Artificial intelligence and criminal liability in India: exploring legal implications and challenges

Abstract

Artificial Intelligence (AI) is revolutionizing various industries, including the legal landscape, in India. As AI technology becomes more prevalent, questions arise regarding its potential impact on criminal liability. This abstract delves into the legal implications and challenges associated with AI’s involvement in criminal activities in India. The intersection of AI and crime poses complex questions about the attribution of criminal liability. The ability of AI algorithms to operate autonomously blurs the lines of accountability, making it challenging to determine who should be held responsible for AI-driven criminal acts. The abstract explores the concept of legal personhood for AI systems and the need for legal frameworks that address the responsibilities of AI developers, operators, and users. Additionally, the abstract highlights the importance of data privacy and security in the context of AI-driven criminal activities. Criminals can exploit AI algorithms to harvest and misuse personal data, necessitating robust data protection laws to safeguard individuals’ privacy rights. Furthermore, AI-generated fake content, such as deepfakes, raises concerns about the integrity of evidence and the potential for manipulating legal proceedings. The abstract also addresses the ethical considerations surrounding AI’s involvement in criminal activities. It highlights the urgent need for the Indian legal system to address the complex implications of AI’s involvement in criminal activities. By developing comprehensive legal frameworks, emphasizing ethical AI development, and prioritizing data privacy, India can navigate the challenges posed by AI-driven crime and ensure that technology advances responsibly and securely within the bounds of criminal liability.

Keywords:

• Artificial intelligence
• machine learning
• legal implications
• challenges
• India

REVIEWING EDITOR:

• Heng Choon (Oliver) Chan, Department of Social Policy, Sociology, and Criminology, University of Birmingham, Edgbaston, UK

SUBJECTS:

• Algorithms & Complexity
• Artificial Intelligence
• Criminal Law & Practice

1. Introduction

Artificial Intelligence (AI) is revolutionizing various sectors, including healthcare, finance, transportation, and law enforcement. As AI systems become increasingly sophisticated and autonomous, questions arise regarding the accountability and criminal liability of these intelligent machines. In India, the concept of criminal liability for AI is a complex and evolving area of law. This comprehensive analysis aims to explore the legal aspects and challenges associated with attributing criminal liability to AI in the Indian context. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans (Sheikh et al., 2023). It involves the development of computer systems capable of performing tasks that would typically require human intelligence, such as visual perception, speech recognition, decision-making, problem-solving, and language translation.

AI can be categorized into two main types: narrow AI and general AI (Naudé & Dimitri, 2020). Narrow AI, also known as weak AI, is designed to perform specific tasks or solve specific problems. It is the most common form of AI that we encounter in our daily lives, such as voice assistants, recommendation systems, and image recognition software. On the other hand, general AI, also referred to as strong AI or artificial general intelligence (AGI), represents machines that possess the ability to understand, learn, and apply knowledge across various domains. General AI aims to mimic human intelligence in a broader sense and can potentially outperform humans in most intellectual tasks (Huawei Technologies Co., Ltd., 2023). AI technology relies on various techniques and approaches, including machine learning, deep learning, natural language processing, computer vision, and robotics (Kavanagh, 2019). Machine learning algorithms allow AI systems to learn from data and improve their performance over time without being explicitly programmed for every task.AI has found applications in numerous fields, including healthcare, finance, transportation, education, customer service, and entertainment. It has the potential to revolutionize industries, increase efficiency, and create new opportunities (Alhosani & Alhashmi, 2024). However, AI also raises ethical concerns and challenges, such as job displacement, data privacy, bias, and the impact on human decision-making (Stahl, 2021). As AI continues to advance, researchers and developers are working towards creating more sophisticated and ethical AI systems that can benefit society while minimizing potential risks. India is experiencing a growing interest and adoption of Artificial Intelligence (AI) across various sectors. With a large population, a flourishing technology industry, and a supportive government, India is poised to leverage AI to drive innovation, economic growth, and social development. AI has the potential to address key challenges faced by India, such as improving healthcare delivery, enhancing agriculture productivity, enabling smart transportation systems, and providing personalized education. The Indian government has recognized the significance of AI and has formulated policies and initiatives to accelerate its adoption.

India’s AI ecosystem comprises a mix of established technology companies, research institutions, startups, and academic institutions. Companies like Tata Consultancy Services (TCS), Infosys, and Wipro are actively investing in AI research and development (Venumuddala & Kamath, 2023). Additionally, leading educational institutions such as the Indian Institutes of Technology (IITs) and Indian Institutes of Information Technology (IIITs) are producing skilled AI professionals. Startups in India are driving innovation in AI across various domains, including healthcare, e-commerce, Fintech, and agriculture (Vempati, 2016). These startups are developing AI-powered solutions that cater to the specific needs of the Indian market. The Indian government has launched initiatives like the National AI Strategy, which aims to create a comprehensive framework for AI development and deployment. Additionally, the government is promoting collaborations between industry, academia, and research institutions to foster AI innovation. Despite the progress, challenges remain, including the need for skilled AI professionals, data privacy concerns, ethical considerations, and the potential impact on jobs. Addressing these challenges will be crucial for the successful and responsible implementation of AI in India. Overall, AI holds immense promise for India’s future, and with the right policies, investments, and collaborations, it can contribute significantly to the country’s growth and development across various sectors.

