You Ask, I Answer: Zoom AI Policies?

In today's episode, Helena asks, What do you make of the Zoom AI kerfuffle? So, for those who are not familiar, Zoom, the company that makes the uh ubiquitous video conferencing software changed its terms of service to say they would use customer data to train uh their language models to train generative AI. This, of course, created a quite the firestorm of people saying it was a violation of their privacy and so on and so forth. Zoom then retracted that policy uh and altered it to be exactly the opposite, actually, to say uh from now on, we're not going to use customer data to train our AI. This raises a much bigger issue for pretty much every company.

Pretty much every company, uh, but especially companies that are in the tech space that provide tech services, are scrambling to have and find and gather up unique data sources. Here's why. Most of the large language models that are out there, like open AI's models, like the Lama family from Facebook, et cetera, these models are all trained on public data, which means that there really isn't a big competitive advantage for one company to use one model over another, right? If you were to take one of these models and tune it or train it on your company's proprietary data, the data behind the scenes, that could give you a competitive advantage. Your model might be better at asking and answering the kinds of questions and content generations that are unique to your business, unique to your way of doing things.

So it's no surprise that we see companies like Zoom and many others saying, hey, we're gonna do what we can to leverage the data we have access to to make a model that works better for our specific use case. You can think about it in the video conferencing space, right? How many different companies there are in the video conferencing space? How many companies have all this transcription software of one kind or another? And could they use that knowledge base to get better at transcription, to answer questions, to predict the topic of a call, and so on and so forth.

The company that leverages data the most smartly would be able to offer that as a service. Now, Zoom kind of went out about it the wrong way. The wrong way was just to make a change to the terms of service and just essentially force people into that policy. That's not a smart way of doing it. And they found out the hard way that a lot of people really don't like that.

The right way to do it is to acknowledge the value of the data, right? If you are running a piece of software and you are collecting user data and you want to leverage it, ask users to opt in and maybe offer them an incentive, right? Say, like, hey, we charge, you know, $300 a month. We will knock $25 off your uh fee every month if you opt into this plan that allows us to anonymize and use your data to train uh some kind of AI service. That would be ethical, that would be lawful, uh, compliant with privacy policies, and it gives users the choice to say, like, what is my data worth?

Uh if I say, hey, I think my data's worth more than 25 bucks a month, you don't opt into it. If you say, you know what, 25 bucks is 25 bucks, I'll take it. Uh particularly if it's maybe on a per seat basis, it might be a considerable savings. Say check the box, yes, I'm in. This is going to become a bigger and bigger problem for everyone as AI continues to proliferate everywhere.

As everyone wants to have their secret sauce, their secret model, their secret library of training data that will improve the performance of foundation models. And that's really important. Again, that you should expect this kind of strategic pivot. And not necessarily the way Zoom did it, but just in general, companies saying, you know what, we need to get better at using this data. We need to get better at um, we need to get better at making use of the data to make our our AI smarter for our company.

And the companies that do that the best will have better AI that generates better results, that creates competitive advantage. So my thoughts on it, ask people, ask for permission, uh, maybe incentivize participation. Definitely don't do it just by forcing everyone into it. That tends to never go well. But recognize that everyone and anyone who is aware of the capabilities of AI is going to want to do that and may even need to do that using customer data, using proprietary data sooner rather than later.

Thanks for the question, and thanks for tuning in. Talk to you next time. If you like this video, go ahead and hit that subscribe button.