Content monitoring through AI technologies, smart cameras for facial identification, DNA profiling algorithms are some of the techniques witnessing a surge throughout the world. Technologies provide us with reliable and trustable data to bank upon, but the questions arising on its accuracy can be a debatable issue. Let’s have a look at a recent case to understand the apprehension.
Recently, in two separate judgements — a judge from the Appellate Division of the Superior Court of New Jersey and a federal judge in Pennsylvania in the United States have ordered the prosecutor to hand over the source code of TrueAllele by Cybergenetics. The software program ran different DNA data available on a gun through complex statistical algorithms to compare the probability of a specific person’s DNA being present.
The program declared that the probability of having the culprit’s DNA on the gun is too high when compared with other people involved. The defence team raised that the software is not even scrutinised; however, the evidence provided by TrueAllele has been accepted by at least 14 states of the US over the last two decades. Thus, it can easily be stated that technology is here to stay, and it can not be done away with. However, it can be updated for more precise decision-making and greater accountability.
Let’s have a look at some of the latest technologies out there that security agencies can rely on to curb crime.
Best Techs for Law Enforcement Agencies
Combining big data, machine learning, and IoTs, this web-based portal management system does a predictive analysis of different areas to observe patterns across the state and marks crime hotspots on a priority basis. Besides, data is analysed to provide deployment planning and crime-specific tactical responses. It maps out a list of offenders recently out on bail for a more informed course of actions to be taken by the field officers.
Taking the help of sensors and AI algorithms, ShotSpotter can identify single, multiple gunshots at a time. With the use of highly specialised software sensors and the time taken to receive the signal, the software can mark the exact location of the gunshot fired and alerts the agencies in 60 seconds. Also, machine learning algorithms are used to identify whether the sound recorded was actually of a gunshot through pattern matching. It thereby supports law enforcement agencies with accurate and reliable court-admissible evidence.
Stands for Automated Virtual Agent for Truth Assessments in Real-Time, AVATAR is a technology employed to recognise faces and detect deceptions, mostly at sensitive public places, including airports. The software operates as an interactive electronic interviewer, and the attached sensors and cameras track the person’s facial expressions to check for signs in their speech, body, and eyes. This information is then analysed by an algorithm that looks for signs to ensure if the individual is telling the truth. It is yet another AI technology that can learn from its feedback.
It scans and analyses millions of real-time data generated over social media platforms and conversations to look out for criminal activities such as financial crimes, drug-trafficking, cyber-attacks and terrorist activities. The platform analyses texts, including semantics, and searches for specific words in the large cloud data-set. Most talked about topics, generated trends, and public-influencing topics are scrutinised to provide a clear picture. Alongside data mapping and geo-locating are some of the added features.
MXSERVER is an AI technology that uses machine learning techniques and facial recognition to provide video and photographic media analysis solutions to security agencies. It allows users to upload massive amounts of video surveillance and image evidence in batches to the MXSERVER framework, which identifies faces and indexes the material for facial recognition technology to work. It will also look out for other data present on its database to identify the suspects and inform the securities concerned with immediate effect.