The swift progression of AI technology and its growing autonomy bring forth inquiries regarding the degree of human responsibility for actions driven by AI. If an AI algorithm engages in criminal activities, should the developer or operator bear exclusive responsibility, or should users who trained the AI with data resulting in criminal behavior also be considered jointly accountable? In such a scenario, multiple approaches can provide an answer. In this context, holding the user accountable is a viable option since they have direct control over the AI.

2. Methodology

This article uses a common method in legal research called the doctrinal methodology to investigate and support the questions mentioned earlier. This approach involves using secondary data sources to guide the research objectives and questions. Additionally, there is a strong emphasis on citing and giving credit to all referenced articles to maintain the scholarly integrity of the discussion.

Doctrinal legal research involves analyzing existing legal principles, statutes, and case law to understand the underlying doctrines that guide legal decision-making. It relies on studying legal texts, judicial opinions, and scholarly writings to develop a comprehensive understanding of the law in a specific area. Legal scholars and practitioners use this research to interpret and apply legal rules, identify trends, and assess the consistency of legal doctrines within a jurisdiction. It is a crucial tool for shaping legal arguments and informing legal practice and policymaking.

3. AI’s involvement in criminal activities

As AI technology advances at a rapid pace in India, its involvement in criminal activities has emerged as a pressing concern within the legal landscape. The intersection of AI and crime has given rise to a new breed of criminals who exploit AI algorithms to carry out sophisticated cybercrimes, hackings, and other illicit activities. One of the most significant challenges faced by the legal system is the detection and attribution of AI-driven crimes (Margetts, 2022). Criminals employ anonymizing technologies and AI-based evasion techniques, making it challenging for law enforcement agencies to trace the origins of the attacks or identify the responsible individuals. The legal ambiguity surrounding AI’s involvement in criminal activities further complicates matters, as the question of liability and accountability becomes increasingly complex when dealing with autonomous and seemingly self-directed AI algorithms.

AI is being used to aid medical professionals in diagnosing diseases more accurately and quickly. AI algorithms could analyze medical images like X-rays, CT scans, and MRIs to detect abnormalities and assist in early disease detection (Puttagunta & Ravi, 2021). AI is helping in the development of personalized treatment plans for patients by analyzing their genetic makeup and medical history. This could lead to more effective treatments with fewer side effects (King, 2023). The COVID-19 pandemic accelerated the adoption of telemedicine in India, and AI played a role in making remote consultations more effective. AI-driven diagnostic tools and remote monitoring systems were being used to provide care to patients from a distance (Bokolo, 2021). AI is aiding medical research by analyzing large datasets and identifying patterns and trends that could lead to breakthroughs in disease understanding and treatment (Dash et al., 2019). AI is playing a crucial role in drug discovery and development. It could analyze vast datasets to identify potential drug candidates and predict their effectiveness, potentially accelerating the drug development process (Gupta et al., 2021). In such cases, while doctors or creators may not necessarily intend to harm someone, if AI makes a wrong decision due to negligence, it could potentially result in an offense. This is because negligence is considered one of the components of mens rea (Baron, 2020).

The evolving use of AI in criminal activities has far-reaching implications for data privacy and security in India. Criminals are leveraging AI algorithms to harvest and misuse personal data, compromising the privacy and safety of individuals. With the ever-increasing reliance on AI in various sectors, the potential for data breaches and unauthorized access to sensitive information is a significant concern for the legal community. As AI-driven crimes continue to grow in complexity and scale, legal frameworks must adapt to safeguard citizens’ data and ensure that data privacy laws remain up-to-date and enforceable. Another critical aspect of AI’s involvement in criminal activities is its potential to exacerbate social inequalities and biases within the justice system. AI algorithms used in predictive policing and law enforcement may unintentionally perpetuate existing biases, leading to disproportionate targeting of certain communities or individuals. This can result in a violation of civil rights and human rights, necessitating careful examination and regulation of AI implementation in the legal domain. The Indian legal system must address these issues proactively to uphold principles of fairness and justice while incorporating AI technologies in its operations.

