The Future Of Work: New Developments in AI Changing Society

New Developments in AI Changing Society

Computers have been making our life easier for many years now. They can solve many problems faster and more efficiently than humans. But they had some limitations and only did what we programmed them to do. However, as always, humans came up with a solution to the problem: we’ve created computers that can learn the way we do. 

That’s what Artificial Intelligence (AI) is—the effort of humans to create machines that emulate human intelligence. The learning process of a human mind is complex. Toddlers learn what a dog is because their parents tell them “this is a dog” every time they see one. Eventually, they see a new dog and know what it is. 

Until now, we haven’t been entirely successful, but we have made some progress. Machines can now be trained with a model of data to give accurate predictions on new information that they haven’t seen before. And like a toddler, they are fed a bunch of pictures of a dog until they learn to recognize one on their own. 

AI is gaining traction. Every year we see new developments that come with a whole new world of possibilities. These are some recent AI developments changing our society. 

Medical Imaging

Medical imaging is the process of creating images of body parts, tissue and organs using different technologies. Doctors use it to see what is happening inside the body so that they can detect and monitor diseases and other health issues. AI enters the picture to potentiate this established technology and improve its results.

The medical sector uses big databases to store patient information. This data—in this case, images—can be used to train AI models. AI algorithms are then able to analyze new medical images in seconds and complement the diagnosis given by healthcare professionals.   

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AI-powered medical imaging can change medical diagnoses and treatments significantly. Doctors, although highly-prepared professionals, are limited by their experience in the field or how much their memory can retain. They can make mistakes and overlook the signs of an illness.

On the other hand, a computer learns with millions of images and then compares in seconds the new image with what they already know. The room for error is a lot smaller, which is why this new technology is an excellent aid to medical practitioners.

Human-Robot Collaboration

Human-robot collaboration is stepping out of science fiction movies and into reality. And AI is a significant component in the development of robots. With more and more discoveries in the field of AI, robots are becoming more human-like. Technology is still far from creating a robot that thinks and behaves exactly like a human, but the achievements are impressive nonetheless.

Today, robots are mainly used in the manufacturing industry. They replace humans in tasks that require heavy physical labour—such as moving equipment and products—or a lot of precision. They have some autonomy, but humans still control them. For example, in the Tesla Motors factory, they have smart robotic forklifts that turn themselves off when they run out of power and are back to work when they are charged. 

But other robots have been developed for entertainment, remote operations and home cleaning, among other uses. Most of them, however, are prototypes with a lot of room for improvement.  

Inclusive Education 

The new developments in AI have enabled data scientists and engineers to create software for voice and speech recognition. This technology has many applications that go farther than the smart assistants on our phones. Speech recognition is a game-changer for people that are disabled or have other special needs.

The technology consists of detecting spoken words and transforming them into text. Later, the smart device analyzes the text and takes appropriate action. It is trained using AI algorithms to recognize each word it hears. This is still a developing technology, and the commercial products don’t necessarily understand words from people with speech disabilities. 

The point is that speech recognition makes education tools more inclusive. For example, kids with dyslexia or hearing impairment can use this tech to make their experience in the classroom more equal to their classmates. This way, kids with disabilities do not feel left out and can keep up with the rest of the class. 

Genetic Evaluation

Genetic evaluation is the process of analyzing the genome to determine hereditary factors in the DNA. It can be done to detect diseases like cancer and inherited disorders. Another application that has become popular in the last few years is to discover your ancestry. The AI algorithm can analyze all the information and detect the patterns that human eyes can’t see. 

Thanks to this development, AI-powered genetic evaluation can detect the exact genetic compositions that are likely to produce cancer or Alzheimer’s disease. Today, this knowledge is mostly for patients to take preventions. But it has the possibility of genetic modification, where parents have genetic evaluations, and then the doctors can create genetically modified babies without the genes that cause diseases. 

Many companies are also working with AI technologies to create drugs that are specific to the patients’ genome or to find perfect subjects, according to their DNA, when a new drug is ready to be tested. Overall, the applications of AI in genetics have barely touched the surface. 

Artificial Emotional Intelligence

Because AI was born in an effort to replicate human intelligence, many scientists and engineers believe that the key to making this possible is to emulate human feelings. Then, Artificial Emotional Intelligence or Emotional AI is a subset of AI that tries to create machines that can respond to human emotions.

This technology allows algorithms and machines to feel more real and make humans more comfortable when interacting with them. Emotional AI can also recognize emotions from interactions with customers, and this knowledge can be used later for marketing campaigns and customer service. 

For example, imagine a virtual professional that can tell if a student is getting distracted. They will change their teaching method to regain the student’s attention. This tech is being developed now and will be in the market soon.

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