Electronic Discovery

Private and Privileged Data: Public Records and FOIA Requests

By:  Julia Romero-Peter, Esq

Information requested from a government agency through a local public records request or the federal Freedom of Information Act (FOIA), may be considered private, personally identifiable information (PII) or privileged. These designations can apply in an ongoing investigation when personal information about an individual is disclosed.  And, in some cases, these designations can be appealed.

What Is Private and Privileged Information?

Private information considered personal in nature can be designated as PII. This can include medical records, financial information, or personal correspondence. Private information is typically exempt from public disclosure laws meaning, government agencies are not required to release such data in a public records request.

Privileged information is not subject to disclosure under the law. Examples of this can include attorney-client privilege, work product, matters of national security, or data related to an ongoing criminal investigation. Privileged information is typically exempt from public disclosure laws, which again, means government agencies are not required to release it in response to a public records request.

If the data requested contains private, privileged information, it may be redacted before being released to a requesting party to prevent the disclosure of national security information, for example.

Tools to Prepare Data for a Public or FOIA Request

CloudNine’s cloud-based solutions can help you locate relevant information for a public record or FOIA request.  CloudNine’s simplified review automation platform can help you manage, review, classify, redact, and prepare productions among all types of digital information. Your team can optimize your workflow and analyze data with precision using the CloudNine Suite, which includes CloudNine ESi Analyst —  the industry’s only investigation platform built and prepared to handle today’s modern data types, such as chat, text, social media, geotracking and more.

To see CloudNine software in action and learn how to save time and costs with an integrated, cloud-based review platform, contact us to schedule a consultation today.

 

To learn about the rise of modern data including social media, SMS, geolocation and corporate chat applications such as Slack and Teams, or click the link to request our newest eBook:  Modern Data Blueprint: Including All Data Sources in Your eDiscovery

 

Three Things to Consider When Moving to the Cloud

By:  Kyle Taylor

Cloud computing is trending today, and for good reasons. Reports from Flexera show that 50% of decision-makers in organizations believe that migration to the cloud will continue to increase.

While some consider it a risky move for data security, others think it’s necessary for business in many ways. What benefits do companies stand to enjoy by moving to the cloud?

Reduce Internal Infrastructure Demands and Hardware Costs

The traditional on-premise Concordance platform has many demands, especially when a company wants to scale upward. It must incur the cost of acquiring additional infrastructure when new employees come on board or it expands operations.

Cloud infrastructure is easier to grow, with a business only having to pay for other resources as required. The cloud environment requires no hardware investment.

Eliminate Time-Consuming Installs, Upgrades, And System Downtime

Migrating legacy systems to a cloud computing solution saves a company time rolling out new software and training. The team has no data centers to update regularly, saving time for more crucial activities. Cloud-based solutions also experience fewer downtimes.

Routine Backups and Disaster Recovery Process

Cloud solutions provide data encryption, regular automatic backups, and speedy data recovery. Cloud hosting providers regularly update security features based on the newest technology to keep your data protected at all times.

Other benefits of moving from the on-premise Concordance platform to the cloud include:

  • No database corruption and data integrity concerns
  • Data migration assistance from professional cloud service providers
  • Access new features, performance improvements, and bug fixes as soon as they are released
  • Unlimited data storage and processing space
  • Flexibility in using the software from anywhere with an internet connection
  • Easily collaborate with internal and external parties
  • Optional overflow services and consulting are available
  • Easy to use modern interface designed for a positive user experience
  • Automated seamless workflows
  • Customizable tag options and formats
  • Cloud-based databases support modern data formats
  • Reviewer statistics
  • Flexible database customization at the user level

The benefits of moving from an on-premise platform (like Concordance) are endless. If you would like to start the migration or get support for your cloud solution, contact us today to schedule a consultation.

Click to Download: Moving to the Cloud: Lessons from the Experts

JSON is not a document, it is data… and lots of it!

By:  Trent Livingston

Modern eDiscovery deals with much more than just documents. In 2020, people created 1.7 MB of data every second, and most of that data was likely stored in a database. Now, newer applications like Facebook, Twitter, Slack are storing copious amounts of data ranging from tweets, wall posts, and chats.

