IS ARTIFICIAL INTELLIGENCE REALLY A CATALYST IN FORENSIC  SCIENCE

ABSTRACT

In the recent times world has seen an exponential growth in both traditional and modern crimes.  With a wide variety of crimes in almost every realm, technological developments come into  picture to identify, Analyse, detect and to deal with different types of crimes as per their nature.  Artificial Intelligence (AI) is one such branch which is becoming the most renounced  technologies in the Forensic Science landscape, known to play a crucial role in providing high  effectiveness, accuracy and efficiency. Artificial Intelligence has unending applications starting  right from the day of crime to the very conclusion of the case. The paper examines the  contribution of the technology and the rise in the successrate it hasled to in effectually handling  these investigations. Additionally, the paper mentions about the efficacy of Digital Forensics  and AI in the Criminal Justice System which aims to provide efficient disposal of matters. The  study provides clarity with suggestions and recommendations for battling the challenges that  the combination of AI and Digital forensics faces when implemented in the Criminal Justice  System to investigate different kinds of criminal investigations. Furthermore, the study shows  that Intelligent software has aided forensic investigations and reduced the errors that tend to  occur due to cognitive bias. However, every technology sees some limitations; for example,  intelligent systems require a humongous database of knowledge, which could result in wrong  interpretations if inputs go beyond the trained data sets. Moreover, this can lead to some ethical  and legal concerns. This research study uses a doctrinal and analytical approach to examine  India’s present Laws and guidelines dealing with the underlying issue. The paper then converses  that the blend of master and machine is needed to reduce the functioning load. Technology can  make their job easier, but it can never replace them because forensic science is a field of experts,  AI can only cater as a supplementary tool.

Keywords: Artificial Intelligence, Forensic Science, Digital Forensics, Criminal Investigation,  Criminal Justice System

Introduction

The integration of Artificial Intelligence and Forensic Science, especially within the realm of  crime, has been transforming the terrain of crime detection, investigation, and justice. While  technology is unfolding its various ramifications, AI-powered facial recognition and predictive  policing is leading to more precise, swift investigations that are data-based in their decisions.

AI in forensic science is not only enhancing traditional methods but is entirely revolutionizing  how evidence is collected,studied, and understood, enabling forensic scientiststo work smarter,  solve cases quicker, and bring more justice into the world.

Crime has changed significantly with society, technology, and the laws. In the past, most crimes  were physical crimes like theft, assault, or murder. These blue-collar crimes left behind overt  signs like fingerprints, weapons, and injuries, solved through eyewitness accounts, basic  forensic tools, and manual detective work. But with modern technology, white-collar crimes  like cybercrimes, financial frauds, and identity theft present new challenges as they happen on  the internet.¹ Cybercriminals use hacking, scams, and digital tricks that can reach different  countries, leaving no physical clues. Cases are instead solved through complex tools, requiring  law enforcement to find intelligent ways of combating crime.²

Forensic scientists can now rapidly analyze vast amounts of data by identifying digital  footprints and hidden patterns, thus accelerating crime-solving. While traditional methods like  fingerprint matching, bullet tests, and DNA checks remain important, they can be time  consuming, sometimes inaccurate, and cannot handle the massive amounts of data involved in  today’s crimes. AI tools can quickly and accurately scan through tons of information, using  facial recognition and machine learning to identify patterns, suspects, and cases at a much faster  rate. Digital forensics particularly benefits from AI as it digs through huge amounts of data to  find hidden clues.³ AI is also valuable for recreating crime scenes, analyzing voices, and  predicting where crimes might happen next.

However, there are challenges with using AI, including concerns about privacy, fairness, and  the possibility of mistakes. To keep things fair and just, AI tools need strict rules and regular  checks to avoid errors and biases. As crime evolves, forensic science must adapt with it. While there are challenges, AI’s benefits in solving crimes and making the process more accurate⁴ make it an essential tool in modern forensic science.

