Together with the rise of the Internet, access to large repositories of data has helped machine learning technology grow exponentially. The incredibly quick pace of growth was unprecedented. As a result, it is obvious that AI will make a significant impact on the world in the years to come. However, with the numerous established and emerging fields of AI around today, such a blanket statement doesn’t provide much concrete meaning.
What fields and applications of AI are receiving the most investment and development? This article will introduce five areas of machine learning that are currently receiving a lot of attention and how they are already changing the world as we know it.
1. Medical Image Diagnostics
Some of the most exciting applications of AI are those in the medical field. One amazing application is the use of computer vision models to diagnose diseases based on images.
How Can Medical Image Diagnostics Change the World?
There is likely no bigger and no better impact than saving lives. Utilizing AI in the modern health care framework has the potential to save many lives by reducing the number of misdiagnoses and false negatives.
Furthermore, AI technology can help us bring specialized health care to more remote or less-developed areas of the world. In countries such as Nigeria, where there are only 60 radiologists per 190 million people, AI-powered medical image diagnostics could help people get the care they need.
Moreover, AI-based medical image diagnostics could prove to be more accurate than conventional screening methods. According to cancer.org, 1 in 5 cases of breast cancer go undiagnosed in traditional mammogram screening. On the other hand, in October of 2018 Google’s LYNA reportedly achieved 99% accuracy in metastatic cancer detection.
2. Autonomous Vehicles
Transportation is another sector of social infrastructure that AI is changing. With more and more Fortune 500 companies competing in the autonomous vehicle market, it is no longer a question of if we will have self-driving cars, but when.
How Can Autonomous Vehicles Change the World?
Aside from changing the way we drive, self-driving cars could also make a strong impact on the job market of the transportation industry. The main resistance to ridesharing services like Uber was their impact on the livelihoods of taxi drivers. If autonomous vehicles become commonplace, they could pose the same threat tenfold, possibly removing the need for ridesharing services altogether.
Image via cnbc.com
On the other hand, they have the potential to increase carpooling. Subsequently, this could both reduce pollution due to vehicle emissions and reduce congestion in major cities.
3. Facial Recognition
Facial recognition is an area of AI research, the goal of which is to enable machines to verify and distinguish between human faces. This technology is already being used today.
Many people have already experienced face recognition technology in their smartphone devices as a security method. Instead of using a fingerprint or passcode, many smartphones have the ability to allow access by using the front-facing camera to scan your face.
How Can Facial Recognition Change the World?
Face recognition is revolutionizing the global technology, retail, and security industries. In some parts of China, it is already being used as a method of payment. Furthermore, just last month, SnapPay launched their own face recognition payment solutions in North America.
Image via snappay.ca
For security and law enforcement, fingerprints have long been a primary method of identifying persons of interest. However, face recognition is now being adopted by law enforcement in some counties as a way to search for certain individuals in real time.
4. Automatic Speech Recognition
Automatic speech recognition (ASR) is the main force behind everyday smart home devices and voice assistants like Amazon Alexa, Siri, and Google Home. It is the ability for a machine to recognize spoken language, understand what was said, and use that information to respond accordingly.
How Can ASR Change the World?
Aside from all of the convenience that virtual assistants bring, ASR technology has a strong potential to help the speech-impaired. An ASR system in development by Google, known as Parrotron, has the ability to adjust to unique forms of atypical speech. After calibrating on someone’s unique speech patterns, it can then convert that atypical speech into clear, fluid speech.
Effectively, Google’s Parrotron could allow those with speech impediments to better communicate with other humans. Meanwhile, it could also make virtual assistants and smart home devices more accessible to those with atypical speech patterns as well.
5. Machine Translation
Through natural language processing, companies have now been able to reach incredible machine translation accuracy in dozens of language pairs.
How Can Machine Translation Change the World?
Before the incredible rise in accuracy of applications like Google Translate, traveling to foreign countries came with a lot more stress. Every interaction, from ordering food to directing a cab driver, was incredibly difficult. Now, thanks to machine translation technology, you can simply take a picture of a menu in a foreign language and have it translated in a matter of seconds.
Devices like Pocketalk even allow you to simply press a button, speak, and have your words vocalized in the target language of your choice. Furthermore, machine translation provides more accessibility to nearly every website in the world. Simply, it is making the world smaller, and helps give us access to information we never would have been able to understand without it.
Development of machine learning technology is vastly changing our modern society. Recent advances in technology such as deepfakes, synthetic media, and generative models have posed threats to job security and identity fraud. However, with any emerging technology, there are going to be pros and cons. Whether the changes incited by AI technology are good or bad is dependent on the policies put in place to regulate them, as well as the responsibility of the users themselves.
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