Legal risks are approaching as companies rush to integrate AI into their daily operations. However, these same organizations are torn between streamlining workflows and protecting sensitive information. Legal transcription companies offer their expertise as a safer alternative, though many businesses still opt for automated solutions without understanding the full implications.
Behind closed doors, legal departments grapple with an uncomfortable reality—the very tools meant to increase efficiency could expose their organizations to liability. However, the risks continue to increase as AI capabilities expand, which forces companies to confront challenges that few could have anticipated just years ago.
In this article, you’ll learn how:
- AI transcription services pose privacy risks by potentially sending confidential meeting content to unintended recipients.
- In healthcare settings, AI transcription tools have concerning error rates and can generate false medical information, creating liability risks.
- Current AI transcription technology falls short of ADA compliance standards, making organizations vulnerable to legal issues.
AI Breaches the Sacred Attorney-Client Bond
Arguably, the most critical legal risk that AI offers to legal professionals is the potential compromise of attorney-client privilege. Since the AI boom, many law firms have increasingly utilized AI for daily administrative tasks like transcription during meetings. Although AI might sound like a convenient solution, AI comes with risks that companies must carefully assess.
The concern stems from how AI transcription companies handle information. Specifically, when transcripts are automatically sent to meeting participants after the meeting, this confidential information could get in the wrong hands. Of course, AI services don’t automatically waive attorney-client privilege; however, these organizations must implement proper access controls over transcripts, especially from legal team meetings, to maintain confidentiality.
Although not exactly a legal matter, one incident involved Alex Bilzerian, an AI researcher who received an unintended full meeting transcript from Otter.ai. This is a major issue because the transcript contained conversations from a venture capital firm after their Zoom meeting. Part of the transcript was private discussions after the official meeting ended.
Alex Bilzerian posted about the incident on X, which unexpectedly got over 5 million views when shared on the platform. Luckily, the information didn’t fall into the wrong hands. That said, the incident is a perfect example of how easily AI transcription services can compromise confidentiality.
However, the implications of such breaches are worse than the immediate confidentiality concerns. Attorney-client privilege goes out the window when AI tools expose confidential details. And, in some cases, related discussions on the same matter. In addition, this kind of risk is acute in the litigation context—inadvertent disclosure of privileged information can impact litigation outcomes.
Other Implications Of Using AI In The Legal Landscape
Here are more things to watch out for when using AI in legal settings.
| Implication | Description |
| AI in Jury Selection | Using AI to scan jurors’ social media and background data could unfairly influence jury selection, turning the process into a sophisticated chess game. |
| Legal Fee Reshaping | With AI handling a junior lawyer’s tasks, firms are forced to reinvent their billing models. |
| Courtroom Decision Support | Courts could wrestle with AI-assisted decision-making. |
| Translation Challenges | Legal AI translations across borders create risky situations where subtle legal meanings get lost between languages. |
| Digital Knowledge Banks | Firms building AI knowledge vaults face a paradox: efficient information sharing might reduce diversity in legal thinking |
| Smart Contract Evolution | Combining AI and blockchain in contracts raises questions about human oversight. |
| Expert Testimony Analysis | AI fact-checking expert witnesses sounds promising, but it struggles to assess human credibility and context. |
Justice System Faces a Dilemma With AI
It’s clear to me that the risk of using AI software within a law enforcement agency has also raised significant concerns, primarily when it comes to accuracy and accountability. Just recently, the King County Prosecuting Attorney’s Office decided to reject all police report narratives produced with any sort of AI assistance. The decision was a result of issues like ensuring compliance with Criminal Justice Information Services (CJIS) requirements, and privacy concerns regarding AI.
According to the new rules, officers must now certify their reports under penalty of perjury, which makes the legal implications of using AI even more serious. In particular, even the tiniest AI-generated mistakes that go unnoticed during officer review could be exposed in courts. Without a system to preserve drafts, officers cannot prove that errors are truly AI-generated rather than their own negligence. Then, you guessed it, AI-generated mistakes can lead to Brady implications for the officer.
I cannot stress the legal risks of using AI software in criminal proceedings. Inaccurate details in police report narratives will only compromise investigations—wrongful arrests or, worse, eroding public trust in the justice system. Not only that, the lack of transparency in how AI systems generate content makes it even more difficult to challenge or verify the accuracy of AI-assisted reports. This leads to a violation of the defendant’s rights to a fair trial.
The Hidden Dangers of AI in Healthcare
The healthcare space was one of the first to adopt AI transcription tools. However, using AI in healthcare presents risks that go far beyond privacy concerns. Let’s talk about Whisper AI for example.
Indeed, OpenAI has always been explicit about warning against using Whisper AI in “high-risk domains,” the tool is still being widely used in the sector, with over 30,000 healthcare workers using Whisper-based tools. Worse, some systems delete the original audio recordings, which means if we ever need to review the audio for correctness, this option is no longer available.
The accuracy issues of AI transcription tools are really where the concern comes from, especially in healthcare. Researchers discovered that OpenAI’s Whisper frequently creates hallucinations, generating sentences that were never actually spoken in the recording. If that isn’t enough to make you change your mind, the error rates were also astonishing; one researcher found hallucinations in 80% of audio transcripts, while another found them in about 50% of over 100 hours analyzed.
