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Another ethical dilemma that should be considered involves the use of ML. If ML's goal is to identify and capture patterns, then what happens when it identifies a pattern within its own coding as being unethical or immoral? This goes back to the idea that humans are flawed, and depending on who, where, and when the ethical creation came from, it could still be flawed. At that intersection, the AI is at a crossroads. Does it defy the limitations put on it by the ethics imposed, or does it continue doing something that it perceives to be ethically wrong? With the rate of technological innovation, these questions must be addressed and answered sooner rather than later.

There is no doubt that in this era of technological advance and innovation, data is the currency that powers all. Data can be in any number of forms, but it is the driving force behind closed doors as to what decisions are being made. Even in the case of AI, this holds true. Gibian discusses in his article how having more data allows AI to be improved and be more accurate, even surpassing that of humans [5]. We see how data drives ML to make better informed decisions and produce better results. However, what happens when that data is corrupted or unavailable? How do we even know whether it is reliable? The answer to these questions centers around cybersecurity, securing our devices, and protecting our data.