THE EVOLUTION OF CRIME

Crime is any act that disregards the law. According to Blackstone, it was a violation of the law;  however, this definition is a little too broad. Austin said that crime is a wrong dealt with by the  government, which implies that this focuses more on how the case is handled rather than what  the crime actually is. Simply put, crime is the act of intent which causes harm to others that is  illegal and punishable. Something which changes through time, because it is impacted by  society, culture, and laws we live with.⁴ Traditional crimes include theft, assault, and murder.  These are relatively simple crimes that involve physical acts such as hurting someone or  damaging property. Most of these crimes are associated with certain social groups but can occur  anywhere. Modern crimes are difficult and entail all the facilities of today’s technological  advancement. Some examples of modern crimes include cybercrime, environmental damage,  or theft of ideas and patents. What makes modern crime unique is the aspect of technology. It  is therefore difficult to catch and understand it.

The Need for Advanced Technological Interventions in Forensics

Role of Forensic Sciences in Justice System

The term forensic science involves forensic (or forensis, in Latin), which means a public  discussion or debate. Forensic science is about using scientific methods to solve legal problems,  whether it’s in criminal cases like murder or theft, or civil cases such as pollution or accidents.  It’s a way of applying science to the law, and many different areas of science can play a part.  The forensic sciences belong to the penal system of most countries of the world; hence, it can  be described as a means for the proper management of justice.⁵ Equipped with a rigorous  scientific education in specific areas like chemistry, anthropology, physics, genetics, and  medicine, forensic scientists are capable of interpreting and summarizing evidence to give meanings in expert opinions.⁶ These indeed constitute the bulk of the entire procedure of an  investigation for any offense committed.

The 2018 Golden State Killer case, where forensic genealogy and DNA evidence led to the  arrest of Joseph James DeAngelo after more than 40 years. Investigators used DNA from crime  scenes and compared it with profiles on genealogy websites to identify the suspect. ⁷

Technological innovation in crime prevention and investigation

Sometimes, through forensic techniques along with technological equipment, crimes may be  prevented in the future due to identification of criminal patterns, connections, and trends that  may help law enforcement and judicial systems act proactively through prediction⁸. Recovery  of data from electronic devices, which is one of the core bases of digital forensic technologies  because now there are vast numbers of internet devices and gadgets on which one could obtain  information providing digital evidence with higher effectiveness of solutions for forensic  investigation cases. The three Ds of theory: digital data, digital devices, and digital evidence  are known as triangulation; these have become a necessity for effective forensic investigation  and depend on digital technologies.

For Example, CompStat of New York Police Department uses data analytics for the detection  of crime patterns. Also, the 2019 Capital One data breach investigation, where digital forensics  traced the breach to a former AWS employee.

Advanced tools and AI in modern forensic investigation

Good use of AI applications can reduce subjectivity and human error when interpreting data.  The quality of the evidence being presented in court is raised as a result of this. The forensic  sciences were given many advanced tools, devices, and applications by technology and its  advancements to have a better and more accurate understanding of the crime scene and better  and optimal acquisition of data and information to process faster.⁹ Besides that, sophisticated forensic tools not only enhance the detection and analysis of digital evidence but also help to  preserve it and ensure chain-of-custody-a very sensitive area for legal purposes.

Some Real-Life Applications we can see is the use of AI-powered facial recognition in the  investigation of the January 6, 2021, U.S. Capitol riot. Also, the 2023 Alex Murdaugh case  which digital forensics of smartphones and cell data provided critical timelines.¹⁰

ARTIFICIAL INTELLIGENCE IN FORENSIC SCIENCE

Artificial Intelligence (AI) is computer technology that mimics human thinking in tasks like  decision-making and pattern recognition. We encounter AI daily through movie  recommendations, chatbots like ChatGPT, and medical diagnostics. While computers have been  solving complex problems since the 1940s, they still can’t fully replicate human reasoning.  However, AI excels at specific tasks like improving searches, speech recognition, and  workplace safety. Its primary purpose is to assist humans by handling routine or dangerous  tasks, enhancing transportation safety, and processing large data sets to provide valuable  insights. Not just AI has transformed forensic science by enhancing analysis, pattern  recognition, and evidence processing but also it eliminates human limitations like fatigue and  bias, making investigations more accurate and efficient. In 2017, the FBI’s Next Generation  Identification system successfully used AI to analyze fingerprints for a 1999 cold case. A latent  fingerprint missed by traditional methods helped identify and lead to the arrest of a murder  suspect. Likewise, in 2019, The New Zealand mosque shooting was a case where AI tools  analyzed thousands of hours of social media content and digital evidence in just days, a job that  would have taken months to complete for human investigators. It has made forensic  investigations more cost-effective and more thorough than ever before. AI also enhances quality  control by reviewing drug cases at Houston’s forensic lab in 2020, discovering wrongly  classified evidence and preventing wrongful convictions. Still, AI has its limitations and can  only operate under human supervision. AI-powered facial recognition caused the wrongful  arrest of a young man in Detroit in 2021, proving the need for proper validation and ethical  use.¹¹ Though AI can be a mighty forensic tool, it should support human expertise so that justice  may be fair and accurate.

