Applications of Artificial Intelligence and Machine Learning Brand Thelen Ferris State University, Dr. Cooper 10/1/2022 When the term artificial intelligence is brought up, most people may think of the obvious use cases of artificial intelligence such as an Alexa being used as a personal assistant, or they may even think of unrealistic examples in movies and videos games where the goal of the artificial intelligence is to take over the world while also having consciousness/self-awareness. But there is much more to the world of artificial intelligence than just being an assistant or a means of entertainment. Artificial intelligence is being utilized all over the globe for an endless number of reasons; many of which get discovered almost daily it feels like. Artificial intelligence is being utilized in virtually every single industry today. Use cases can include activities such as collecting and analyzing data, personalizing advertisements, media creation, and the list goes on and on. These are just basic uses cases of what artificial intelligence is capable of. On the more advanced side, artificial intelligence is being used for extremely important activities. These activities can include things such as saving lives, preventing fraud, and even identifying faces and voices. One of the more vital uses for artificial intelligence that is quickly evolving due to advancements in technology is the ability for it to detect different types of cancers and tumors within patients. The use of artificial intelligence to aid in detecting different cancers within patients isn’t a new idea by any means. In fact, this type of aid has been around for nearly 20 years. However, it has now gotten to the point where it is extremely efficient due to other technology advancements. (Artificial Intelligence, 2020) Advancements in artificial intelligence and other computer technology has led to an increase in the effectiveness of detecting cervical cancer within patients specifically. This technology uses over 60,000 (most likely more today) cervical images and deep learning methods and compares them to cervical lesions of present patients. (Artificial Intelligence, 2020) This method of screening for cervical cancer has proved to be far more effective in detecting cervical cancer but has also proved to be far more cost-effective as well. (Artificial Intelligence, 2020) There are a few ethical considerations that pertain to this technology, however. For starters, the data being utilized within this technology can be categorized as patient data as the images being used have to be collected from individuals themselves. Therefore, ethically, this data would need to be covered like any other personal patient data that is stored. Also, this data would need to be collected in an ethical way as well. Patients need to give consent for their cervical images to be used and there could be major repercussions if unauthorized data/images are used. However, once the data is collected, there is still the matter of storing it and securing it so that it doesn’t suffer from any corruption or data loss as it could mean life or death in the grand scheme of things. There are specific security controls that could be put in place in order to make sure that this data is secured. Specifically, authorized access should only be allowed. Not everyone needs access to the technology and the data it gets inputted and outputs. Limiting the access to only screening staff and other IT staff decreases the chance that an unwanted party accesses the data because they will need proper credentials. Another security control that could be implemented in order to protect the data is to segment a section of the internal network to function as a storage area for the information. This network segment can have upgraded security measures such as internal firewalls, different encryption techniques/protocols, hashing methods, as well as the ability to completely hide the network. The ability to detect early signs of cancer within patients is just one example of how powerful and beneficial the incorporation of artificial intelligence is to the medical industry. As previously mentioned, artificial intelligence isn’t limited to the medial industry, however. Essentially any industry imaginable is making use of, or can make use of, artificial intelligence in order to improve business functions. One of the industries developing different use cases for artificial intelligence at an increasing rate is the finance and banking industry. Primarily, artificial intelligence is being used to detect and prevent fraudulent activities. (FINTECH, 2022) The artificial intelligence being deployed by financial and banking institutions learns what “normal” customer behavior looks like and will then flag, and in some cases block, suspicious activity that deviates from what the typical behavior looks like. (FINTECH, 2022) This technology is also capable of combing through historical data to review transactions. From here, the artificial intelligence can further learn what typical customer behavior looks like and assign “fraud scores” for specific customers. (FINTECH, 2022) These fraud scores essentially define what the specific customer’s activity usually looks like. From here, the artificial intelligence can “personalize” how to deals with each customer’s account individually. (FINTECH, 2022) Much like the patient protected data that is handled with the first example, the data handled by the artificial intelligence in the financial industry can be classified as PCI (payment card industry) data. This data is extremely important and should be treated as such. Ethically, this data should be protected as best as possible while also allowing for ease of access by authorized individuals. This may be a difficult task, but it is one that is required in the digital age. Also, the customers should be notified of how their data is being used and monitored as to not lose anything in translation. Storing and using this data has plenty of risks given the importance of it. In order to minimize and in some cases, eliminate risks, there are a plethora of security controls that can be implemented. To start, making sure this data is stored properly is one of the most important security controls that should be considered. Secure protocols should be used when data is at rest and in transfer, the most up-to-data encryption standards/methods, as well as authorized use and access of said data. Another security control that should be implemented when working with this data is the use of a Data Loss Prevention policy. Ensuring the use of a DLP policy can increase customer satisfaction and trust as well as increasing the overall protection of the data itself. References Artificial Intelligence - Opportunities in Cancer Research (2020, August 31). In cancer.gov. Retrieved from https://www.cancer.gov/research/areas/diagnosis/artificial-intelligence FINTECH & FINANCIAL SERVICES, . (2022, February 17). How is AI transforming fraud detection in banks?. In Telusinternantional.com. Retrieved from https://www.telusinternational.com/articles/ai-fraud-detection-in-banks
