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Court Conundrums: AI on Trial

by Trish Lomonosov / October 12, 2023

As artificial intelligence (AI) becomes increasingly integrated into various aspects of our lives, the complexities related to the technology are resulting in a wide range of legal issues that parties are turning to courts to resolve. The rapid advancement of AI has brought numerous benefits to society, but it is also raising complicated issues for the judiciary as it applies existing laws to an AI-driven world. The judiciary is proving to be an essential player in establishing boundaries around AI technology as it navigates through uncharted waters and sets legal precedent in AI matters.

As members of the judiciary are challenged to understand this emerging and complex body of law, they may be asking themselves, “How will this changing landscape impact future caseloads in my jurisdiction?” 

Some judges and court managers may nervously look to the past and recall catalysts that caused caseloads to soar or resulted in increased case complexity. Some examples I’ve seen in my role as a court planner include changes in immigration laws, the U.S. Bankruptcy Code, health care fraud enforcement, and Sentencing Commission guidelines. In each of these areas, shifting external factors either flooded courts with a greater volume of cases or required considerably more time for judges and counsel to litigate increasingly complex proceedings. 

Although shifting trends can be cause for concern, I would argue that as the nature and complexity of caseloads have shifted in recent decades, courts have proven adept at evolving and effectively responding to changing landscapes. I believe this will be the case as courts continue to define the legal boundaries surrounding AI.

The Legal Maze of AI

Let’s explore some examples of legal issues arising from AI that courts are addressing.

Intellectual Property Infringement. AI-generated content, such as art, music, and writing, can raise copyright and intellectual property concerns. Legal disputes may revolve around ownership and attribution of AI-generated works.

Data Privacy and Security.  AI relies heavily on vast amounts of data, raising concerns about data privacy and security breaches. Unauthorized access or misuse of personal data by AI systems can result in legal actions.

Autonomous Vehicles and Liability. The rise of autonomous vehicles, which use a combination of sensors, cameras, radar, and AI, introduces complex liability questions. Accidents involving self-driving cars may lead to disputes about responsibility, including whether fault is attributable to AI or human error. Manufacturers, software developers, and vehicle owners may become parties in litigation. 

Healthcare and Medical Malpractice. AI systems are increasingly involved in medical diagnosis and treatment decisions. Errors or misdiagnoses made by AI algorithms can result in medical malpractice claims. Determining the standard of care and responsibility in AI-assisted healthcare settings can result in legal disputes.

Law Enforcement. Law enforcement may use AI for surveillance and profiling, raising civil liberties concerns among citizens. Legal actions may focus on the legality and ethics of AI in relation to law enforcement practices.

Facial Recognition for Unlawful Surveillance. Unauthorized use of facial recognition technology for surveillance purposes without consent can violate privacy rights and civil liberties.

Malicious AI Applications. Criminals can use AI to develop malicious software, such as malware and ransomware, that can steal sensitive information, disrupt computer systems, or demand ransom payments.

Deepfakes. AI-powered deepfake technology can be used to create realistic-looking videos or audio recordings of individuals saying or doing things they never did. These can be used for defamation, misinformation, or other illicit purposes.

Phishing Attacks. AI can be used to create highly convincing phishing emails or messages that trick people into divulging personal information or login credentials.

Automated Fraud. AI can be employed to commit various types of fraud, such as credit card fraud, insurance fraud, and identity theft, by rapidly analyzing large datasets to identify vulnerabilities or impersonate individuals.

Algorithmic Trading Manipulation. In the financial industry, AI can be misused for manipulating stock, currency, and commodity prices and engaging in illegal trading activities.

Now that I’ve touched on some of the potential legal issues stemming from AI technology, let’s take a closer look at some of the challenges these issues pose for courts.

The AI Challenge for Modern Courts

Courts today face multifaceted challenges posed by AI, including issues of accountability and liability when algorithms make decisions, as well as the need to interpret complex technical concepts in legal proceedings. Striking a balance between harnessing AI's potential benefits and safeguarding legal principles is an emerging challenge for courts. Let’s explore how these issues could impact court caseloads as the use of AI tools permeates our everyday lives. 

Growing Caseloads.  Given the overwhelming number of potential uses for AI, courts may be concerned about how AI could impact the volume of cases it handles. From my experience visiting court jurisdictions across the nation, I’ve learned that many judges and courts are already overburdened. The reasons for this vary and include lack of funding for new judgeships, increased case complexity, and a slow return to fully normal court operations post-pandemic. Given these existing challenges, courts could be stretched to handle a new influx of cases involving AI.

Lack of Legal Precedent. A significant challenge that courts face, at least in the short term, is the lack of legal precedent. Given that AI technology is relatively new, there is a limited body of case law on which judges can rely. As judges chart this unfamiliar course, they must interpret existing laws to address AI-specific issues, which can be ambiguous and resource-intensive. Appellate courts will ultimately need to weigh in on key issues.

Caseload Complexity. One thing is clear - AI cases can be complex. AI systems are intricate and operate on algorithms that may be challenging for judges with limited technical expertise to fully understand. Judges may need to rely on expert witnesses to explain technical concepts and the AI's role in a case. In recognition of this challenge, organizations including scientific groups are receiving government funding to produce materials that assist judges in understanding and navigating complex legal issues involving AI. Some jurisdictions may eventually establish specialty courts, whose judges have specific training and expertise, to manage AI-related cases.

Determining Liability.  Assigning responsibility in AI-related disputes can be difficult due to multiple parties involved, including AI developers and operators and victims of AI use gone awry. Judges must carefully assess the responsibility of each party for any harm caused by AI systems.

Rapid Technological Advancements.  AI technology evolves rapidly, making it challenging for judges to stay up-to-date with the latest developments. Courts must adapt and interpret existing laws in light of ever-changing AI capabilities.

Courts and AI:  A Roadmap for the Future

I predict courts could struggle in the short term with the volume of AI cases and with acquiring the expertise necessary to apply existing laws to the sophisticated, high-tech field of Al. I believe courts will also be challenged over time to keep pace with AI as it further evolves and becomes more entrenched in our everyday lives.

But just as courts have historically adapted to surging caseload drivers, shifting law enforcement initiatives, changes in law, and advancements in technology, I expect courts to forge a path forward as they set the standard of conduct for AI in our society. So although AI on trial could pose a conundrum for courts, I don’t believe it’s one that can’t be overcome.

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Trish Lomonosov

Trish Lomonosov

Trish is a senior analyst/planning consultant for Fentress. She holds an M.S. in criminal justice and is certified by the American Institute of Certified Planners (AICP). She is also a certified Crime Prevention Through Environmental Design (CPTED) practitioner. Her personal interests include hiking, kayaking, and spending time with her two daughters.