Many of these artifacts are stored with complementary data that can include file links, reactions (such as “likes”), and even geolocation information. Accessing this modern data in order to leverage it for a discovery request often requires some sort of archive process from the originating application, and that is when JSON enters the picture.

JSON stands for “JavaScript Object Notation”, but that doesn’t mean you need to know how to write JavaScript (or any code for that matter)!  If you’ve ever dealt with discovery surrounding any of the aforementioned applications, you’ve likely come across a few JSON files. In a nutshell, think of JSON as a relational spreadsheet where one column of data in one tab of your spreadsheet is defined by another column of data in another tab in another spreadsheet.

For example, you might have a column called “Address” in a spreadsheet and that column contains a series of numeric “id” values that reference another tab in that same spreadsheet. In this secondary tab, each address is broken down into values for that address that may include things like “country”, “zip”, or “street”.  All those values that have the same “id” belong to the “address” reference in the previous tab. Simply put, this is structured data. JSON data is no different. However, JSON can contain a multitude of data structures varying from simple to complex.

The problem with JSON is while there are multiple JSON viewers and formatters online, they do not understand the defined data structures within.  Each platform defines these data structures differently, and while the vehicle may be the same, the defined structure is usually different from application to application (as well as the application’s version).  Therefore, the data within the JSON often comes out in an unexpected format when using a generic formatting tool, and the relationships between the data are often lost or jumbled. (By the way, you should never use any online “free” tool to format potentially confidential or privileged information).

Therefore, it is important to work with someone who understands JSON as an eDiscovery data source.  A single JSON file just a few megabytes in size may represent hundreds, if not thousands of messages, contain numerous links to files, as well as key data relevant to your investigation or litigation. Contained within a JSON file could be any number of nested data formats, including:

  • Strings: a sequence of zero or more Unicode characters, which could include emojis in a Unicode format, usernames, or an actual text message.
  • Numbers: a numeric value that can represent a date, intrinsic value, id, or potentially a true/false value represented as “1” or “0”.
  • Objects: a series or collection of one or more data points represented as named value pairs that create meaning as a whole, such as longitude, latitude, elevation, rate of speed, and direction that make up the components of a device’s location.
  • Arrays: a collection of values or elements of the same type that can be individually referenced by using an index to a unique identifier, such as the choices of a color of a car on a website or a set of canned response values listed in a software chat application.

The thing to remember is the JSON file is actually one big “object”, which is the parent to all of the named value pairs beneath it.  Within this object, you can have more objects that contain numbers, strings, arrays, and yet even more objects. Confused yet?

Not to worry! It is understandable that all this JSON data can quickly become a source of frustration!  The question that remains is, “How do I make sense of all of this structured data and present it for review in a reasonably usable format?” 

Here are some tips:

  1. Make sure you do not overlook JSON as part of your electronic discovery protocol
  2. Leverage an experienced team to help you understand the JSON output
    • Document the source application whenever possible (some JSON include access keys that can expire or be terminated at any time, such as Slack)
    • Preserve the JSON file as you would any other evidentiary data source
    • Document the chain of custody for the JSON file (originating application and version of that application, who conducted the export, as well as any access keys that may be transitory or temporary and their date of expiration)
    • Treat each JSON file and associated content as a potential source of PII, confidential, and/or privileged information given the breadth of data that each may contain
  3. Work with a team and a product that can parse, ingest, and subsequently present JSON data in a usable format for review and production

While there is not an off-the-shelf solution for every JSON file in existence, CloudNine ESI Analyst is a platform designed for the multitude of data types that can be extracted from just about any JSON file out there. Many of which can be easily mapped to a data type construct within our SaaS application that allows for presentation, review, and production in a reasonably usable format.

Contact us today for a demonstration and further detail!

Three Use Cases to Navigate Modern Data in eDiscovery

In litigation, knowing the full picture is the only way to effectively represent your clients. The only problem is most of the story is often stored on electronic devices like smartphones, laptops, or tablets.

While eDiscovery can be dated back to 1981 and the first substantial use of email in litigation (Governors of United State Postal Service v. United States Postal Rate Commission), integrating newer, modern data types like text messages, computer activity, and financial data, has been a bit more challenging. These challenges relate back to how eDiscovery has historically worked and why modern data sources don’t fit nicely into that process. 

