Webinar Recap: Business Growth With Direct Customer Experiences in the Age of Privacy

1 year ago
Webinar Recap: Business Growth With Direct Customer Experiences in the Age of Privacy Image

In this discussion, CEOs Tim Hayden of Brain+Trust and Brad Weber of InspiringApps took us inside the world of customer data, privacy, and security. 

You can watch the webinar replay or skim through the conversation explored below.

The Importance of Data, Privacy, & Customer Experience

It’s a bold new digital world. AI and IoT are disrupting big tech, social media uncertainties abound, and security and privacy challenges continue to grow. Changes in data regulations will make it more difficult to learn about your customers in the future.

Whether you’re on the cusp of building your next app, maintaining a current app, or introducing an app into the marketplace for the first time, your digital product and your brand must connect with customers in ways that build trust and create engaging, personalized experiences.

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About Brain+Trust: Brain+Trust is a strategic consultancy empowering brands to compete at the speed of the customer and grow revenue. By helping brands and leaders make sense of an evolving marketplace, they can better understand their customers and grow their business. Brain+Trust Partners counsels companies and organizations with strategic consulting, governance and compliance, automation, product development and more.

About Tim Hayden: With more than 20 years of marketing and business leadership experience, Tim Hayden has been a founder of new ventures and a catalyst for transformational progress within some of the world’s largest brands. Part social anthropologist, part strategic business executive, Tim studies human behavior and how media and mobility are reshaping all of business. From operations to marketing and customer service, he assembles technology and communications initiatives that lead to efficiency and revenue growth. A past and current investor/advisor to technology startups, Tim works with entrepreneurs and ventures to capitalize on opportunities and shifts across many industries. He also proudly serves in executive board and volunteer leadership positions with non-profit organizations.

About InspiringApps: App development that makes an impact. InspiringApps builds digital products that help companies impact their employees, customers, and communities. Yes, we build web, mobile, and custom apps, but what we offer is something above and beyond that. What we offer is inspiration. Our award-winning work has included 200+ apps since the dawn of the iPhone. Our core values: integrity, respect, commitment, inclusivity, and empathy. Our guarantee: finish line, every time, for every project. Get in touch at hello@InspiringApps.com.

About Brad Weber: Brad Weber has more than 25 years of software development experience. Brad received his MBA from the Leeds School of Business at the University of Colorado and spent several years with Accenture before striking off on his own adventures, including the successful founding of four different technology companies. With a passion for software artisanship, Brad founded InspiringApps to build a team that could tackle larger app development challenges than he was able to handle on his own. His leadership creates an environment where the most innovative digital products continue to come to life.

Read the Transcript

Stephanie Mikuls

Welcome everyone. We might have people joining here, but we can go ahead and get started. Thank you for joining us today on our webinar: Business Growth with Direct Customer Experiences in the Age of Privacy. This is a joint session between InspiringApps and Brain+Trust partners. The first webinar in a series where we’re talking about the current landscape as it relates to businesses navigating changing privacy restrictions, evolving AI, and more. We’ll see where it takes us. I’m Stephanie, I’m the Marketing Director here at InspiringApps. Just a few notes as we get started, we are recording this, so I think you’ll see a notification pop up if you haven’t already. Hit OK, and then we’ll have time for some questions at the end. So throughout the webinar, if you want to enter any questions into the q&a panel, there’s a little modal at the bottom bar. And then Tim and Brad should take some questions at the end. I’ll kick it over to you guys if you want to introduce yourselves and share a little bit about each company, and then we can just dive into today’s discussion.

Brad Weber

That’s good. After you, Tim.

Tim Hayden

Thanks for that, Stephanie, and thanks to everyone who’s joining us or watching this and watching the recording. I’m Tim Hayden. I’m the CEO and founder of Brain+Trust. We’re a consultancy that helps organizations and brands leverage their first-party data. We see it as the order of the day, and that includes customer data platforms, hybrid cloud environments, and working with partners like InspiringApps to make what’s next possible.

Brad Weber

Awesome, thanks, Tim. I’m Brad Weber and the founder and CEO of InspiringApps. We design and build custom web and mobile apps for funded startups and large enterprises. As Stephanie and Tim both alluded to, we are here to talk about data privacy today and the challenge that brands face in maintaining or establishing relationships with their customers in that environment. So that’d be helpful to set the stage, provide a little context as to how we got here and where we are today to frame this discussion. I think if we if we go back long enough, the relationship between brand and customer was extremely personal. Tim, I know you have a story you’d like to share about that if you want to kick it off. 

Tim Hayden

Sure. You know, Brad, as I share with a lot of folks, I’m a recovering mobile strategist. Back in 2008 to 2013 or 14, I was really focused on companies building mobile experiences. Many times that was apps, and that was text messaging. But you know, everybody, I think that’s when some of the first conversations about personalization really started to bubble. And with it, I’ve started to remember back in the days of being a child and going with my mother to the grocery store, and the folks at the checkout line are back at the meat counter. The Butcher would actually know our names, would know our favorite cuts of meat, would know where I went to school or if I was playing T-ball, baseball—whatever it was. To me, that was the epitome of a customer relationship, right? It’s the reason we kept coming back because it was empathetic, and it was personalized, and obviously, where we are today with digital technology, I think we’ve really relegated ourselves to transactional clicks, shares, web traffic, you know, time spent listening. We try to quantify that as a customer relationship, and really personalization means more than that, and I think you agree.

Brad Weber

I do agree, and beyond the conversation with the butcher, and I can remember those days with parents grocery shopping as well too, brands were starting to collect data about us. Even back then, it could have been mail order history of learning what products were going to our houses. We’ve had grocery store loyalty programs for a really long time, where our purchases are being monitored in that way. And really, even just using the same credit card for transactions over and over again give companies some data to start trying to piece together a picture of who we are as consumers. But a lot of that was educated guesses until social media came along and really took all the mystery away, and consumers were willing to share personal information. Maybe we could use Facebook as a glaring example of that certainly, not only with one another but at the same time—they’re really sharing information with Facebook about what they did on their weekend, how active they are, what kind of dog they have you know, how many kids. Things like that show up on posts and photos, and so there are 2 billion people a day that are still using Facebook and 3 billion per month on a regular basis. So we moved into a phase where there’s a tremendous amount of activity and really a pretty willing audience, or willing user base, to share that data. And with that, you know, Facebook was able to really understand us in great depth. They could provide that information to companies either selling it or making it available to the brand, and that was related to your login with sort of entry into a particular platform. But once we added mobile and you talked to Tim about your experience as a mobile strategist, that really took things to a new level. So now we have a device, you know, a phone that we’re carrying with us everywhere. We’ve got it with us at all times. You add to all the information that Facebook had been gathering about us over the years—our location, some health data, and some other really personal things that the mobile devices make possible. And as I said, there’s really little mystery left in terms of who we are as consumers. So that was big business.

Tim Hayden

Absolutely. Yeah, no, I think you’ve said it, though, at the beginning when you were really quantifying the volume of users that are with Facebook. I mean, if you think about just how you opened up that account, and it asked you where you went to high school, where your hometown was. They started off at the beginning, being able to build some semblance of a network around you and then to be able to suggest people for you to connect to that had answered questions similarly. All right. And then, of course, everything you just outlined there in terms of our behavior, as the metadata, our location, the places that we eat, or we drink, we shop—all the things that we do to leave breadcrumbs in Facebook, as it’s an app that runs in the background if we allow it. It’s an app that, if you even allow the app on your phone, I do not, but you know, at the end of the day, we’re seeing the manifestation of, you know, probably a good 15 years of digitization of our lives. And where we have basically outsourced what used to be phone calls, what used to be saying hello to your neighbor, you know, what used to be very simple pleasantries and just orders of the day in terms of how we communicated have now moved over to digital means, and with that, it’s become quite noisy in quite a mess online. And that’s kind of where we are today, and what you and I can really address is not getting it all figured out and not just talk about all this happening today to clean it up, but the order of the day and what’s happening legislatively and also from a big tech standpoint, that’s trying to clean up that mess, right?

