're using your unique knowledge, wisdom, data, knowledge. other things to produce [00:54:00] a co pilot that is actually more useful than something else. Uh, you, you will have a commercial competitive advantage and you're going to most likely want to use trade secret protection, maybe some copyright protection on the input side.

Um, and then, you know, I don't know how associations are dealing with this, but in the private. Commercial context. Very right now, there's a lot of talk and debate and experimentation with what happens on the output side, right? Obviously, these systems of all they're living and they develop. They're not static, as you said already.

So once the copilot produces data, I mean, very often you want to retrain based on that or update based on that. And then, you know, there's going to be some question. Who owns the output? Who has rights to use it? Is it licensed? Is it? Is that maintained as a trade secret somehow? Is that? And very often that's going to be governed as much by contract, you know, an end user [00:55:00] license agreement or something else as it's going to be by core intellectual property like copyright or trade secret.

Amith Nagarajan: Let me pare it back what I think I heard just to make sure I've got this right. So in the context of the example I gave, patents are probably not the route that would make sense there because there isn't anything. Uh, in that mix that the association has created, the underlying AI might be, you know, interesting, but they typically wouldn't have built their own model.

They would have leveraged something out there and then fed their content to it. But there's other routes for IP protection through trade secrets protection, possibly copyright, um, that could indeed make something, an asset of that nature, indeed, a strategic mode, even though there's not necessarily patent protection available for that category of innovation.

Robert Plotkin: Yeah, you said it much more succinctly than I did. Thank you.

Amith Nagarajan: And then the other related question is, we have some clients we're working with, um, who are associations and to extend on the, the concept that is described, they actually want to build some additional [00:56:00] capability on top of a base copilot where they want to say, Hey, listen, in my field, um, I want my copilot to help clients, their clients, right?

Not the associations and customers. with building new products in their field. They might have this expertise around how to formulate a new product, a new chemical, right? Going back to the drug example or a new consumer good of some sort. And these co pilots go beyond the idea of simply knowledge bots that can talk to you chat GPT style, but they can actually help you create something.

I bet that was an interesting thing to bring up in this podcast because there's an IP question around that product itself. That's like, let's call it a super co pilot. Um, but then there's also the question of who owns the IP it generates, you know, the, and obviously by license, you can determine if there's an assignment or whatever.

But, um, what are your thoughts on that scenario?

Robert Plotkin: Yeah, it's very interesting going back to, to the book I wrote in 2009, the genie in the machine, that co pilot would be an example of what I call the genie. And then I explored, do you patent the genie? Do you keep the genie as a trade secret? To [00:57:00] use a different metaphor, I just published an article on IP Watchdog about the genie.

Um, evaluating patent versus trade secret for AI, which I use the analogy, if you remember the old Aesop's fable of the goose that laid the golden egg, uh, you know, which is the analogy there is if you have this co pilot that can design new things, whether or create new content or potentially create new patentable inventions, one option is you keep that co pilot secret and hidden.

That's the goose laying the golden eggs, right? And then it produces the golden eggs. The new inventions, the new useful things. Maybe you sell those publicly. Maybe you patent those. Maybe you license them. Who knows? But you can do, you might want to do that. While you're keeping this goose laying golden eggs for a long time in secret without revealing to anyone else how it works.

There's a bunch of trade offs involved because you might want to patent that as well. One reason you might want to patent is if you think someone else might figure [00:58:00] out how to create that same copilot in the relatively near future. Uh, maybe it's better to patent it because a patent will give you protection against someone else who invents after you filed your patent application, whereas a trade secret won't.

So, so if you, if you keep that copilot as a trade secret, you're sort of making a bet that the idea you came up with is something other people are not going to figure out in the near future. And it's hard to predict the future, but I think, uh, people make, you make your bets and you do, you do, you do your best, but I think one of the trade offs in terms of patent versus trade secret protection, even including whether you, you know, you don't necessarily, you may not have to make the, uh, output public.

