Transforming Legal Aid in India: Can AI Bridge the Justice Divide?

 

Rochak Bansal ¹ , Dr. Monica Chawla

 

¹ Research Scholar, Department of Law, Punjabi University Patiala, Punjab, India

² Department of Law, Punjabi University Patiala, Punjab, India

 

1. INTRODUCTION

Legal aid is a bedrock of democracy by ensuring justice for all notwithstanding their economic status Chalid & Rizqita (2018). Legal aid conveys the right that legal representation should not become a privilege of the rich but a fundamental right in its own regard, thereby fostering the rule of law and engendering public faith in the justice system. The United Nations reiterates that legal aid is necessary to enable individuals to navigate the justice system, make informed decisions, and obtain remedies, thus linking populations with their justice systems and guiding them through complicated legal proceedings Rhode (2004).

In India, this commitment to equitable justice is steeped in Article 39A of the Constitution, which requires the state to provide free legal aid to ensure that opportunities for securing justice are not denied to any citizen by reason of economic or other disabilities A Brief History of Legal Aid. (2023).Thus the constitutional provision gave rise to the enactment of the Legal Services Authorities Act in 1987 constituting a uniform nationwide mechanism to provide free and competent legal services to the weaker sections of the society White Black Legal. (2012).The operation of this act was commenced on the 9th day of November 1995, which was a giant step in the institutionalization of legal aid in the country (2023).

Yet, due to the existence of some restrictive laws, there is a huge justice gap in India. Barriers like unawareness of legal rights, financial conditions, and a lack of legal aid lawyers challenge access to justice for the underprivileged. Also, the overloaded judiciary status with numerous court case proceedings piles the delay further prompting individuals to shy away from seeking legal remedies P. S. C. (2024).

In this light, the use of Artificial Intelligence (AI) in legal aid services appears to be an encouraging avenue to knitting the justice hemisphere. AI technologies such as legal chatbots, predictive analytics, and automated document drafting tools are capable of extracting legal work processes, minimizing expenses, and boosting civilian access to justice and efficiency of legal processes Dhani et al. (2021). Therefore, AI can automate administrative work and provide immediate legal information to help people understand their rights and assert them, thereby democratizing the access to justice Abiodun & Lekan (2020).

That said, the introduction of AI in legal aid raises practical and ethical questions. A consideration of these issues, specifically data privacy, algorithmic biases, and the digital divide, is required to ensure that AI-based legal services avoid unintentional perpetuation of disparities. Therefore, a careful exploration of the application of AI for advancing legal aid in India is needed, ensuring technological advances are counterbalanced by ethical barricades Balan (2024). By evaluating the intersection of legal aid and AI, this paper hopes to determine whether the avenue can enable technological advancements to fill the justice divide in India wherein the promise of equal access to justice is shared among all citizens.

 

2. The Current State of Legal Aid in India

The efficiency of legal aid in India depends on the functioning of both the National Legal Services Authority and the State Legal Services Authorities. NALSA is meant to be the apex body established under the Legal Services Authorities Act of 1987 for the formulation of policies and guidelines for the provision of free legal services to the underprivileged section of the populace Nigam (2008). It also organizes the Lok Adalats that act as an engine to fuel the efficient settlement of disputes. SLSAs thus come under the umbrella of national policy advocacy by NALSA and operationalize these policies at the state level, reaching to all jurisdictions about legal aid necessary for a specific section of people Pandey (2020). Such a structured framework does not mean that legal aid is easily available in India. There are a myriad of barriers causing hindrance to the effective delivery of legal aid in India Jüriloo (2015). A major problem that gives rise is lack of awareness among the masses about some fundamental legal rights and free legal services available. The layman's ignorance entails partaking of less knowledge pertaining to legal aid relevance and needy people find it very difficult to be supported during legal complications Jüriloo (2015). Moreover, financial stringencies further compound the problem; economically poor persons could not pay collateral costs for conducting legal proceedings, even if legal representation is free for them. There is also a relatively lower number of lawyers who are willing to do pro bono service, thereby adding pressure to the already crammed legal aid system and reducing the effectiveness of these services Plata (1997). Another compounding challenge is the agonizing backlog of cases in courts across the nation. The heavy burden on the judiciary due to this case backlog results in delays, discouraging people from approaching court for justice and negatively affecting their faith in the efficiency of the justice delivery system. This backlog not only contributes to a delay in justice but also results in pressure on legal aid providers, and they now have to juggle increased caseloads with limited resources. Thus, much can be said for the challenges in accessing legal aid in India Chouhan (2019). These multifaceted issues require a multi-pronged process comprising better legal literacy, more funds for legal aid services, incentives for pro bono work for lawyers, and judicial reforms to expedite the resolution of cases. These are much-needed initiatives to narrow the gap between the promise of legal aid and its actual accessibility, thus reinforcing the very fabric of justice delivery in India. Role of National and State Legal Services Authorities (NALSA, SLSAs) and Barriers to effective legal aid: Lack of awareness, financial constraints, lawyer shortages and Case backlogs and legal aid effectiveness