Brad Weber

Yeah, I think that’s important. That’s a good segue into an important topic, which is that I think after an age of great data providing on the part of we consumers and data collection on the part of social media and brands, some people in recent years have decided that we’ve gone too far. And so the EU was probably the most prominent to cast the first stone in that battle and new regulations for collection, use, sale, and removal of user data in the form of GDPR. And not long after, California was the first state in the US to implement similar regulations, and as we’ve talked, five others have since fall to start in January this year, so it’s definitely a trend in that direction. Combine that with Apple requiring developers to disclose the collection and use of data in their apps, even in the app store, before consumers are downloading or making their choice to install an app. And they’ve restricted the practice that Facebook has implemented to provide data about users that they didn’t know was being shared with app developers. And the financial impact on Facebook or meta was dramatic. About a year ago, their stock dropped 75%, which was billions and billions of dollars. It was astonishing. So clearly a move—Google has joined the fight as well by killing third-party cookies in browsers that we’ve used for decades to track users. And now we’ve got Apple, Google, and others who are kind of positioning themselves as gatekeepers to this consumer data. So that is, you know, it’s a big picture, and it is a big challenging picture for brands in order to try to establish these relationships with customers. So Tim, what are your thoughts about what’s behind the regulations and this backlash that we’re seeing now?

Tim Hayden

Well, you know what, I think we set the stage there in terms of if, for those of you listening and watching this, you know, the overall volume of information that a handful of companies, maybe two handfuls of companies, have been able to collect over the better part of a decade right now. There’s obviously people within government, as Brad said, as you said, you know, you’ve got this feeling that they’ve gone too far or they’ve gotten too big. There’s all kinds of talk about antitrust and anti-monopolistic moves and measures that governments can take to try to limit or rein in these companies. But at the end of the day, what I think is fascinating is these data privacy laws, the continuity between them. There’s a few things to your point. It started in Europe, and it actually was some Scandinavians and maybe Germany as well that started to have more rigor to data governance in terms of government oversight and the policies that were in place, but the Scandinavians called it what it was, they call it digital suicide, right? Your ability to go to a company and say, forget everything you know about me, or the freedom to be forgotten. And what each of these privacy laws you’ve mentioned? The five you’ve got—California, you’ve got Utah, Colorado, Connecticut, and Virginia. Those laws look very similar to what GDPR said in its initial versions and as its iterated and manifested in what it is today. And it comes down to four or five basic things, right? It’s what I already mentioned, you know, your ability to ask a company to be able to see the data that they have on you and, more importantly, to be able to correct it. Right. And not only that, but to ask the company to pause using it. You know, it’s kind of interesting because Facebook will give you the opportunity to take a break from a friend if you don’t want to see him in your feed. It’s fundamentally very similar, right, is to say, Listen, I don’t want you putting a display ads in front of me, I don’t want you to send me any direct mail or email—different than unsubscribe. I want to be clear about that. This is different than unsubscribe. And actually, the freedom to be forgotten is different than unsubscribe as well. But lastly, is this notion that we’re giving the consumer a total control of the data that they’re emitting from their devices and from their activity on websites, social networks, and apps as it is. And I think you brought up Facebook with iOS 14, I was 14.5. It was any brand that had an app deployed for their users. They noticed all of a sudden that dashboards went over the course of just six weeks. Their dashboards went all but flat because Apple had basically flipped the switch and gave all the control to the Apple user, the iPhone user, the iPad user, and the Apple TV, which was what I think a lot of people was their first time they see it watching Apple TV. Do you want National Geographic to follow your traffic between the website and apps on Apple TV? And most people said no. Still today. I think it’s somewhere near 80% of folks have said no; I don’t want that tracking. So that’s what big Tech is doing what I just said but the data privacy laws themselves. When you think about it, what it is it’s a prescription for companies to get their data in order, to structure their data. And you and I know what that means. That means that you can with structured data and clean data, organized information, all of a sudden, you can bring automation to bear. You can bring artificial intelligence and machine learning into your organization to help automate some of your business operations and just to the point, I think we’re talking about today, how to personalize, if not individualize many of the customer experiences that your customers have. So while it may seem freaky and almost big brotherly when we talk about personalization, and others talk about it. It’s actually the thing that companies have to do in order to be able to comply with a lot of the legislative and the rulemaking that governmental bodies are putting in place.

Brad Weber

And we, as consumers, want some of this right. I don’t think that either one of us are suggesting that data collection in its entirety is a bad thing and that no consumer wants that. There are benefits, and you alluded to this as well. There are usability improvements that come potentially from the data that’s collected to personalize your experience with a brand or in an app, or on a website. There’s also financial reward—even if you go back to the grocery store loyalty program that I mentioned, you’re you’re sharing data about your purchases in exchange for a discount on the goods that you buy. We continue to see that pattern on both web and mobile today. So legitimate reasons for collecting it. Would you agree?

Tim Hayden

I totally agree. I mean, I think, you know, that what the responsible brands of the world are doing and the ones that are doing it right with compelling, relevant content, and, you know, user experiences and customer experiences that have gleaned insights through whatever way possible. Whether that’s surveys, it’s polls, it’s post transaction, questionnaires, and being able to understand your customers really to build, and I’ve mentioned it before, empathy, to just kind of put yourself in their shoes and ask them questions. Why are they buying from you? It goes beyond net promoter score. CSAT scores, those kinds of things. The companies that have done them, I think, are the ones that continue to have trust and confidence with their audiences. And with that, the opportunity to continue collecting data in many of the ways that they have in the past. And I think that’s where this whole notion of that direct experience, right? And if we could just peel back for a second. Think about Facebook, right? And think about Twitter, think about Instagram, Tiktok. You know, this is what the advertising world has always known that there are mediums. There is something between the brand and the audience, and we have to pay to get there. And a lot of people say I like to fish where the fish are, right? They’ve always thought that when, in fact, what the app world both with websites and with mobile apps, and let’s be honest, what else is mobile the watches that we wear today, our cars are connected, myriad channels or places and venues now that have app opportunities. Those are actually the big, I think, opportunity right now for a brand to tailor the experience, right? To provide a utilitarian not just a sales channel but a utilitarian and much more meaningful relationship with your customers. Those that you know and those that you can, you know, think about in a funnel like way that are on that journey to becoming not just a customer once but a repetitive customer, a return customer and putting some type of utility in front of them that allows you to collect data, and of course, double down on that meaningful experience.

