Academic Nonfiction Written Works

A “Not-So” Dystopian Future by Jordan Phillips

“Hey Siri, how will the implementation of artificial intelligence advance human beings into the next technological revolution?” Hollywood cinema might suggest a horrifying visual of a technology obsessed culture suffering its demise through a robotic uprising. While it makes for an action-packed science-fiction thriller, no handsome hunk protagonist is needed to save the day. Fortunately, the world is not ending tomorrow, and we do not need to concern ourselves with unlikely dystopian predictions of a certain doom. What we need to consider is how to advance as a society, to better the people and the planet through optimizing our processes. The first models of basic computing came to life at the hands of the Bell Company in 1939, a century later simple systems have advanced to complex robotics and quantum computing. At a standard rate of progression, the next step in human and technological evolution is to welcome the advancement and implementation of artificial intelligence.

Artificial intelligence, AI, is a form of algorithmic machine learning divided into four categories of intelligent processing: reactive, limited, theory of mind, and self-aware. Reactive systems perform simple tasks in real time but are unable to store data or build a memory. Modern examples might include text and speech tools, content filters, search engines, or defeating humans in strategic games such as chess. Limited systems use and store data to learn how to complete future tasks. Driving assisted cars like Tesla’s Model S are a prime example of limited memory intelligence as sensors gather data in real-time while onboard computers store speed, distance, and physical object data to safely navigate unpredictable traffic scenarios. Theory of mind introduces predictability based on human emotions which allows for artificial intelligence to better understand how to interact with human beings. Self-aware or point of singularity is where machine learning is equivalent to deep learning or human level intelligence, emotion, and sense of identity. Reactive and limited systems are known as weak AI, where theory of mind and self-aware systems are referred to as strong AI and are in preliminary stages of development as of this writing. Everyday use of artificial intelligence became relevant within the past decade as companies like Google, Apple, Amazon, HP, Tesla, DeepMind, OpenAI, and many others develop convenience software to fill in the blanks, grant access to password protected possessions, or get you from point A to point B safely while napping.

Imagination is what drove humanity to harness fire, create tools, civilizations, governments, technology, and a structured sense of free-will. Having an imagination is a crucial part of the human process that led to the development of society as we know it today, but it can also lead us astray. While Hollywood portrays an entertaining version of a dystopian robotic future, the reality is that we already exist among the machines and fear stems solely from imagination. From mobile devices to advanced monitoring systems, artificial intelligence is a necessary and functioning part of everyday life. Implementation of artificial intelligence provides for strategic and real-time response to emergencies such as wildfires, hurricanes, volcanoes, or other climate related events seen frequently over the past decade. According to Jenifer Strong, podcast host of M.I.T.’s In Machines We Trust, satellite-based monitoring systems using reactive and limited intelligence to inform fire districts of when to evacuate neighborhoods as the first sign of wildfire smoke is detected in the atmosphere. At the same time, limited memory algorithms can determine if a detected wildfire is of benefit to the land while maintaining minimal risk of human casualties or structural loss. Having access to real-time data provided by intelligent monitoring systems is already saving lives by allocating an appropriate emergency response.

Artificial intelligence ranges in use in the modern world from simple everyday tasks to complex medical procedures that are known to change human lives for the better. Advancements in the medical field have provided useful tools for patients and medical professionals alike. Though limited by Amyotrophic Lateral Sclerosis (ALS), Stephen Hawking was one of the greatest minds to ever exist. Hawking worked with a team of computer scientists and doctors to implement reactive artificial intelligence in the form of infrared sensors that were connected to his glasses, and a speech synthesizer developed by Intel and AMD to turn phrases on a computer screen into intentional and meaningful spoken words. Technology advances medicine in ways that improve human longevity thanks to precision machinery and early detection. Where complicated surgical procedures are required, human error can occur. A combination of reactive and limited artificial intelligence is used in operating rooms to perform complex surgical procedures with absolute precision, easing tension on medical staff while increasing the probability of recovery for the patient. Seamless integration of human and artificial intelligence provides for rapid adaptation and solution to complex situations.