 

3. AI in Legal Aid: Opportunities and Potential

Artificial intelligence (AI) has started finding its increased application areas in legal aid services denial and permit society access to justice in a more efficient, cost-effective, and widely available manner. In the Indian context, where a large section of the population is unable to gain adequate legal representation due to financial and logistic factors, AI solutions have a unique window to bridge the justice divide. Traditional methods of legal aid often fall behind in meeting the rising demand for legal assistance due to limited resources, an overburdened judiciary, and a grave shortage of legal aid lawyers. With the unparalleled ability to handle large amounts of data and automate mundane legal tasks, while giving real-time feedback, AI can bring widespread enhancement to legal aid services that were unthinkable, until recently Dhani et al. (2021). This section surveys various applications of AI in legal aid, including AI-enabled legal chatbots, machine learning for case management, automated legal research, AI-enabled legal aid helpline, and more broad impacts of AI on access to justice Abiodun & Lekan (2020).

 

4. AI-Powered Legal Chatbots: Revolutionizing Legal Assistance

The most noteworthy developmental changes brought by artificial intelligence in legal technology of the legal provision are the introduction of AI based legal chatbots that give instant access to individuals seeking help. These chatbots use natural language processing along with machine learning algorithms to interpret and respond to questions in law as a human legal professional. An excellent instance of such chatbots was DoNotPay, an AI chatbot that assists users with contesting parking violations, filing small claims, and creating legal documents at no cost Necz, D. (2024). Such successes now encourage many around the world into seeing similar initiatives; India legal tech startups like Law Bot Pro and Legal Mind have started developing customized AI chatbots for India and its multitude of laws Kalamkar et al. (2022). These AI chatbots would offer legal assistance in various languages, including those who are not only knowledgeable in English or Hindi. Such chatbots can help minimise the reliance on a legal aid attorney. By using this, an individual can access basic legal information without waiting for an in-person appointment. In the case of India, this would benefit most rural communities that are far apart and do not also have funds available for legal assistance. AI-based chatbots can make a significant contribution here by providing free-of-charge legal aid around the clock and not requiring a visit to legal aid offices Queudot et al. (2020).

 

5. Machine Learning and Predictive Analytics for Case Management

The application of machine learning and predictive analytics for case management is another transformational field in AI and legal aid. The Indian courts are flooded by an overwhelming backlog of cases, with pending cases in the courts numbering over 50 million Jin & Wang (2023). AI-driven case management can help legal aid organizations and courts prioritize cases and allocate resources efficiently to comply with such backlogs, as it can analyze precedent, identify patterns, and predict potential outcomes of cases Kalamkar et al. (2022). Such machine learning models, trained on historical case data, can help in:

1)     Trying to assess the chances of winning a case based on past verdicts.

2)     Recommend the best legal strategies for legal aid lawyers.

3)     Could cut short the time needed to create legal arguments by collecting data-driven observations.

AI-enabled case management is likely to enhance efficiency for legal aid providers by ensuring that resources are channelized into those cases predicted to have highest chances of success or the greatest societal impact. Predictive analytics can be applied to ADR mechanisms such as mediation or arbitration too, which will further relieve the courts from increased loads and better speed up justice to people Goldstein (1995).