Brad Weber

Yeah, let’s talk about building trust a little bit. So we can use a mobile experience for an example and talk a little bit about best practices there. So in my first experience as a user with your brand, what I want to see in the mobile app is the value that you’re going to provide. I downloaded this with some expectations. Now I want to see how you can deliver, and I want to experience it. I at least want to experience it enough to make an informed decision about whether or not I want to provide data to you. So one of the things that we look to do in apps that we’re designing with clients is to delay as long as possible that registration process or the initial disclosure of your data. If you launch an app, you know, like I said, you have some expectation of what it’s going to provide to you, but you don’t know for sure yet because you haven’t experienced that if the first thing you see when you launch the app is a registration screen. I think that is you’re just putting a barrier between you and that customer. So thinking creatively about how that user experience can be and how onboarding can be such that you give them a taste of what the app is going to be like and what your brand promises to deliver them before you go asking for their user information. So I think that’s step one. Step two is that once you get them to a point where now I’m interested, I am willing to share some data I’m gonna register for an account—limiting the data that’s collected to what’s absolutely critical, and especially critical to that particular experience in the app is another best practice that we promote as well with our clients. So it is easy to put a user registration form together. It just feels like it’s a normal registration form—Isn’t everybody asking for first name, last name, physical address, email address, phone number, birth dates, that sort of thing? Well, maybe, but you should have a legitimate reason for every one of those fields that you put on that registration page. And there’s one in particular that I want to pick on from recent experience of my own, and that is birthdate. And that’s an easy one where I think people can fall into the trap of thinking I want to do something age-related in my app; maybe it’s important that we’re going to segment users by decades. So are you in your 20s or 30s in your 40s? We may use it for different things in the future. So rather than just to ask if you’re in your 20s, 30s, or 40s, we’re going to ask for your birth date so that we can calculate things in the future—that’s not a good way to go. If all you need is to the nearest decade, then just ask for that. Right? And an example that I had recently on my own phone was installing an ordering app for a local sandwich shop that I like. And in that registration process, they asked me for my birthdate. And there was no security reason for this there. They weren’t going to validate that against my social security number or, you know, grant me access into nations in the future, and want to make sure that that’s correct. So I gave them a fake birthday because they don’t need to know what my real birthday is. Turns out the purpose of collecting it was to be able to give me a free sandwich as a birthday gift. When that event triggered for me, it was not even on the fake birthday that I had entered. They sent me a message on the first day of the month that they thought my birthday fell within and said anytime this month, come in, you know, show us this message, and we’ll give you a free sandwich during your birthday month. So collecting age in that example was a complete failure, in my opinion. They didn’t need to know the day of the month. They certainly didn’t need to know the year. They really just need to know what month I was born, and honestly, I would have felt much more comfortable providing that information if they’ve just given me a choice list of the 12 months, and I probably would have told them the correct month, but they didn’t need to know the day in the year. So that’s a kind of a classic example as we’re scrutinizing the data that’s being collected on these registration forms. We really want to think carefully and creatively about what we’re collecting and why.

Tim Hayden

No, I agree. And actually, in terms of the internet, right, which you had mentioned earlier how Apple requires, from a T&C standpoint, for an app maker someone in the App Store, right? To be able to disclose what type of information they’re going to collect. And the challenge there is it’s in a, you know, a five-point font, and it’s a user agreement that nobody reads, right? The big challenge in that world is what was called fingerprinting of devices, right? That big thing that happened starting a decade ago, plus that you download an app, and while you sleep at night, it crawls all over your phone and sees everything that you’ve done, right? There’s that kind of thing actually happened and, unfortunately, still is out there today as a concern. But the big thing that’s happened in the web world, too, is this idea of consent management, right? And consent management platforms, companies like OneTrust and Osano and these are companies that are basically monitoring all of the systems, content management systems, media networks, the apps that you have on your website. You think about car dealers, for instance, if you know certain browsers from Firefox and others will show you as apps are loading on a website whenever you first land on the homepage. And car dealers are always funny to me because they sometimes have anywhere from 50 to 100 different wingding apps and plugins on their websites. Well, what these content management platforms do is they monitor all those systems in real time to do two things, one to let you, the user know whenever you accept cookies or get into the nitty gritty of seeing all the systems and what they do. You can self-select that you do or do not want your data going to those systems. The other side of it, too, is being able to quantify, and Osano has a privacy monitor thing that plugs into your browser, that I love. When you land on a website, it gives you a privacy score. Things are getting better, or they’re getting worse. Well, I think they’re about the same. I think there’s only three possibilities, but they give that to you. And with that, your ability to understand that it’s not the website, but it is one or two of the systems marketing automation content management system that has been detected that maybe they had a breach or maybe they have some susceptibility from a cyber standpoint, right? So it’s not all about privacy, but it’s also just about the security of our data. I mean, and I wonder if we can talk about that for a second because this is the jam. When you talk about birthdays and cell phone numbers. Here in the United States, that’s all I need to be able to go and get your social security number, run a credit score on you, find out where you go to church, how many kids you have. There’s a lot I can tell just from those two bits of information, right? And identity graphs, there’s probably a handful of them here in the States still today. I think that’s a short-lived industry. But you know, at the end of the day, what is this about? Let’s talk about the relationship between security and privacy because that’s the other thing that we’re all realizing as we have text messages from political organizations that we never signed up for or people call us to offer us a new extended warranty on our vehicles. And we don’t even have a vehicle now. I mean, you know, it’s what I said beginning, right? The sloppiness, the mess that we have of data. There’s a matter of security, not just privacy, right?

Brad Weber

And what are you seeing with some of the bigger brands that you work with in that arena, Tim?

Tim Hayden

Well, I mean, I think that we’re seeing the table stakes, which is SOC 2 compliance and penetration testing on their systems to make sure that they can put up some type of fight and be monitored to avoid breaches. You know, avoid anyone hacking into databases. Their cloud, infrastructure, or anything else where data may reside. I think that’s the bare minimum that folks have got to do right now. We live in a world right now where you think about phishing the emails that you get that say, hey, click here, and you get a $100 gift card to Walmart, or Starbucks, or somebody else, right? The biggest rule of thumb to tell folks, and I see lots of big corporations starting to do this with their employees and also with their customers. To say listen, we don’t give anything away for free. So do not click on this, right? They already do this with multi factor authentication. When they send you a text message, give you a code, they say do not share this with anybody, and we will never, and trust me, will never call you to confirm that you get this code. So they know there’s that plausibility that somebody somewhere may be monitoring or just in a place to take advantage and exploit just a gap in the system or a susceptibility that exists within a social network or a or a company’s network, as it were, in terms of the systems they use to manage data.

Brad Weber

But email vulnerability is a big topic. We could talk for quite a while, but I’m glad you raised that. I’d like to showcase some work that we’ve done recently with one of our clients about that specifically. So you know, the phishing campaigns of old, where there’s just a simple request that you send $1,000 to the Nigerian prince or whatever the scam may be, has gotten a lot more sophisticated. And one of our clients came to us with the challenge in the mortgage space. So it’s high stakes, as people are buying, you know, potentially their dream home. And there’s a large sum of money involved. And there’s information on social media and elsewhere about the fact that you’re looking for a house. And so scammers have, sadly, compromised many email addresses, email accounts of realtors or configure out the realtor that you’re working with and create an email address that looks very much like that realtor or your title agent or someone else legitimately involved in the transaction—send you an email address or send you an email message rather, requesting funds related to your closing. But it’s not a legitimate party to that closing. So, for instance, the message would be we know that your closing is scheduled on Friday, but we’ve just heard from the bank that if you pay on Wednesday and wire your money to these accounts, we can save you 5% on your closing costs. So the money gets transferred. It can be 10s hundreds of 1000s of dollars in some cases, and it’s terribly sad, and it’s a multibillion-dollar problem that there was a terrific Bloomberg article about this last fall. If you’re up for a sad tale, you can pick that up, but the message was to try and get the communication related to those real estate transactions out of email, which is a vulnerable medium. It’s a vulnerable means of communicating and get them into an app or a website that is specifically dedicated for that purpose that all parties have little more control over the security environment, and you’re not going to see the same phishing campaigns to try to bilk you out of your money. So that’s, like I said, big topic, but just wanted to touch on that as an example.

