THE ROLE OF NON-HUMAN ENTITIES IN PROVIDING EVIDENCE: A LEGAL ANALYSIS

This article is written by Tejal Vengurlekar of Victor Dantas Law College, Kudal, an intern under Legal Vidhiya

ABSTRACT

The integration of non-human entities into the legal landscape, such as artificial intelligence (AI) systems, digital records, autonomous devices, and advanced technologies, represents a significant shift away from traditional concepts of evidence provision. This transition creates unprecedented prospects for efficiency and precision in evidence collecting and analysis, but it also raises numerous concerns about dependability, openness, and ethical consequences. This article explores the nuances of incorporating non-human entities as evidence providers within the legal framework in India.

The need for a complex legal framework to decide whether evidence produced by non-human entities is admissible, as well as the importance of guaranteeing responsibility, dependability, and transparency, are important subjects covered. Examined are difficulties including guaranteeing the reliability and correctness of the evidence, dealing with questions of responsibility and openness, and striking a balance between privacy concerns and the requirement for convincing evidence. Indian court decisions show how the adoption of electronic evidence and its authentication procedures has changed over time.

Keywords

Non-human entities, evidence provision, artificial intelligence, Role, challenges, opportunities, ethical considerations, legal precedents, future implications.

INTRODUCTION

In the contemporary legal landscape, the integration of non-human entities into the process of providing evidence represents a significant departure from traditional notions of justice. With the rise of artificial intelligence (AI) systems, digital records, autonomous machines, and other sophisticated technologies, the scope of evidence has expanded beyond human testimony and physical artifacts to include data generated and analyzed by these entities. This shift offers unprecedented opportunities for efficiency and accuracy in evidence collection and analysis, as non-human entities can process vast amounts of information rapidly and uncover patterns that may elude human observers. However, this evolution also presents a myriad of challenges, including questions about the reliability, transparency, and ethical implications of relying on AI-generated evidence. As courts grapple with these complexities, it becomes essential to establish clear legal frameworks that balance the benefits of technological innovation with the imperatives of fairness, accountability, and individual rights in the pursuit of justice.

MEANING

Non-human entities are entities that are not human in nature, such as artificial intelligence (AI) systems, autonomous machines, robots, algorithms, Surveillance Footage and other advanced technologies. These entities have data collecting, processing, decision-making, and interaction capabilities that are comparable to or exceed those of humans. Non-human entities play increasingly important roles in a variety of contexts, including legal procedures, scientific study, and technological advancement, creating complicated ethical, legal, and societal issues. The word refers to a wide range of technologies and systems meant to do activities autonomously or semi-autonomously, frequently with little or no direct human participation.

TYPES OF NON-HUMAN ENTITIES

Non-human entities can encompass a variety of forms and technologies, each with its own potential to serve as evidence in legal proceedings. Some common types of non-human entities that can be utilized as evidence include:

1. Artificial Intelligence (AI) Systems: Artificial intelligence (AI) systems are made to look like human cognitive processes including learning, thinking, and decision-making. [1]These systems can analyze data, identify patterns, and make predictions, making them valuable tools for generating evidence in areas such as predictive policing, financial fraud detection, and risk assessment.
2. Autonomous Machines: Autonomous machines, such as drones and self-driving cars, may function independently without direct human interaction. These gadgets can record audio, video, and sensor data, which can be used as evidence in cases of surveillance, accidents, or environmental monitoring.
3. Robots: Robots equipped with sensors and cameras may collect data and perform tasks in a variety of settings. Robot-generated data or observations may be used in legal procedures involving workplace accidents, product responsibility, or property damage.
4. Algorithms: Algorithms are mathematical formulas or processes used to perform specific tasks, such as data analysis, image recognition, or language translation. Evidence generated by algorithms, such as computer-generated images, audio transcripts, or text analysis results, may be admissible in court under certain circumstances.
5. Surveillance Footage: Surveillance cameras and other monitoring equipment collect visual and audio data from public areas, private residences, and commercial businesses. Surveillance footage can be used as evidence in criminal cases, civil disputes, and insurance claims.
6. IoT Devices: Internet of Things (IoT) devices, such as smart home appliances, wearables, and environmental sensors, collect information on their users’ activities, health, and surroundings. Data from IoT devices could be useful in cases of personal injury, medical negligence, or property damage.
7. Biometric Systems: Biometric systems identify people based on their unique biological characteristics, such as fingerprints, facial features, and DNA. Biometric data can be used as evidence in cases of identity theft, fraud, and criminal investigations.
8. Forensic Tools: Forensic tools, such as DNA analysis kits, fingerprint scanners, and ballistics analysis software, enable the collection and analysis of physical evidence from crime scenes. Results from forensic examinations can be presented as evidence in criminal trials.