 

6. Automated Legal Research and Document Drafting: Enhancing Efficiency

One of the most arduous services legal aid involves is legal research in conjunction with drafting of documents. AI-powered such as ROSS Intelligence and Bloomberg Law, use NLP-natural language processing-to analyze legal databases, precedent, statutes, and case laws with much greater speed than any human can manage Abiodun & Lekan (2020). So legal professionals can conduct exhaustive legal research in a matter of minutes using these AI tools; such as decreasing the burden of legal aid lawyers. And equally, these are the automated documents generated by AI:

1)     Legal petitions and affidavits

2)     Contracts and agreements

3)     Bail applications and legal notices

Automating these tasks enables legal aid agencies to spend their time on the substance of legal work so that more people reach the goal of quality legal services in a shorter period of time Abiodun & Lekan (2020). This is aimed at India. It is where most legal aids or flood legal lawyers are over burdened and also short of resources.

 

 

 

 

 

7. AI-Driven Legal Aid Helplines: Expanding Access to Justice

AI is also going to play an important role in expanding legal aid services in rural and marginalized communities with help from AI-powered, voice recognition, and multilingual helplines: INSTANT providing legal assistance over-the-phone to those without internet access or legal literacy. For instance, efforts such as India Justice Helpline AI integrate AI-based voice assistants capable of responding to legal queries, particularly for women, laborers, and economically disadvantaged people(2023). Such helplines generate real-time responses helping individuals know their legal rights, remedies available, and next steps in legal proceedings Westermann & Benyekhlef (2023). AI-powered helplines can also terminate the dependence on in-person legal aid clinics thereby widening access to legal assistance in remote and underserved areas. This is particularly important in India, where still a significant part of the population remains without connectivity regarding the internet in rural areas, and access to legal aid services is geographically constrained.

 

8. Potential Benefits of AI in Legal Aid: Speed, Cost Reduction, and Accessibility

The incorporation of artificial intelligence into legal aid services benefits the services in several ways. They include:

1)    Speed: AI tools speed up the provision of legal queries, research and document generation, so lawyers have reduced waiting times to avail themselves of legal aid.

2)    Cost-Reduction: Automating legal aid makes it cheaper and allows for more people to gain assistance through a service agency without raising their cost burden.

3)    Accessibility: Legal aid through AI empowers all the walls that would make it impossible for people to access such services, such as distance, lack of funds, or language.

At the same time, however, there are high barriers to the implementation of AI in legal aiding. Such ethical challenges range from algorithmic bias, which is bias in algorithmic predictions based on data input. That leads to data privacy issues and reinforces the existing social inequalities that already plague society. Therefore, policymakers might consider coming up with coherent, well-defined regulations that ensure that AI technology in the delivery of legal aid is kept as transparent, unbiased, and equitable as possible Araujo et al. (2020).

1)    Challenges and Ethical Considerations

The integration of AI into legal aid systems has great potential to increase access to justice. But the introduction of such technology has its share of challenges and ethical issues that require thorough consideration to attain the equitable and efficient delivery of legal services.

·        Risk of Bias in AI Algorithms and Legal Decision-Making

Machine learning systems or even AI systems may work on a training data set, which sometimes contains flaws and therefore leads to biased outcomes. In the legal context, such bias often results in a format of unfair outcomes that mainly affect already marginalized communities. For example, an algorithm called COMPAS has been substantially criticized in America because, instead of measuring recidivism risk, it gives a higher risk score to an African-American defendant over a white defendant Angwin & Larson (2016). Using AI for legal translating in India without addressing internal bias is likely going to worsen the situation and deteriorate that much treated principle of justice being impartial. Hence, it is necessary to evolve the models of AI with better bias mitigation techniques and ensure continuous monitoring so that fairness in deciding the law can inquire Ferrara (2023).

·        Data Privacy and Confidentiality Concerns

Still, the success of artificial intelligence in providing legal aid depends on the availability of huge datasets, which usually include very sensitive personal information. This brings up important questions on data privacy and confidentiality. Unauthorized access and breaches could bring down that confidentiality and lead to violations of ethical obligations by legal practitioners to maintain confidentiality toward their clients Appelbaum (2002). In India, where data protection laws continue to grow, this problem becomes a bit harder to solve. Protecting from such risks is required with stringent data protection protocols and compliance with existing emerging regulations in order to sustain public trust in AI-imbued legal services.

