Artificial intelligence -- it’s in just about all the technology we use today. It’s in your phone, television, on your laptop, your tablet -- it can even be in your refrigerator! But as AI continues to advance and grow, people have started to question its capabilities in both positive and threatening lights. The hypothetical threat artificial intelligence (AI) imposes on today’s society should not be menacing and only creates new opportunities that push our society towards a positive, more efficient future. AI is making tasks simpler and also change how people interact with technology. Multiple studies have also been done, showing how AI will be able to help in medical fields like Radiology.
Artificial intelligence has made positive contributions to society today in several ways – more specifically in the medical field, as this paper will show. In the medical field, various companies and organizations have shown how AI can improve things. According to the Journal of Family Medicine and Primary Care (2019), the medical branch of Radiology has been eagerly integrating new technologies like AI into its study. Computers started out being used for simple jobs like storing files or getting images, but now they are “becoming an indispensable component of the work environment with the origin of picture archiving and communication system” (p.2329). Computers are starting to have the capability to carry out actual tasks, not just making documents paperless.
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Some companies are continuing to develop new beneficial technologies for radiology. For example, Meskó, Hetényi, and Győrffy (2018) stated that the “Medical Sieve project aims at building the next-generation “cognitive assistant” with analytical, reasoning capabilities and a range of clinical knowledge.” These assistants are going to be able to identify medical issues from the images they are given (Meskó et al. p. 2). AI has not just changed things in Radiology, but also in other areas of the medical field.
Various areas in the world of healthcare and medicine have been impacted by the advancements of AI. In an “Overview of artificial intelligence in medicine,” Amisha, Malik, Pathania, and Rathaur explain how DXplain is a decision support system that helps medical students gain knowledge in some areas that may not have been included in their textbooks. Created by the University of Massachusetts in 1986, the application gives “a list of probable differentials based on the symptom complex.” This program helps medical students close any open spaces in their education and will help them become better medical professionals (p. 2329).
How people are taken care of at hospitals and clinics is affected by AI. According to an article for CMAJ, Caroline O’Neill (2017) explains that AI can “reduce the number of interruptions a nurse endures during a shift, help with diagnosis, and handle mundane tasks such as scheduling and tracking the number of available beds, which they argued would give medical professionals more time with patients,” (p. 1). AI will help complete menial hospital tasks so that nurses can focus more time and energy on the patients themselves and more important tasks. Amisha et. al cites a 2016 study by Ann Intern Med discovered spent 27% of their office day with their patients and spent 49.2% of their office day on electronic hospital records and desk work. When in the examination room with patients, physicians spent 52.9% of their time” with electronic health records (EHRs) and other work. Documenting their work with the help of electronic devices give physicians more time to spend with their patient (p. 2330). AI has helped make time physicians use at work more effectively with patients, but there are still more ideas planned for the future with AI.
There have already been many positive contributions that AI has made in the medical field alone, and there is still more room for potential. Sometimes, there are not enough people that are willing or available to help care for senior citizens. For those cases, Amisha et al. (2019) detail how Stanford University is working on program AI-assisted care (PAC). This program has an intelligent senior wellbeing support system and smart ICUs. The program will be able to sense any behavioral changes in elderly people living on their own (p. 2329). AI continues to change how tasks are carried out, even outside of the field of medicine and health.
Our world is impacted by AI and a process called “deep learning” that computers use to imitate human thought. In a news article titled, “The Learning Machines,” Nicola Jones (2014) writes that deep learning is a machine learning method in which computers have to process large amounts of data to figure out problems that humans solve almost naturally. This method is not new—three decades old—and is capable of giving computers thinking capabilities ranging from remembering faces to understanding languages. The neural networks for deep learning were made for computers to imitate how human brains work through simulated neural connections. Computers artificially gain knowledge by processing large amounts of information (p. 146). Thinking is a task that comes quite naturally to humans, but computers have to go through massive amounts of data to do a small fraction of what humans are capable of.
Jones (2014) mentions an example of the usage of deep learning: the creation of the Google Brain. It was a network of 1,000 computers programmed to absorb all the knowledge in the world in the same way a toddler does. The “brain” was given 10 million images from YouTube and was able to find a pattern in all the images given…cats! The Google Brain was made of one million simulated neurons and one billion simulated connections making it 10 times larger than any attempt at a neural network before it (p. 146). It was quite impressive for a computer to be able to artificially make the neural connections that we make easily. It also showed the potential of thinking computers can do for us.
The process of giving computers AI with deep learning has proven itself useful to different areas of science. Jones (2014) points out that biologists and computer researchers use deep learning to map out and count the tangles on lines and neurons in three-dimensional images of brain slices. Before deep learning, researchers had to seek help from undergraduates at their respective colleges to trace the lines. The use of deep learning saved a lot of time that would have been spent mapping out the billions of connections that are in the brain (p. 148).
Another example of deep learning is facial recognition. Jones (2014) explains how neural networks use a series of layers to identify faces. The first two layers teach the computer to differentiate between light and dark pixels and identify simple shapes and edges. These two layers come first and lay a base for the next two layers. The third layer combines the first two layers, so the computer learns complex shapes and objects, made up of different edges and shapes, both light and dark. These complex shapes make up parts of the face, like an eyebrow or a nose. The final fourth layer teaches the computer to put all the face parts together in certain areas to make up a human face (p. 149). These processes are how programs like Apple’s Face ID work. Andrew Ng, director of the AI Lab at Stanford University is quoted by Jones (2014), saying that “Deep learning has the property that if you feed it more data, it gets better and better” (p. 148). As computers continue to process new pieces of information, they will continue to think a little bit closer to human thinking and open opportunities to make our society more efficient.
Artificial intelligence has progressed and improved in several ways. While AI poses a potential threat, but new, positive opportunities that are created are impacting the world and making it more efficient. Many studies in the medical field have shown how AI makes long, complex jobs shorter and gives health professionals more time to spend on important jobs. Tasks have become simpler because of AI. Artificial intelligence will only become more and more prominent as time progresses, so we should be embracing it, not being afraid of it.
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