ROLE ON NON-HUMAN ENTITIES

Non-human entities, such as forensic evidence, technology, or even animals, can play crucial roles in legal proceedings by providing evidence or aiding in investigations. Such as:

1. Forensic Evidence: Forensic evidence includes physical evidence like fingerprints, DNA, fibers, bloodstains, and ballistics. These materials can be analyzed to provide valuable information in criminal investigations and trials. For example, DNA evidence can link a suspect to a crime scene or exonerate someone wrongly accused.
2. Surveillance Technology: Non-human entities like surveillance cameras, GPS tracking systems, and audio recording devices can provide valuable evidence in legal cases. Video footage or audio recordings can capture events as they unfold, providing an objective record of what happened.
3. Digital Evidence: In the digital age, electronic devices such as computers, smartphones, and tablets often contain valuable evidence like emails, text messages, browsing history, and metadata. Digital forensics experts can extract and analyze this data to uncover evidence relevant to a case.[2]
4. Expert Witnesses: While not technically non-human, expert witnesses can provide specialized knowledge and analysis in legal proceedings. For example, forensic scientists, medical professionals, and engineers can offer expert opinions based on their expertise in their respective fields.
5. Animals: Animals like dogs can be trained to detect drugs, explosives, or even human remains. Their keen senses make them valuable assets in law enforcement investigations, particularly in search and rescue operations or in detecting contraband.
6. Artificial Intelligence (AI) and Machine Learning: AI technologies can analyze large datasets to identify patterns or anomalies that humans might overlook. For example, AI algorithms can help identify potential instances of fraud, predict criminal behavior, or analyze large volumes of legal documents for relevant information.[3]

CHALLENGES AND OPPORTUNITIES

The integration of non-human entities as evidence providers presents both challenges and opportunities within the legal framework.

Challenges

1. Reliability and Accuracy: One of the key issues is assuring the dependability and accuracy of evidence supplied by non-human creatures. AI systems and algorithms may be prone to biases, errors, or limits in their training data, which can lead to inaccurate or misleading findings.
2. Transparency and Accountability: Non-human entities frequently use complex algorithms and decision-making processes that may lack transparency. This complicates understanding how evidence is collected and evaluated, raising issues about accountability and the possibility of unfair decisions.
3. Privacy and Data Protection: Non-human entities frequently rely on massive volumes of data to establish proof, creating worries about privacy violations and data security. Courts must strike a balance between the necessity for probative evidence and the rights of individuals to protect their personal information and prevent unlawful access or misuse.
4. Legal Admissibility: There may be doubts about the legal admissibility of evidence produced by non-human entities, especially if it does not fit customary requirements of relevance, authenticity, or dependability. Courts may request more validation or expert testimony to determine the admissibility of such evidence.

Opportunities

1. Efficiency and Speed: Non-human entities have the potential to streamline the evidence collection and analysis process, offering increased efficiency and speed in legal proceedings. Many systems are capable of rapidly processing through huge amounts of data to find relevant data, which saves time and resources.
2. Enhanced Objectivity: Unlike human witnesses or experts, non-human entities are not susceptible to biases or subjective interpretations. They can analyze evidence objectively, potentially reducing the risk of errors or prejudices influencing legal outcomes.
3. Access to New Sources of Evidence: Non-human beings can access and examine sources of evidence that humans may find inaccessible or difficult to understand. For example, advanced algorithms can examine patterns in big datasets or understand complex technical information, revealing insights that human observers may not see.
4. Innovation in Legal Practice: The incorporation of non-human entities creates opportunities for innovation in legal practice, stimulating the creation of new tools, technology, and procedures to improve evidence gathering, analysis, and presentation. This can result in more effective and informed decisions in judicial proceedings.

LEGAL PRECEDENTS

1. Siddharam Satlingappa Mhetre v. State of Maharashtra (2011)[4]: In this judgment, the Supreme Court of India stressed the value of forensic evidence, including scientific and technological means, in criminal investigations and legal proceedings. The court emphasized the need of properly documenting, analyzing, and presenting forensic evidence to ensure its admissibility and trustworthiness in court.
2. State of Karnataka v. Srikanth (2014)[5]: This case featured the use of mobile phone records as evidence to determine the accused’s whereabouts at the time of the crime. The Karnataka High Court confirmed the validity of mobile phone records as electronic evidence, emphasizing the importance of rigorous authentication and verification to maintain their credibility in court.
3. Anvar P.V. v. P.K. Basheer and Others (2014)[6]: In this case, the Supreme Court of India established criteria for the admissibility of electronic evidence, such as computer-generated records and documents. The court stressed the significance of maintaining the integrity, legitimacy, and dependability of electronic evidence through proper certification and authentication procedures.
4. Navjot Sandhu alias Afsan Guru v. State of NCT of Delhi (2005)[7]: This case, known as the Parliament Attack case, featured the use of CCTV footage as evidence to identify and prosecute the terrorists who attacked the Indian Parliament in 2001. The Supreme Court relied on CCTV evidence to determine the accused’s identify and movements during the conduct of the crime.