The use of AI-generated fake content, such as deepfakes, raises new challenges for India’s legal system. Deepfakes have the potential to manipulate evidence, tarnish reputations, and spread misinformation, significantly impacting the integrity of legal proceedings (Helmus, 2022). Ascertaining the authenticity of evidence and ensuring the accuracy of information become paramount concerns for courts and lawyers. Legal professionals need to be vigilant in recognizing and challenging the veracity of AI-generated content to protect the integrity of the legal process.The rise of automated financial crimes is yet another area where AI’s involvement poses significant legal challenges. Criminals can exploit AI algorithms to identify vulnerabilities and weaknesses in financial systems, facilitating money laundering, fraud, and other illicit financial activities (Seth, 2017). Detecting and prosecuting such crimes may require specialized legal expertise and an understanding of the intricate AI-driven techniques employed by criminals. Strengthening India’s financial regulations and collaborating with international counterparts to combat cross-border financial crimes are essential steps in mitigating this threat. The legal community must also consider the broader ethical implications of AI’s involvement in criminal activities. The responsible and ethical development of AI algorithms is critical to ensuring that these technologies are not used to perpetrate crimes or harm individuals and society at large. Developing and adhering to comprehensive ethical guidelines can help prevent the misuse of AI and hold developers and operators accountable for any intentional misuse of AI technology for criminal purposes.

As AI technology evolves, so does the concept of autonomous weapons (Leys, 2018). Although not yet prevalent in India, the potential misuse of AI in the development of autonomous weapons raises serious legal and ethical concerns. Such weapons could operate without human intervention, leading to unintended consequences and indiscriminate attacks (Gunawan et al., 2022). The legal community must remain vigilant in monitoring the international developments related to AI-driven weapons and advocate for robust regulations to prevent their misuse. Addressing AI’s involvement in criminal activities requires a collaborative effort from lawmakers, legal experts, AI developers, and civil society. India’s legal system must stay at the forefront of technological advancements and be agile in adapting to the evolving landscape of AI-driven crimes. Regular policy review and adaptation are necessary to keep pace with the rapidly changing technological landscape and to ensure that India’s legal framework remains effective in combating AI-related criminal activities.

To foster innovation and development while safeguarding against AI’s misuse, India needs to strike a delicate balance between fostering technological growth and maintaining stringent legal controls. This balance will help the legal system respond effectively to emerging AI-driven criminal threats without stifling technological advancement or infringing on individual rights (Martín et al., 2021). Further, fostering international collaboration and information sharing will be crucial to address the transnational nature of cybercrime and AI-related criminal activities (Horowitz et al., 2018). AI’s involvement in criminal activities in India presents a myriad of legal challenges that demand a proactive and comprehensive approach from the legal community. As AI technology continues to advance, it is imperative to continuously evaluate and adapt legal frameworks to combat the ever-evolving landscape of AI-driven crimes. Striking a balance between innovation and regulation is crucial to harnessing the benefits of AI while mitigating its misuse for criminal purposes. By addressing these challenges head-on and working collaboratively, India can establish a robust legal framework that safeguards against AI-related criminal activities while fostering technological progress for the greater good of society.

4. Criminal liability framework in India

The criminal liability framework in India forms the foundation of its legal system, defining the conditions under which individuals can be held accountable for their actions that violate the law. Criminal liability refers to the legal responsibility of a person for committing a crime, which can result in punishment, such as imprisonment, fines, or other penalties. In India, criminal liability is based on principles established in various statutes, case laws, and constitutional provisions (Eggett, 2019). One of the fundamental elements of criminal liability in India is the concept of mens rea, which refers to the mental state or intention of the accused at the time of committing the offense. This means that for someone to be held criminally liable, they must have acted with a guilty mind, having the intent to commit the crime or having knowledge of the wrongful nature of their actions. Mens rea is a crucial aspect as it distinguishes between intentional and unintentional acts, playing a vital role in determining the appropriate degree of punishment.

The Indian Penal Code (IPC), 1860, is the principal legislation governing criminal liability in India (Kethineni, 2020). The IPC classifies offenses into various categories based on the severity of the crime and prescribes corresponding punishments. It also outlines the circumstances under which certain acts are considered criminal, such as murder, theft, fraud, and assault, among others. The IPC also addresses the issue of defenses against criminal liability, such as self-defense, insanity, intoxication, and mistake of fact (Kilara, 2007). The criminal liability framework in India emphasizes the principle of presumption of innocence until proven guilty. This means that the burden of proof lies with the prosecution to establish the guilt of the accused beyond a reasonable doubt. To ensure a fair trial, the accused is provided with various legal rights, including the right to remain silent, the right to legal representation, and the right to a speedy and public trial. In India, criminal liability extends not only to individuals but also to certain entities, such as corporations. Corporate criminal liability is based on the concept of vicarious liability, where a company can be held accountable for the criminal acts committed by its employees if the offense is related to the course of the company’s business and with the intent of benefiting the organization. In recent years, the emergence of technology, including AI and other advanced technologies, has posed unique challenges to the criminal liability framework in India. As AI systems become more sophisticated and autonomous, questions arise about their accountability in case of involvement in criminal activities. India currently lacks dedicated legislation addressing Artificial Intelligence, but there are plans to substitute the Information Technology Act with the Digital India Act to encompass AI-related regulations (Chauriha, 2023). The issue of legal personhood for AI systems remains a subject of debate, as it influences the potential liability of AI developers, operators, and users. One of the fundamental elements of an offence involves doing an act, and in the context of Artificial Intelligence, the individual who manages or controls the AI will bear responsibility for any offense that the AI commits.