Generally, the success of artificial intelligence in providing legal assistance is primarily based on having a huge volume of data, which usually includes very sensitive personal information. Such a need raises very pertinent questions on data privacy and confidentiality. Unauthorized access or breaches could infringe that confidentiality by way of violations of ethical obligations by legal professionals to keep the client confidential Dyke et al. (2016). This makes the entire matter even more difficult in a country like India, where the data protection laws are still in a process of evolution. There is a need for stringent data protection protocols and compliance with emerging regulations for building trust in AI-driven legal services as per these different conditions Urbani et al. (2024).

·        The Digital Divide: Accessibility Issues for Rural Populations

Although AI could democratize legal aid, the huge digital divide would act as a constraint against its reach, especially in rural India. Limited internet connectivity, inadequate digital literacy, and lack of infrastructure can act against the coming together of rural populations in AI-based legal services. This disparity could further widen the justice gap, thus leaving vulnerable communities without an important foot of legal support. Therefore, a concerted approach to improvement in digital infrastructure, advocacy for digital literacy, and creation of user-friendly AI applications will be required, meeting the demands of rural users Torous et al. (2023).

·        Legal and Regulatory Challenges in AI Implementation

Second, these issues all require thorough regulation: liability for the decision made by an AI system, intellectual property rights regarding works created by the AI system, and potentially the unauthorized practice of law by AI systems Ahmed et al. (2023). In India, the absence of specific regulations about AI within the legal domain invites some uncertainty that considerably impedes the responsible use of AI technologies. The setting up of guidelines or standards seems to be essential for mapping the legal complexities posed by the AI implementation in legal aid services Антонов et al. (2021).

Thus, in summary, though AI looks good to revolutionize legal aid in India, the problems of ethics and practicalities must be tackled for the system to uphold justice instead of sowing the seeds of the prevalent injustices.

2)     Global Best Practices and Lessons for India

 For instance, these both hold into consideration of intensive regulations: liability of an AI system decision, intellectual property rights regarding works generated by the AI system, and most likely the unauthorized practice of law by AI systems Maheshwari & Co. (2023). Specific guidelines are not present in India in terms of using AI under the legal domain; this generalizes uncertainty that denies the proper utilization of AI technology. Establishing guidelines or standards is required to lay out the judicial issues posed by AI use in legal aid services.

Thus, this means that however good AI may seem at revolutionizing legal aid in India, the issues of ethics and practicalities must be tackled for the system to hold justice rather than sowing the seeds for the existing injustices.

·        AI-Based Legal Aid Models in the US, UK, and Other Jurisdictions

In the U.S., AI platforms like DoNotPay allow wider access to legal help by automating processes such as parking ticket appeals and document generation.Using natural language processing, this platform communicates with users to provide cost-effective legal solutions Browne (2020).Likewise, the UK is allowing the further integration of AI applications into legal practice in order to modernize and improve efficiency and accessibility.AI has been piloted by the UK government to refine court procedures and reduce case backlogs, an act that seeks to modernize the legal system Araujo et al. (2020).These examples clearly show how AI can relieve chronic stressors on the system and facilitate public access to legal resources.

·        Success Stories and Failures: Lessons for India

False, in addition, AIs have been very successful in legal applications, but there are serious challenges as well. In the U.S., although AI platforms have helped increase legal access, they have also drawn controversy around issues of algorithmic bias and data privacy, which will require proper oversight Gerke et al. (2020). Case law from the UK example demonstrates the need for feeding AI with human input to avoid offending the public Lovell (2024). An example: Failures with technology in general seem to arise because either the data aren't of high enough quality or no consideration of the context has been made at all, with poor judgment being exercised after the fact. In that sense, these experiences call upon India to gather high-quality representative data and to develop culturally-aware AI systems for the purpose of appropriate legal aid delivery (2024).

·        Policy Frameworks for Responsible AI in Legal Aid

The establishment of a responsible AI framework is important for the ethical deployment of any AI in the area of legal aid. The proposed AI Act in the European Union is a good example of a comprehensive approach, emphasizing risk-based regulation to protect fundamental rights White Black Legal. (2012).Likewise, the Responsible AI Institute has developed policy templates to aid in ethical AI deployment and emphasizes transparency, accountability, and fairness (Responsible AI Institute, 2024). In India, similar frameworks, developed on parallel lines as per local legal and cultural context, can be helpful in the responsible integration of AI into legal aid offering, ensuring that advancement does not come at the cost of justice and equity.

·        Can AI Truly Bridge the Justice Divide in India?

