There's no question that Slack is discoverable ESI—but it's not the same ESI most legal professionals are used to. Handling Slack data poses unique questions around interpretation, spoliation, and burden and proportionality objections.
There is no question that data created in Slack is electronically stored information that can be subject to discovery in litigation. There is also no question that Slack data can be essential to investigations, whether as part of litigation or not. Slack data is a potential treasure trove for legal professionals.
That’s where the certainty ends.
“Today it is black letter law that computerized data is discoverable if relevant.” Anti-Monopoly, Inc. v. Hasbro, Inc., 94 Civ. 2120, 1995 WL 649934 (S.D.N.Y. 1995).
For modern legal teams, Slack presents a host of difficult, unanswered questions. How are legal professionals supposed to make sense of Slack’s more informal communication styles, such as the inclusion of emojis and gifs, or the ability to pin, react to, and star, messages? Who is a custodian on Slack? Who is responsible for data preservation when users can set their own retention policies? What is proportional discovery of Slack data and how does it align with users’ privacy interests?
In a small but important development that could bear on the ability of attorneys to make a reasonable inquiry and diligent search, a handful of judicially-sanctioned ESI stipulations explicitly governing the treatment of Slack and other modern messaging apps have begun to emerge in federal courts.
Slack works more like an oral conversation than a document. Participants "speak" (or type) back and forth. Topics can float in an out. A conversation that began in one channel can be taken aside, for a more one-on-one discussion, or pop up again days later in an entirely other space. And all of it's recorded in multiple streams of information, rather than single, organized documents.
Yet most discovery and litigation processes are based on documents: emails, word processing files, spreadsheets. That means that old approaches need to be updated for more chat-based communications.
When dealing with Slack and similar data in discovery, begin by considering such questions as:
These, of course, are all answerable questions. And, indeed, sophisticated parties will often come to a consensus on how to treat Slack data during the meet and confer process. But there is currently no industry standard on how to answer them.
Similarly, when determining a pre-litigation, information-governance approach to Slack data, or advising clients on theirs, consider questions such as:
Given Slack’s novelty, and some of the difficulties associated with Slack data, it’s not uncommon to encounter objections that the reviewing and producing Slack data is disproportionate and burdensome. And it can be. Without the right tools, Slack data can present significant challenges around review and production. Exported directly from the Slack platform, for example, Slack data appears as virtually unreadable JSON code. But with discovery software that can parse and process that data, those burdens can be significantly reduced.
Often, simple facts are the most effective response to claims that the discovery of Slack data would be disproportional or burdensome. Consider the effort involved in obtaining Slack data for discovery. For all plans, the process of exporting public Slack data can be completed in minutes. For messages in private channels, direct messages, and editing logs, that data can be obtained directly under top-tier plans or after showing that the data is subject to discovery or other legal process.
Once obtained, the burden of reviewing Slack data for discovery will depend significantly on the review process and software used. In its native form, Slack data is a virtually incomprehensible mass of JSON code. Because Slack data is so rich with information, a single line of text can result in pages of JSON code.
And because Slack data is novel, many legacy eDiscovery platforms may not be able to handle it, and many vendors may charge a premium. But, with the right software, that data can be rendered and reviewed as easily as any other document type—and often at costs far below traditional approaches to discovery.
See how legal professionals are responding to Slack discovery objections—and finding data that can change their case.
When it comes to business communication, Slack is unique. Let’s start with the way communication occurs in Slack, not just its channels, integrations, and messages, but its tone and idiosyncrasies. In few corporate meetings would you respond to a colleague with a simple thumbs down emoji.
You probably would not communicate with a coworker through a .GIF of Betty White doing a shoulder shimmy.
pose interpretive challenges
centralize data in Slack
create a unique vocabulary
can risk spoliation
In Slack, such informality is much more common. Because Slack so closely resembles the informal chat rooms of the early internet, because it allows people to communicate rapidly, as they might in face-to-face conversations, because it creates a veneer of privacy and impermanence through its secret channels and editable messages, and because it allows for media-saturated discussions, conversations in Slack often disregard typical office decorum.
This, in turn, raises interpretive difficulties. How is a legal professional, a judge, or a jury, supposed to make sense of a heart emoji in reaction to a Slack message, a ̄\_(ツ)_/ ̄ in response to an inquiry, or that .GIF of Betty White?
To complicate things even more, Slack allows users to create their own emojis by uploading a small image. In addition to the Unicode-regulated world of peach emojis, dancing ladies, and clap-backs, users can add a whole universe of emojis, from Star Wars images to their coworkers’ faces, meant to convey... what exactly? That’s the problem, isn’t it?
Of course, these aren’t issues unique to Slack. Legal professionals working on the forefront of internet communications have been struggling with these same interpretive issues for a while now. As Santa Clara University School of Law Professor Eric Goldman has noted, the profession is currently struggling with at least nine specific “emoji-related interpretive challenges,” from how to report them in court opinions, to how to convey them to a jury, to how to search from them during discovery. But Slack brings these issues increasingly to the forefront by bringing them from the margins and into the center of corporate communication.
Interpretive issues are not the only challenges Slack creates. Take, for example, the traditional idea of the custodian. The Electronic Discovery Reference Model’s glossary defines “data custodian” as a person “having administrative control of a document or electronic file”. It identifies the owner of an email account as the prototypical example.
With Slack data, determining custodians is a bit more complicated. Individuals with administrative access to a workspace have the ability to export public information. But they may not have easy access to private channels, direct messages, and changelogs. Individual users, who can see their own private communications, cannot export that data without administrative access. And while Slack makes it difficult for one custodian to truly control data, it creates the sense of control through private channels and editable, deletable messages.
The control Slack allows over an individual’s messages also creates significant risks of spoliation. Under Federal Rule of Civil Procedure 37(e), as with most state analogues, the loss or destruction of electronically stored information that should have been preserved in the anticipation or conduction of litigation can result in significant sanctions. Where there is a showing that the spoliating party acted with the intent to deprive another of evidence, those sanctions can be case-dispositive.
(e) Failure to Preserve Electronically Stored Information. If electronically stored information that should have been preserved in the anticipation or conduct of litigation is lost because a party failed to take reasonable steps to preserve it, and it cannot be restored or replaced through additional discovery, the court:
It’s not difficult to image, for example, a Slack user deleting a host of messages in an attempt to remove potential evidence. Consider, for instance, a manager who has been accused of creating a hostile work environment. Before a lawsuit is filed, before even an investigation has been launched by H.R., she deletes several Slack messages that could be “taken the wrong way.” She edits a few. In her mind, those are simply gone. After all, there is no way to see original messages once they’re edited in Slack. Only an (edited) note marks the change. And when messages are deleted altogether, they seem, in the user’s eyes, to fully disappear.
Yet, unless the underlying workspace data is destroyed, many of these attempts at spoliation will remain just attempts. With the proper retention settings, Slack records all messages, edits, and deletions. With the right eDiscovery software, finding this hidden information is simple.
Before legal professionals can tackle these issues, though, they have to deal with the most pressing one:
How do you even make sense of Slack data?