Introduction
Artificial intelligence (AI) is rapidly transforming the legal landscape. Gone are the days of sifting through mountains of paperwork. This technological wave can make legal services faster, more affordable, and more widely available. Traditionally time-consuming tasks such as legal research, case law analysis, contract drafting, contract reviews, and due diligence are significantly accelerated by AI-powered tools. Utilizing these tools, vast amounts of legal data can be processed in mere seconds, pinpointing relevant cases and clauses with unmatched speed and accuracy. However, alongside these exciting possibilities lies a multitude of ethical concerns. This article delves into the complex relationship between AI and the law, exploring the potential pitfalls alongside its benefits and addressing some of the ethical implications that arise with the development and deployment of AI.
Defining Ethics
Ethics are the set of moral principles that govern what is good or bad generally. Legal ethics refers to the unique responsibilities of lawyers and the legal system, given the important role and influence they have in society. Because of the nature of their work and their close involvement in the administration of law, lawyers are subject to special standards, regulations, and liability.[1] AI Ethics are principles and guidelines that guide the responsible use of AI tools. These can also be defined as the sets of guidelines, considerations, and principles that have been created to responsibly inform the research, development, and usage of artificial intelligence systems.[2] Legal professionals including lawyers, law students, and paralegals need to ensure that professional codes are observed when incorporating AI into research and decision-making. This means actively checking AI outputs for bias and making sure the information received is fair and unbiased.
Training AI
Training artificial intelligence (AI) involves using complex datasets to build models that can reach conclusions without human intervention. AI models apply various algorithms to relevant data inputs to accomplish their programmed tasks. The output generated by AI is based on the data they have been trained with, but there is a possibility that this output may be biased or inaccurate due to already existing biases in the training data. In the legal field, it is crucial for lawyers, paralegals, and law students to critically review AI-generated outputs and make informed decisions based on the information provided. While it can be tempting to trust these algorithms, legal professionals should always apply their reason and judgment to AI-generated information. By carefully analysing these ethical considerations, we can ensure that AI is used for good while upholding the core principles of fairness and justice.
Ethical Considerations
It’s crucial to understand that AI in the legal field is meant to complement human expertise rather than replace decision-making. When integrating AI into their practice, legal professionals must consider ethical concerns to uphold justice, fairness, and ethical standards. This ensures that AI enhances the legal process while maintaining important human values. It’s essential to balance the benefits of AI with the need for accountability and transparency. By carefully addressing these ethical considerations, legal professionals can leverage AI to improve their practice without compromising the integrity and fairness of the legal system. Let’s now explore these critical issues in more details:
1. Bias and Fairness
An AI model’s output is based on the data which was used during the training process. Where the AI system is trained with biased data, one should expect the output to reflect the bias. One well-known example is the COMPAS system used in the United States criminal justice system, which predicts the likelihood of a defendant reoffending. A study by ProPublica found that the system was biased against African-American defendants, as they were more likely to be labelled as high-risk even if they had no prior convictions. Another study found similar biases in a similar system used in the state of Wisconsin.[3] Most times, the algorithms might inherently favour certain outcomes over others, leading to biased results. Moreover, it is a requirement that the legal professionals ought to do an oversight on the generated outcome. This is because the work product and conclusions reached by AI cannot replace human judgment and must be reviewed by lawyers for completeness and accuracy.[4]
2. Accuracy
Regardless of the size and complexity of the dataset used to train an AI system, no AI is perfect. AI models tend to hallucinate, an AI hallucination occurs when a model perceives patterns or objects that do not exist, resulting in nonsensical or inaccurate outputs. “These models generate text that looks very human-like, looks very factually correct, competent, coherent, but it might contain errors because these models were not trained on any notion of the truth, they were just trained to generate text that looks human-like, looks like the text they read.”[5] To account for accuracy, one has to cross-check and verify if the cases, research work, or any output generated or produced by an AI Model are authentic and sound.