AI has become a transformative force in several sectors, including law. In India, these applications of AI are viewed as a possible way to bridge the justice gap where the justice system is hindered by case backlogs and lack of access to legal help. However, we need to critically analyze whether AI is indeed capable of complementing traditional support for legal aid, how much actual human involvement is required for the work with AI, and what infrastructural and legal hurdles may have to be addressed.

·        Evaluating AI’s Potential in Complementing Traditional Legal Aid

AI can supplement the traditional legal aid services by automating those repetitive and tedious tasks so that legal professionals can put their time and effort into other complex aspects of the practice. For instance, these tools are by assisting legal research by dramatically exploring the massive database of case law, statutes and precedents in a much shorter time than that taken for manual research. Startups such as CaseMine in India are putting AI to work to make extensive legal databases intuitive portals into legal research by feeding the legal practitioner even more efficiently with. AI will also give people access to legal information even if they cannot afford to talk to an attorney. For example, such users would only have to turn to an AI-driven chatbot for preliminary legal advice which would help them to understand their legal standing and help such users make informed decisions about whether to resolve matters amicably or pursue legal remedies.

·        The Need for Human-AI Collaboration in Legal Services

Whereas machines work well with data-heavy routines, legal reasoning, ethical aspects, and the ability to advocate for clients require some amount of human oversight. Human-AI interaction ensures that this balancing act is conducted with maximum effectiveness. Lawyers bring contextual knowledge, ethical judgment, and application of law to social value, which are currently qualities absent in AI. For this reason, the integration of AI within legal services should ultimately serve human competence, not undermine it. This man-machine synergy may even create efficiency and accuracy in rendering legal services by allowing AI to deal with the mundane while also keeping lawyers busy with strategy development and client-facing interactions Kaomea (2023).

·        Addressing Infrastructural and Legal Barriers

There are quite a lot of infrastructural and legal challenges to successful AI implementation in the legal system of India. One of the problems posed by this challenge is that it is the digital divide. Many of the peripherally situated regions of the country lack the appropriate infrastructure to encourage AI-based legal intervention or services. Reliable connectivity, along with digital literacy, is required by these areas to provide proper access to the AI-driven legal services. The solution to this will require investing heavily in developing digital infrastructure and education to ensure equal access to AI instruments by diverse sections of the population Semmler & Rose (2017). There are major concerns regarding the privacy and security of data. Legal data is always going to be sensitive in nature and requires an impregnable data protection regimen to keep unauthorized access and breaches away. Designing suitable and strong legal structures governing the usage, storage, and sharing of data through artificial intelligence needs to be built into the system to ensure that the public regains its trust and that the confidentiality that is inherent to legal practice is an extension of it Rodgers et al. (2023). Finally, AI's part in legal services has to clear a set of regulations that will define the applications' scope and limitations. It should include setting standards for AI accuracy while ensuring mechanisms for accountability in case of errors through the AI and compliance of AI tools with existing legal and ethical norms. These frameworks will make responsible adoption of AI technology in the legal sector possible to ensure that technological advancement adds to rather than detracts from the justice system.

 

3)    Policy Recommendations

Integrating Artificial Intelligence (AI) in India's legal aid ecosystem is an opportunity to transform justice by making it accessible and automated while minimizing inefficiencies in the legal framework  Abiodun & Lekan (2020). The integration shall necessitate thoughtful strategies, enforceable regulations, attempts to close the digital divide, and a forward-looking approach towards the future of AI in legal aid.

·        Strategies for Integrating AI into India’s Legal Aid Framework

The legal aid services have to adopt a whole gamut of solutions to incorporate AI effectively. First, AI-based legal research tools should assist law practitioners in analyzing enormous blocks of legal data, thereby speeding up actual case preparations and aiding Case Management Decisions. One such program is the SUPACE (Supreme Court Portal for Assistance in Court's Efficiency) system, initiated by the Supreme Court of India to improve judicial efficiency through AI-facilitated research Jin & Wang (2023).

Second, the implementation of AI-based case management systems may help with the automation of monotonous administrative tasks, the keeping track of case status, and the prediction of case outcomes based on past data. This would allow legal aid Providers to set their priorities straight about which cases to pursue and where to deploy their available resources efficiently. For instance, AI algorithms that are capable of long-term prediction of case duration and outcomes can aid in case-working backlogs by encouraging alternative dispute resolution mechanisms Abiodun & Lekan (2020).