When eDiscovery was introduced with email and electronic documents as the primary source of information, simple messages and documents were sufficient to tell the story in a linear document review workflow. But, with sophisticated technology like Slack, chat applications and smartphone messaging where communications occur in real time, the conversion to documents for review hinders a proper evidence analysis.

Making sense of all that data only works when it is presented in the way it was originally communicated. The old documentation process simply doesn’t provide the insight you need to leverage modern data in litigation.

Case Study 1: Tackling Disparate Modern Data from Multiple Sources

No matter how small or large your case is, reviewing modern data can be challenging. Between smartphones, laptops, social media apps, and other connected devices, there’s a plethora of data to sift through to find the evidence you need to support your case. This process becomes even more complicated when the data is presented through the lens of traditional eDiscovery meaning, in traditional document format. What once worked for simple electronic communications no longer tells the whole story within complex, real-time and editable messaging technologies like WhatsApp, Slack and social media.

So what happens when you have to produce data from hundreds of international sources, and need it to tell the story of what actually happened? Let’s look at a case study of a construction company who had to do exactly that.

The Problem:

One of the largest construction companies in the world required the collection of modern data from 300 international sources. While the sheer number of sources was a challenge in itself, the real difficulty was working with disparate data from so many different sources.

Each business unit within the company used different technology so data had to be collected from a vast number of sources – local desktops, laptops, smartphones, tablets, and backup servers.

Plus, because so many BYOD devices were used, legal, data privacy, IT, and risk & compliance departments had to be consulted throughout the collection and review process to ensure no U.S. or international privacy laws were broken.

The Solution:

Ultimately, our client needed to understand who said or did what, and when. Basic documents with communications from readily available sources wouldn’t be enough, because they couldn’t easily identify the critical timeline of events or the intentions of each party. In the end, CloudNine ESI’s actor normalization function was the key to finding the evidence needed.

The Results:

By matching specific individuals to different aliases and phone numbers, attorneys were able to identify a handful of photos shared from the vast amount of data collected that proved the construction company was at fault. These photos were presented to the court in the form of inline bubble messaging that was easy to read and view.  To learn more about this use case, click here.

Case Study 2: Overcoming the Personal Device eDiscovery Challenge

There’s an expected, inherent trust between a company and its employees which means employees typically won’t do work that’s a conflict of interest with their current employer. Unfortunately, that trust is sometimes broken by actors that take advantage of their position.

The Problem:

When a heavy equipment manager became the target of a moonlighting case that cost his company money, attorneys were discouraged when they couldn’t find any evidence of wrongdoing. There were no documents, emails, or invoices to be found through traditional eDiscovery.

The Solution:

Fortunately, the key to the case was the manager’s smartphone.

By gaining access to his phone, attorneys were able to secure tens of thousands of text messages directly related to the case. This helped them discover how he operated his illegal side hustle. They also learned he was sharing confidential, copyrighted, and proprietary information through photos sent via text message.

The Results:

Through CloudNine ESI Analyst, attorneys were able to create conversation threads which were easy to review and produce. These threads not only helped them identify other involved parties, but let them produce messages, including embedded images, videos, GIFs, and emojis.

Without the ability to review and analyze the bad actor’s smartphone data, the case likely would not have gone forward.  

To learn more about this use case, click here.

Case Study 3: Protecting Company Data with Modern eDiscovery

The average American holds 12 jobs in their lifetime so it’s safe to say you will lose employees from time to time. Whether purposeful or accidental, the odds are good their personal devices will contain confidential or proprietary information when they walk through the door for the final time.

So what if you could examine their devices and remove all sensitive material before they left?

The Problem:

An employee spent six months working from home on a personal laptop before announcing his resignation to work for a competitor. If the employee was allowed to leave without a device review, he’d likely be leaving with documents that would benefit both him and his new employer.

Whether he would ever used those documents or not, chances are he’d find himself in the middle of a long, expensive trade secrets case which would also impact his new employer.

The Solution:

The representatives of the employee’s current company needed a way to access his personal laptop and identify any confidential or proprietary documents to be destroyed before he went to work for their competitor. They sought out a solution to easily identify these risks to protect their company, the employee and the employee’s future company.

