Artificial Intelligence can do wonders if used in the right situation. We’ll review some of its best ways of application.
Don’t fear AI
Artificial Intelligence (AI) is often feared. And sometimes for a good reason: computer science has even come up with spoofing detection to tackles deepfakes and biometric attacks that can serious sabotage informational security.
But AI doesn’t have to be that way. Actually, there’s a myriad of ways to make it serve the right cause.
1. Saving bees
Since at least 1988, the bee population has been declining in America, possibly due to the varroa mite. The ominous trend can be observed globally too. The World Bee Project is dedicated to solving this problem.
It employs AI and cloud storage to analyze huge chunks of bee-related data in real time to help the buzzy workaholics survive and restore population numbers. Another project Arugga AI Farming uses robots equipped with cameras and object-recognizing deep learning to artificially pollinate flowers from nozzles attached to a mast.
2. Saving children
As reported, 2,300 children go missing each day in the US alone. While reasons may differ, one of the most viable threats are abductions for sexual exploitation. But facial recognition algorithms can help the police track the little victims and reunite them with families.
One of the proposed solutions detects 80 identification points of a human face and then compares it against vast chunks of data it can find online. Especially websites where photos of rescued/sheltered children are posted. It’s avidly used in India and helps bring thousands of lost kids back to their families.
Such a technology can also work with the street surveillance in unison to momentarily recognize a missing face and warn the authorities.
3. Helping people overcome their disabilities
Huawei introduced two apps — StorySign and FacingEmotions — to help people with auditory and sight limitations. StorySign helps deaf kids learn how to read by interpreting the alphabet into hand signs, so they can learn to read.
FacingEmotions uses a facial recognition algorithm, trained with a respective dataset, that can detect facial expressions that convey emotions and translate them to sound. Project Euphoria by Google helps people with atypical speech communicate with voice assistants and other people thanks to improved recognition models.
4. Averting hunger
Just like Biblical Joseph, AI can interpret input data to predict bad or good harvest. It takes into consideration a set of variables — climatic conditions, seeds and fertilizers used, agricultural work patterns and schedules — to calculate the best methods to raise the best harvest. These tools employ big data and deep learning with the brightest example being Nutrition Early Warning System (NEWS).
5. Cutting the lines
In retail deep learning works miracles too. Such a sophisticated system — that employs a constellation of cameras, object recognition, and pattern analysis — is capable of predicting queues 10 seconds before they appear.
It takes into consideration how many customers are present at the store, how much stuff they have in their carts, how fast they move and how many of them seem to be moving to the checkout. If the queues seem to be piling up, the system will alarm the staff to open more checkouts and reduce tedious waiting.
6. Checking medical data
Medical image assessment is one of the most prioritized branches of deep learning. It helps to examine hundreds of images and allow the over-taxed specialists to focus on anomalies, pathologies, and emergencies.
One of the best-known examples is AI-Pathway Companion, which takes care of routine image-assessment by aggregating and correlating data retrieved.
7. Reducing truancy
Poor discipline can undermine both commercial enterprises and government-run services. To curb truancy, it is proposed to use facial recognition that can also look beyond facial occlusions that insubordinate workers may use to disguise: sanitary masks, scarfs, shades, etc. Eventually, the system will help identify the staff’s ‘weakest links’ each week, month, or quarter.
Artificial intelligence isn’t an answer to all problems. But thanks to its ability to shovel grandiose piles of data and track patterns, we can find effective solutions quicker.