I mean, it depends. Uh, you might. [00:59:00] Yeah,

Amith Nagarajan: that's a, that's a really interesting, um, angle on it. And I think that for associations thinking through this. I want the listeners here to, first of all, recognize they have a valuable asset somewhere in there and that there are opportunities to create monetization schemes around this in various ways.

And there's ways to protect that asset in various ways. Um, but what isn't protectable ultimately would be, you know, a scenario where you do nothing. And that's why I'm saying that from a business perspective. So if you simply have your content sitting there and you're saying, Hey, we've got a great brand and we've got great content.

Uh, Um, and someone else has okay brand and okay content, but they do this and they make their content super charged with super copilot. Um, even though your content is the excellent content and the next guy's content might be the very good content, the very good content put into a novel format with better intelligence around it is likely going to run circles around.

Uh, with the better content, sitting still [01:00:00] will do. Um, you know, one thing that I wanted to extend in this conversation is when associations are thinking about, um, their approach to IP protection, Um, they're also thinking about the flip side of it, which is how do they defend against other people taking advantage of them, uh, taking advantage of their content or their assets.

Uh, what are your thoughts on, if you're, uh, an association, you have years of journal articles and other things, um, What, what's your point of view in terms of how you create like a defense, defensive strategy against potential misuse in the age of AI?

Robert Plotkin: Well, you know, this is a very active question right now in the copyright office, in the courts, it's really evolving very rapidly.

Uh, probably you and your listeners are aware of, uh, you know, the big New York Times lawsuit against OpenAI, this question of, well, a lot of the big models out there were created by being trained on [01:01:00] publicly available data on the web. They were made possible by the fact that the web exists and there is freely available content out on it, lots of it.

And the fact that these models have now been created and are being used on their own, independently of the content that they are creating. That was used to train them is causing a lot of content creators and owners to question, should we keep doing this? The, this being publishing everything online for free.

I mean, this has been a question since the beginning of the web, right? I mean, uh, newspapers, uh, Grappled with it in the beginning. Should we be putting our stuff up for free? A lot of them, I think, answered that the wrong way for themselves, but it was a legitimate question. They had a business model that worked for them for a long time, you know, decades, at least, if not a couple of centuries, and then they were up against a totally new technology and set of business models, which relied on giving away or making available lots and lots of stuff [01:02:00] for free and and Ever since the early web, uh, journalists and, and content creators and content creation and own owning organizations have been grappling with it.

But AI models take it to the next level, because then once the model exists, it potentially can be used and be valuable. I don't want to say more valuable than the original content, but the nature of the, uh, The technological and business and economic relationship between the content creators and owners and the AI companies and the models they create that are trained based on them is very much in, in flux right now.

I'll say that to say the least, but I guess going back to your question, it raises the question of, I think you need to ask yourself for every piece of content you create. Should we make it available publicly for free? More so than people have been asking that question, I think, for the last 30 years. Yeah,

Amith Nagarajan: [01:03:00] that's a great point.

I think people need to put some thought process into it. And associations are famous for creating tremendous amounts of governance and structure around every decision. So, I think it's important to be nimble with this because you have to have a volume of content constantly going through so you can't, you know, run everything by a committee necessarily, but I think some kind of a, uh, a very light and nimble framework for conceptualizing what to consider publishing, what not to, uh, could be very, very helpful, um, something along those lines I think would be a great asset for associations to be, uh, to build and to, to take advantage of.

Robert Plotkin: I mean, there are people who think that, uh, even if you have an organization that's got really great proprietary data, that An AI system will sort of generate the equivalent of it in the near future or that someone else will generate, generate that. And so you can't really maintain a competitive advantage based on your data.

I personally disagree with that. I can't prove it. But I [01:04:00] suspect, and this is just a suspicion that might also be wrong, you know, and I think this is where you're heading. But, but tell me if I'm misinterpreting you, that if you are an organization and part of your value, Is this unique, really valuable data that you have, that if you marry that with a I and think carefully about how you do that, both from a technological and business model perspective, you could then keep building on and developing and leveraging that original core that you had to maintain and increase your relevance and value over time.