And don’t get me wrong, these hallucinations aren’t simple word substitutes (i.e. their vs there). No, these hallucinations includes problematic content like medical treatments that never actually happned, statements that were never spoken during pauses in the audio, and, worse yet, violent rhetoric. So, it’s clear as day that The legal consequences of all these mistakes will undoubtedly lead to medical malpractice claims or regulatory compliance issues.
On the topic of compliance in healthcare, the case for not using AI is even greater when you throw the requirements of the Health Insurance Portability and Accountability ACT (HIPAA) into the mix. Healthcare providers must ensure that their AI software meets HIPAA’s requirements for keeping health information confidential, and not many AI services comply with this law.
Universities Wrestling with AI Security
AI tools also raise concerns in an educational environment, particularly when we have to consider AI to provide greater student accessibility, but at the risk of privacy. And, it’s apparent. Recent actions taken by major universities across the United States have exemplified these challenges. For example, the University of Massachusetts IT department recently decided to restrict Otter.ai and MeetGeek’s transcription services thanks to them violating Massachusetts’ all-party consent statute and the University’s acceptable Use Policy.
However, these restrictions also affected Michele Cooke, a deaf professor at the same university. When the AI transcription services were blocked, she was left without accommodations. And there lies the problem – accessibility for the disabled vs privacy.
In a fairly similar situation, Vanderbilt University disabled third-party AI meeting tools on its network, which includes Read.AI and Otter.ai. These events reflect a growing trend among education institutions to reassess their relationship with technology. The university’s decision came from analyzing vulnerabilities in its communication systems.
In my opinion, educational institutions should also consider their obligations under the Family Educational Rights and Privacy Act (FERPA), which protects the privacy of student education records. AI transcription tools in education settings can lead to FERPA compliance issues if the students’ information gets out or is improperly handled by these systems. And this takes me back to the first section where Otter.ai unintentionally sent a meeting transcript to someone who didn’t intend to see the contents.
Making Technology Truly Accessible Beyond the Law
The Americans with Disabilities Act (ADA) creates an additional legal risk from using AI software like transcription tools. In fact, major universities like Maryland, Harvard, and MIT have faced lawsuits due to inadequate captioning—claims were that poor captions violated the ADA.
Despite the recent advancements, the current AI captioning tech still falls short of accessibility requirements. For instance, YouTube’s automatic captions can only achieve up to 70% accuracy rates, and AI transcription, in general, can only achieve 86% accuracy at best, while the ADA requirement is at least 99%. The significant gap creates liability risk for organizations relying solely on AI solutions for accessibility needs. Not to mention how accuracy drastically dissipates with background noises, accepts, and even multi-syllable words.
On top of the immediate legal risks of ADA violations, inadequate captioning can effectively exclude disabled individuals from full participation in activities. Also, when AI-generated captions contain errors, some disabled individuals may have no way to verify these inaccuracies. And guess what? The exclusion can lead to discrimination claims against the educational institution.
Your Data in AI’s Hands
As lightly tackled in the last hundreds of words, data security is another legal risk in using AI software. For the same reason, organizations must carefully consider third-party vendor access to information, as these relationships create vulnerabilities in data security frameworks.
That said, the risk becomes acute when AI tools are granted access to calendars, meetings, organizational communications, or anything crucial within the organization without proper controls to differentiate between confidential and general information.
Data retention policies are another area of concern from using AI software. Organizations must ensure that an AI provider’s data handling practices align with their own legal obligations, which is something not quite easy to do. Even so, this includes understanding how providers might use collected data for mode training or other purposes that could expose information to unauthorized use.
In addition, the global structure of many AI service providers amplifies the complexity of security considerations. Because of this, understanding different jurisdictional requirements for data protection is essential, such as the European Union’s General Data Protection Regulation (GDPR), California’s Consumer Privacy Act (CCPA), and other regional laws.
However, being compliant with these carrying requirements can be challenging when AI tools just process data without minding geographic boundaries.
Why Ditto’s Human Transcription Is Still The Gold Standard
I know I’ve said this before, but it bears repeating: the consequences of inaccurate transcription are heavy, far-reaching, and unpredictable. Some potential effects of incorrect transcripts include miscommunications, legal ramifications, loss of credibility, misinformation, operational errors, medical errors, negative financial consequences, damaged relationships, and time and resource waste.
Ditto offers 100% human transcription—no AI, no automated tools, no soulless machines like ChatGPT listening to your recordings and spitting out inaccurate transcripts by the boatload.
We’re a professional transcription company, so we won’t settle with giving our clients the bare minimum. Our services come with the following features:
- 100% human transcription: Ditto’s human transcription guarantees the highest possible accuracy, from initial checks to final edits.
- U.S.-based Transcribers: We only work with native English speakers to ensure quality, comprehension, and accuracy.
- Certified Transcripts: Any transcripts involved in litigation can be certified—an extra layer of protection.
- No long-term contracts: We operate on a pay-as-you-go option; give us as much or as little work as possible without paying through the nose for quality transcription.
- Fast turnaround times: To ensure your workflow runs smoothly, you’ll get your transcripts in as little as 24 hours.
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So what are you waiting for? Call us for world-class human transcription service.
Ditto Transcripts is a Denver, Colorado-based FINRA, HIPAA, and CJIS-compliant transcription services company that provides fast, accurate, and affordable transcripts for individuals and companies of all sizes. Call (720) 287-3710 today for a free quote, and ask about our free five-day trial.