Furthermore, the proliferation of AI-generated fake content, such as deepfakes, has the potential to complicate criminal trials by manipulating evidence and raising doubts about the authenticity of information presented in court. The legal system faces the challenge of adopting appropriate measures to counter such manipulation and ensure the integrity of evidence in the digital age. The criminal liability framework in India also has to grapple with issues related to data privacy and security. With the increasing use of AI and data-driven technologies, the unauthorized access to and misuse of personal data has become a significant concern. The need for robust data protection laws and stringent measures to prevent data breaches is essential to safeguard individuals’ privacy rights and prevent criminal activities involving data manipulation and exploitation. Moreover, ethical considerations are paramount in the criminal liability framework, especially concerning AI’s involvement in criminal activities. Responsible AI development practices are critical to prevent the intentional misuse of AI technologies for criminal purposes. Ensuring fairness and justice within the justice system also requires addressing biases that AI algorithms may inadvertently perpetuate, particularly in predictive policing and law enforcement. The criminal liability framework in India is a crucial aspect of its legal system, determining the accountability and punishment for those who commit crimes. The framework is founded on the principles of men’s rea, presumption of innocence, and various constitutional rights for the accused. However, the emergence of AI and technology poses unique challenges, including questions about the liability of AI systems, the authenticity of AI-generated content, data privacy concerns, and ethical considerations. Addressing these challenges will require the Indian legal system to remain agile and responsive to technological advancements while ensuring that criminal liability principles uphold justice, fairness, and individual rights.

5. Challenges in attributing criminal liability to AI in India

Attributing criminal liability to AI in India presents a myriad of complex challenges that intersect at the crossroads of technological advancement and legal principles. As AI technology becomes more prevalent and sophisticated, the question of who should be held accountable for AI-driven criminal activities has become a pressing concern within the legal landscape. One of the primary challenges lies in the autonomy of AI algorithms, which can operate without direct human intervention, blurring the lines of traditional legal liability based on human intent. Unlike human actors, AI lacks a conscience and moral agency, making it difficult to ascribe the necessary men’s rea or guilty mind to hold it criminally liable (Gruodytė & Čerka, 2020). The absence of legal personhood for AI systems further complicates matters. In India, as in many other jurisdictions, legal personhood is conferred upon human beings and certain entities, like corporations, but not AI systems. Without legal personhood, AI cannot be treated as an independent legal entity with rights and obligations, including criminal liability (Chopra & White, 2011). Consequently, the question arises as to whom the responsibility should be attributed when AI is involved in criminal activities, whether it should fall on the AI developer, operator, user, or a combination of these parties.

The rapid advancement of AI technology and its increasing autonomy raise questions about the extent to which humans are responsible for AI-driven actions. If an AI algorithm commits a crime, should the developer or operator be solely held accountable, or should the users who trained the AI with data that led to the criminal behavior also share culpability? Delineating the precise extent of human involvement and responsibility in AI’s actions presents a significant challenge, particularly in cases where the AI system has learned from a diverse range of data sources, making it challenging to pinpoint the exact cause of the AI’s criminal conduct. Additionally, the ‘black box’ nature of certain AI algorithms complicates the ability to ascertain how an AI arrived at a specific decision or action. Some AI systems, especially those based on deep learning and neural networks can be highly opaque, making it challenging to understand the rationale behind their outputs (Richbourg, 2018). The lack of transparency hinders efforts to establish the cause and responsibility in AI-related criminal activities, further exacerbating the challenges in attributing criminal liability.

Moreover, the current legal framework in India may not adequately address the novel issues arising from AI-driven crimes. The Indian Penal Code (IPC), enacted in 1860, predated the emergence of AI technology and does not explicitly cover AI or technology-specific offenses. As a result, legal provisions and precedents may not directly apply to the complexities of AI-driven criminal activities. Adapting the legal framework to encompass AI-related offenses and ensuring that it keeps pace with rapid technological advancements is crucial to effectively attribute criminal liability to AI in India.

