As a specialized branch of forensics, digital forensics focuses heavily on extracting electronic data that can be used as evidence in an investigation. During a time when artificial intelligence (AI) is transforming everyday technology, it’s not surprising that this incredibly intuitive technology is expected to redefine the field of digital forensics.
AI and Digital Forensics: A Powerful Partnership
Digital forensics is defined by Interpol as a specialized branch of forensic science that focuses on electronic data. Digital forensic scientists are charged with extracting, identifying, storing, analyzing and reporting digital data that may be relevant to an investigation, and the explosion of digital data in recent years has made it more challenging to complete these investigations. Many forensic experts believe that AI in digital forensics could redefine the industry, ultimately enhancing the efficiency and effectiveness of digital forensic investigations.
Automating Evidence Analysis
When completed manually by humans, evidence analysis can be difficult and time-consuming, and it also can be prone to human error. AI technology has the capability of automating analysis by gathering and interpreting large volumes of digital data, which can include emails, images, videos and more, giving investigators the opportunity to focus their efforts on the critical and creative thinking required during the analysis phase.
According to the Journal of Medical Society, AI algorithms are capable of identifying patterns and anomalies that human analysts may not recognize or identify, making AI a powerful tool in digital forensic investigations.
Enhancing Image and Video Analysis
In the digital era, there is ample video evidence. From security camera footage to smartphone video captures, there is often some type of video evidence to collect and analyze in an investigation. Prior to the advent of AI technology, investigators had to work with the quality of the evidence they received, often trying to interpret grainy or low-resolution video footage. However, AI technology can help enhance image and video clarity, and AI also allows investigators to utilize facial recognition technology and object detection. By utilizing AI to enhance image and video analysis, investigators can improve the precision and outcomes of their investigations.
Cybercrime Investigations
The applications of AI can be particularly beneficial during cybercrime investigations, which are increasing in their frequency and complexity. AI technology can help investigators quickly become aware of common cybercrimes, such as hacking, malware attacks and online fraud, because it is able to analyze network traffic and identify suspicious patterns that allow investigators to monitor and track cybercriminals.
AI in Traditional Forensic Disciplines
While digital forensic science is still growing and evolving, forensic science is a field that has long played a critical role in society. Some of the primary forensic science disciplines include DNA analysis, fingerprint analysis and forensic pathology, with forensic scientists working in a variety of settings, including criminal justice departments, medical examiner’s offices, private practices and research-based universities.
Even within these traditional fields, AI is proving to be a powerful partner. AI technology is revolutionizing the process of collecting and analyzing evidence, giving forensic scientists both the time and ability to better interpret the data that they have.
DNA Analysis
Forensic DNA testing has revolutionized the criminal justice field in recent decades. The ability to collect and analyze DNA evidence has allowed law enforcement officials and criminal justice experts to improve the results of their investigations, and in some cases, they have been able to overturn wrongful convictions.
The National Institute of Justice notes that AI can significantly accelerate DNA analysis, thanks to its ability to automate processes, predict DNA profiles and assist in complex kinship analysis. Many forensic scientists are finding a hybrid approach, which involves human investigators as well as machine learning processes, allowing them to improve the analysis of DNA samples and enhance the results of their investigations.
Fingerprint Analysis
Fingerprint analysis has long been a traditional technique in digital forensics, but like other traditional techniques, human investigators were limited by their own ability to interpret and analyze results. Often, human fingerprint analysis has led to mistakes and errors that compromise the integrity of the investigation.
That said, AI technology can help improve the accuracy and speed of fingerprint analysis in a variety of ways, such as automating fingerprint matching, enhancing latent prints and identifying unique features. AI technology can help reduce the risk of human error, while simultaneously speeding up the investigation process.
Forensic Pathology
Forensic pathology is a specialized field within pathology, in which investigators focus on collecting and analyzing medical evidence from non-natural deaths. Forensic pathologists are responsible for performing autopsies in a strategic way to identify the cause of death or estimate when the death occurred. AI technology can expedite the process of analyzing the autopsy results, ultimately improving the accuracy of the results and aiding in the investigation into the death.
The Impact of AI on Forensic and Legal Psychology
The fields of forensic and legal psychology are often used to better understand criminal behavior. Criminal profiling requires investigators to be experts in forensic and legal psychology, so that they can understand the nuanced behavior of criminals and the causes that may have triggered that criminal behavior.
Similar to digital forensics, AI technology is becoming a valuable partner in both of these fields, which rely heavily on data collection, interpretation and analysis to come to conclusions about a criminal’s profile. Within these fields, investigators can use machine learning algorithms to analyze vast amounts of data. This ultimately uncovers previously unseen patterns that may offer additional insight into the behavior or actions of the individual.
