It is often said that when we get too used to the behaviour of artificial intelligence (AI), we stop calling it “artificial intelligence.” It has become an everyday thing, like Siri, using your fingerprint to unlock your phone or setting your car’s speed when travelling on the road. Artificial intelligence also helps people’s safety in various ways that go unnoticed.
All this is good because it indicates that AI is integrated into our lives as the internet, mobile phones and other technologies have already done. But it doesn’t hurt to review some aspects where AI is key to improving people’s safety.
AI makes it possible to recognize typical patterns of attacks on communication networks, such as “denial of service” attacks and unauthorized intrusions. On top of that, they can detect spam (junk mail) and everything that comes with it, especially threats like malicious software (malware) that tries to pass itself off as real messages.
Elements such as security cameras benefit from algorithms capable of recognizing people, animals or specific situations. A typical example would be detecting that an older adult has fallen to the ground or that a dog is walking in the garden and not a thief. This information makes alerts more efficient, false alarms reduced, and security improved.
Although experts are good at detecting strange behaviour in markets, bank accounts or credit cards, AI algorithms work 24 hours a day without rest. They can associate more factors: operations outside business hours, unusual locations, etc. Typical patterns of theft and fraud.
We use AI algorithms daily when unlocking mobile device access using facial or fingerprint recognition. These visual algorithms are trained and fine-tuned using AI techniques so that only the authorized person can use them.
Systems for businesses such as the Japanese Vaakeye or the British Third Eye can detect thefts in stores before they occur, analyzing the behaviour patterns and movements of those who buy in stores. A similar is used in some countries to analyze potential threats in the streets, public buildings or certain homes.
Visual object recognition technologies – such as the one seen in a Microsoft video from years ago – can be used to recognize dangerous products, obstacles or problems with structures and heavy machinery on construction sites, factories and warehouses, avoiding potential issues for those who work over there.
The list of driving assistance that uses AI algorithms is long: automatic braking, anti-collision systems, pedestrian and cyclist detection, and cruise control… What were previously purely mechanical aids are now controlled with more precision and criteria by much more advanced AI algorithms.
Until recently, the big robots and mechanical arms in factories were little more than mechanical brutes with basic safety measures. AI robots are equipped with cameras and proximity sensors to know when someone has entered their work area. They can stop with a mere gesture from the operators and sometimes even make that decision themselves if they detect an imminent danger.
Although still supervised by medical teams, AIs are already successfully used to diagnose certain diseases. Its ability to assimilate data and find patterns makes AI a valuable aid that provides speed and accuracy when analyzing large volumes of X-rays, scans, and medical images.
AI systems capable of analyzing texts and social media content are skilled at detecting certain typical patterns of stress, fatigue, and lack of attention… These are psychological factors in many cases, which fall within the so-called sentiment analysis. . The AI relentlessly searches all this data for psychological connotations on which it can act preventively.
Also Read: Experimentation to the Success of Artificial Intelligence
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