The Results:

With CloudNine ESI Analyst, company representatives were able to access his personal laptop, create a chain of custody and review the data found on it. This allowed them to find confidential and proprietary data and remove it before the employee left for his new position, protecting all parties involved.

By doing this in advance, you preserve the data and protect it without relying on your employees to remember if they have sensitive information on their devices or not.

To learn more about this use case, click here

CloudNine ESI Analyst – A Modern eDiscovery Solution for Modern Data Review

While most law firms, corporations, and LSPs are challenged to review modern data through traditional eDiscovery tools, they struggle to pull the true value out of the data. Each text and corporate chat message are recreated as stand-alone documents, leaving you to piece them all together like a giant legal jigsaw puzzle with missing pieces and others that simply don’t fit the storyline.

With a robust and flexible modern eDiscovery tool like CloudNine ESI Analyst, you have access to alternative data to help you put the puzzle together through linear storytelling that creates a digital trail of evidence, including some of these popular sources:

  • Text messages (SMS and MMS)
  • Call logs
  • Voicemails
  • Messenger applications (Slack, Teams, WhatsApp, Messenger, etc.)
  • Computer activity
  • Financial transactions
  • Geolocation

Modernize your investigations and litigation by effectively managing the data in a single platform instead of wasting time managing a menagerie of documents in siloed systems.

Every case is unique and requires you to find the facts and context to tell the complete story. Contact CloudNine and learn how we can help you leverage all the data to get to the truth of the matter. Contact us to learn more.

Modern Data Discussions by Leading Experts at The Master’s Conference in DC

Last week, CloudNine Senior Director Rick Clark, VP Rob Lekowski and industry thought leaders convened in Washington, DC for The Master’s Conference first in-person event since early 2020. The two-day event tackled the latest challenges in eDiscovery, cybersecurity, and information governance. Managing modern data was the most popular recurrent topic with four distinct panels on the subject.

Smartphones, collaboration apps, and social media platforms all store a plethora of relevant information and is where today’s most important evidence resides. By avoiding or mismanaging this evidence, lawyers miss out on critical insights. So, how should legal teams incorporate modern data into investigations? Rick Clark addressed this question and more during the panel titled “Telling The Full Story: Leveraging the Data Between the Documents” with panelists Dave Rogers, Kroll; Kevin Albert, PAE; and Sonya Judkins, T-Mobile.

Here are three key takeaways from the panel discussion:

Modern data types can no longer be ignored – Emails and traditional documents are always going to be a part of discovery and investigations, but key data has moved away from these platforms. Conversations in Slack, MS Teams, device chat applications and text messages are additional communications needed to follow the conversation. Nowadays, modern data expands above communications into geolocation, social media posts, user activities and offer the largest insights. Recent case decisions have proven that judges are open to admitting modern data so long as the evidence is relevant and properly authenticated.

 Data shouldn’t be treated like documents – One reason why legal teams avoid modern data is linear document review. Imaging and exporting modern data leads to issues like missing metadata, families, threads, and file types. This method also requires legal teams to review evidence without any threading, deduplication, or link-analysis tools. Instead, large volumes of data are analyzed document by document. Linear document review is tedious, inefficient, and time-consuming but most important is legal teams who use linear document review also run the risk of overlooking important details. By opting for link analysis, litigants can connect various data points together to find relevant information faster.

“There just isn’t a good solution out there” – NOT TRUE – Four panels at the Master’s Conference discussed the challenges of modern data, but only Rick Clark’s panel offered a solution. CloudNine ESI Analyst is the only software that renders modern data in a near-native state. The platform uniquely offers users the ability to ingest and investigate multiple data sources within a single platform. Attendees of the CloudNine breakout session were given a full demonstration of ESI Analyst’s capabilities. Through timelines and 24-hour threads, ESI Analyst enables native analysis of communications, transactions, and computer activities.

Missed the Washington, DC event? Join us May 18th, 2022 for the next Master’s Conference in Chicago, Illinois.

Click here to learn more about how CloudNine ESI Analyst can help you manage your modern data.

CloudNine’s LegalWeek 2022 Recap

Last week, the CloudNine team visited New York City to provide virtual and in-person demos during LegalWeek 2022. Rick Clark, Robert Lekowski, Clint Lehew, and Jess Moore were able to share the capabilities of CloudNine ESI Analyst with over 50 attendees.