Risk Assessment and Prediction
Legal and forensic psychologists are often charged with evaluating the behavior of a criminal and their personal circumstances to determine if they are at risk of returning to previous criminal behavior after they have served their sentence. There is potential for AI technology to help predict future criminal behavior, and some legal experts are beginning to see how AI can be used to help inform sentencing and parole decisions.
AI can assist the jobs of parole officers through the use of wearable technology, allowing parole officers to focus less on monitoring and more on determining the risk of recidivism. While AI may help increase the precision of risk assessment, there are still ethical concerns and potential biases to be aware of. This makes it crucial for legal and forensic psychologists to consider both the risks and benefits before adopting this new technology.
Deception Detection
Forensic psychologists are often involved in interrogations and criminal interviews, because they are aware of minor behaviors that criminals may display when they are answering questions. While legal and forensic psychologists can be particularly intuitive, AI technology can help improve the precision of deception detection, because it can be used to analyze both verbal and nonverbal cues during interviews.
It’s important to recognize that there are limitations to this technology, and as always, there are ethical implications to consider when relying heavily on AI for lie detection. Likewise, it’s vital to acknowledge the potential bias that can exist within this technology, highlighting the need for human cultural awareness and responsiveness during interviews and interrogations.
Criminal Profiling
Criminal profilers are investigators who analyze crime scene data as well as criminal behavior to develop precise criminal profiles. These profiles can aid investigations as well as help officers narrow down suspect pools. Similar to other areas of forensic science and legal psychology, AI technology and machine learning algorithms can speed up the investigative process, but there are concerns that exist about racial profiling as well as the limitations of criminal profiling. Given the fact that criminal behavior is incredibly complex and can be influenced by a wide range of factors, it’s important for legal and forensic psychologists to utilize AI results within the full context of the investigation.
Ethical and Legal Considerations of AI in Forensics
Artificial intelligence is the new technology that everyone is talking about. It’s redefining nearly every industry around the world, and it can be exciting for those who see its potential. However, there are ethical and legal considerations to consider, particularly when it comes to AI and digital forensics. At this time, most forensics experts are only just beginning to understand the full power of AI technology and machine learning, and it’s essential that all forensic scientists using this technology are transparent about it. Maintaining accountability and fairness is necessary, particularly because there is the risk of bias within the algorithms.
Transparency and Explainability of AI Algorithms
AI algorithms are incredibly complex, and most people who utilize everyday technology do not have a comprehensive understanding of the implications of machine learning. Digital forensic scientists relying on AI technology must be able to explain how the algorithms they are using have been developed, and subsequently, how they are being utilized within the context of their forensic investigations. Given the fact that many of these results are going to be shared as evidence within a courtroom, it’s essential that forensic experts can explain the results of AI analysis in a way that can be understood both by lawyers and members of the public who are serving on a jury.
Bias and Fairness in AI Systems
AI algorithms are based on human-created patterns, which means that bias can exist within these algorithms, just as they do within human nature. Acknowledging the fact that AI bias can exist, particularly in areas such as facial recognition, risk assessment and criminal profiling, is essential. AI bias can be found within the training data that the algorithm uses, the algorithm itself or within the predictive analysis produced by the algorithm. Digital forensic scientists must work to develop and implement AI systems that are fair and unbiased to protect the integrity of their investigations and ensure that results are accurate.
Data Privacy and Security
Within a digital forensic investigation, protecting data privacy and enhancing security measures is critical. Given the fact that mass amounts of digital data are extracted and analyzed within a digital investigation, it’s important to have strong data protection measures and ethical guidelines in place.
AI and Digital Forensics: Prepare For the Next Chapter at Marymount University
Artificial intelligence will continue to redefine and reshape the future, particularly in the field of forensics. At Marymount University, we offer a master’s in Forensic and Legal Psychology program that allows students to develop a solid foundation in forensics, preparing graduates to adapt to the changes that AI may bring into the field.
Request more information about our degree programs today.
Sources
https://www.interpol.int/en/How-we-work/Innovation/Digital-forensics
https://oxygenforensics.com/en/resources/digital-investigations-with-ai/
https://aceds.org/digital-forensics-the-good-the-bad-and-the-ai-generated-aceds-blog/
https://www.justice.gov/archives/dag/forensic-science
https://nij.ojp.gov/topics/articles/using-artificial-intelligence-address-criminal-justice-needs
https://www.cap.org/member-resources/articles/what-you-need-to-know-about-forensic-pathology
https://www.techopedia.com/ai-and-forensic-psychology
https://www.indeed.com/hire/c/info/what-is-a-profiler
https://www.ibm.com/blog/shedding-light-on-ai-bias-with-real-world-examples/