The question of criminal liability for AI becomes more pronounced in situations where AI is deployed in high-stakes domains like autonomous vehicles or medical diagnosis systems. If an AI-powered autonomous vehicle is involved in an accident resulting in loss of life, should the AI manufacturer or the owner of the vehicle be held criminally liable? Defining the boundaries of responsibility becomes crucial when dealing with AI systems that can have life-altering consequences (Mazzolin, 2020). Furthermore, the increasing use of AI-generated fake content, such as deepfakes, poses a new challenge for legal systems worldwide, including India. Deepfakes can manipulate audio and video recordings to create deceptive and misleading content, raising questions about the veracity of evidence in criminal trials. Ensuring the authenticity of evidence becomes paramount to maintaining the integrity of the legal process. However, verifying the authenticity of AI-generated content can be a complex and resource-intensive task.

Data privacy and security concerns also intersect with criminal liability when it comes to AI. Criminals can exploit AI algorithms to harvest and misuse personal data, leading to severe consequences for individuals and organizations. Strengthening data protection laws and ensuring robust cyber security measures are essential to safeguard individuals’ privacy rights and prevent AI’s involvement in criminal activities related to data manipulation and exploitation. Addressing the challenges of attributing criminal liability to AI in India requires a multi-faceted approach. It involves considering legal personhood for AI, updating the legal framework to accommodate AI-related offenses, enhancing transparency and explainability of AI algorithms, and promoting responsible AI development practices. The legal system must also engage in proactive measures to address potential AI-driven crimes in high-stakes domains and tackle the ethical and societal implications of autonomous AI decision-making. The challenges in attributing criminal liability to AI in India are complex and multifaceted. The autonomy of AI algorithms, the absence of legal personhood, the extent of human responsibility, the opacity of certain AI models, and the need to adapt the legal framework all pose significant hurdles. Overcoming these challenges necessitates a collaborative effort from policymakers, legal experts, AI developers, and civil society to strike a balance between technological advancements and legal accountability. Finding solutions to these challenges is essential to uphold the principles of justice, fairness, and accountability in an increasingly AI-driven world.

6. Ethics and fairness in AI criminal liability

Ethics and fairness are paramount considerations in the evolving landscape of AI criminal liability in India. As AI technology becomes more integrated into various aspects of society, including the legal system, ensuring that the attribution of criminal liability is conducted ethically and fairly becomes crucial. AI-driven criminal liability introduces unique challenges, such as the autonomy of AI algorithms and the absence of legal personhood for AI systems. These challenges demand careful examination to uphold principles of justice and fairness while holding responsible parties accountable for AI-driven criminal activities. Ethical considerations in AI criminal liability involve evaluating the intent and actions of the involved parties, including developers, operators, and users. Determining the intent behind AI-driven criminal acts can be complex, given the absence of human consciousness and moral agency in AI systems. Ethics demand a thorough examination of the role of humans in training and deploying AI algorithms (Kleinfeld, 2016). Developers and operators must be mindful of the potential consequences of AI’s actions and ensure that the algorithms are designed responsibly, adhering to ethical guidelines to prevent intentional misuse for criminal purposes. Moreover, users must also be aware of the implications of training AI with data that may lead to criminal conduct, emphasizing the importance of data ethics in AI development and deployment.

Fairness in AI criminal liability entails ensuring that AI-driven criminal acts are treated impartially and equitably within the legal system. The absence of legal personhood for AI systems raises questions about how responsibility should be allocated among the involved parties (Martín et al., 2021). Fairness demands that attributing criminal liability to AI does not result in unfair burden-shifting or scape-goating of developers, operators, or users. Striking a balance between holding individuals accountable for their actions while recognizing the role of AI in influencing those actions is crucial. The legal system must be vigilant in considering the societal implications of AI criminal liability and ensure that the principles of due process and presumption of innocence are upheld in AI-related criminal proceedings. Transparency and explainability are vital aspects of ensuring ethics and fairness in AI criminal liability. The opacity of certain AI algorithms can hinder the ability to understand how an AI arrived at a particular decision or action (Deeks, 2019). In cases where AI-driven evidence is presented in court, transparency is essential to allow judges, juries, and legal professionals to evaluate the authenticity and reliability of AI-generated content, such as deepfakes. Explainability also becomes essential in attributing criminal liability, as clear documentation and audit trails of AI algorithms can assist in understanding the decisions made by AI systems and help establish human involvement in their actions.