FUTURE IMPLICATIONS

The incorporation of non-human beings into evidence provision within the legal framework has important ramifications for the future of justice and legal proceedings in India. While the conversation frequently focuses on artificial intelligence (AI), it is critical to acknowledge a larger range of non-human entities, such as advanced robots, IoT devices, biometric systems, and other developing technologies that will influence the country’s legal landscape.

Looking ahead, one significant implication is the potential to increase access to justice and legal services, especially in a country as large and diverse as India. Non-human entities can help transmit legal information, support, and conflict resolution procedures to rural or underserved populations, increasing inclusivity and lowering barriers to justice.

Moreover, including non-human entities in evidence provision can improve the efficiency and effectiveness of legal proceedings in India. Advanced technology, such as robotics and IoT devices, may help collect and analyze evidence from crime scenes or conduct forensic investigations, speeding up case resolution and decreasing the judicial system’s workload.

Additionally, the inclusion of non-human entities in evidence provision poses fundamental questions about data privacy, security, and protection in India. With the rise of technologies that rely on massive volumes of personal data, there is an urgent need to establish strong legislative frameworks and protections to protect individuals’ privacy rights and prevent unlawful access to or exploitation of sensitive information.

Furthermore, the ethical ramifications of engaging nonhuman beings in legal proceedings must be carefully considered in India. This includes issues about algorithmic bias, justice, transparency, and accountability, especially given India’s diverse population and complex socioeconomic landscape. Ethical rules and standards must be established to control the development, deployment, and use of nonhuman entities in evidence supply, ensuring that legal practice remains consistent.

Lastly, incorporating non-human entities into evidence provision creates chances for innovation, collaboration, and capacity building in India’s legal ecosystem. India can use emerging technology to strengthen justice administration, improve access to legal services, and promote the rule of law by building collaborations among legal professionals, technologists, policymakers, and civil society groups.

CONCLUSION

In conclusion, the incorporation of non-human entities as evidence providers represents a pivotal shift in the legal paradigm, necessitating a nuanced understanding of its implications. While the integration of artificial intelligence systems, autonomous machines, and other advanced technologies offers the promise of efficiency, accuracy, and objectivity in evidence provision, it also poses significant challenges and ethical considerations.

The complexities surrounding reliability, transparency, and accountability underscore the need for a robust legal framework that safeguards against potential biases, errors, and privacy infringements. Courts, policymakers, and legal practitioners must navigate these challenges while ensuring that the principles of fairness, transparency, and individual rights are upheld.

In this ever-evolving landscape, the integration of non-human entities as evidence providers presents both opportunities and responsibilities. By embracing innovation while upholding core legal principles, we can harness the potential of technology to strengthen the administration of justice and uphold the rule of law in the digital age.

REFERENCES

1) Pranav Sethi, Admissibility of CCTV recordings as evidence in courts, Ipleaders, https://blog.ipleaders.in/admissibility-cctv-recordings-evidence-courts/ (last visited 12 feb. 2024)

2) Unesco, How to determine the admissibility of AI-generated evidence in courts? https://www.unesco.org/en/articles/how-determine-admissibility-ai-generated-evidence-courts#:~:text=Predictive%20AI%20models%20can%20provide,examples%20of%20AI%2Dgenerated%20evidence. (Last visited 11^th feb. 2024)

3) Bharat Vasani & Varun Kanna, Cyril amarchand mangaldas, https://corporate.cyrilamarchandblogs.com/2021/01/supreme-court-on-the-admissibility-of-electronic-evidence-under-section-65b-of-the-evidence-act/

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[1]Artificial Intelligence Definitions, https://www.unf.edu/ofe/ai/definitions.html (Last visited Feb. 20, 2024)

[2] ) Bharat Vasani & Varun Kanna, Cyril amarchand mangaldas, https://corporate.cyrilamarchandblogs.com/2021/01/supreme-court-on-the-admissibility-of-electronic-evidence-under-section-65b-of-the-evidence-act/ (Last visited Feb. 11, 2024)

[3] Aditi Prabhu, Artificial intelligence in the context of the Indian legal profession and judicial system, (Last visited Feb. 21, 2024) https://www.barandbench.com/columns/artificial-intelligence-in-context-of-legal-profession-and-indian-judicial-system.

[4] Siddharam Satlingappa Mhetre v. State of Maharashtra, https://indiankanoon.org/doc/1108032/

[5] State of Karnataka v. Srikanth, https://indiankanoon.org/doc/70641538/

[6] Anvar P.V. v. P.K. Basheer and Others, https://indiankanoon.org/doc/187283766/

[7] Navjot Sandhu alias Afsan Guru v. State of NCT of Delhi, https://indiankanoon.org/doc/1769219/

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