Tag Archives: criminal law

Fitbit Data Provides Clues in Murder Case: eDiscovery & Criminal Investigation

ediscovery criminal investigation

Once again, eDiscovery and emerging data sources are at the center of a criminal murder investigation. A recent article in Wired highlights how investigators used data from the victim’s Fitbit and a neighbor’s Ring digital doorbell camera to establish a timeline, identify a suspect (the victim’s 92 year-old step father), and gain a warrant to search the suspect’s home, all of which led to his arrest.

Similar to other cases involving the use of data from mobile phones, social media, and the Internet of Things, it wasn’t the electronically stored information (ESI) alone leading to the arrest, but instead it gave investigators leads that otherwise wouldn’t have existed in a pre-digital world. These leads then gave them enough evidence to request warrants for further searches and investigations of specific suspects, which then brought about arrests. In other words, solving crimes still boils down to good old-fashioned detective work, only now, investigators have new ways to uncover what might have happened and who may have been involved.

Fitbit first introduced its personal fitness tracking device ten years ago, and today around 27 million people use them. Add that to other competitor’s devices (such as the Apple Watch) and it’s not hard to imagine how investigators often have ready access to biometric data of suspects and/or victims. Last year alone, 170 million wearables were shipped worldwide.

But while much of electronic data is self-authenticating under Federal Rules of Evidence rule 902(14), biometric data gathered from wearable devices is much harder to authenticate as accurate. An analysis of 67 studies on Fitbit’s movement tracking concluded that, “the device worked best on able-bodied adults walking at typical speeds. Even then, the devices weren’t perfect—they got within 10 percent of the actual number of steps a person took half of the time—and became even less accurate in counting steps when someone was resting their wrist on a walker or stroller, for example. ‘It’s not measuring actual behavior,’ says Lynne Feehan, a clinical associate professor at the University of British Columbia and the lead researcher on the paper. ‘It’s interpreting motion.’”

Evidence from fitness trackers has been admitted in homicide cases in Europe and the US, but expert witnesses and analysts are often used in conjunction with the data to authenticate it. Only a few judges have ruled on how to handle evidence from fitness trackers. For example, “In a 2016 Wisconsin case, Fitbit data was used to eliminate the possibility that a woman was murdered by her live-in boyfriend. The judge ruled that an affidavit from Fitbit established the device’s authenticity and allowed lawyers to introduce its step-counting data; at trial, a sheriff’s department analyst vouched for the reliability of the man’s particular device. However, the judge barred the Fitbit’s sleep data, citing a class-action suit that claims the sleep tracking could be off by as much as 45 minutes.”

Similar to older technologies (such as the polygraph), electronically created data isn’t necessarily irrefutable. Antigone Peyton, an intellectual property and technology law attorney who has used data from wearables in civil cases, states that people tend to see “data is equivalent to truth,” but there are “many ways the information on these devices can be interpreted.”

Another aspect that investigators have to consider with this type of data is users’ privacy. Last year, the Supreme Court ruled that police must have a warrant to search phone location data under the 4th Amendment. At times, the companies that have the data, refuse to hand it over to law enforcement if they feel privacy is being infringed upon, but largely, the tech industry seems to cooperate, especially as procedures for handling this type of data are becoming more defined.

What is important for the legal industry to consider is how different types of data and data sources work, and what that means when it comes to authenticating it. It’s similar to when wiretaps, phone data, and other electronic surveillance was introduced into the detective’s toolkit in the 20th century. The difference is the amount of information created today is much greater, and it’s created by every person on a near continuous basis from a large number of sources. And none of this data can be looked at in the same way.

But what this new data does provide is more ways to reconstruct scenes, rule out potential suspects, corroborate or contradict testimony, and gather information which allows investigators to pursue new tactics and lines of questioning which lead to further warrants and arrests. For attorneys, it’s important to stay up on the most recent investigative uses and court-rulings on these data sources, which will continue to define and clarify how ESI is being used in both criminal and civil cases.

 

Written by Jim Gill
Content Writer, Ipro

 

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Where Does eDiscovery Fit in the Facial Recognition Conversation?

ediscovery facial recognition

Where Does eDiscovery Fit in the Facial Recognition Conversation?

JD Supra Readers Choice Top Author 2020Written by Jim Gill
Content Chief, Ipro

For most of us, the concept of facial recognition – like so much technology of the last decade – began as a sci-fi detail we accepted on the big screen but didn’t give much thought to in our day-to-day lives. Then one day, our phones started tagging photos automatically, asking, almost sheepishly, “Is this you?” And just like that, the idea that an algorithm could learn to recognize our faces was real. But we’ve moved on from that innocuous beginning and now are treading more and more into the realm of another type of film (I’m thinking here of Brazil or Minority Report) where technology aids law enforcement in making our world a safer place, but also introduces new privacy and ethics conundrums when that technology fails or is corrupted. And, as always, eDiscovery has a place where legal and tech (in this instance law-enforcement and facial recognition) collide.