Tim Hayden

No, I understand. And that’s, you know, that is a good point to talk about customer data platforms, right? And the role of machine learning and in being able to look at a company who is using 60, 70, maybe more systems to manage customer data. But then establishing an API connection, or at least a mother’s real-time, or it’s an API call that happens once a week from a CRM marketing automation system, supply chain management systems. You know, all the different things that may have customer information in them, bringing those into a customer data platform. And with that, allowing machine learning to be able to build a record for each customer based on the disparate email addresses, phone numbers, devices, and other information that is stored and all those 50-plus systems that are out there. And what that does is it basically puts in a company in a place where they can improve the integrity of the information that they have across all their systems. It’s not just what comes in the CDP or the customer data platform. It’s what also goes back out to make sure that the records that are in the CRM are clean and accurate as well or the mobile app management tool or whatever it is you’re using, right? With that, we’ve got this incredible opportunity to deal with what I call is misinformation, not disinformation. But the bad data that exists within the organization, which will help a company be able to rein things in when it comes to things that could lead to phishing events, right? Both internally with employees, for them to be able to verify people’s identity, but also on the outbound side, right? To assure customers that you’re not going to send them and what they’ve come to learn from you that you’re going to send them three or four different emails or five pieces of direct mail. It’s all about D duping that, eliminating the redundancy. So there’s a number of things that you can do with that as well as having more empathy and personalizing the experience in a display ad, an email, or the content that is delivered through a mobile app.

Brad Weber

That’s a great point, and I think that one of the ways that organizations can improve their security stance, their security position, is to limit the amount of personally identifiable information in databases so that those are the stuff that really is personally identifiable is smaller in number and easier to manage and monitor. And related to your comments around machine learning—we don’t necessarily have to know on the server side that the data we’re evaluating through this particular record that we’re looking at is "Jane." What is important in crafting personalized experiences or semi-personalized experiences for users is to be able to categorize them in some way. So you don’t necessarily have to know that it’s Jane, you have to know a handful of characteristics about Jane, what she likes, you know, depending on the environment that we’re talking about her habits, but you don’t have to know individual transactions to be able to evaluate necessarily all the time. If, on the server side, we’re able to categorize users or create categories based on patterns that we see across users, then we can have the mobile app or the web app teaming up and keeping data on the mobile platform, so on the mobile device, and just sending the characteristics. So you don’t have to know that I’m logged into that phone. You just have to know that it’s someone using it who likes the color blue and, you know, works out three times a week. If that information is important, then send that to the cloud and get recommendations back based on the criteria that’s been shared, without necessarily having to constantly exchange the intimate details about individual users back and forth just makes the whole system less vulnerable. So I think that’s an interesting approach that is kind of emerging recently as well. 

Tim Hayden

No, I agree. I mean, there used to be an app called TabbedOut, that allows you to basically pair your phone with a POS system in a bar restaurant, and then you’d be able to pay your tab from your phone, and even more fun—you could see on social media that your friends were at a pizza place and you could then send a code to them and say: “hey, this rounds on me”, right? You could do that. But the whole notion was that all the credit card information, all your personal information, stayed on your phone. It never was shared with the restaurant. It never went there. And it’s that reality is that hackers, if we want to call them that, if we want to call what the bad actors are in the world that are trying to access our information, that are trying to reach into a system and hold it for ransom. They’re looking for hundreds of 1000s if not millions of pieces of information, credit card information, social security numbers, other personal information—that would allow them to steal your identity and go do other things. They’re not looking for you on the coffee shop Wi-Fi network for that one phone to come in and get your credit card information. They’re not doing that at all. So that’s a that’s a fantastic point. The only thing I’ll stick with Jane for one second, though. Having that golden record and knowing a little bit more about Jane, I’m not challenging you but knowing a little bit more about Jane and having that information on the supply side on the brand side. Say Jane buys something from us. We send it to her, it lands in a box, and it lands on her front porch, and the box gets broken. Jane calls us, and this is the beautiful thing about, you know, great governance of data is that you can leverage technology in a way now to know when Jane’s calling in that it’s Jane it’s caller ID, right? It’s now prompting from the customer data platform. It is pulling over to the contact center Jane’s information. So you remember, and you know the minute you pick up the phone, you have to confirm it’s Jane. But you don’t have to ask her a bunch of questions. You just say Listen, are you calling about the thing we sent to you in a box last week? Right? And that, to me, is where the real opportunity for personalization is most critical is being able to spend less time on the phone. We know bad customer experiences mean that I had to take time out of my day to deal with a problem if the time is very short, then I’m happier. In this case, Jane’s happier, and the happier Jane is, the more likely she is not only to buy again, but to run and tell her friends—you’re not going to believe this, but the box was broken I called them, it took two minutes, they immediately said they’re sending me a new box, right? So that type of thing when we talk about direct experiences, when we talk about personalization. I think most brands need to understand it’s not all about creepy display ads that are put in front of Jane and only Jane sees. It’s more about that empathy on the inbound side is just to say, Hey, I know who you are, and I have some semblance of what your needs are. In the moment I pick up the phone, and the moment we start to have an exchange.

Brad Weber

Yeah, I think it’s important to separate those business cases that you’re talking about and to remember that each one needs to be evaluated individually. So the customer service use case that you talked about is a perfect example where it is going to say both parties who were engaged in that phone call a lot of time to know exactly who Jane is. And be able to look up her purchase transactions or previous transactions to support that call. I would say, though, if we’re talking about like a recommendation engine, you know, people who purchased X also like Y, you don’t need to know this specific person for that sort of thing. I mean, isn’t the only person that bought that stereo system, or that bar of soap, like their great aggregations that we can do at that level. So often, there are large and separated systems within a big organization and knowing which ones need that sort of individual customer identity and which ones don’t is an important part of the process. You think?

Tim Hayden

Oh, totally. No and I think that’s as you were delineating earlier about not needing all the data going all the way back to birthdays and just being able to compartmentalize yourself into a certain decade range, you know? With that, let’s just talk about what humans can really process, you know? People that are in marketing, and because the customer experience business, they can’t understand all the archetypes and all the different ways to slice and dice an audience. Because when you really look at it, Jane is pretty unique. She, you know, her customer journey, the way she got to us, the way she bought from us, and the frequency at which we see her. And we look at and peel it back, and we understand a little bit more about her. We don’t have any other customers look like Jane; you don’t need to know that, right? You need to be able to say—we have something manageable. And this is where I’m quick to stay is that standard persona mapping where you just ask people that are in customer facing directions, who are our customers? That practice may be dead, but being able to leverage data and be able to pare it down to that which is necessary to make great decisions. What you’re doing with content, maybe what you’re doing with product development or service development. That right there is the grand opportunity, I think, with responsible use of data.