AI’s potential to perpetuate biases further underscores the need for ethics and fairness in AI criminal liability. AI algorithms can inadvertently inherit biases present in the training data, leading to discriminatory outcomes in predictive policing, law enforcement, and criminal sentencing (Peters, 2022). Law enforcement agencies can utilize AI for the prevention and investigation of crimes. An illustrative instance of this is the implementation of predictive policing in Germany (Gerstner, 2018). Another concept is Geospatial predictive policing which is founded on the idea that it’s feasible to forecast the occurrence and timing of future crimes through computer analysis of data related to past criminal incidents (Sommerer, 2017). Virtual reality (VR) has been applied in the study of numerous subjects pertinent to criminologists, including but not limited to stereotyping and racial bias, disorderly conduct, obedience and authoritarianism, aggression, moral judgment, delinquency, and criminal behavior (van Gelder, 2019). Hence, the utilization of VR can aid in comprehending the underlying causes for the commission of offences. Fairness demands that AI technologies be developed with a focus on mitigating bias and promoting equitable outcomes. Addressing biases within AI systems requires continuous monitoring, auditing, and iterative improvements to ensure that AI criminal liability does not disproportionately impact certain communities or individuals. Data privacy and security concerns are closely tied to ethics and fairness in AI criminal liability. Criminals may exploit AI algorithms to harvest and misuse personal data, compromising individuals’ privacy rights. Strengthening data protection laws and implementing robust cyber security measures are ethical imperatives to safeguard against AI-driven criminal activities related to data manipulation and exploitation. Though India have the Digital Personal Data Protection Act, 2023 which imposes a duty on Data fiduciaries to maintain the accuracy of data, keep data secure, and delete data once its purpose has been met The legal system must prioritize protecting individuals’ sensitive information while balancing the needs of effective AI applications within the criminal justice domain. When employing AI, it’s essential to consider fundamental ethical considerations, including but not limited to respecting human autonomy, preventing harm, ensuring fairness, and promoting transparency (Roksandić et al., 2022).

As AI technology continues to advance, India must keep abreast of ethical frameworks and best practices to guide the integration of AI within the legal system responsibly. Ethical considerations should be integrated into the development, deployment, and regulation of AI algorithms to prevent the intentional misuse of AI technology for criminal purposes. The legal system should establish clear guidelines and standards for developers, operators, and users of AI, promoting transparency, explainability, and accountability in AI criminal liability. Fairness in AI criminal liability necessitates an equitable approach to assigning responsibility, while avoiding undue burden-shifting or unfair allocation of blame. By prioritizing ethics and fairness in AI criminal liability, India can navigate the challenges of AI’s involvement in criminal activities while upholding principles of justice and societal welfare.

7. International approaches to AI criminal liability

International approaches to AI criminal liability vary significantly across different jurisdictions, reflecting the complex and evolving nature of the relationship between AI technology and legal systems. As AI continues to advance and become integrated into various aspects of society, including criminal activities, countries worldwide face challenges in determining how to attribute criminal responsibility for AI-driven actions (Vuletić & Petrašević, 2020). This paragraph explores key international approaches to AI criminal liability, examining the legal frameworks, ethical considerations, and emerging trends in different regions. One of the primary challenges in addressing AI criminal liability internationally lies in the autonomy of AI algorithms. Some jurisdictions, like the European Union, have established the principle of ‘strict liability’ for AI systems, meaning that the developer or operator can be held liable for AI-driven actions, regardless of whether there was any intent or knowledge of the offense. This approach prioritizes the accountability of human actors involved in deploying AI, emphasizing the need for responsible AI development and deployment practices to prevent AI-driven criminal activities.

Conversely, other jurisdictions, including the United States, follow a ‘causation-based’ approach, where criminal liability is attributed to human actors who directly caused the AI to commit the criminal act (Crawford & Schultz, 2019). In such cases, the burden is on the prosecution to establish a causal link between the human’s actions and the AI’s criminal behavior. This approach requires a careful examination of the level of human control over the AI system and the extent to which the AI operated autonomously. Another aspect of international approaches to AI criminal liability involves the legal personhood of AI systems. While some countries, like Japan and Saudi Arabia, have considered granting legal personhood to AI systems, most jurisdictions do not confer legal personhood on AI. Instead, legal responsibility is typically attributed to human actors involved in the development, deployment, or use of AI technology. This approach reflects the view that AI is a tool or technology created and utilized by humans and, therefore, humans should be held accountable for its actions.

Ethical considerations play a significant role in international approaches to AI criminal liability. Countries like Germany and the European Union have proposed ethical guidelines for AI development that emphasize transparency, fairness, and accountability (Franke & Sartori, 2019). These guidelines aim to ensure that AI systems are developed and deployed responsibly, reducing the risk of AI being used for criminal purposes. Ethical frameworks also focus on addressing biases in AI algorithms, particularly in criminal justice applications, to prevent discriminatory outcomes. In addition to ethical considerations, international efforts to address AI criminal liability involve the promotion of transparency and explainability in AI systems. Several countries have proposed regulations that require developers and operators to provide clear documentation and audit trails of AI algorithms, especially in high-stakes applications like autonomous vehicles and medical diagnosis systems. This emphasis on transparency aims to enhance public trust in AI systems and enables better assessment of the decision-making processes of AI in cases involving criminal activities. Data privacy and security are other critical aspects of international approaches to AI criminal liability. Many countries have enacted data protection laws to safeguard individuals’ personal information from misuse or unauthorized access by AI systems (Hornuf et al., 2023). These laws aim to mitigate the risk of AI being exploited by criminals to harvest and misuse sensitive data for criminal purposes. Ensuring robust cyber security measures is also vital to prevent data breaches that could compromise the privacy and security of individuals and organizations.

