Proportionality of Data in eDiscovery

03 April 2023 by Anith eDiscovery data-proportionality

Takeaway: Law firms now have a broader bandwidth of data that they can access with the Internet of Things. But, just additional data doesn’t mean better evidence. Attorneys still need to justify that the new data is worth the additional cost and effort. (For example, from the 3M Combat Arms case we can learn that it was not worth the cost/effort of getting the smartphone data even though it was available.)

The Internet of Things (IoT) is the new digital world order.

With Web 3.0 we are moving towards a network of data-gathering devices and away from a single data source. The Internet of Things (IoT) brings with it an added degree of convenience as gadgets can communicate with each other without any conscious instructions from the user. For example, let us take the sequence of events that are automatically triggered as you pull into your garage without having to initiate them deliberately. Your home security system can switch itself off based on the sensors found on your garage door. This in turn can trigger the air-conditioning in your house to turn on and finally, the smart light can adjust itself to the appropriate light setting.

Besides being convenient for everyday functions IoT devices the data trail generated by them is proving to be valuable for eDiscovery.

Metadata as we know it has been elevated to a level beyond what we are used to with the advent of IoT. Previously we just needed to be concerned with the metadata from a few unconnected devices. Now we have a huge network that records each of our digital steps so to speak. Suppose you use a Fitbit, then a business that deals with fitness or health-related products could potentially track the data (steps taken, calories burned, heart rate, etc.) generated by your Fitbit. With the help of this data, they can then build your profile in relation to your locations and activity throughout the day. This could then potentially be used by attorneys in a personal injury case by showing the activity level or location at the time of the incident. Likewise, in a case of cheating smartphone logs can be used to prove the same.

All this data comes with a caveat, making us think about some very tricky questions

As we venture into this new digital world there are some tricky questions that demand our attention as well as some answers. One very important question is, who is the owner of all this valuable data? Let us take a look at the Fitbit example from the previous paragraph. Are you the owner of the data or is the manufacturer the owner? How will attorneys retrieve the data if you are the owner (as the data is stored on networked devices, servers, archives, etc.)? Will the data justify the cost of retrieval? Another important question that needs to be answered is, will another person be okay with you invading their privacy when you request their Fitbit data?

Let us take a look at the landmark 3M Combat Arms Earplugs proportionality issue to further understand this conundrum

Judge Gary R. Jones who was presiding over the 3M Combat Arms Earplugs case (September 23, 2022), made a very important ruling on eDiscovery proportionality. The case in question is concerned with plaintiffs accusing 3M of not protecting their hearing adequately with their headphones. 3M’s defense required the noise exposure data that was supposed to have been captured by the plaintiffs smartphones and smartwatches. They maintained that this data would exhibit how loud the headphones’ volume was, the duration of use, the duration of the ‘damaging’ environmental noise, the duration the plaintiffs were exposed to this ‘damaging’ environmental noise, and the number of times they were warned of danger by their smartphone. The plaintiffs rejected this request with the reasoning that the data was not pertinent to the injury claims and that data retrieval would be extremely complex

Added to this there were logistical and technical issues with the data retrieval process.

Apple iOS devices (post-2019) could record noise exposure and hearing data so the defendant’s request was theoretically valid. But for this theory to be applicable the following needed to be in order -

The plaintiffs should have been using an Apple iOS device with a post-2019 operating system since the earlier versions did not have the ability to capture environmental noise
All these measuring options should have been enabled and synced to the relevant devices like the Apple Smartwatch

The retrieval of this data required quite a bit of effort and technical know-how even though 3M had issued clear written instructions of the same.

At this point, the plaintiffs raised the issue of the proportionality of retrieving all this data.

The requested data was produced by one of the plaintiffs whereas others said that the cost of retrieving the data was not worth the effort, Others went on to say that they had searched their devices but were unable to find the required data. (The irony is that some of the plaintiffs later confessed that they hadn’t put in the effort to try and find the requested data.) The plaintiffs also contended that even if they made an effort to collect the data it would not be relevant or admissible.

In due course, the Court ruled in favor of the plaintiffs citing that the motion had failed on proportionality grounds.

In its ruling, the Court stated that the effort-to-payoff ratio was not low enough (i.e., the cost and effort spent to gather and review the data would be extremely high) and that the noise exposure data would not favor the defendant’s stand. To have an idea of the effort required we need to know that the defendant had failed to check if the plaintiffs had Apple devices, and if those who had them had an operating system that was post-2019, or if the ‘collect environmental sound’ feature had been enabled by them. Retrieving the data without any one of these prerequisites would be extremely difficult and nearly impossible. Additionally, in the eventuality that the data was retrieved and it showed how loud the noise was, there was no way to establish who was holding the device, where they were situated, and where the noise was coming from. This led to the failure of the motion on grounds of proportionality. (Also, the Court had ruled that some privacy issues also existed, but that is a story for a separate blog)

Let’s see what this means. An IoT footprint is not a panacea for all our eDiscovery problems and to have a better case you need more than just data.

Our takeaway from the 3M case is that we need to have evidence that can be optimally utilized rather than just a lot of data from a network of devices. Attorneys will also need to take into consideration various issues such as proportionality, relevance, and privacy issues before making a decision on which eDiscovery application can best aid them in the review of the permissible data. The IoT is not the cure-all for our eDiscovery woes but it does open up some exciting possibilities. Despite the changing times eDiscovery still requires you to put in some legal grunt work.

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