Thirdly, AI-enabled chatbots and virtual assistants can provide preliminary legal information and guidance for people seeking legal assistance, thus lightening the initial workload on legal aid offices while increasing public access to legal information. Chatbots can be operational 24/7, providing immediate assistance while directing users to appropriate legal resources. The incorporation of AI in legal service promotes access to justice especially for the lesser privileged and weaker sections of the society Queudot et al. (2020).

·        Regulatory Measures to Ensure Fairn ess and Transparency

Regulatory frameworks for AI in legal aid must be created so that fairness, transparency, and accountability can be assured. Imposing a well-developed data protection law will go a long way in safeguarding the right to privacy and confidentiality of an individual with respect to any legal information. Today India does not have any specific regulations for AI; however, some regulations, such as the Digital Personal Data Protection Act, 2023, would cover some of the concerns regarding data privacy (2024). Furthermore, guidelines would be necessary to promote transparency in AI systems' decisions. Such AI systems can be made to explain their outputs so that their users, be it legal professionals or clients, can comprehend the rationale for AI's recommendations to them. The need for such transparency is reiterated in the NITI Aayog "Principles for Responsible AI". Also, setting up independent monitoring boards that can examine AI application practices in the legal sector would prevent possible biases and discrimination. Such bodies would audit AI systems for adherence with relevant ethical standards and address any unintended adverse effects arising from the deployment of AI. With no specific AI evidence regulations so far, the establishment of such oversight mechanisms is required to guarantee ethical integration of AI.

Bridging the Digital Divide: Strengthening Accessibility through Legal Tech Literacy

AI is revolutionizing the legal landscape, and in reality it is doing so because it will eliminate legal barriers that prevent access to such technologies by diverse populations. By closing the gap between miners and mining companies in the digital divide, we will need to steadily improve digital infrastructure especially in rural and underdeveloped areas, extend internet access, ensure affordable availability of digital devices, and create AI applications that enhance accessibility at the community level Kasimov et al. (2021). Then, that would have to be complemented by law-tech literacy because otherwise, that people can properly use AI tools for their own benefit. Educational programs and workshops may equip both legal professionals with the public in packing skills to navigate artificial intelligence-enabled legal services. Joint initiatives, in this case, set up between government agencies, non-profit organizations, and educational institutions might clear the way to spread the knowledge in legal tech without putting any further gaps to widen that technological advancement.

·        Future Prospects for AI and Legal Aid in India

With the future integration of AI in India's legal aid framework, a more expedient, accessible, and equal justice system is heralded. AI technology is continuously improving its performance in the areas of legal reasoning, predictive analytics, and natural language processing and will thus continue to increase its importance in legal aid services Chouhan (2019). This potential has to be harnessed in such a way that it develops new technological innovations while ensuring ethical principles and human rights are safeguarded. Continuous engagement among all stakeholders including policymakers, legal practitioners, technologists, and the public will be necessary to navigate between the benefits and challenges that arise from the introduction of AI into legal aid Abujaber & Nashwan (2024). Through well-conceived strategies, solid regulations, and inclusive educational initiatives, India can bring AI to bear on the justice divide so that its benefits in legal aid become accessible to all.

 

9. Conclusion

 Integration of Artificial Intelligence (AI) with legal aid in India throws in considerable opportunities and challenges favoring either side. The study was to try to discern the current scenario of legal aid in India by analyzing the potential of AI-induced improvements to the provision of legal services and best practices as well as the ethical considerations that guide its judicious implementation.

Synopsis of Major Observations: In India the legal aid system is constrained by narrow publicity, financial sustenance, and specifics concerning an acute shortage of Lawyers while generally denying access to justice. By the use of AI technologies inclusive of legal chatbots, machine learning on case management, and legal research on cases, the efficiency of offering legal aid can be scaled up.AI technologies have the potential to provide solutions for efficiency-raising and enlargement of client bases. Nevertheless, adoption of AI will have to grapple with variety of ethical matter-like bias calculations, data, privacy, and the social divides, which will negotiate the promise of AI in the legal industry. According to the lessons that have been learned from validated AI technology use cases vis à vis legal services, it is seen that successful interlinkages are reflected in sound policy and deep contextual analysis.