Emerging trends in international approaches to AI criminal liability involve cross-border cooperation and information sharing. Given the transnational nature of cybercrimes and AI-related offenses, collaboration between countries is essential to effectively combat AI-driven criminal activities that transcend national boundaries. Inter-governmental partnerships, such as mutual legal assistance treaties, play a critical role in exchanging information, evidence, and intelligence related to AI crimes, enabling a more comprehensive and coordinated response to transnational AI-driven offenses. Moreover, international organizations and alliances, such as the United Nations and the G7, have also taken an interest in AI governance and criminal liability. These forums serve as platforms for discussing global AI-related challenges, sharing best practices, and formulating international norms and standards concerning AI ethics, fairness, and accountability. International approaches to AI criminal liability vary considerably, reflecting the diverse legal frameworks, ethical considerations, and emerging trends in different jurisdictions. While some countries adopt a strict liability approach, holding developers or operators responsible for AI-driven actions, others focus on causation-based liability, attributing criminal responsibility to human actors who directly caused the AI’s behavior. Ethical considerations, transparency, data privacy, and cyber security play significant roles in shaping international approaches to AI criminal liability, as countries strive to balance technological advancements with ethical principles and public welfare. Cross-border cooperation and information sharing are also becoming increasingly vital as AI-driven criminal activities transcend national boundaries, requiring collaborative efforts to address the challenges posed by AI’s involvement in criminal acts (King et al., 2020). As the field of AI continues to evolve, international cooperation and coordination will be essential in formulating comprehensive and equitable responses to AI criminal liability.

8. Proposed regulatory measures for imposing criminal liability on AI in India

Proposed regulatory measures for imposing criminal liability on AI in India seek to address the unique challenges posed by the integration of AI technology into various sectors, including criminal activities. As AI continues to advance and become more autonomous, it becomes imperative to establish a clear legal framework that holds accountable the relevant human actors involved in the development, deployment, and use of AI systems. One proposed measure is to emphasize the principle of strict liability, wherein AI developers and operators can be held criminally liable for AI-driven actions, irrespective of intent or knowledge of the criminal conduct. This approach prioritizes the responsibility of humans in ensuring that AI algorithms are designed and deployed responsibly to prevent any intentional misuse for criminal purposes. By imposing strict liability on developers and operators, this measure aims to promote responsible AI development practices, fostering transparency and accountability in the AI industry in India. Additionally, proposed regulatory measures for AI criminal liability in India may focus on establishing clear guidelines for explainability and transparency in AI systems. By requiring developers and operators to provide detailed documentation and audit trails of AI algorithms, the legal system can better understand the decision-making processes of AI, especially in cases involving criminal activities. This measure ensures that the mechanisms and rationale behind AI-driven actions are transparent, enabling legal professionals to assess the extent of human involvement and responsibility in AI-driven offenses. Transparency measures contribute to building public trust in AI technologies while ensuring fairness and accountability in attributing criminal liability.

Furthermore, the implementation of comprehensive data protection laws is crucial in proposed regulatory measures for AI criminal liability in India. These laws aim to safeguard individuals’ personal information from misuse or unauthorized access by AI systems. By prioritizing data privacy and security, India can mitigate the risk of AI being exploited by criminals to harvest and misuse sensitive data for criminal purposes. Strengthening cyber security measures also plays a vital role in preventing data breaches that could compromise the privacy and security of individuals and organizations, thereby reducing the potential for AI involvement in criminal activities related to data manipulation and exploitation. To address ethical considerations in AI criminal liability, proposed regulatory measures may include guidelines for responsible AI development practices. This measure emphasizes that AI technologies should be developed and deployed in a manner that upholds ethical principles and societal values, reducing the likelihood of AI-driven criminal acts. By encouraging ethical frameworks for AI, the legal system can ensure that AI technologies are designed to minimize biases and promote fair and equitable outcomes, particularly in criminal justice applications.

Proposed regulatory measures may also involve creating specialized AI-related offenses and updating existing laws to encompass AI-driven crimes. Given the rapid advancement of AI technology and its potential to introduce novel criminal activities, adapting the legal framework is crucial to effectively address emerging AI-related offenses. This measure enables the legal system to keep pace with technological advancements and ensure that AI-driven crimes are adequately addressed and punished within the Indian legal system. Proposed regulatory measures for imposing criminal liability on AI in India seek to address the complexities of attributing responsibility in the context of AI-driven criminal activities. By emphasizing strict liability for developers and operators, promoting transparency and explainability in AI systems, implementing comprehensive data protection laws, and encouraging ethical AI development practices, India can create a robust legal framework to hold accountable the relevant human actors involved in AI technology. These measures will not only foster responsible AI development and deployment but also ensure fairness, accountability, and trust in the use of AI within the criminal justice domain. As AI technology continues to evolve, the implementation of effective regulatory measures will be crucial in upholding principles of justice and protecting society from potential risks posed by AI-driven criminal activities.