3. Data Privacy
Data privacy is an important ethical consideration. Legal professionals are committed to protecting the personal data of clients, therefore ensuring that the information shared by their clients is kept confidential. Using an AI model for document summarization, legal research, clause analysis, risk assessment, review checklist, and contract comparison may contain highly sensitive information. A data breach in an AI system could have its disadvantages for clients, exposing their financial records, personal details, or legal strategies. Ensuring that the AI system adheres to strict data privacy and confidentiality standards to protect information is of utmost importance.
4. Responsibility and Accountability
Responsibility involves the ethical duty to act with care and consideration in the development, deployment, and use of AI models. Accountability also refers to duty to be answerable for the actions of the AI. Legal professionals and organizations must be prepared to take responsibility for the results generated by the AI system, including any errors, biases, or adverse effects. The final responsibility for legal decisions should rest with judges and legal professionals, who must exercise their professional judgment and consider the broader legal and ethical implications. [6]
5. Transparency
Transparency in AI is crucial in the legal field because it allows stakeholders to understand how AI systems reach their conclusions, fostering trust and accountability. This visibility helps ensure that AI-driven decisions are fair, accurate, and free from biases, aligning with ethical standards. By informing clients when AI contributes to their cases, legal professionals promote informed consent, enabling clients to engage more meaningfully with their legal representation. Transparent AI systems also facilitate compliance with regulatory requirements by providing clear audit trails, essential for defending AI-assisted decisions. Additionally, transparency supports the continuous improvement of AI technologies by highlighting areas for refinement, ultimately enhancing their reliability and performance. Overall, transparency not only builds trust and encourages the responsible use of AI in legal practice but also promotes the widespread adoption of these innovative tools by demonstrating their fairness and effectiveness.
Conclusion
The importance and benefits of AI in the legal field are undeniable. It is equally important to note that responsible use of AI in law involves addressing accountability, bias, data privacy, and transparency. By integrating ethical practices and refining our approaches, we can confidently use AI’s power to help legal professionals focus on client-centered tasks. This ensures that advancements in artificial intelligence serve the legal profession efficiently and ethically, upholding fairness and individual rights. Legal institutions, policymakers, and AI developers need to collaborate in establishing guidelines for the responsible and transparent use of AI in the legal field. This collaboration can help in developing frameworks that mitigate bias, protect sensitive data, and provide mechanisms for accountability in AI-powered legal applications. Ongoing training and education programs can further assist legal professionals in understanding, using, and monitoring AI tools effectively while maintaining ethical and legal standards, and enhancing public trust in AI-enabled legal systems.
[3] Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias risk assessments in criminal sentencing. ProPublica, May, 23.
[4] AI and Ethical Concerns for Legal Practitioners, https://www.lexisnexis.com/community/insights/legal/b/thought-leadership/posts/ai-and-ethical-cconcerns-for-legal-practitioners#:~:text=Proper%20 oversight%20 is%20 essential%20to,any%20work%20 product%20it%20 generates.
[5] Simon Little(February 5, 2024)B.C. ruling on AI ‘hallucinated’ fake legal cases could set precedent, experts say https://globalnews.ca/news/10273910/chatgpt-bc-legal-precendent/
[6] Exploring The Use of AI In Legal Decision-Making: Benefits and Ethical Implications https://woxsen.edu.in/research/white-papers/exploring-the-use-of-ai-in-legal-decision-making-benefits-and-ethical-implications/
BY; NICOLINN NANA ADJOWA KWAW
Nartey Law Firm is a leading corporate and commercial law firm in Ghana providing legal services to individuals, domestic and international businesses. Ensuring the success of our clients’ objectives is at the core of what we do. Comprised of a dedicated team of lawyers with extensive experience in corporate, commercial and international law and litigation, we pride ourselves with the diligent execution of all client matters, whilst guaranteeing an uncompromising standard with respect to excellence in service delivery. Some of our focus areas are Real Estate, Intellectual Property, Energy, Trade and Commerce, Banking and Finance, Regulatory Advisory, Capital Markets and Mergers and Acquisitions.
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