Artificial Intelligence And The Law: Navigating The Legal Landscape In The Age Of Artificial Intelligence
Artificial Intelligence, commonly referred to as AI, refers to a technology engineered to carry out tasks that usually require human intelligence. It revolves around creating intelligent applications capable of simulating human-like cognitive functions, including problem-solving, reasoning, learning, and perception. AI systems make use of algorithms and data to process information and make informed decisions.
AI can be broadly categorized into two main types:
1. Narrow or Weak AI - These AI systems are tailored for specific tasks and perform in their designated domains but do not perform tasks beyond their specialized roles. For example, voice assistants like Siri and Alexa.
2. General or Strong AI - This represents a more advanced form of AI, theoretically endowed with the capacity to undertake any intellectual task that humans can. Strong AI remains a topic of ongoing research and debate.
AI in the Legal Industry
AI is continuously used across various sectors, including Healthcare, Finance, Retail, Manufacturing, Transportation, Entertainment, and Education. AI has steadily entered the legal industry, enhancing the capabilities of legal professionals. Various AI tools, applications, and software enhance efficiency and accuracy across different legal functions, ranging from document review to due diligence, contract management, and predictive analysis. Legal professionals often deal with large volumes of documents during litigation, due diligence, and contract analysis. AI tools are adept in efficiently processing vast amounts of data, segregating relevant information from irrelevant information, thereby significantly reducing time and costs. AI can also analyse legal precedents and case laws, offering historical data that aids legal professionals in informed decision-making and litigation strategy development. Additionally, AI assists in contract management by automatically extracting key terms, clauses, and provisions from contracts, identifying potential risks, ensuring compliance, and generating personalized contracts according to predefined inputs. Through automating repetitive and time-consuming tasks, AI increases the efficiency of the procedure / process, which sometimes can be very long and drawn out.
Challenges
While AI offers numerous advantages, it also poses new and unique challenges in the legal sector:
A. Privacy and Data Protection
AI systems in the legal domain often require access to extensive volumes of sensitive data, raising significant privacy concerns. Legal professionals bear the responsibility of safeguarding client information and maintaining the confidentiality of case-related data when utilizing AI, necessitating stringent data security and privacy measures. Data protection regulations, such as the European Union's General Data Protection Regulation (GDPR), impose strict requirements for data handling, including Data Protection Impact Assessments (DPIAs) for AI applications processing personal data[1]. Italy's data regulator in March 2021 issued a temporary emergency decision ordering OpenAI to stop using personal information whilst observing that OpenAI does not have legal rights to use a person's personal information in Chat GPT[2]. Additionally, the 'Joint Opinion on proposal for a Regulation of European Parliament and of Council laying down harmonised rules on AI' by EDPB-EDPS observed that private companies, such as social media and cloud service providers, also can process vast amounts of personal data and conduct social scoring and hence, future AI Regulation should prohibit any type of social scoring[3]. GDPR mandates explicit informed consent from data subjects for data processing activities. India also intends to regulate AI[4] and the newly introduced Digital Personal Data Protection Act, 2023 (DPDPA) recognises the rights of individuals to protect personal data and presents compliance challenges for domestic and international AI applications[5]. US President Joe Biden also signed an Executive Order on safe, secure and trustworthy AI.[6]
AI systems also remain vulnerable to data breaches, which can compromise sensitive personal information. Legal scrutiny is required for AI algorithms that engage in monitoring and data collection. These systems must also consider national security concerns and potential biases in their decision-making processes. Legal professionals must address issues related to data ownership and consent, ensuring that individuals retain control over their data and provide informed consent for its utilization. Transparency in data processing is mandatory as per the DPDPA, and data protection regulations may require organizations to facilitate data portability in AI applications. Legal professionals play a crucial role in advising AI developers to align their applications with existing laws.
B. Ethical Challenges
The integration of AI into the legal field raises a multitude of ethical considerations, with bias in AI algorithms emerging as a significant concern. Bias can result from various sources, including biased training data, unreliable databases, flawed algorithms, or unintended human biases encoded in the code. This bias can lead to unfair legal outcomes and incorrect decisions, where AI algorithms trained on biased historical data may incorporate these biases. In 2015, Google Photos tagged two African-American people as Gorillas through their facial recognition[7]. In 2018, Amazon scrapped the AI-based tool that it used for the hiring process as it favoured male candidates by disregarding resumes that had words like “women's”. Recently, deepfakes have emerged on the internet imitating Bollywood actresses and the Hon'ble Delhi High Court has sought a response from the Central Government on its stance on the issue in a PIL[8]. Ensuring fairness in AI-driven legal processes is not only about addressing bias but also holding AI systems accountable for their actions.
