Should Artificial Intelligence be Considered a Potential Threat to Humanity?

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Should Artificial Intelligence be Considered a Potential Threat to Humanity?

From washing machines to Siri, we live surrounded by technology, Artificial Intelligence (AI) is no longer science fiction. According to Techopedia, AI is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Not every technology is artificial intelligence but every artificial intelligence is technology. Although this seems as a breathtaking idea for developing futuristic technologies it can eventually backlash against humanity, which is understood by the Merriam-Webster dictionary, as the the totality of human beings. The idea of potential threat could be understood as the human decision of using it to our favour or against us, especially in issues such as science, technology or even economy.

Everyday technology is updated, it grows faster than any one can imagine as it counts with an exponential rate of improvement, just as Ray Kurzweil states in an essay wrote by him on 2001: An analysis of the history of technology shows that technological change is exponential, contrary to the common-sense intuitive linear view. So we wont experience 100 years of progress in the 21st century it will be more like 20,000 years of progress (at todays rate). As AI grows, so does science as they are directly connected with each other. This resembles how our lives are improved by AI. For example, it has been proved by an article published in Science Daily that robots can detect breast cancer just as well as radiologists. Breast cancer counts with approximately 500,000 annual deaths worldwide this disease can be reduced in a considerable amount with effective mammography. With the use of AI, the amount of screening that can be done is a lot more as the process is intense and long lasting for radiologists alone, taking artificial intelligence as a helping hand would increase the number and effectiveness of mammograms leading to an increase in early detection and so a reduction of mortalities due to breast cancer.

Another use of this technology in medicine is also for the detection of neurodegenerative diseases, including Alzheimer. As experimented in a study made at the Icahn School of Medicine, published in the Nature medical journal Laboratory Investigation and rewritten on a Science Daily article, Applying deep learning, these images were used to create a convolutional neural network capable of identifying neurofibrillary tangles with a high degree of accuracy directly from digitized images. Again, this method allows the detection of diseases that are sometimes able to cure if the detection is made at an early stage. Usually what happens is that this detection is extremely difficult to make, however, with the use of this new methods involving AI technology, precision and effectiveness are highly increased.

Even though AI systems clearly do outshine human doctors in reading images such as CT scans, MRIs and x-rays, as they provide patients with more precise information, it exists the possibility that there is a biased intention behind the algorithms. According to an article published recently in The New York Times written by Cade Metz and Craig S. Smith, If an insurance company uses A.I. to evaluate medical scans, for instance, a hospital could manipulate scans in an effort to boost payouts as by changing a small number of pixels in an image of a benign skin lesion, a diagnostic A.I system could be tricked into identifying the lesion as malignant.. This reaffirms the idea that regarding the way this technology is handled and who is it handled by, we can answer the to the question if it should be considered as a risk or not. This examples shows how results can be altered in order to benefit the ones with power. This article also goes own talking about how when the time comes and A.I completely takes over the health system businesses will make sure to find the way this technology can bring them the most money possible. In addition, this source is both reliable and convincing as both authors are technology correspondents with The New York Times, meaning they are skilled journalists that work for a well known paper, and they give realistic evidence to support their ideas throughout the whole article.

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