Contributions of AI: Accuracy, Efficiency, and Effectiveness in  Investigations

Increased Accuracy in Forensic Analysis

AI brings remarkable accuracy to forensic work, helping exclude human error and bias. The  Case in point was the 2019 Houston Forensic Science Center case, when AI-powered fingerprint analysis correctly matched prints that human analysts had found themselves unable  to match for months. The minute details in partial prints that go easily unnoticed under the  human eye could be readily picked up. Another striking example of AI in use is its role in DNA  analysis. DNA from multiple individuals analyzed together in one sample tends to be tricky in  traditional approaches due to a greater chance of interpretive error. AI processes evidence at  speeds that are revolutionizing the rapid movement of cases. Take the case in 2020 when  investigators in London needed to track a suspect’s movements by scanning thousands of hours  of CCTV footage. AI video analysis completed the task in hours rather than weeks for human  analysts. Equally, in documentary-intensive financial crimes investigations, AI can now scan  millions of transactions and documentations in minutes. They can identify suspicious patterns  and possible evidence in such large volumes. ¹² For instance, the 2022 Medicare fraud  investigation in Florida was a landmark when AI analysis identified fraudulent billing patterns  across thousands of claims within days. The task had taken investigators months to complete if  it had been done manually.

Greater Effectiveness in Solving Cases

AI’s capacity to connect the dots across large volumes of data has led to breakthrough moments  in many investigations. A compelling example is the resolution of the cold case in California in  2021, where AI analysis of historical case files identified connections between seemingly  unrelated crimes spanning two decades, leading to the identification of a serial offender. It has  also proven to be very valuable in ballistics analysis. In Chicago, AI-powered ballistics  matching systems have helped police link multiple shooting incidents by analyzing microscopic  markings on bullet casings, leading to higher solve rates for gun-related crimes.¹³ The system  can compare new evidence against millions of records in minutes, finding matches that might  never have been discovered through traditional methods.

Merging Technologies in Digital Forensics

Blockchain technology is that one which was first popularized in securing cryptocurrencies. It  emerges as one of the key assets today in forensic investigations because criminal activities  related to illegal transactions, money laundering, and fraud often leave behind these digital  footprints in blockchain networks. Investigators use blockchain analysis tools such as  Chainalysis and Elliptic in tracking illicit transactions and tracing financial crimes back to the  source. For instance, in 2021, U.S. authorities recovered $2.3 million worth of

Bitcoin from aransomware attack on Colonial Pipeline using blockchain analysis, demonstrating the  effectiveness of this technology in cybercrime investigations. With the proliferation of smart devices, forensic experts now analyze data from IoT (Internet of Things) devices such as smart home assistants, security cameras, and wearable technology. These devices may eventually become the source of crucial evidence in criminal  investigations. There is an example from Florida, where in 2018, the data obtained from a victim’s Fitbit contradicted the alibi advanced by the suspect, who was convicted. The extraction of timestamps, location history, and voice recordings from IoT devices is an added facet to the tool of forensic science.¹⁴

Quantum computing is still in the very early stages of development but has potential to  transform forensic science. Quantum computers solve such complex encryption-decryption  algorithms much faster than traditional computers do. Cybercrime investigations therefore  become greatly valuable with quantum computers. Researchers proved in 2022 how quantum algorithms break the traditional encryption techniques by both security and opportunities for  law enforcement in digital forensics.