Brad Weber

I agree, and one of the things I want to get back to the point that you made early in the conversation. You talked about the freedom to be forgotten. We’ve talked about users being able to opt out. I think another important best practice to consider is that you may not get the data that you’re asking for. So I think another classic example that I can share that I think many have experienced at this point is if you go to a brick and mortar retailers website to place an order, for instance, and maybe you want to pick up your merchandise instead of waiting for it to be delivered to you there will no doubt be a store finder on that site. And when you click the Find a store near me, the first message you’re going to see is that this site wants to know your location. Do you want to share that or not? And that is going to be a fairly precise location. It could be your house, for instance, that they would have it at that level of granularity. There is always the option, at least on well crafted sites, to opt out of that and just type in a zip code or an address or a city name. And that’s usually close enough for you to then be able to see on a map that other three stores kind of close to me. I can tell that that one’s the closest I don’t need you to necessarily know my home address to tell me exactly how many yards or miles or meters that is away. So being prepared to deal with the user declining to share that is really important. And then the other is the degree of granularity that we’re talking about. So location is a good example for ongoing data collection, and potentially, if an app needs location data for some reason—we can walk clients through we typically talk about specifically why we need that one. Do we need to collect location information in the background when the app isn’t even in the foreground. You talked about Facebook, for instance, running in the background. That’s is a perfectly legitimate use case for a fitness app that’s going to track your run, and you want to be able to see it on a map and exactly where you went. And you might be listening to music or checking email or something while you’re running; that app is going to be backgrounded, and so that makes complete sense. Do you have as the product developers, the app developer, different degrees of granularity so it works in the background or only in the foreground when the app is running? We can specify how coarse or fine grain we want that location data. So we want it to within 10 meters, which is pretty darn small radius, or is it enough to know kilometers or even like which timezone you’re in? If you’re developing an app that is a calendaring app, for instance and you really just want to make sure that your appointments reflect the timezone that you’re in. There are events that we can listen to in our apps where the operating system will tell us that there’s been a major change in location. You don’t even have to know what the specific location is. You just know from the operating system the user has moved in a way that the phone has determined is significant. And at that point, you can check one time to see where the user is at devices, update the timezone for the sake of display for for that calendar for your appointments and move on. It is not something you need to track on an ongoing basis, and it’s not something you need to track with great fine grain control. So a couple other points I just wanted to share. They’re about kind of best practices for ongoing collection data.

Tim Hayden

Well, and real quick, I know we’ve only got a few more minutes left. But I mean, when you talk about ongoing collection of data, to many marketers, that falls in the category of retargeting, right? In terms of saying, Hey, you, you clicked on something, and now you’re over somewhere else. We’re going to put another ad in front of you while you’re there. Leaving the social network and going to a new site, for instance. While that’s good in all, this year, a lot of that stands to change. As Google sunsets. Universal Analytics moves everybody to GA, for that fuse is lit for Google to finally deprecate third party tracking through the browser. So we’re not going to unpack that right now on what the cookie being killed is all about, but it is, you know, I hope that folks understand that you’ve got this fantastic opportunity through the customers you already know today to have a better, deeper understanding of the people who bought from you and who you’re looking for in terms of an ideal customer, it’s out there. Demand side platforms and media can help you in terms of identifying those audiences. But at the end of the day, just that Google is making that move, because we talked a whole lot about Apple earlier. We didn’t talk a whole lot about Google. But when you look at what Apple’s already done, and what Apple continues to do what Google is doing this year, there’s not a better time right now then to get your data in order and just start to look at those direct engagements that you can have this much more personalized engagements that you can have through an app and through let’s call it the mobile channel, which of course is not limited to the phone anymore.

Brad Weber

Yeah, that’s a good point. And also a good point that we’re winding down in terms of time as Tim and I are putting together some final thoughts here to share if there’s any questions from participants, feel free to submit those in the q&a section there at the bottom of the screen for Zoom and we’ll be happy to entertain those before we wrap up, but with that, Tim, thoughts, I guess, what’s next? You mentioned we are today; we kind of set the stage for the challenge and talk a lot about data collection and data governance on the server side. We’re kicking off a series of these conversations. Are there some highlights that you’d like to forecast that you think are worthy of a deeper dive and subsequent sessions? 

Tim Hayden

Well, absolutely. We already talked about structured data and how that makes it easier for machines to process data right to make sense of it. We spoke about it in the context of machine learning and building golden records. But what actually that does is well as it allows you to do much more with AI. And you know, I think where we are right now in February of 2023. We’re two months in to open AI, giving us chat GPT to play with. We’ve got Microsoft, who owns LinkedIn, and over the past few weeks, if you if you’re a LinkedIn user, you’ve noticed that LinkedIn is now suggesting completions of your sentences. It’s starting to do some writing for you. That’s not open AI, even though Microsoft invested 11 billion in open AI. That’s Microsoft and what their data science team has done. There. So I mean, you know, I think where our conversations could go in the future, I think we should always give a nod to privacy, no doubt about it. We’ve got to understand that to do these things with artificial intelligence and automation that are exciting, no doubt about it. Maybe a little scary for some people, but they’re certainly exciting to do that and to do that responsibly, we have to respect privacy, and we’ve got to make sure security is in place. So I don’t know Brad. I mean that’s that’s at least one more conversation. 

Brad Weber

At least one more, yeah.

Tim Hayden

Right. 

Brad Weber

I think you make a great point. And this may seem a strange parallel to draw here, but I feel like we had QR codes for years and years, and they were modestly popular, and people understood what they did but didn’t really take off until we had a global pandemic, right? You couldn’t hold a menu in your hand anymore. And now every restaurant you went to and still today, even though we’re hopefully at the tail end of that, or maybe have emerged from it. Restaurants are realizing that maybe we shouldn’t invest the money in printing those things. There’s some business benefit to it but QR codes at their moment during COVID. And the same well not COVID related, but AI has been around for a long time. I mean, decades and decades is improving. And it feels like there was a spark for sure at the beginning of this year, where I feel like AI and machine learning is having its moment, I think, definitely worth another conversation about that.

Tim Hayden

Definitely. And I think, you know, we certainly could dive a little bit deeper into some of the current events. We’re going to be afforded more. 

Brad Weber

For sure. 

Tim Hayden

Yeah, definitely. Yeah.

Brad Weber

It’ll be fun. So we have one question here, Tim, about where people can find more information about this topic. Do you have any favorite sites? resources? What would you recommend?

Tim Hayden

You know, I encourage people to follow the Customer Data Platform Institute because that’s, you know, at the intersection of everything we’re talking about in terms of data collection in terms of personalization, and obviously everything that’s happening on the privacy standards side of things and security. IAPP is an international group of privacy professionals. They have some incredible maps and resources there for you to watch legislation, as it’s in committee, state by state or country by country, and that’s being considered and being passed and enforced. Of course, anybody can find me on Twitter @TheTimHayden, or on LinkedIn. You can find me online at BrainTrust.partners. Those are the three ways to find more about what we do. And you, Brad?

Brad Weber

Nice, yeah, I was gonna say that I could probably put words in your mouth and say that we’re certainly open to continuing conversations about this, so reach out to BrainTrust.partners and InspiringApps.com. Your friendly local app developers, including InspiringApps, will be staying on top of regulations from Apple and Google in order to be compliant to get your apps into the store and keep them compliant. So you don’t have any surprise/takedowns in your future. But yeah, I would just offer in addition to the resources that you already shared and feel free to lean on to Tim and me personally and the teams that we have behind us. So Tim, thank you so much in the Stephanie and the team for organizing this. Thank you for all those who participated, and we’ll be back with another session soon.

Tim Hayden

Absolutely. Thanks for joining, and thanks for the team for putting this together. We’ll see you next time.