Is that fair? That's

Amith Nagarajan: exactly right. I mean, that's what we're proposing. Most associations. Consider because, you know, they're essentially associations act and, you know, there's several capacities, but one of the which is knowledge center for their domain. So being Kind of the expert resource in a given field, the connector, uh, connecting people to people, and also people within the profession, the people who want access to professionals in the space.

Um, and, and also there's a social element, but, um, you know, those, those core [01:05:00] functions, I think, are amplified by AI. They can do them at scale better than ever before, as opposed to looking at it from the viewpoint of a limited pie or that fixed mindset you mentioned earlier. Um, so that's the opportunity that's out there.

The other thing is, is the association on a daily basis goes from being really administrative in nature, where they're processing membership transactions or event registrations, to actually being relevant in the mind, in the eye of the profession. Uh, on a daily basis. You know, most people who deal with, you know, attorneys deal with their bar association to make sure they have enough C CLEs, you know, to stay certified for the next year or whatever.

They're not really thinking about the bar association as part of their daily practice, nor is the medical professional in a per a particular specialty area of medicine. But if the association could leverage and harness that technology coupled with the content that they uniquely own, that could be a reason, a legitimate reason from the perspective of the audience to engage with them on More than episodically.

So I find that exciting. I think many associations have a significant opportunity in [01:06:00] front of them. Uh, the alternative is, is that people go to the good enough content. What I mean by that is Google Gemini or ChatGPT or whatever else is contemporary in terms of the way you engage with it. Uh, and not quite as good as what the association should be able to create.

Um, but good enough, um, and increasingly better, right? You know, CHATGPT, I know there's a famous example last year sometime where an attorney, uh, composed some kind of brief or something and cited cases that didn't exist, but of course that person, I don't think, actually checked any of the work, and that was an early version of CHATGPT.

But it's kind of a beautiful example of what could go wrong if you don't, you know, have Reasonable, you know, discipline and using these tools. You know, it's like I always tell people Imagine you just got like a really really smart college grad brilliant person works hard never rests, you know, and there's they're amazing They're encyclopedia, you know the kind of knowledge Uh yet they make mistakes and so would you take that person's output and just publish it directly on your website?

Or would you actually take a look at it? I'd recommend you take a look at it just like you do with ai So [01:07:00] anyway, I digress but the point is is I think there's this massive opportunity for associations to do exactly what you described.

Robert Plotkin: Yeah, I would love I would be drawn more to the bar associations if they did exactly what you just talked about

Amith Nagarajan: Yep

Mallory Mejias: I've got to insert a plug here If all our listeners are enjoying this conversation around what it means to stay relevant and thrive as an association what it means to be We're having these exact conversations at Digital Now this year, which is October 27th through 30th in D.C. at the Omni Shoreham Hotel. And we'll be talking about this conversation, essentially, and leveraging your competitive moat. So you can get more info on that at digitalnowconference. com. Robert, so much for an incredible conversation today. I know I have learned a ton. Amith, I feel like you've probably learned a ton as well, and I'm sure this will be really insightful for our listeners.

Um, so thank you so much. And can you let everyone know where they can keep up with you?

Robert Plotkin: Yeah, absolutely. The feeling is mutual. Uh, I learned a lot from both of you today. Uh, you [01:08:00] can catch up with me on LinkedIn. I post there all the time. LinkedIn. com slash in slash Robert Plotkin. Follow me there. Message me there and also on our website.

BlueShiftIP. com. You can learn about how to use IP for your growing tech company, or if you want to contact us if you might be in need of patent or intellectual property services, you can contact us, schedule initial consultation with us, BlueShiftIP. com.

Mallory Mejias: Thank you.

Mallory Mejias
Post by Mallory Mejias
May 2, 2024
Mallory Mejias is the Manager at Sidecar, and she's passionate about creating opportunities for association professionals to learn, grow, and better serve their members using artificial intelligence. She enjoys blending creativity and innovation to produce fresh, meaningful content for the association space. Mallory co-hosts and produces the Sidecar Sync podcast, where she delves into the latest trends in AI and technology, translating them into actionable insights.