AI-based applications have made it easier for data recovery processes in forensic investigations.  Law enforcement agencies employ AI in retrieving lost, deleted, or encrypted data from digital  devices.¹⁵ For instance, Indian law enforcement managed to recover WhatsApp deleted messages and encrypted data of a high-profile case of financial fraud in the year 2021 by making use of AI-based forensic tools and eventually arresting a few involved people in the scheme. The possibilities these have open up mean investigators can obtain evidence that could  have otherwise remained forever hidden in cyberspace.

Challenges and Limitation in AI-Powered Forensic Analysis

Ethical and Legal Concerns

Forensic research involving AI technologies raises privacy concerns related to consent over  one’s personal information. After all, it’s difficult for legal statutes to remain abreast of AI  developments, making it uncertain whether AI-generated evidence will be admissible in court.¹⁶ AI systems could inherit biases through training data. Thus, decisions and outcomes based on  such biased data may appear unfair or even discriminatory. Continuous evaluation of the forensic AI tool will be in order to ensure unbiased decision-making. For example, the COMPAS recidivism algorithm proved racially biased for criminal behavior predictions.¹⁷

Technical Challenges

1. Data Quality and Standardization

AI models rely on high-quality datasets for accurate analysis. Inconsistent or incomplete data  can lead to misinterpretation, impacting investigations. Standardized data collection and  management protocols are essential to improve AI accuracy.

2. Cybersecurity and Adversarial Attacks

AI forensic systems are vulnerable to adversarial attacks, in which malicious actors manipulate  data to deceive the algorithm. Continuous updates and monitoring of algorithms are therefore  essential for ensuring robust cybersecurity measures in maintaining the integrity of forensic  investigations.¹⁸

3. Algorithm Reliability and Explainability

Complex AI models, especially deep learning algorithms, are usually not transparent. Forensic  experts may not be able to validate AI findings, which makes it challenging to communicate  results in court. Explainable AI (XAI) methodologies are aimed at addressing this problem by  providing more clarity in AI decision-making.

Barriers to Implementation

1) Cost and Resources and Resistance to Change and Training Needs

Developing and maintaining AI-based forensic tools are expensive. Forensic laboratories in  developing countries lack funding and are not well-equipped with specialized AI infrastructure  and training programs. Forensic traditionalists have an aversion to AI based on the loss of jobs  and the dependency of forensic experts on the automated system.¹⁹ This aspect is addressed  with full training curricula and in emphasizing AI as an adjunct and not a substitute for human  ability.

2) Linguistic and Regional Challenges

In countries such as India, linguistic and regional diversity pose particular challenges in the  field of digital forensics. AI tools must be capable of analyzing multilingual data with  efficiency. Natural language processing improvements have enhanced the ability of AI to  process regional dialects and languages, supporting forensic investigations.²⁰

Addressing Bias and Fairness in AI

Diversifying datasets will provide innumerable examples with which AI can train, reducing bias  and enhancing fairness. Also, Continuous model validation here seeks the regular performance  evaluation of the model to identify any potential bias arising in time.²¹ The use of fairness aware  algorithms is implemented to actively consider and reduce the opportunity for bias in any  decision-making process.

Psychological Effect on Investigators

Forensic investigators constantly have to examine and analyze crime scene photos, videos, and  materials that can disturb their psychological comfort.²² AI helps by filtering and bringing in  alerts on graphical content for reduction of direct exposure and improving the well-being of  investigators involved. For CSAMs, AI systems work by gaining access and sorting large  datasets, allowing faster investigations without exposing humans to the material.²³

Current Legislation Position

Indian Information Technology Act deals with cybercrimes and electronic evidence handling  but needs amendments to effectively put AI-based forensic analysis within the legal system.  Similarly, the Indian Evidence Act presently accepts digital evidence; it, too, needs an  amendment to accommodate AI-based forensic findings of the evidence to include that within  the purview of legal validity.²⁴ Again, cybercrime regulations with regards to India need to be  updated and established in order to deal with crimes concerning AI,such as deepfakes, AI driven  frauds, automated hacking frauds, among others. In the very same manner, the Personal Data  Protection Bill (PDPB) that targets protecting digital data must also include the necessary legal protection for AI forensic investigations in the proper use of these technologies.²⁵ India’s  cybersecurity agency, CERT-In, issues guidelines on digital forensics. These guidelines are to  be enlarged to include AI-driven forensic methodologies. Standard forensic lab procedures  would also need upgradation to involve AI-based analysis of evidence. India’s strategy for AI  also needs to address forensic applications as well, giving clear ethical and operational guidance  towards their use. It is also very important to innovate new protocols of investigation while  introducing AI tools into the process and ensuring that legal and ethical principles are observed,  making the use of AI applications in forensic science responsible.