Human beings have placed lofty expectations on artificial intelligence as a sense of modern robotic slavery. Artificial intelligence is simply designed for generalized learning, reasoning, and problem solving; not post-apocalyptic tyranny. There is compelling evidence that implementation of artificial intelligence in the real world could be increasingly useful for human beings; however, in his book Superintelligence, Nick Bostrom suggests human beings are still decades away from what is commonly referred to as the point of singularity. Outside of simple reactive and limited artificial intelligence, advanced systems such as theory of mind or self-aware systems are in the initial stages of development operating at a fraction of the capabilities of the human mind. According to Bostrom, artificial intelligence will not become human-level intelligence until 2093 at the current rate of progression. As of now there is no clear blueprint or path to strong artificial intelligence. So, what other than imagination drives human fear of implementing artificial intelligence in the modern world?

With strong AI considered a thing of the future, concerns of artificial intelligence implementation in the modern world can be as simple as reactive systems themselves. When easy tasks are fulfilled by machines operating on basic lines of code, the need for human labor and payroll becomes obsolete. Assembly lines are no longer limited by an overwhelmed Lucille Ball chowing down pounds of chocolate as her coded counterpart of the surgical program mentioned earlier places manufactured products precisely where they need to be in a consistent and timely manner. Grocery stores were once a cultural congregation of the community; now they are a rushed and robotic world of sensors and advanced monitoring systems. Human cashiers and store clerks have been replaced by self-checkout stands and automated inventory tracking systems that command self-guided shelf stocking robots. Worst of all is dock workers dwelling from the hundreds of thousands to hundreds as the SARS CoV-2 pandemic sent most of the world into a lengthy quarantine. Containers now move around our ports thanks to self-propelled modular transport vehicles operating on the same technology as self-driving cars.

Maybe the concern is not exactly that of a dystopian future but that of record unemployment rates collapsing the economy. If a simple machine can consume our careers, then what is left when technology advances to deep learning with strong artificial intelligence? Doctors, scientists, engineers, skilled, and unskilled laborers alike face the same financial fate when one machine can manage an assembly line with surgical accuracy or perform complex surgeries with assembly line consistency. If not unemployment, most certainly the greatest concern is that of biased artificial intelligence. Afterall, artificial intelligence learns from all knowledge available to humanity. Given the nature of systemic racism, artificial intelligence is sure to favor white males over people of color, LGBTQIA2S+, or women. Flynn Coleman, author of A Human Algorithm provides a daunting reminder that the tech industry is still dominated by white males, with a 20% disparity and only 9% of leadership positions being filled by women. To create better and stronger artificial intelligence, humanity must do and be better to each other as we lead by example.

Artificial intelligence has become a buzz word in the tech industry as multiple startups develop various models of reactive, limited, theory of mind, and self-aware artificial intelligence. Though simple systems have been helpful to humanity, not one model has broken the point of singularity. In a recent interview with Greylock partner Reid Hoffman, OpenAI CEO Sam Altman states that early artificial intelligence will be great for optimizing what has already been done but will not add to the “sum total of human scientific knowledge” anytime soon. We have only begun to scratch the surface of human and artificial intelligence integration, but we do so with caution every step of the way. Systemic racism, or biased algorithms will not be a source to inspire, but a source for artificial intelligence to learn and grow from. Given the rapid rate of progression in technology already happening in the modern world, implementation of artificial intelligence will advance humanity into the next technological revolution equally.

Works Cited

Bostrom, Nick. Superintelligence: Paths, Dangers, Strategies. Oxford University Press, 2016.

Coleman, Flynn. A Human Algorithm: How Artificial Intelligence Is Redefining Who We Are. Counterpoint, 2020.

Greylockpartners, director. OpenAi Sam Altman: AI For The Next Era. YouTube, GreyLock, 21 Sept. 2022, Accessed 7 Dec. 2022.

Medeiros, Joao. “How Intel Gave Stephen Hawking a Voice.” Wired, Conde Nast, 13 Jan. 2015,

*Other information comes from personal experience within the field of AI and presented as common knowledge.