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This is a joint session between InspiringApps and Brain+Trust, the second in a series of webinars where we’re talking about data privacy restrictions, artificial intelligence, and app and software development in this new space. Brad and Tim, I’ll have you guys introduce yourselves, and then we can just get into it. Tim Hayden Sure, thanks. Brad—great to see you again. I’m Tim Hayden, the CEO of Brain+Trust. At Brain+Trust, we help companies with their first-party data, usually with customer data platforms or hybrid cloud environments. And we are exploring the world of artificial intelligence in an effort to help companies with both privacy and cybersecurity, but also all the mapping of how to go about implementing customer data platforms and hybrid cloud management. I’m excited to be here with you, Brad, because, of course, to leverage all that data, many times you need apps, and that’s what you guys do. Brad Weber That’s true. Thanks. Good to see you again, Tim. I’m Brad Weber. I’m the founder and president of InspiringApps. We design and develop custom web and mobile apps for funded startups and large enterprises and have experience across this space. Certainly, many of our customers are running into the data challenges and privacy challenges that we’ve been talking about in this series. So I’m excited to dive more deeply with you into that, Tim. And today, our focus is on artificial intelligence, specifically, as you mentioned, and the data privacy implications of that. I thought I’d take just a moment and take care of a little “artificial intelligence” housekeeping and talk about what it is, just at a very basic level. As you mentioned, we develop and create custom software solutions. The majority of those solutions—especially in recent decades—have been explicitly programmed. So a lot of what we create is a matter of implementing business rules. It’s: “If this customer’s age is greater than X, then do this.” Or, “If the bank balance is greater than Y, then do this.” There are a lot of explicit rules in the code that cause it to behave the way that it does—and those are very black and white. What we’re talking about with artificial intelligence is really getting into the gray areas and giving the computers and the processors the opportunity to come up with their own solutions. They don’t necessarily have to be explicitly programmed in order to reach conclusions. Those conclusions may be things that you’ve seen in your life. It could be an identification of an object—there are popular apps that will help you identify a planet or a flower or that type of food based on the photo that you take. That’s artificial intelligence that’s driving that to support object recognition in that kind of application. There are also many applications where the technology of the system is given a goal or an outcome, and it has a lot more flexibility in determining what the appropriate or best path is and in reaching that outcome. In order to accomplish all of these things, you need a lot of data. It is not enough to tell the difference between an apple and an orange or an orange and a banana reliably by just using one photo of each. Models that do that sort of thing rely on hundreds or thousands of examples to make those kinds of determinations. Certainly, as you get into more complex challenges like self-driving vehicles or fraud detection in transactions, you need lots and lots and lots of data. And the focus of our last episode together was talking about the privacy implications of that data collection. So that’s probably a good place for us to pick this up and look at privacy through the lens of these advancements in artificial intelligence. Tim Hayden Definitely. And Brad, when you talk about artificial intelligence—I think we mentioned this the last time we spoke, but—it’s math, right? It is. It is really fascinating, complex math—probably not so complex for mathematicians. But it’s not easy math, right? If it was easy math, everybody would be doing it. But it’s math that’s been around for decades. And now that it’s been digitized, it’s able to make sense or basically identify patterns within data. And what we saw most recently just over the last several months and including a very exciting week last week—I don’t think it’s coincidental at all that it happened during South by Southwest—but you know, OpenAI released to the world ChatGPT 4, and I saw on LinkedIn everyone sharing that. I say everyone, but many people are sharing this illustration of a small circle and saying this is ChatGPT 3 and then a much larger circle and saying this is ChatGPT 4 and basically talking about the exponential number of parameters that GPT 4 would have. And, of course, out of the gate, there’s hype around the fact that it can pass a bar exam and be in the 98 percentile versus ChatGPT 3 only being in the 10th percentile. When you look at these things, it’s certainly impressive. But where did the data come from? To your point, Brad. Where, exactly? And this is where I think there are privacy and security concerns and many more that we might get to or might not while we talk today. What OpenAI has access to, and increasingly has more access to, through its relationship with Microsoft and other big tech firms, is essentially data that you, me, and everyone else helped populate the internet with. And many times it was—What kind of car are we shopping for? Or, what are we searching for dinner?—Or, scarily—What are my symptoms? What symptoms do I have? What do they mean that I have? A lot of this data that was public or accessible by OpenAI is now being used to inform those “parameters” and the language model itself to do more. And Brad, I’ll toss it back to you. But I mean, that, to me, is at least questionable. I’m not going to say scary yet, but it’s certainly questionable. Brad Weber Yeah, I agree. There was a great Ars Technica article about the privacy implications of ChatGPT. Their focus, given the timing of the article, was on ChatGPT 3. I don’t have updated numbers for this specifically, but the scale of this was astounding. And what caught my attention were several things. One was just the immense amount of data like you talked about. The number that I saw quoted was that ChatGPT 3 was driven by a vocabulary of 300 billion words that it accumulated. Now, granted, there were many repeated words. It’s not saying that there are 300 billion unique words. But the assembly of those words that it has gathered from blog posts and books and articles and transcripts of webinars and podcasts like we’re sharing right now. The majority of the data appears to be publicly available. But, in the example of books, the author in this article noted that they made a request of ChatGPT to cite a chapter from a copyrighted book. And ChatGPT happily reproduced the entire chapter and provided no copyright annotation for that. So, that’s troubling, certainly, for authors. Tim Hayden It is. Brad Weber But you had mentioned that there could be medical data—we don’t really know what is being shared. And I think that we’ve been somewhat complicit in this in our decades of accepting privacy policies. And, more recently, disclosures about how data might be shared from one platform to partner platforms. This is an example of how that data might be used in surprising ways. As you mentioned, where we individually are, in many ways, populating ChatGPT and other similar engines like this. And I think that’s worth further discussion. Tim Hayden Oh, it absolutely is. I mean, when you talk about terms and conditions and privacy policies and privacy statements that you check and say that you understand—it’s just like car dealer advertising on the 10:00 news, when they say at the very end, very fast, that “The vehicles we’re talking about do not exist on the lot. And if you come in, we reserve the right to throw $2,000 on top of you through the entire process.” The bottom line is the legalese—the fine print—in terms of the wares that we’ve used and in terms of user agreements over the past decade-plus. That’s exactly the data that is being used now to inform and train these language models. And kudos to OpenAI, who has come up with a very sleek, intuitive, and easy-to-use interface for us to be able to leverage—I hate to call it intelligence, but—to leverage some of the math that is able to make sense of our prompts and go find out with a certain degree of correctness. And what it is we’re looking for, the answers that we need, or the answers that we’ve asked it to provide. You know, what’s funny—because you mentioned it earlier about the book and a chapter out of a book—is the U.S. Copyright Office, over the weekend, actually came out with a formal statement saying that they were going to revisit copyright law. And as we do, they left it open-ended. But they said, “We can tell you this much: that if you are using generative AI to produce copy or a book, you cannot claim the copyright to that content.” And I think this is where things are probably for a different webinar and a different conversation for us to have about authenticity. But, certainly, when we think about the one-two punch of private, sensitive, or otherwise nonpublic data that has been used and has been generated in some type of content, or some type of prescriptive advice that one of these language models is providing, it gets a little spooky in this. Now, I will say it. Now, I will say scary, right? This gets scary and a little bit spooky when we think of college students, and we think of someone sitting in their home who is trying to generate a report or type up something for their PPA and claim that they’re the author of it, right? It’s happening. Those kinds of things are happening right now. It’s what we always talk about with “Garbage in. Garbage out.” Maybe it’s not garbage. It’s just somebody else’s. It’s somebody else’s work that’s going somewhere else. And someone else claiming that it’s their own. Brad Weber Yeah. I think it’s an interesting point—that we’re talking about two different aspects of copyright material. One is the copyrighted material that might be used to populate the collection of data that’s being used for generative AI. And then the other is when the AI produces potentially copyrightable