As the industry’s only near-native investigative platform, CloudNine ESI Analyst simplifies the discovery of mobile, chat, social, and geolocation data from collection to production. Through our platform, users can filter, search, and tag items at the individual level. Messages can also be viewed through our 24-hour thread feature which increases review speeds by permitting the numbering, tagging, and production of individual messages while displaying the full context of a conversation. The key difference between ESI Analyst and traditional review is our way of processing modern data. Traditional review turns all data into documents without providing sufficient means for filtering and searching conversations. Each message or thread must be reviewed page by page. By rendering messages and media inline, ESI Analyst allows legal teams to piece evidence together at a faster rate.

During LegalWeek, the CloudNine team was able to speak to our clients directly and learn how our platform changed their tactics on approaching data and case strategies. Clients like Phil Hodgkins raved about the user-based pricing and clarity that ESI Analyst offers in telling the whole story. While conducting an internal investigation, Phil’s team found that ESI Analyst saved time and yielded better insights than two traditional review platforms. Since then, Phil has encouraged lawyers to stop cramming mobile data into document-based spaces.

“If [our clients] start talking about mobile data [and getting] into the nuts and bolts of a laptop or any device, we immediately start talking about your tool. It allows you to gain insights much more quickly than putting the data into a typical review space” – Phil Hodgkins, Director of Data Insights and Forensics at Kroll. To learn more about Phil’s experiences with ESI Analyst, click here.

Missed out on CloudNine’s LegalWeek demos? Book a demo today to learn how our software simplifies and accelerates modern data discovery.

Discover the Power of ESI Analyst During LegalWeek 2022

The past two days have been a blast for the CloudNine team. From now until Friday, March 11, CloudNine is offering in-person and virtual demos while we visit New York during LegalWeek 2022. We would love to see you there as we reconnect with long-time clients and welcome new faces. The CloudNine team is also eager for the opportunity to showcase our latest eDiscovery innovation, ESI Analyst.

Modern discovery is more than documents, it’s about telling the story. Nowadays, emails and Microsoft Office files aren’t enough to piece a narrative together. Large amounts of information can be obtained from financial transactions, geolocation data, social media activity, text messaging, and more. Through customer feedback and client experiences, we recognized how taxing modern data types could be without the right tools. As an emerging solution for modern investigations, ESI Analyst uniquely offers users the ability to ingest and investigate multiple data sources within a single platform. CloudNine’s recent acquisition of ESI Analyst allows us to provide our customers with an in-depth solution for collecting, processing, and reviewing modern data.

Ready to learn more about our latest updates and solutions? There’s still time to schedule a demo. Virtually or in-person, our team is excited to provide demonstrations on the latest integration between CloudNine Review and ESI Analyst. Meetings will also feature updates on CloudNine Review’s other integrations with LAW, Concordance, and Explore via CloudNine’s Discovery Portal. Click here to book a demo before the end of LegalWeek. Or click on the banner below to request a virtual demo later this month.

Understanding and Managing eDiscovery Costs

For a medium-sized lawsuit, eDiscovery costs can range anywhere from 2.5 to 3.5 million dollars. [1] This price has been exacerbated by the effects of COVID-19 on communication data. According to the International Legal Technology Association (ILTA), the pandemic has created a data explosion by encouraging frequent usage of chat applications. Meanwhile, the levels of email and other data types have remained constant. [2] As time passes, the list of communication types will continue to expand with new collaboration tools and social media platforms. On one hand, these changes have made communicating with loved ones and coworkers easier than ever. On the other hand, the influx of modern data types has created an expensive headache for legal teams.