Further Insight on the Enhancement Process of Legal Aid Through Application of AI: AI, which implies computerized intelligence, holds great credit that will transform legal aid in India by automating and performing routine tasks and supplementing the intelligence of judicial and legal actors, for instance legal counsel-to some extent. A good example of that is how NyayGuru or LAWFYI, which are AI-engined platforms, offer some legal education to the public. Still, AI must be applied to supplement the critical eye of many who are the fundamental under-providers for legal services. To further penetrate, a combined approach has to be adopted, the human being's professional validation being the apex of AI.

The Trails to Accessible and Tech-Based Judiciary: India needs to work on a superior platform, so as to effectively employ AI in legal aid, to involve preparing AI applications that fit into the legal sector around which to frame regulations ensuring fair use of this technology pilfered in the age of technology, while ensuring proceeds from investments back into digital infrastructure. This also implies generating some legal-related technological literacy within the space of law practitioners and general public, so that AI can be effectively transformed. Addressing these areas opens ways for India to have a more inclusive, more efficient, and more technology-driven judiciary that would underscore the principles of fairness and access.

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

REFERENCES

A Brief History of Legal Aid. (2023).

Abiodun, O. S., & Lekan, A. J. (2020). Exploring the Potentials of Artificial Intelligence in the Judiciary. International Journal of Engineering Applied Sciences and Technology, 5(8). https://doi.org/10.33564/ijeast.2020.v05i08.004

Abujaber, A. A., & Nashwan, A. J. (2024). Ethical Framework for Artificial Intelligence in Healthcare Research: A Path to integrity. World Journal of Methodology, 14(3). https://doi.org/10.5662/wjm.v14.i3.94071

Ahmed, M. I., Spooner, B., Isherwood, J., Lane, M. A., Orrock, E., & Dennison, A. R. (2023). A systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare [Review of A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare]. Cureus. https://doi.org/10.7759/cureus.46454

Ahtohob, В. В., Kharisova, Z. I., Kalimullin, N. R., & Abdulnagimov, A. (2021). Modeling Problems Legal Regulation of the Field of Artificial Intelligence. Iop Conference Series: Materials Science And Engineering, 1069(1), 012002. https://doi.org/10.1088/1757-899X/1069/1/012002

Angwin, J., & Larson, J. (2016). Bias in Criminal Risk Scores is Mathematically Inevitable, Researchers say.

Appelbaum, P. S. (2002). Privacy in Psychiatric Treatment: Threats and Responses [Review of Privacy in Psychiatric treatment: Threats and Responses]. American Journal of Psychiatry, 159(11), 1809. https://doi.org/10.1176/appi.ajp.159.11.1809

Araujo, T., Helberger, N., Kruikemeier, S., & Vreese, C. H. de. (2020). In AI we trust? Perceptions About Automated Decision-Making By Artificial Intelligence. AI & Society, 35(3), 611. https://doi.org/10.1007/s00146-019-00931-w

Authors. (2024). Artificial Intelligence 2024 - India.

Balan, A. (2024). Examining the Ethical and Sustainability Challenges of legal Education’s AI Revolution. International Journal of the Legal Profession, 1.  https://doi.org/10.1080/09695958.2024.2421179

Chalid, P., & Rizqita, A. N. (2018). Existing Social Justice Choice for Underprivileged Society Members. https://doi.org/10.2991/iclj-17.2018.10

Chouhan, K. S. (2019). Role of AI in Legal aid and Access to Criminal Justice. SSRN Electronic Journal.

Contributors to Wikimedia projects. (2023). Legal Services Authorities Act, 1987.

Contributors to Wikimedia Projects. (2023). Tele-Law Programme.

Dhani, J. S., Bhatt, R., Ganesan, B., Sirohi, P., & Bhatnagar, V. (2021). Similar Cases Recommendation Using Legal knowledge graphs. arXiv. https://doi.org/10.48550/arXiv.2107

Dyke, S. O. M., Dove, E. S., & Knoppers, B. M. (2016). Sharing Health-Related Data: A Privacy Test. npj Genomic Medicine, 1(1). https://doi.org/10.1038/npjgenmed.2016.24

Ferrara, E. (2023). Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models. arXiv. https://doi.org/10.48550/arXiv.2304