material, whether it be in written form or artwork out the other end. And so, I think this is probably one of the larger changes that have come to the Copyright Office in a long time. So it wouldn’t surprise me if this takes them a little while to digest. Tim Hayden Definitely, and I think, in the vein of privacy—I’ve had a few clients who’ve read up on the OpenAI API documents and have asked me, “We can simply plug ChatGPT into our CRM. We can plug it into our marketing automation system.” And the premise is to be able to generate content faster and better. But, what’s happening there, when you make those connections with something that has that processing power—a model that has the ability to identify patterns and to supposedly help you in a utilitarian way—there’s a way, I think, that could backfire, right? I’ve told each of those clients that asked me that question: my short answer is “No, don’t do it.” Stay using ChatGPT in the browser. If you want to have it help you with outlines or help you write a paragraph—sure. But then wordsmith it as your own. But don’t plug it into your systems. Don’t do that. Because that’s where I think we have this opportunity to misstep and move in a direction where certain systems, for better or worse, all of a sudden know things that they shouldn’t or have access to things that they shouldn’t when it comes to information. Brad Weber So we’ve talked a lot in both of our episodes about the implications for personal privacy and personal data. But I think what you’re touching on now is also an important subject. There is plenty of private data in a corporate environment, so would you like to explore that a little further? Tim—I think that’s what you’re talking about, the CRM, right? Tim Hayden Yeah. I mean, you live in Colorado, right? And Colorado has a Colorado data privacy law, as does Utah. California has got a couple of them with CCPA and CPRA. And on January 1, when yours went into force, it did so along with Utah, Connecticut, and Virginia, as well, and a revamp of CPRA. These laws—basically, I giggle a little bit when it’s general counsel or a CFO who’s really worried about a violation of them, and I say absolutely you should be ready for some type of litigious call or letter that will show up because someone says they unsubscribed and you’re still sending them email. That’s been around for a while, and I think we’re going to see that only grow. But the other side of that is: when you read these laws, they’re basically a prescription for restructuring your data to be a better steward of the data that are entrusted to you. When you talk about CRM or customer data platforms, cloud management, all of these systems today, in terms of how they leverage IA/ML, are there to help you move faster internally to the organization. And that, by all means, is proprietary in some regard. That’s proprietary information, a competitive advantage, if you will. If you know why people are buying from you or what’s working and what’s not with business operations, data can help you inform that. Especially if it’s structured and you have the right systems in place to make sense of it, to derive patterns from it, and to detect all of those things. So, I mean, there’s the front side of that too. The interface side of it, which is where I look to you, Brad. I mean, where do apps play in all this, right? Where do apps stand in terms of privilege—of access to information? What do you see happening there, and what does that have to do with this world of privacy, especially when you’re plugging into a CRM or some other large database of information? Brad Weber Yeah, good question. So I think the mobile app specifically, although this certainly applies to web applications as well, oftentimes provide the window into that data that we’re talking about—the immense amount of data that’s driving ChatGPT and its competitors is petabytes of information that’s in the cloud. That certainly eclipses what you’re going to be able to carry around in your pocket anytime soon. So what we see on the client side of this, both web and mobile, are the results often of that analysis that’s happening in the cloud or in a giant server farm that’s coming up with the information or the tips or the driving information for the sales team, or what regions they should focus on, all that sort of thing. The numbers are being crunched oftentimes in the cloud and being presented at the phone or the browser level in order for a user to make sense of it and to be able to write from that. The phones, in particular, we talk about this a little bit in our last episode—are also participating in collecting some of that data, oftentimes through our active input and other times very possibly behind the scenes, whether it’s our location data, our health data, the number of steps that we’ve taken—that sort of information is helping to feed the machine as well. So I think we see it in two different ways. And when you’re talking about the things that corporations and IT departments might be considering and actions that they might be taking in this regard. I think one thing is important, the distinction to make is that they don’t really need the scale of a 300 billion word or phrase vocabulary in order to get answers to their corporate questions. I think what we see is that the questions that our clients want to answer—either about their customer behavior, about their employees, or about products—are much more focused. And so I think it’s far more practical for organizations whose sole purpose is not to answer these questions for the general public but to answer very specific questions about how to improve the performance of their operations and create their own models and manage their own data. Keeping it private within the walls of their organization to perform the analysis and maintain that competitive advantage that you were talking about. Tim Hayden Definitely, I think it’s all fascinating. I think the next time we talk, we probably should talk about edge computing because it’s not just the phone. It’s not just the browser in the conventional or traditional sense. It is machines themselves now that are connected, and they’re also processing millions of signals that come from wheels that go round and piston the churn and traffic that walks by, right? I mean, all the different ways that the world’s connected now. But, you know, back to where we are right now. You know, I’m of the belief I shared this morning in an article that I read from TechCrunch that Google Glass is finally being sunset. And we’ll defer a conversation about Google Glass and all of that for IoT and edge computing because that’s what was happening with Google Glass. There was a lot of processing happening in the frame of the glasses. Right. But the harbinger, I call it, I always thought Google Glass was just not right any time soon because we as humans don’t need a heads-up display. And at the time I said that—this was a decade plus ago—I was a mobile strategist myself, and I was helping companies figure out more things to do utilitarian with mobile apps at the time. But at the same time, I was very cognizant that we don’t need people staring at their phones while they’re driving their cars. We don’t need people staring at them as they’re walking down the street, and as that happened, you know, it just seemed like it wasn’t any safer to have a heads-up visualization and Google Glass. I don’t think it’s too far of a reach to say that where people are enamored right now with ChatGPT and what Microsoft has done with Bing and pulled back a little bit and then come back a little bit more. What Google’s doing right? And what they say they can do and what they will do more of. We could probably talk about them specifically. But do we, as humans, absolutely need to have a Siri or an Alexa or now something that is much deeper and much more capable to constantly be the thing that we go to, to answer a question for us? Especially when we are able-bodied to get around and to experience life ourselves and to know where to query information when we need it, that which is necessary. Right? I understand if you have encyclopedic needs, you’re going to have to go to the internet anyway. But I just wonder—what is the shelf life going to be? What is the run? It looks really good right now. It’s new; it’s shiny. But I don’t know, Brad—what do you think will be in six months, nine months from now, with ChatGPT or any other of these other language models? Brad Weber I think we’re definitely going to see privacy at the forefront of that conversation. I think right now, there is, as you said, such excitement around the tool, and people are learning about what’s possible. What’s interesting is that it isn’t new. You talk about being around for decades. I mean, over 75 years, you can go back into some early research papers, like in the 1940s, talking about the possibilities of this. So the idea isn’t new. And the military—US and others—have been advancing artificial intelligence for a long time. And in public view, I remember early over 20 years ago, meeting teams there were participating in the DARPA’s challenge to create autonomous vehicles that were able to complete a course. It was unknown. And ahead of time, it wasn’t mapped out. They were given a challenge on the day for their vehicle to be able to figure out how to get from point A to point B over really challenging terrain. So those problems have been worked on, and you know what? What that evolves into is Tesla and others working on their self-driving car capabilities and, you know, just other conveniences that are popping up in our everyday lives that we talked about in the last session as well. I think it’s exciting. I think there are a lot of things we’ve talked about that, as you noted, are a little scary. Maybe we’re going a little too far to start. But what’s really exciting is that ChatGPT, in particular, has really thrown the notion of artificial intelligence and ML into the conversations of the general public. And I think that is an important step in the process for us to continue to advance and for that to expand in. So I talked about privacy, and you said what’s coming in the next six months? One thing to note about ChatGPT, it’s entirely text-based at this point. It doesn’t do