Current Approaches to the Problem

To handle litigation costs, companies often try to cut labor costs, increase review rates, and group documents together. However, each of these approaches can only do so much. For instance, it’s risky for companies to save money through temporary attorneys or LPO companies. Though the strategy is cost-efficient, it creates new challenges surrounding logistics, data security, attorney-client privilege, and oversight. The second method was increasing the speed of review. This method holds some promise, but its efficiency depends on the type of review. Automated review is great at accelerating the process, but human review speeds are harder to manage. At best, an expert review can review 100 documents per hour. Yet, the benefit of speed comes at the chance of comprehension errors. Grouping documents isn’t an efficient solution either. The technique uses computerized technology to categorize similar documents together. Though this method is good for organizational purposes, it does nothing to minimize the volume of data. [3]

Cost-Saving eDiscovery Strategies

  1. Don’t spend too much time on search term negotiations. It’s easy for opposing parties to lose time and money while fretting over each search term; however, this practice forces counsel to work overtime to meet deadlines. Consequently, companies will have to pay higher attorney fees. The best solution would be to agree on a handful of search terms and run the data through machine learning systems for review.
  2. Avoid overusing issue coding. Though issue codes are useful for organizing documents, excessive issue coding makes the review process slower and more expensive. Consider limiting the codes to 8-10 per document.
  3. Eliminate unnecessary attachments from important documents (i.e. company logos and icons). These attachments can be eliminated manually or through a modern data processing system. [4]
  4. Engage in the discovery process as soon as possible. By contacting legal counsel early on, companies can reduce the time and money needed for processing and review.
  5. Stay prepared for the possibility of litigation by instructing employees on storing and accessing important documents. This method will save time and money by making the documents easier to find. [5]

 

[1] “Reducing eDiscovery Costs” Whitepaper, Canon Discovery Services, 2018.

[2] Sarah Gayda, “How Law Firms Can Proactively Reduce eDiscovery Risk & Cost,” Iltanet, May 21, 2021.

[3] Nicholas M. Pace, Laura Zakaras, “The Cost of Producing Electronic Documents in Civil Lawsuits,” RAND Institute for Civil Justice, 2012.

[4] Lisa Prowse, “Review is Not the Most Expensive Part of E-discovery,” KMWorld, October 29, 2020.

[5] Scott Carvo, Madelaine C. Lane, and Janet Ramsey, “Creative Ways to Cut Down on E-discovery Costs,” Grand Rapid’s Business Journal, September 4, 2020.

How COVID-19 Has Reinforced the Need for Comprehensive BYOD Policies

Even before the pandemic started, working from home was on the rise. The trend allowed employees to be both productive and comfortable. Like any change, the transition to remote work was met with some skepticism. Many worried that limited in-person interaction would negatively impact work relations and company culture. Another concern was that employees wouldn’t get their work done at home. Though the research is mixed, several studies suggest that working from home greatly improves productivity. Amid the controversy, remote work skyrocketed as quarantine guidelines were set in the United States. This shift boosted the popularity of BYOD policies in the workplace. BYOD is shorthand for “bring your own device,” a practice in which businesses allow employees to conduct work activities on personal devices.

From both the employer and employee perspectives, BYOD policies come with a list of pros and cons. Employees typically enjoy the change, grateful that they don’t have to carry two phones everywhere. BYOD allows them to conveniently handle business and personal affairs from the same device. Through this system, an employee can work from anywhere at any time. From the employer’s standpoint, BYOD practices can be a money saver. Companies that supply and maintain work phones are expected to foot the bill. BYOD, however, eliminates those business expenditures.[1] In terms of ediscovery, BYOD poses significant privacy and security concerns. Now more than ever, companies should reevaluate their BYOD policies, ensuring that sensitive data is well-protected.

Questions to Consider

Before drafting or revising BYOD policies, there are several questions that a company should ask itself. Below is a list of sample questions to get the ball rolling:

BYOD Recommendations

  • Ask new employees about the BYOD policies at their former jobs. If the employee previously used their personal device for business matters, their device could still contain competitor data. Detecting and eliminating competitor data early on reduces the risk of lawsuits. [2]
  • Pay particular attention to securing data from your legal department. Legal departments, specifically, are a popular target for hackers because they manage large amounts of sensitive information.
  • Consider setting time limits on employee access to highly sensitive material.
  • Consider an employee’s position in the company before allowing them to operate through a personal device. If their position requires consistent interaction with confidential information, it’s safer to supply them with a work phone. [3]
  • Outline any software and applications that employees should not use.
  • Establish protocols for litigation holds and employee departure. [1]
References

[1] Russell Beets, “BYOD (Bring Your Own Device) Policies and Best Practices,” LitSmart E-Discovery, November 17, 2017.
[2] Will Kelly, “BYOD and the danger of litigation” TechRepublic, November 3, 2015.
[3] Frank Ready, “When Should Companies Refresh BYOD Policies? With COVID-19, It’s Now” Legaltech News, July 16, 2020.

