Tuesday, March 5, 2024
-1.2 C
Vancouver
Tuesday, March 5, 2024
HomeArtificial IntelligenceArtificial Intelligence In Forensic Science

Artificial Intelligence In Forensic Science

Artificial intelligence has had a huge impact on all aspects of life, from our communication to our way of working. It is no surprise then that artificial intelligence is becoming a popular tool to find evidence in forensic science and criminal investigations.

Additionally, according to Gartner, firms using AI may anticipate a 25% increase in customer satisfaction by 2023.

Artificial Intelligence has already proven its worth in applying analytical data and providing mathematically-driven solutions. Additionally, the development of AI involves more transparency to improve the quality of data in criminal investigations. The future looks bright for this technology!

What Is Artificial Intelligence In Forensic Science

Source: www.depositphotos.com

A very basic and simple definition of Artificial Intelligence for Forensic Science is allowing computers to analyze data, patterns, images and provide possible outcomes.

AI can be applied to all facets of forensic science from crime scene analysis to predicting the location of the next crime. The process involves teaching a computer how to learn like humans.

It involves teaching computers how to think and process data in a way that parallels human thinking while eliminating bias and errors we humans make during our decision-making processes. AI helps forensic scientists not only in analyzing data but also in providing a possible outcome based on that inputted data or information.

Research shows that just 12% of shooting incidents are reported to the police.

Thus, AI not only automates tedious tasks which would consume considerable time otherwise but also provides better solutions to complex problems.

Benefits Of Artificial Intelligence In Forensic Science

A forensic investigation is a type of data mining that uses machine learning and data analysis to examine data for clues that may be used in a legal case. Statistical analysis is often used in forensic investigations to help find patterns in the data that can be used to identify suspects or understand how a crime was committed.

Forensic investigators may use statistical evidence to help them solve crimes. This type of evidence can be found in existing data, such as crime statistics. Forensic experts can also use digital forensics to help them collect and analyze evidence.

1. Automation Of Tedious Tasks

One of the easiest ways to improve the quality of forensic science is to automate tedious tasks. For example, instead of trying different equipment and chemicals to analyze blood samples, there exists a software that conducts an automated analysis on the sample in seconds.

AI helps forensic scientists in automating the most time-consuming aspects at much lower cost. This results in faster analysis which can provide better results and be able to focus more on other aspects of the case (like forensics investigation or linking proofs).

2. Better Consistency & Accuracy As Results Are Produced Faster And By Machines

In many instances, we humans make mistakes when we’re making decisions or analyzing evidence. This results in an inaccurate analysis. With AI, a consistent and accurate analysis can be provided, not by humans but by computers.

Thus, no bias is possible because the computer is completely unbiased. This results in extremely accurate outcomes and consistency of findings which ensure more confidence for the process.

3. Improved Standardization Of Methodologies And Techniques

Source: www.depositphotos.com

According to Forbes, 20% of businesses report major budget increases and 50% of businesses aim to boost their spending on AI and machine learning in 2021. With AI in place, forensic scientists are able to document and classify their techniques, methods and processes to improve consistency and accuracy of results or findings while at it improving the quality of data they collect through the process. This helps them to provide better solutions resulting in better forensics investigations as well as improved legal prosecution cases as well.

4. Improved Efficiency & Accuracy

We all know how tedious it is to go over a lot of information or data, manually analysing and interpreting the results. We humans are prone to make mistakes and can often miss a piece of information here and there.

With AI, computers can access every piece of information available, provided by the investigation’s hypothesis or premise. Artificial Intelligence then follows this process to arrive at an accurate analysis in almost no time! Thus, we gain efficiency of analysis with accuracy in data collected by applying machines to our work.

5. More Accurate Imagery Analysis Of Evidence

Recent developments in Artificial Intelligence will allow Forensic scientists to automate a lot of the processes that involve imaging techniques. This leads to better and more precise results on questionable cases where there have been doubts or concerns if the findings are genuine or not.

For example, AI can be used to perform an automated analysis of the images such as using a computer vision algorithm to automatically classify certain objects in an image as red cars in a certain shot; it can classify the number and make up of humans in an image including letters, numbers etc… This promotes a higher accuracy in reporting but also provides better coordination between investigators as well.

6. Easier Image Comparison & Analysis

Using AI, it becomes easier for forensic scientists to compare and analyse multiple images without the need of an expert view or that of an investigator. For example, a crime scene investigator could upload relevant images from forensic evidence and compare them with other images such as photos of suspects for identification.

The results are received usually within a few minutes which is much quicker than having to wait for the analyst to do it manually. This enables the investigators to arrive at more accurate results in lesser time!

Competent investigators can spend more time on investigations and provide better quality solutions as well. This also helps in reducing cases of human error too because the computers are completely unbiased and make no human errors while doing their job!