anything with audio. It doesn’t do anything with video. There are a lot of other areas where we’re most certainly going to see this start to permeate. But this is an important “big bang” to get everyone’s attention at this point. I think it’s an exciting part of the process. Tim Hayden Sure, I absolutely agree. And to that point about privacy, we mentioned the US Copyright Office, right? You have the US Copyright Office, and you have several states that have data privacy laws in place. You have hungry attorneys out there that will make something out of nothing and make something out of something that has substance right now in terms of how data is being used. A client of ours here at Brain+Trust said to me about two weeks ago, “You know, people say that data is the new oil, and certainly, data has value, but data is actually dynamite. At the end of the day, you have to handle it with care.” And that’s where this is going with privacy. It’s where it’s going with security. And I think we’re going to see it to be most fascinating. When we talk about three or four months from now or nine months from now, in 2023, there are a number of economic economists and economic analysts that are forecasting that there will be some type of economic recession. That there will be corners of the economy that will shrink, and there will be others that just continue to grow and expand. AI is certainly one of those that I think we’re just going to watch because it does hold that promise that technology has always given us to do more with less. And it’s proving it day in and day out. But at the end of the day, when you think about patterns, right? We’re coming off the end of a pandemic. We’re just now getting the emergency label removed. And with that, things weren’t normal. This is not a conversation about normal, but things are just not linear. The way that they were, and they won’t be. As we continue to have innovation move at the breakneck pace that it is. So when it comes to predictive analytics, which is what I think I heard, and I forgot who it was, but I saw some people quoting speakers at South by Southwest that said, you know, all ChatGPT is—is fantastic statistical intelligence, right? It’s able to detect patterns. It’s able to identify things based on a problem. But it’s that statistical intelligence. Right. And, you know, it’s something that I see if we look in the future—how smart machines are going to be able to really detect our patterns if the world is changing at the pace that it is. Brad Weber It’s interesting, and I think it’s worth noting before we part or close out on this subject that it’s not all doom and gloom. I mean, it’s important for organizations to think about treating data. I like your references. Data is dynamite, but be very careful with the data they collect. I think it’s important for consumers, the general public, to be aware of the data that they’re sharing and maybe pay a little more attention to that than we have in the past. But there’s really a lot of benefit from this as well. I mean, the science, the technology that we’re talking about is helping with medical advances, you know, being able to review medical imagery and make a diagnosis perhaps more effectively than humans would. Or as an initial screening of that is really helpful. I have just a silly example of where some artificial intelligence has gotten my attention in a positive way. On the road recently, I was taking a couple of long car trips in rental cars and took advantage of the cruise control feature. And although I’m sure plenty of people watching this will be familiar with this, this was new to me: As I approach another vehicle, I’m used to my “cruise control experience of the past” as tapping on the brake very inconveniently. And then once I get around the vehicle that I was approaching, I had to reset my cruise control. And it was a pain. It was a small pain, but a pain. And I am now pleased to find that multiple vehicle manufacturers have an automatic detection feature associated with that cruise control, so I can set a certain speed as I approach another vehicle, the car will automatically start cruising and slowing down on its own. If I just change lanes, it recognizes that there’s no longer vehicle in front of me, and it’ll automatically resume to the speed that I had. That is convenient. It also requires absolutely no personal data from me. Now, there is a ton of data that went into that feature to determine what an appropriate distance is, taking into account the speed of my vehicle and trying to anticipate the speed of the vehicle in front of me. But it doesn’t have to know anything about Brad in order for that to be effective. And I think one of the messages for brands who are looking to add that kind of delightful customer experience is to, again, be critical about the data that you’re collecting and scrutinizing each individual. But is that absolutely necessary for us to know “Brad” individually in order to provide this capability that’s going to add some time to his life or somehow simplify the process of his day-to-day moving around? So some thoughts for you to reflect on there, too, Tim. Tim Hayden I’m with you. Adaptive cruise control and lane assist, and things like that are in place to provide us with a safer life. You know, Apple’s handoff: With just being able to intelligently know that I was listening to a Spotify playlist or a podcast in the car but when I walk in the house and it connects to the wifi, and all of a sudden, Sonos comes on, and it plays there as well. I mean, this is, by all means, really great coding. It is intelligence and with the respect to “if this, then, that” type of logic that is put in the systems now. And this is what I think is fascinating—is that there’s a balancing act. If we want to keep on this path of privacy—we have to understand that opting in and allowing that type of data, which you just described, which isn’t really that much about me, the individual, but me and my disposition in terms of geographic location, in terms of velocity and direction, in terms of the time of day, in terms of maybe the thing or where I was, you know, 5 minutes before or where I happen to be headed next. The fascinating thing is a lot of this is the way that the advertising world works right now. That we can start to deliver programmatically the best message to the right person at the right time. So, a lot of this has already been in play for a while, and I wonder how we’re going to see systems and language models start to inform that as well. If you do have your data structured right and all of your systems, I’m thinking of a customer data platform now where you have 100% of your customer-related technologies that are connected via a real-time API. Most of them, not all would be, but most include both for the real-time API. You’ve got your finger on the pulse of customer behavior all the time. Do you see the language model coming in to automate how that would then go inform a demand-side platform with advertising or even better things that happen within a store and apps that inform people that are working on the floor about customers or certain kinds of customers that are headed that way? And maybe we need to change our script. Maybe we need to move the sweaters to the front of the store—I don’t know. You know how I think, Brad. It’s all connected. And it’s fun to play with in a browser. When are we going to put this thing to real work to help us with that data we have today and to make sure we’re doing so very responsibly? Brad Weber Yeah. And I really think that’s the theme of what we’ve been talking about. I think that’s a good summation. Are there any other key points if we were to bullet, any takeaways that you think are important to revisit here? Tim Hayden You know, what we stated before is to go out and experiment with this, right? If you don’t have an OpenAI account, it’s free. There are things that you can and can’t do with that free account, and think twice before you start to give them $20 a month or any more than that. Right. And certainly, I would say talk to your attorneys and go find legal advice. There’s some of it online, but talk to your personal business attorney who, if it’s not them, they’ll have somebody in the practice or somebody they know who’s been looking at these matters. To understand—is it the smart thing to start to talk to OpenAI about an API connection? Is that really a prudent thing to do right now? And I’d say lastly is what you and I both know. With the data you have today, if you want to employ automation and if you want to really have intelligence that can inform what you do next with your business—you need to look at something like a customer data platform; you need to look at companies like Snowflake that help you organize information that’s in the cloud. That’s where we are today, folks. And those are the two things. Don’t jump off the deep end for the shiny water when what you’re sitting on right now is already pretty much what you would need to innovate and to do some pretty magical things. Brad Weber Remember that there are tools available for organizations to realize the benefits of AI that we’ve been talking about within their own walls of the organization and not necessarily having to jump on (like you said) the latest “shiny solution.” There are more focused tools—more focused solutions that will help companies get to the answers that they need to improve those internal operations. I think that’s great; thank you, Tim. And we alluded to it in this session that you had mentioned as well that there’s a lot going on with the Internet of Things, connected devices, and edge computing. I know you and your customers have a lot of experience with connected vehicles. And so it seems like that would be a great thing for us to turn our attention to next time. Tim Hayden Definitely, we alluded to it, but when you get into the adaptive cruise control and the lane assist, there’s a lot of play there. There’s actually some work we’re doing in that space that I’m looking forward to uncovering with you. Brad Weber Excellent. Terrific. Well, we will look forward to doing this again next month. It’s good to see you, Tim. Take care. Tim Hayden Thanks, Brad.

1 year ago

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