The Discoverability of IoT Devices

What are IoT Devices

The Internet has transformed the way we conduct daily chores. Simple objects such as fridges, watches, doorbells, and washing machines can now be connected to secure networks. This technology is quick, efficient, and the perfect replacement for manual tasks. Whenever the user is within range and connected to WiFi, IoT devices can be used to turn on the lights, preheat the oven, and more. But what exactly is the definition of an IoT device? IoT is shorthand for the Internet of Things, a term used to describe physical objects that transmit data through wireless networks. [1] Fortunately for legal teams, IoT devices are effective in the courtroom as well as the home.

IoT Devices in Court

  • Four years ago in Arkansas, data from an Amazon Echo was used to investigate the death of Victor Collins. When Collins was found dead in his hot tub, his friend James Bates was charged with first-degree murder and evidence tampering. The charges were later dismissed due to reasonable doubt amongst the court. Unfortunately, news sources haven’t disclosed what the voice recordings revealed. [2]
  • After Timothy Burke was accused of shooting his brother, the prosecutor requested the admittance of audios from a Ring doorbell. The defendant objected to its admittance, claiming that it violated New York’s wiretapping and eavesdropping law. The objection was overruled. [3]
  • In an aggravated arson and insurance fraud case, Ross Compton’s guilt was proven by his pacemaker. The man claimed that he packed up his belongings and threw them out the window after discovering the fire. Medical examiners concluded that the pacemaker’s heart rate and cardiac rhythm data disproved Compton’s claims. [4]
  • In State of Wisconsin v. Burch, the defendant was accused of killing her boyfriend. However, the charges were dropped after Fitbit data revealed that Burch had only taken 12 steps in the hours before the death. [5]

Key Considerations

  • Legal teams should explain the significance of IoT data to their clients and evaluate any IoT devices that might be useful.
  • During (or in the prospect of) litigation, disable auto-deletion features on IoT devices.
  • Investigate the reliability of the device’s data.
  • Assess the accessibility of IoT data and the cost of its production. [6]

Conclusion

IoT devices are too valuable to be overlooked in litigation. As demonstrated by the aforementioned court cases, IoT data is quite useful in criminal cases. However, its utility doesn’t stop there. IoT data can also play a significant part in personal injury claims, family law, IP litigation, and more. It would be remiss of litigants to ignore IoT devices during the discovery process. Instead, litigants should consider the relevance and proportionality of IoT devices when drafting their ESI protocol.

 

[1] Brian Morrison and Joann Militano, “E-Discovery for IoT Devices: Primer for Representing Individual Clients,” New York Law Journal, February 1, 2021, https://advance.lexis.com/api/document?collection=legalnews&id=urn:contentItem:61X0-8FG1-JBM3-R471-00000-00&context=1516831.

[2] Erik De La Garza, “Charges Dropped in Amazon Echo Murder Case,” Courthouse News Service, November 29, 2017, https://www.courthousenews.com/charges-dropped-in-amazon-echo-murder-case/

[3] Kimberley Haas, “Judge: Audio from Ring doorbell can be used as evidence in Rochester shooting case,” New Hampshire Union Leader, March 5, 2020, https://www.unionleader.com/news/crime/judge-audio-from-ring-doorbell-can-be-used-as-evidence-in-rochester-shooting-case/article_ee1ddcd1-b193-5ec9-ad9b-08c22fbcdc2f.html

[4] Debra Cassens Weiss, “Data on Man’s Pacemaker Led to His Arrest on Arson Charges,” ABA Journal, February 16, 2017, https://www.abajournal.com/news/article/data_on_mans_pacemaker_led_to_his_arrest_on_arson_charges

[5] Greg Goth. “Can Wearables Testify Against Their Owners?” IEEE Spectrum, Sept. 27, 2021, https://spectrum.ieee.org/wearable-data-court

[6] Briar Morrison and Joann Militano, “E-Discovery for IoT Devices: Primer for Representing Individual Clients.”