9. Conclusion

The intersection of artificial intelligence (AI) and criminal liability in India presents a complex and evolving landscape that demands careful consideration from legal experts, policymakers, and technologists. As AI technology continues to advance, its involvement in criminal activities poses significant legal implications and challenges that require proactive and adaptive responses. The attribution of criminal liability to AI systems raises fundamental questions about intent, accountability, and the ethical responsibility of human actors. The absence of legal personhood for AI further complicates matters, necessitating a careful examination of the roles and responsibilities of AI developers, operators, and users in AI-driven criminal acts. The challenges in attributing criminal liability to AI in India demand a multi-faceted approach that encompasses legal, ethical, and technological considerations. The legal system must grapple with the autonomy of AI algorithms and find innovative ways to establish intent and culpability in AI-driven crimes. Ethical frameworks that prioritize transparency, fairness, and responsibility in AI development and deployment are essential in preventing the intentional misuse of AI technology for criminal purposes. Additionally, data privacy and security concerns underscore the need for robust data protection laws and cyber security measures to safeguard against AI-driven criminal activities related to data manipulation and exploitation.

Adapting the legal framework to accommodate AI-related offenses is crucial to ensure that existing laws remain relevant and effective in addressing the complexities of AI-driven crimes. Moreover, the legal system must remain agile and responsive to rapid technological advancements, as AI’s potential involvement in criminal activities continues to evolve. While addressing AI’s involvement in criminal liability, India must strike a delicate balance between fostering innovation and maintaining stringent controls. Encouraging responsible AI development practices while upholding ethical guidelines will be pivotal in harnessing the benefits of AI technology while mitigating its misuse for criminal purposes. The cooperation and collaboration of stakeholders, including legal experts, AI developers, policymakers, and civil society, are essential to navigate the challenges presented by AI’s involvement in criminal activities effectively. International partnerships and information sharing will play a crucial role in addressing the transnational nature of AI-driven crimes, fostering a global response to this emerging issue.

To ensure the fairness and integrity of the criminal justice system, efforts should be directed at reducing biases in AI algorithms used in predictive policing, law enforcement, and sentencing. Transparency and explainability in AI systems are critical in ensuring that AI-driven evidence presented in court is authentic and reliable, maintaining the credibility of the legal process.

The evolution of AI and its increasing autonomy necessitate a proactive approach in updating and revising legal frameworks to stay ahead of emerging AI-driven offenses. Policymakers should continuously engage with AI developers and researchers to understand technological advancements and anticipate potential challenges, paving the way for a more informed and adaptable legal response. In India, laws regarding AI should include the concept of strict liability (Rylands vs. Fletcher, 1868). This means that developers and operators would be held accountable for the actions of AI, regardless of their intentions or knowledge. This emphasizes the responsibility of humans in using AI, highlighting the need for responsible development and deployment to prevent AI-related crimes. The principle of strict liability is in line with the changing world of technology, highlighting the importance of putting human responsibility first when it comes to using AI. By following strict liability guidelines, the legal system can promote responsible development methods, reducing the potential dangers that can come from AI-related actions. This method not only guarantees fairness in situations where AI goes wrong, but also pushes for the adoption of ethical practices in the design and use of AI. As India’s technology industry grows and more AI technologies are used, including strict liability in AI laws is crucial for protecting the public and encouraging long-lasting technological progress.

The exploration of AI’s involvement in criminal liability in India is a complex and dynamic endeavor. By recognizing the legal implications and challenges posed by AI technology, India can foster a comprehensive approach that emphasizes ethics, fairness, and accountability. The responsible and ethical integration of AI within the criminal justice system can help safeguard against potential risks while leveraging the transformative potential of AI for the greater good of society. With a forward-looking approach, India can navigate this evolving landscape and create a robust legal framework that ensures the responsible use of AI technology while upholding principles of justice, fairness, and societal welfare.

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No potential conflict of interest was reported by the author(s).

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Hifajatali Sayyed

Mr. Hifajatali Sayyed is currently working as an Assistant Professor at Symbiosis Law School Hyderabad, A Constituent of Symbiosis International Deemed University Pune. He is the In-charge of Centre for Criminology and Criminal Justice (CCCJ) of SLSH. He is also the Co-Head (Student Research) of the Research and Publication Cell of SLSH. He is the Examination In-charge and also the In-charge of Admission Committee.