Law Enforcement, Facial Recognition, and Privacy Concerns

In a Washington Post article in July 2019, it was revealed that agents with the Federal Bureau of Investigation and Immigration and Customs Enforcement were using facial recognition software to scan state driver’s license databases, analyzing millions of Americans’ photos without their knowledge or consent.

In the past, police have used fingerprints, DNA and other “biometric data” collected from criminal suspects (think of those large binders of mugshots you always see victims flipping through in cop shows), but the photos in DMV records are of a state’s residents, most of whom have never been charged with a crime.

According to the Government Accountability Office, the FBI has logged more than 390,000 facial-recognition searches of federal and local databases, including state DMV databases, since 2011. Even though neither Congress nor state legislatures have authorized the development of such a system, and now lawmakers on both sides of the political spectrum are concerned.

“Law enforcement’s access of state databases,” House Oversight Committee Chairman Elijah E. Cummings (D-Md.) said is “often done in the shadows with no consent.” And Rep. Jim Jordan (Ohio), the House Oversight Committee’s ranking Republican, seemed particularly incensed during a hearing into the technology earlier this year.

“They’ve just given access to that to the FBI,” he said. “No individual signed off on that when they renewed their driver’s license, got their driver’s licenses. They didn’t sign any waiver saying, ‘Oh, it’s okay to turn my information, my photo, over to the FBI.’ No elected officials voted for that to happen.”

Off-The-Shelf Facial Recognition Tools for Law Enforcement

In Oregon, back in 2017, the Washington County Sheriff’s Office became the first law enforcement agency in the country known to use Amazon’s artificial-intelligence tool Rekognition, and almost overnight, the deputies of this small county in the suburbs outside of Portland had ramped up their investigative ability. With this off-the-shelf technology, they were able to scan for matches of a suspect’s face across more than 300,000 mug shots taken at the county jail since 2001. With that information, they can take a picture – perhaps captured by a security camera, social-media account, or cellphone – and link it to an identity.

But linking a photo to previous mug shots is analogous to the same action that happened prior to the addition of technology. It’s something detectives used to do manually but now are assisted with the use of AI. Still, there are significant problems with the technology itself.

Facial Recognition Bans Due to Concerns Ranging from Privacy to Racial Equity

Some places have already taken measures to ban face recognition software. In 2019, San Francisco became the first city to ban the technology for law enforcement and government agencies. Similar measures are under consideration in Oakland and Massachusetts. Lawmakers in California are also considering a statewide ban on facial recognition programs.

To add to that list, the largest manufacturer of police body cameras, Axon, is rejecting the possibility of selling facial recognition technology at the recommendation of an independent ethics board which it created last year after acquiring two artificial intelligence companies.

In a 42-page report, the ethics panel found that face recognition technology is not advanced enough for law enforcement to depend on, with concerns ranging from “privacy costs to racial equity.” In fact, the technology was found to be less accurate in identifying the faces of women than men, and younger people compared to older ones. The same was true in people of color, who were harder to correctly identify than white people.

But the lack of regulation or precedent means that, while the technology is being banned in some places, it’s being pursued in others. For instance, Detroit reportedly signed a $1 million deal for software that let it continuously monitor “hundreds of private and public cameras set up around the city,” including gas stations, restaurants, churches and schools, according to the New York Times.

Facial Recognition and eDiscovery

So where does facial recognition fit in eDiscovery? As with any emerging technology, it’s worthwhile for those of us in legaltech to stay abreast of these changes. For one, any new technology is potential ESI that must be discoverable should a criminal or civil case arise in which that electronic data is evidence. Often, people in legal circles might argue, “That hasn’t happened yet, so we’ll worry about it later.” Then again, people a few decades ago might find it unbelievable that data from a phone app (“phone app?” they might add with a puzzled look) meant for requesting rides from a stranger would be used in a nationally covered murder case.

But there is also the notion that facial recognition tools might be used to help attorneys and litigation support specialists do their work. In fact, the company Veritone recently announced an AI eDiscovery tool that makes unstructured data searchable by keywords, faces, and objects.

As technology continues to forge ahead, it’s important that the legal world engages in the conversations surrounding these technologies, before they find themselves deeper in the state of catch up many say they’re already playing.

 

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Two Murder Investigations in the Last Week Highlight the Role of eDiscovery in Criminal Investigations

ediscovery in criminal investigations

More and more, eDiscovery plays a larger role in criminal investigations. These two recent murder cases have again highlighted the use of electronic forensics to solve cases that only a few decades ago, would have been difficult to crack in the relatively short time frame between the crime and the arrest.

The Sydney Loofe Case

In the second week of his trial this June, murder suspect Aubrey Trail tried to cut his own throat in the courtroom. A year ago, the then 51-year-old Trail and his alleged girlfriend 24-year-old Bailey Boswell, were charged with the murder of a 24-year-old Nebraska woman, Sydney Loofe.

