Assignment #1

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University of Central Oklahoma *

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12416

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Information Systems

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Dec 6, 2023

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Spencer Flatt Management Information Systems Assignment #1 Alexa, can you hear me? 1. Identify how machine learning can transform a traditional business process like checking out of a grocery store? For one, machine learning speeds up the process of most businesses, especially grocery stores. Say you only have a few items you need to grab for dinner tonight, you do not have to wait in those long lines behind people with carts full of groceries. You can go to the self-checkout area and usually get out within 10 minutes. Along with making your trips to the grocery store shorter, machine learning could mostly impact in ways of security and anti-theft prevention. Face recognition could monitor entry ways and checkout lines to monitor if a previous theft has made their way back into the store and monitor people placing items in their bags without scanning them. If a machine notices a customer did not scan, it could remind them to scan again or pause checkout until you scan an item you missed. I also believe this intelligence could be programmed into shelves to monitor when items become low in inventory and place an order for these specific products so that a human does not have to. I am personally old fashioned and believe a human should still monitor these machines even if we allow new machine- based technology into our grocery stores. 2. Explain the relationship between bias and machine learning for Alexa. The learning abilities of Alexa would help “her” understand what you like or suggest in your household. My family has an Alexa sitting on the bar in our house and she always suggest songs that I have asked her to play or suggests new shows based off what we have watched in the past. This learning ability makes a custom query internally so that she can make our lives easier and quicker, like making your grocery list for you and placing your order through amazon without even lifting a finger. Alexa also has her bias side, she will not respond to dirty humor, racism, or bad words. These internal programs cannot be changed, and I feel as if it is to prevent liability for amazon, if say, someone posted videos of an Alexa saying harmful things about another group or religion. Alexa also has preprogrammed applications that seem to be the same in all of them, programs that can turn on the lights, fans, and even lower and raise your blinds.
3.) Argue for or against the following statement: Machine learning systems like Alexa invade privacy. Personally yes, I do believe Alexa can be an invasion of privacy, she is listening all the time and ready to help any chance she gets, but I think most people that own them do not think it is actually capable of inflicting actual harm to our private information or safety. Amazon being the massive company that it is has to have an outrageous security database for these devices systems in order to keep themselves from being sued or shut down completely. I think most people around our area are worried about the government always being able to listen to us and taking advantage of the things we say in private in our homes. Like I mentioned before, I own one and if you are not saying or doing anything illegal then you have nothing to worry about in the first place, kind of like every other aspect in life. I have actually seen people cover their camera on an Alexa, so they do not feel as if they are being watched in their own home. However, the same people carry their phones, tablets, and computers with all the same listening technology every day without the same bias as they do toward Alexa.
References Stegner, B. (2018, January 10). 7 ways Alexa and Amazon Echo pose a privacy risk. MUO. https://www.makeuseof.com/tag/alexa-amazon-echo-privacy-risk/ Website above was listed for references to topic, no direct quotes or wordings were used.
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