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Our society has become inundated by the wide-ranging uses of artificial intelligence, and while its primary utilization has served us well thus far, many fear that there will be a day that we will serve it. Depictions of artificial intellectual beings becoming our rulers fill the box offices and book stores and remain a popular entertainment genre in entertainment for nearly a century. Most of us grew up as childhood fans of movies and television shows, such as Star Wars, Star Trek, and Terminator. I would bet that many of you reading this wished, at some point in life, that you lived in a world like those of your favorite Sci-Fi series, but now that fiction may be entering reality, you are becoming wary of its fruition. Or, if you are like me, you are looking forward to it and are thrilled about the advances the field of artificial intelligence has made thus far.

Depending on which category you are in, I have either good news or bad news for you, and whether this news comes across as good or bad will also depend on your subjective feelings of what I am about to share with you. I am going to provide you with a more thorough understanding of where we are in the realm of artificial intelligence and its current capabilities. First, I will just give a quick spoiler alert, a West World theme park will not arrive anytime soon, so you can save your vacation days for something else.

For an artificial being to be deemed intelligent, it must first pass a rigorous test known as the Turing Test, which was proposed by Alan Turing in 1950 (Russell, 2016). To pass the Turing Test, a machine must be able to respond to written questions that are produced by a human interrogator and cause the interrogator to believe the thing responding to the questions is human (Russell, 2016). As for most of us, our conversations with Siri or Alexa quickly come to a halt due to their inability to answer simple questions. For those of you who are curious about what a machine would have to be capable of doing, here is the list: natural language processing, knowledge representation, automated reasoning, and machine learning (Russell, 2016).

If you have driven on a busy highway over the past few years or have been in a large city mall, you may have noticed these new sports cars that run on only electricity, yes, I am talking about a Tesla. And if you know what a Tesla is, you have probably heard of its inventor, Elon Musk, and if you haven’t heard of him then you have successfully avoided every news station, website, and magazine for the past decade, well done! But, for those who do admire this man’s ambition for inventing some the most state of the art technological devices, as I do, you have probably heard of his latest endeavor, the implementation of neuralink into the human brain’s cortex (Musk, 2019). These devices are known as brain-machine interfaces (BMI), and he and his colleagues plan to begin implanting them in humans for the first time in late 2020 or early 2021. While its primary use will be for helping individuals with neurological diseases, Musk plans to develop it to the point of being a device straight out of a Sci-Fi novel, which is where he got this idea, to begin with.

Unfortunately, for those who are eager to stream Netflix directly through a Neuralink implant while you sit through lectures, you are probably better off using your smartphone and convincing yourself that your professor or boss does not notice. But in case you thought you were clever, I have to break the news to you, everyone sees you scrolling Instagram instead of taking notes. To give a better explanation as to why we won’t be able to send text messages without ever touching a phone again, it is because we simply do not understand how our brain creates images, stores memories, and produces information through the means of electrical and chemical signals through the use of neurons, synapses, and cell assemblies (Clark, 2014). Standard computational machines, such as the device you are reading this on, use symbols and systems that are programmed to produce a specific outcome (Clark, 2014), such as this sentence you are reading. The coding used within computational machines, like computers, is precise and follow a rigid set of “rules” and are unable to deviate from them (Clark, 2014). A computer’s strict method of information processing is unlike our brain that can understand semantic information that would go against the normal functioning of a computer (Clark, 2014; Kassan, 2014). The differences between the algorithmic coding a Neuralink implant and the none encoded cortex of your brain would be unable to properly communicate with one another, it would be a classic case of a dysfunctional relationship. This information is not to say that the possibility of a BMI becoming the Sci-Fi reality that Musk hopes it to be is impossible, but the technological advances we currently have would be unable to bring his dream into fruition.

In Andy Clark’s book, Mindware: An introduction to the philosophy of cognitive science, the first chapter is titled Meat Machine. This chapter’s title is a reminder that our brain does function as a unique type of machine, inviting neuroscientists and the like, to investigate how our brain is put together. The elaborate structure of our brain is organized in a manner that produces, what Clark calls, mindware. Mindware is the combination of all the aspects of our consciousness, our thoughts, fears, desires, and intellect (Clark, 2014). And for us to create the artificial intelligence we were obsessed with, and or terrified of, as kids, and maybe still are as adults, we must first grasp the understanding of how our brain and all its various parts function. Well, that is if we want it to function similarly to us, but here is some possibly unsettling news for those of you who fear an A.I. takeover, there is a possibility for something to become intelligent and autonomous without it being like us or even having to communicate with us. As Andy Clark puts it, “given that certain preconditions are met, the same functionality can be pressed from multiple different materials and designs” (Clark, 2014). So who knows, maybe one day Siri will be asking you to do things for it!

References

Clark, A. (2014). Mindware: An introduction to the philsophy of cognitive science. New York,

New York: Oxford University Press

Kassan, P. (2014). A.I. gone awry: The futile quest for artificial intelligence.

Musk, E. (2019). An integrated brain-machine interface platform with thousands of channels. doi: 10.1101/703801

Russell, S. J. (2016). Artificial intelligence: A modern approach. Harlow, New Jersey: Pearson.