The webinar presented by iDiscovery Solutions on May 16 (and hosted by MCC) was packed with a lot of information about the internet of things (IoT). But what made it different from other webinars we host was that it was doubly interactive. There were only two presenters, but Charlie Platt and Dan Regard did a lot of interacting. They used a polling tool to engage their audience, and that was an effective way to move the conversation. But what was most effective wasn’t the tool, which is fairly common these days in both online and live presentations. It was the presentation itself.
Instead of taking turns lecturing the audience, they talked to each other. They traded the usual monologues for a dialogue. It felt more like a talk show with two hosts than a typical CLE offering.
The title of the presentation was The Internet of Things: Disparate Data Tells the Story. (You can access it by going to bit.ly/2qJzSM5, filling out the form and clicking on Register.) Platt, who is a director at iDS and is a Certified Ethical Hacker, and Regard, the company’s CEO and co-founder, started with a seemingly innocuous poll question: Do you ever use the free Wi-Fi at Starbucks? Half of the audience said yes and half said no.
This wasn’t about a cybersecurity issue, the duo quickly assured the audience. It was all about data. The first time you sign on, “you’re teaching your phone how to connect,” Regard explained. And that means that Starbucks has information about you. He doesn’t know what they do with it, he said, but in this day and age it would not be “unreasonable” to think that the company would keep the information and figure out uses later.
And if the company keeps the electronic “handshakes” between your phone and Starbucks’ Wi-Fi network, he continued, he could extrapolate from that data “when you go to Starbucks, how often. I could correlate what you buy at Starbucks. I could determine how long it takes you to walk between two Starbucks. I could estimate your height,” and from that he might even get a read on your health. And you wouldn’t have to give your permission for any of this.
“And, of course, this is Starbucks,” added Platt, “so there’s one every 20 feet.”
The point, Regard explained, is that “something we did in the past could cause us to be leaving a data footprint when we don’t even realize it.” They summed it up nicely with a slide: “The IoT Is the Opposite of Virtual Reality.” Augmented reality adds artifacts to the world around us to create an immersive fantasy world, Platt noted, while the internet of things measures what’s happening in the real one.
“This isn’t just related to phones,” Regard observed. Many people swipe ID badges when they enter their places of employment. And devices in our homes also collect information. Platt cited a well-publicized murder investigation in Arkansas in which the police wanted to obtain potential evidence from an Amazon Echo device. They also secured potential evidence from a “smart water meter” that may prove useful as well.
When you add information recorded on smartphones to photographs that people post on Facebook to information contained on devices in their homes, the results are inescapable. Many of us are surrounded by our own data. And this multiplicity of sources, Platt and Regard argued, can be used to extrapolate reliable information about us. One source may present a clue, they said, but two sources can add context, three can create a convincing picture and four may be compelling. Court cases can be built on this kind of information.
Are you creeped out yet? If not, keep reading. The second question they asked the audience was: “Do you download and access apps for your city’s sports teams? The answer: 27 percent said they do.
The reason that Platt and Regard brought this up was a lawsuit filed against the Indianapolis Colts football team. The suit alleged that the team was listening in on fans’ conversations through the app. “The app’s not running,” said Regard, “the phone’s in your pocket, and the app is still listening to your conversation, and feeding ads to you based on the conversation.”
Creeped out now? Platt opined that this was, indeed, on the creepy side of the spectrum. He suggested that all technologies strike a balance between two extremes: “cool and creepy.” But what qualifies as cool and what falls on the creepy side of the gauge is a personal judgment that changes over time, and may be viewed quite differently by different generations.
Turning to the world of e-discovery, the duo described the sea change that they’ve seen in this field. Lawyers have traditionally focused on “the documents” and what they can learn about the case from them. But iDS suggests that sometimes that’s the wrong approach. “In some of our cases,” Regard explained, “we’ve been able to flip that around. Instead of looking at the documents first, let’s look at the data first.” Platt said that in his experience, lawyers almost always want to start with the documents, thinking, “I’ll get to the databases later.” This is often a euphemism, he added, for “I will get to the databases never.”
But some savvy lawyers are flipping the order. Platt recently worked on two cases where they started with the databases and never even needed documents. They had all they needed without them. From the data they were able to determine employee movement patterns and on-the-clock, off-the-clock exposure. They resolved the issues without reviewing any documents at all. “That’s a paradigm shift,” Platt said.
It’s also a great opportunity to cut costs, Regard added, because document reviews are very expensive. How expensive? If e-discovery often amounts to 50 percent of litigation costs, said Platt, document review can easily swallow 80 percent of the e-discovery bill. And the reason is pretty simple. It’s a lot more time-consurming to review a multitude of documents than it is to review data.
The sources of the data they review aren’t limited to smartphones and GPS devices. There’s also metadata from documents, text messages, email. And you may not have to read any of the emails, if the metadata tells you what you need to know (like timing and locations). The information extracted about an employee can be compared to the employee’s own account of what he was doing and where and for how long. The machine-recorded data can be presented as objective proof that outweighs an individual’s subjective recollection.
Toward the end of the webinar, Platt and Regard presented case studies that illustrated how they use data in litigation. And this is where they explained their key theme: If you use data correctly, you can turn liabilities into assets.
For example, a Fortune 10 company was hit with a labor class action brought by 1,200 class members seeking damages for off-the-clock work. They claimed that they hadn’t been given lunch breaks. The evidence included four years of data comprising billions of records and data points. That data, Regard and Platt said, can weigh on a company as a very big liability.
But it doesn’t have to be. Since the company had been forced to collect the data, the defense decided to use it. What did it demonstrate? In a variety of ways, some of the plaintiffs’ actions contradicted their claims. A combination of GPS data, invoices, time cards, transaction tags and more showed that some employees were moonlighting – working a second job during the hours that they were supposed to be working for the defendant. Others were running personal errands during those hours. And the time they were shorting the company was considerably longer than the lunch breaks they complained they’d missed. In sum, said Regard, “analyzing the data had a big impact on the case.”
The importance of this information, said Platt, is that the defense was able to reconstruct employees’ days to show what they were really doing when they claimed they’d been forced to work through what should have a been a lunch break. And those stories can make all the difference in litigation, he said, because “it’s the narrative that really has the impact in prevailing in these cases.”
Regard and Platt ended the webinar with some tips. If you can handle the data, “be data hungry.” Get as much as you can. But if you can’t, then data really can prove to be a liability. Another: “Speed wins.” Analyzing data early gives you a much better chance to quickly resolve disputes before either side has invested much money on depositions or briefs.
The last point led to a final prediction. Data from the world of IoT may help boost the percentage of cases that settle even higher than it already is.
Published October 19, 2017.