Gerke, S., Minssen, T., & Cohen, G. (2020). Ethical and Legal Challenges of Artificial Intelligence-Driven Healthcare. In Elsevier eBooks, 295. https://doi.org/10.1016/b978-0-12-818438-7.00012-5

Goldstein, J. I. (1995). Alternatives to High-Cost Litigation. Cornell Hotel and Restaurant Administration Quarterly, 36(1), 28. https://doi.org/10.1177/001088049503600115

Jin, X., & Wang, Y. (2023). Understand Legal Documents with Contextualized Large Language Models. arXiv. https://doi.org/10.48550/arXiv.2303

Jüriloo, K. (2015). Free legal aid – A Human Right. Nordic Journal of Human Rights, 33(3), 203. https://doi.org/10.1080/18918131.2015.1066143

Kalamkar, P., Agarwal, A., Tiwari, A., Gupta, S., Karn, S., & Raghavan, V. (2022). Named Entity Recognition in Indian court judgments. https://doi.org/10.18653/v1/2022.nllp-1.15

Kaomea, P. (2023). An Intelligence Coordination System Toward Creating the Super-Intelligent Law Firm. Frontiers in Artificial Intelligence, 6. https://doi.org/10.3389/frai.2023.1145308

Kasimov, A., Provalenova, N., Parmakli, D., & Zaikin, W. P. (2021). An Integrated Approach to Digitalization of Rural Areas as a Condition for their Sustainable Development. IOP Conference Series: Earth and Environmental Science, 857(1), 12004. https://doi.org/10.1088/1755-1315/857/1/012004

Kerala Judicial Academy. (2024). Artificial Intelligence Assisted Judicial Processes.

Lovell, J. J. (2024). Legal Aspects of Artificial Intelligence Personhood: Exploring the Possibility of Granting Legal Personhood to Advanced AI systems and the Implications for Liability, Rights and Responsibilities. International Journal of Artificial Intelligence and Machine Learning, 4 2), 23–40. https://doi.org/10.51483/ijaiml.4.2.2024.23-40

Necz, D. (2024). Rules over words: Regulation of Chatbots in the Legal Market and Ethical Considerations. Hungarian Journal of Legal Studies, 64(3), 472. https://doi.org/10.1556/2052.2023.00472

Nigam, S. (2008). Legal Literacy: A Tool for Empowerment. SSRN Electronic Journal.

P. S. C. (2024). Legal aid in India: Enhancing Access to Justice for all. International Journal for Multidisciplinary Research, 6(2). https://doi.org/10.36948/ijfmr.2024.v06i02.14836

Pandey, A. (2020). Social justice, the Raison D’etre of Clinical Legal Education. Jindal Global Law Review, 11(2), 201. https://doi.org/10.1007/s41020-020-00132-3

Plata, M. C. (1997). Justice for whom.

Queudot, M., Charton, É., & Meurs, M. (2020). Improving Access to Justice with Legal Chatbots. Stats, 3(3), 356. https://doi.org/10.3390/stats3030023

Rhode, D. L. (2004). Access to justice.  http://ci.nii.ac.jp/ncid/BA70899476

Rodgers, I., Armour, J., & Sako, M. (2023). How Technology is (or is not) Transforming Law Firms. Annual Review of Law and Social Science, 19(1), 299. https://doi.org/10.1146/annurev-lawsocsci-111522-074716

Semmler, S., & Rose, Z. (2017). Artificial Intelligence: Application Today and Implications Tomorrow. Duke Law and Technology Review, 16(1), 85.  

Torous, J., Myrick, K. J., & Aguilera, A. (2023). The Need for a New Generation of digital mental health Tools to Support more Accessible, Effective and Equitable Care. World Psychiatry, 22(1), 1. https://doi.org/10.1002/wps.21058

Urbani, R., Ferreira, C., & Lam, J. (2024). Managerial Framework for Evaluating AI Chatbot Integration: Bridging Organizational Readiness and Technological Challenges. Business Horizons, 67(5), 595. https://doi.org/10.1016/j.bushor.2024.05.004

Westermann, H., & Benyekhlef, K. (2023). JusticeBot: A Methodology for Building Augmented Intelligence Tools for Laypeople to Increase Access to justice. arXiv. https://doi.org/10.48550/arxiv.2308.02032

White Black Legal. (2012). Evaluating the Impact of Legal Aid Programs on Access to Justice in India.