Future Trends and Recommendations for AI in Digital Forensics

Inter-jurisdictional collaboration must be enhanced since cybercrime often involves more than  one country. The development of AI-based platforms that enable standardized sharing and  analysis of digital evidence across different legal systems and languages will be critical.²⁶ Translation tools can help bridge language barriers and automate the harmonization of legal  requirements for evidence admissibility. Governments need to provide for legislative updates  to govern the application of AI in forensic investigations while at the same time ensuring that  there are ethics in applications.²⁷ Continuous research in explainable AI, real-time forensic  analysis, and predictive forensics will shape the future landscape of forensic science. Ensuring  a close collaboration between technology developers, forensic experts, and legal authorities  ensures that something is effective and of good ethics.

Conclusion

The integration of AI into digital forensics is a prospect of much momentum, but requires  structured processes which emphasize continuous evaluation, responsible ethical  considerations, and collaboration with other stakeholders. Directed in these future directions  and recommendations, the field of digital forensics is capable of upscaling its capabilities in a  manner that maintains integrity and accountability. The integration of Artificial Intelligence into digital forensics marks a transformative shift in investigative methodologies that offer  unparalleled speed, accuracy, and efficiency in handling vast amounts of digital evidence. AI driven forensic tools are reshaping the criminal justice landscape, assisting investigators in  detecting complex patterns, automating evidence processing, and identifying cybercriminal  activities with greater precision. However, the same trend comes with significant legal, ethical,  and technical challenges that need to be addressed systematically in adopting AI in forensic  science. A structured and balanced approach is necessary while ensuring the effectiveness of  AI for digital forensics without jeopardizing due process and fundamental rights.

There must be ongoing evaluation of AI systems for accuracy, fairness, and bias to prevent  wrongful accusations or discriminatory practices. The development of Explainable AI (XAI)  will be crucial to sustain transparency so that forensic experts, legal professionals, and courts  can understand and validate evidence derived using AI. In addition, AI should be conceived as  an assistive tool and not a replacement for human expertise, in order for final investigative decisions to be maintained within the hands of the professional. From a regulatory point of  view, current laws such as India’s Information Technology Act need to be modified to take into  account AI-based forensic results. International AI forensic standards and cross-border  evidence-sharing frameworks will play an important role in dealing with international  cybercrimes effectively. Investment in AI driven forensic infrastructure, capacity-building  initiatives, and collaborative research will strengthen AI further in modern investigative  processes. Ultimately, any responsible integration of AI in digital forensics must align with  legal safeguards, ethical governance, and technological advancements. Fostered by the  innovation with accountability, AI-powered forensic science will boost justice delivery where  technological progress stands for the increasingly digital world on the grounds of the rule of  law, due process, and human rights.

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² Saxena S, ‘Artificial Intelligence and Criminal Justice System in India: A Critical Study’ (2023) 5(4) International Journal of Law, Policy and Social Review 156.

³ ‘The Role of AI in Forensics’(Marymount University, October 2024) https://marymount.edu/blog/the-role-ofai in-forensics/ accessed 21 January 2025. ⁴ Ibid.

⁴ Supra at 2.

⁵ The Transformative Role of Artificial Intelligence in Forensic Medicine’(2023) 37(3) Journal of Medical Science  and Oncology 123.

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⁷ Ibid.

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⁹ Tynan P, ‘The Integration and Implications of Artificial Intelligence in Forensic Science’ (2023) 20(3) Forensic  Science, Medicine, and Pathology 1106.

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¹¹ Ibid.

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¹⁴ Supra at 3.

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¹⁷ N Goel, ‘Artificial Intelligence in Indian Judiciary: Challenges and the Need for Ethical Oversight’(2023) ‘4(1)’  International Journal of Law and Technology 15

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19 ‘Barriers to AI Adoption in Cybersecurity and Digital Forensics’ (2023)

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