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Discovery in an Economy of Distraction
In a world of expanding data, how can legal teams afford the rising price of attention?
You know the trend, “Things That Would Send a Victorian Era Child into a Coma?”
Well, the sheer number of notifications the average adult receives daily would put a Victorian child on a respirator in seconds.
On average, people daily:
We are constantly bombarded with information, begging for our attention. Every time a little notification bubble appears, or a message preview slides onto your screen, it’s yelling, “I’m important!” “Pay attention to me!” “Over here!” “Yoo-hoo!” regardless of whether the notification is a message from your boss about an important deadline or another person trying to sell you something you don’t need.
Overwhelming, right?
Attention Economy
Psychologist and economist Herbert A. Simon refers to this communication structure as an “attention economy.” Think of this as “a wealth of information [that] creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
In other words, you only have so many attention dollars. Where are you spending them and how do you determine that?
Simon coined the term “attention economy” in 1971, foreseeing the chaos that would ensue as the internet spread and global data exploded. In 2025, global data is expected to reach a record level, with 180 zettabytes (ZB) of data anticipated to be created by the end of the year. The entire Library of Congress (the largest Library in the world) is estimated to be about 20 terabytes, so 180 ZB equals about 9 billion Libraries of Congress.
It’s also growing at a faster rate than ever, with 90% of the world’s data being created in the last two years, the parallel processing capabilities of AI and LLMs’ fueling this acceleration. On an individual level, that means an internet user generates about 1.7 megabytes (MB) of data per second. The original floppy disk only held 1.44 MB, so every second, you generate slightly more than a whole floppy disk worth of data.
Think of how many seconds you spend on the internet per day.
But how are we generating all this data? What is the information our keystrokes and scrolls are producing? Let’s use a Slack message (1 of the 40 you may receive each day) as an example.
Every Slack message you receive from a coworker cascade into a pool of metadata points that include:
- Message Content
- Message ID
- Timestamp
- Author
- Channel
- Reactions
- File metadata
- Audio/Video metadata
- Replies
- User ID of an assignee
- A unique identifier for a specific event
- Structure data to facilitate app integrations
- IP Address
- Browser type
- Language preference
- And Beyond
Now take those 15+ data points, multiply them by every message you send, and every message sent by everyone in the world. That is an ocean of details, an exorbitant supply of data points, and that’s just Slack.
Humans can’t keep up; we fundamentally don’t have enough attention (time, interest, focus) to intake all that information. So, this is where we are today, living with a surplus of information and a deficit of attention, in Herbert A. Simon’s “attention economy.”
Big Data and Legal Investigations
The conundrum of the attention economy poses an interesting challenge in the context of eDiscovery.
Studies on organizational data management report that by the end of 2025, 80% of organizations anticipate they will be managing zettabytes of data, with between 50%-90% of that data being unstructured. This becomes a challenge when an organization is involved in an investigation, litigation, or subpoena response. Because now they have an overabundance of electronically stored information that must be identified, collected, preserved, and produced in a timely manner. It’s like digging through a messy attic the size of an airplane hangar, where everything’s been dumped randomly, half the boxes are mislabeled, and you’re looking for a single receipt from 2019.
Do attorneys, IT teams, paralegals have enough attention to manually process all this data? Overwhelmingly, the answer is becoming No.
Why not?
- Data is spread far and wide across cloud-based applications.
- Unstructured data is difficult to collect, translate, and review.
- The overabundance of data makes it difficult to identify the relevant details.
- The cost of attention is rising with every gigabyte.
What can you do?
Herbert A. Simon laid out the solution for us in 1971; we need to actively pursue ways to allocate our attention efficiently. We need tools that can bring our data down from the cloud, translate unreadable information, guide us to relevant information, and let us discover while the data tries to distract us.