Loofe was last seen 11/15/2018 before going on a Tinder date with Boswell. Police found the remains of Loofe’s body in a field a few weeks later, and in the months that followed, used a wide variety of electronic data, along with traditional forensics, to link Trail and Boswell to the murder. From an eDiscovery point of view, the list of evidence pieces together a vivid story:

  • Tinder Profiles: 140 messages between Loofe and Boswell in the days before November 15th were pulled from their online dating profiles. The last was on Nov. 15 at 6:54 p.m., when Boswell said she’d arrived at Loofe’s apartment. Police also found that Boswell went by “Audrey” on her online-dating profile.
  • Snapchat Photo: Loofe sent a selfie to a friend via Snapchat on November 15th with the caption, “Ready for my date.”
  • Facebook Videos: Trail and Boswell both posted Facebook videos claiming innocence while police were looking for them. In one, Boswell said she was “Audrey on Tinder and a few other names because I have warrants.”
  • iPhone Reset: After her arrest, Boswell gave investigators permission to search her iPhone 7, which they found had been reset to factory default settings on November 17.
  • Cellphone Pings/GPS Locations: Loofe’s phone last pinged a cell tower near Wilber, where Boswell and Trail lived in a basement apartment. When detectives searched that residence, the landlord, who lived upstairs, “reported a strong odor of bleach coming from the basement.” Data from Boswell’s phone showed its location was “in close proximity to the area where the remains were discovered Dec. 16th.”
  • Security Video Footage: Security footage from a local Home Depot showed Trail and Boswell on Nov. 15 around 10:35 a.m., shopping for tools and supplies that could be used to cover up the crime.
  • Phone Calls from Jail: In two different phone calls, one to the Lincoln Journal Star and the other to the Omaha World-Herald, Trail gave different accounts, claiming he unintentionally killed Loofe in a sex game gone wrong.

All of this led to a confession from Trail, stating that he had killed Loofe, and then he and Boswell covered up the crime scene and disposed of the body.

The MacKenzie Lueck Case

MacKenzie Lueck was a 23-year-old University of Utah student who disappeared in the early hours of June 17th, 2019. Her parents reported her missing on June 20th, and on June 28th, Ayoola Ajayi, 31, was arrested as a suspect for her murder. Once again, a combination of digital and traditional forensics created a narrative of what happened to her, and led investigators to her remains and the arrest in just over a week.

  • Airport Data: Lueck arrived at the Salt Lake City airport at 2:09am on June 17th from California after attending her grandmother’s funeral. Security photos from the airport show Lueck in the airport after deboarding her plane, giving investigators an image of what she looked like, what she was wearing, and personal belongings she had with her at the time.
  • Text to her Mother: While at the airport, Lueck texted her mother to let her know she had arrived safely.
  • Lyft Data: Lueck requested a ride through the ride-share app Lyft. Data from Lyft showed that the driver took her to Hatch Park, which is 8.5 miles from her home in Trolley Square. It also showed that nothing out of the ordinary happened on the drive, and that the Lyft driver immediately picked up other passengers after dropping her off. An interview with the driver indicated she was meeting someone in the park, but the driver didn’t know who that might be or the make/model of another car they were driving.
  • Park Surveillance: There are no surveillance cameras inside Hatch Park, but police began investigating security footage in the areas surrounding the park.
  • Social Media: Police looked at Lueck’s social media and dating profiles, and also asked the public if they had any information on alternate accounts, due to the growing trend of people keeping online profiles that aren’t known to family or close friends in order to maintain a layer of anonymity.
  • Phone Data: Cell phone data showed that the last person Lueck communicated with before going missing was Ayoola Ajayi. It also showed that Lueck’s and Ajayi’s phones were in Hatch Park the night of the 17th within one minute of each other. Hatch Park was the last place Lueck’s phone transmitted data. Ajayi’s phone also had several pictures of Lueck, including one from an online profile, after he had said in a police interview that he had no idea what Lueck looked like, had never visited her online profiles, and had last texted her at 6pm on June 16th.
  • Suspect’s Online Image: Investigators used data from Ajayi’s online footprint—from sites as varied as LinkedIn and Goodreads—along with interviews of people who knew the suspect, as well as public records, to put together a profile.
  • Search of Suspect’s Home: A forensic excavation found charred items matching Lueck’s clothing and personal belongings, and Lueck’s DNA matched remains found on site. Police also located a mattress and box-spring Ajayi had given away using a social media app just prior to his arrest.

Conclusion:

These tragic events show how law enforcement are more and more relying on electronic data to solve cases. And as these cases move to the courts, it highlights how important eDiscovery is in today’s legal world. Mobile phone data, GPS, social media, surveillance video, and other new media types are continually being used to investigate criminal cases and bring them to trial. Which is why companies that create eDiscovery and trial presentation software must continue to stay on the cutting edge of technology trends in order to maintain data integrity used in criminal and civil court. Since the use of these types of data are being used to solve crimes, attorneys and courts must be prepared to handle the electronic data while trying these cases.

Written By Jim Gill
Content Writer, Ipro Tech

 

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