7. Improved And Efficient Communication

AI is a great technology for forensics which helps in improving communications and coordination between investigators. For example, AI can help analysts in providing an all-in-one solution by integrating the output with other evidence such as documents or pictures.

Thus, there’s no need to manually conduct this process! Human investigators also have better access to data collected as they no longer have to visit several different departments in order to retrieve information that has been recorded.

8. Improved Efficiency

For fewer than 50 years, artificial intelligence has been in use. AI is not only for improving workflow and analysis of forensic evidence. It can also be used to provide better automation to other aspects of forensics such as building DNA profiles from biological material. This results in significant time savings, a more accurate and consistent analysis, reduced human error and lesser need for human investigators!

Risks Of Artificial Intelligence In Forensic Science

Source: www.depositphotos.com

Existing criminal records can provide valuable information for forensic investigators trying to detect patterns. By gaining access to system databases, investigators can use pattern recognition to identify potential suspects.

The legal community has long relied on logical conclusions to solve cases. However, with the advent of more sophisticated probabilistic methods, the forensic field is beginning to change. These new methods are based on normal computational methods, but they are much more accurate.

1. Limitation Of Automation

It does not mean that you can completely hand over everything to the computer and expect it to do perfectly. Even though AI has a great capacity for automation, there are limitations.

For example, when it comes to analysing an image or fingerprint, it is best left to humans as they have a better understanding of the context of the source material. The AI may produce a result but it can be hard to understand why a certain segment has been marked out as important or why it has been given more weightage than another.

2. Automated Decisions May Cause Mistakes In Results Or Investigations

One of the major issues with AI is the decision-making part or automating processes which involves interpretation. As mentioned before, the capacity of AI is only limited and a human expert input may be required during the process to improve reliability and accuracy.

3. The Ability Of AI To Predict Patterns Is Limited If Not Aided By Human Input

In many instances, it is true that computers can better pattern recognition than humans because they use algorithms which aid them in analysing data more carefully and with more efficiency. However, this process relies on the data which has been provided as input by humans. If this data is inaccurate or modified in some way, then there’s a chance that results may not be produced as expected either.

4. The Ability To Solve Crime May Be Limited In Certain Cases

This involves the case where AI can solve a crime but there are several factors involved which have not been properly accounted for by the computer model. For example, if an algorithm is unable to determine what type of weapon was used in the crime, this will affect its accuracy significantly and result in a different view on who it suspects of committing the crime.

This is due to an inability to account for other variables such as the distance between victims and perpetrators as well as their physical state. These are all factors that humans understand better than computers do so AI may find it difficult if not impossible to accurately predict them!

5. The Use Of AI In Forensic Science May Lead To Bias In Results

AI software sales are expected to climb by 21.3% from 2021 to $62 billion in total in 2022, according to Gartner. AI is not biased (as such) if there is enough diversity in the training data that it is provided with.

However, there may be the possibility of bias if this has not been accounted for. For example, there are several instances where algorithms have been trained with biased data which results in an image of a white man being used when searching for missing persons which may result in human biases.

Even though AI and machine learning models are changing this, there are chances that some errors still happen due to this so it is best to train models with a spectrum of diverse exposure to ensure more fairness!

6. The Future Of AI In Forensics Is Still Uncertain

As technology advances, various other changes are also happening which may affect the way forensic science will be done in the future. For example, there is an increasing trend of decentralization, off-chain processing and cloud computing which may make it difficult for investigators to recover data or evidence from within these systems!

This may mean that certain forms of evidence can’t be trusted as they can be destroyed or altered without it being noticed. Thus, if AI robots have been programmed with previous data and not updated with new information, then they may not be able to function accurately.

This is called “the Turing test” and it refers to the ability of AI to impersonate a human in a conversation. The future of AI within forensics may not be as secure as it used to be in the past!

7. The Reliability Of AI Algorithms Will Depend On More Factors Than Just Data

Even though AI is better at complex tasks with more variables involved, it may not always provide the most accurate results because other aspects like formatting, security and privacy may have a significant impact on its reliability.

For example, if data is being analysed by an algorithm which has been previously damaged, then results can be unreliable or damaged. This may not be detected accurately by the system itself and can lead to false or biased results.

8. Even If AI Is Used, It May Not Be Able To Completely Replace Human Investigators Completely

The predicted yearly growth rate for AI between 2020 and 2027 is 33.2%, according to Semrush. The main reason for this is that humans are still required to interpret results and verify any data retrieved by machines. Thus, in summary, humans will still have a lot of input in the process of solving crimes even if AI is used!

Final Note

Many people are still sceptical about AI as it does not have a good influence on the future of forensics. While many critics believe that AI makes it easier to detect patterns and mistakes, there are others who believe that it may leave the field of forensics like how technology affected photography.

The truth is, both positive and negative effects can be derived from AI so the future of AI in forensics will depend on what technologies and applications are being developed to optimise the system itself!

Author

latest articles

explore more