C. Liability
Determining liability in cases where AI systems make erroneous legal decisions remains a pertinent issue. Questions surrounding whether liability falls on the AI developer, the user, or both require further clarification from law-making bodies as well as the judicial system. For example, in “Jones v. W + M Automation, Inc.”, New York's Appellate Division dismissed the plaintiff's complaint about a product defect against a manufacturer and programmer of a robotic loading system. In the court's view, the defendants were not liable for the plaintiff's injuries at the GM plant where he worked because these defendants showed they “manufactured only non-defective component parts.” As long as the robot – and associated software – was “reasonably safe when designed and installed,” the defendants were not liable for plaintiff's damages. GM, the end user, however, could still be liable for improperly modifying the hardware or software. The implication is that creators of AI software or hardware aren't liable for any injuries as long as these products were non-defective when made. That being said, defectively made AI, or AI that is modified by a licensee and causes damages as a result, can create liability for both the licensor and/or licensee. Whether AI is defectively made will depend, like in other product liability cases, on prevailing industry standards[9].
D. Intellectual Property Rights
Issues revolving around Intellectual Property Rights(IPR) are also relevant when AI generates content, inventions, or works. One of the most prominent issues in AI and IPR is ownership of AI-generated content.
Trademark: The Rome Court of First Instance in the matter of “Juventus FC v. Blockeras” granted an injunction in favour of Juventus FC restraining Non-Fungible Tokens (NFTs) creator Blockeras from selling NFTs, Action Cards etc. containing images of Christian Vieri wearing a Juventus shirt featuring Club's trademark. Even though the footballer had authorised the use of his image to Blockeras for NFT, Juventus FC did not permit to use of its trade mark[10].
Copyright: The question of who owns the copyright to content generated by AI is a critical issue. Traditionally, the creator of a work holds the copyright. In the case of AI-generated content, it's often the person or organization that operates the AI system. However, there is no clear legal framework on this issue. Another issue is the originality of the AI-generated content. Copyright law often requires works to be original and the result of human creativity. What constitutes originality in the context of AI is still a subject of debate. It would be interesting to see the judicial pronouncements on this aspect across various jurisdictions.
Patents: AI-generated inventions must meet the criteria of novelty, non-obviousness, and utility to be patentable. The issue of ownership also arises in patent law, similar to copyright. Determining who owns the rights to an AI-generated invention can be complex, especially when the AI system is operated by an organization.
AI in the Indian Legal Landscape
Indian law firms and legal practitioners have recognized the advantages of integrating AI into their daily operations. AI-driven tools are being used for tasks such as document review, contract analysis, legal research, and legal prediction. These technologies streamline routine tasks, reduce errors, and enhance productivity. AI's ability to rapidly review extensive volumes of documents has expedited due diligence procedures. Contract analysis and management have also benefited, saving time and reducing the risk of errors, particularly in India's diverse business landscape with an increasing number of legal transactions.
The Indian Judicial System has also adopted AI to improve its functioning. The National Judicial Data Grid (NJDG) is a prime example of technology, including AI, being used to enhance the legal system's operation in India. AI's potential in legal prediction, analysing past cases, and automating processes like e-notices and e-summons can alleviate the burden on the judicial system. AI has also been integral in holding virtual courts through e-courts and video-conferencing tools, as exemplified by the Live Transcription Project initiated by the Supreme Court of India.
The Indian government has shown interest in promoting AI technology and its ethical use, releasing the National Artificial Intelligence Strategy in 2018. Legal tech start-ups in India are thriving and actively developing AI solutions for the legal sector. These start-ups create platforms that employ machine learning and natural language processing to retrieve and summarize relevant legal documents, improving the accuracy and efficiency of legal research.
Way Forward
The integration of AI into the Indian legal landscape is gaining momentum, poised to reshape how legal professionals work. Collaboration between legal professionals and AI systems is key to utilizing AI effectively in the legal field, with AI designed to complement, not replace, lawyers. AI presents novel challenges to intellectual property laws, necessitating the evolution of existing legal frameworks to address issues like AI-generated content ownership.
Legal ethics in the context of AI are crucial, demanding that law schools offer practical training on using AI tools for legal research, contract analysis, document review, due diligence, and more. AI holds the promise of enhancing the efficiency and accessibility of legal services, furthering the interests of justice.
As the legal landscape evolves in the age of AI, the legal community bears the responsibility of guiding this transformation while upholding the principles of fairness, transparency, and accountability that underpin the legal profession.
Authors: Yeshi Rinchhen (Partner, Litigation) and Akash Yadav (Senior Associate, Litigation) at Zeus Law. Views are personal.
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