When we think about the implications of introducing deep learning programs into our decision-making processes, we tend to imagine far-off futures that follow singular monumental developments of the technology. Edison’s “lightbulb moment” or Bell’s inaugural telephone call may come to mind.
The truth is that technological progress is most often much more gradual. Because Artificial Intelligence’s ability to learn is dependent on its access to real-world data, it has already been integrated into our society to quite a shocking level, unbeknownst to many people.
Here are three ways that AI is affecting us right under our noses.
Artificial intelligence has already drastically impacted us economically. Financial institutions have been making lightning-speed decisions at the behest of machine learning programs for almost two decades. These decisions are made using such a complex set of data that some providers have begun marketing their services as “explainable ai” so that their clients can speak on the decisions dictated to them by the algorithms.
Wall Street has been using high-frequency trading (HFT) methods since 2005 when the SEC cleared the algorithm-fueled process for use. Otherwise known as algo trading, these decisions are made and acted upon in milliseconds. Many have argued that financial institutions’ access to the capital necessary to use HFT puts the average human retail investor at a significant disadvantage, helping to solidify trends in wealth disparity.
Lending institutions adopting deep learning algorithms into their practices have added fuel to these anxieties. Creditors will use artificial intelligence to calculate whether an individual or organization is deserving of a loan or line of credit.
Are you familiar with the philosopher Phillipa Foot’s “Trolley Problem?” The Trolley Problem is an ethical thought experiment in which the participant is charged with deciding on the value of one group of lives over another. Pop culture has theorized on the issue of leaving such ethical quandaries to machine-based logic systems since Asimov created his laws of robots in his book, “I, Robot.”
Asimov’s concerns have been thrust into the real world with the advent of self-driving mechanics. When a self-driving car is confronted with a hazardous situation, it must use the information available to make split-second decisions that result in the safest outcome.
Yet, there are questions as to whose safety should be most valued. The car’s occupants? A legally acting pedestrian? Is one of these people a child? The ethics of these situations get confusing fast once details are introduced into the case.
In 2021, over 31,000 people died in the United Statesfrom motor vehicle accidents. At that time, there were already 200,000 cars on the road with some sort of autopilot function installed. It’s likely that if most cars become driverless, the mortality rate will be significantly reduced. However, the number also depends on how AI will determine to handle the accident. We also must factor in any mechanical failures caused by self-driving technology as either the cause of the accident or the failure to protect passengers during a crash.
The introduction of “Deep Fake” technology was initially entertaining. Observing an actor’s face projected onto another’s mannerisms so that you could imagine alternate casting in movies was a charming introduction to what has developed into a frightening situation. Deep Fake tech uses machine learning to predict visuals upon request.
Ethical, practical applications of deep fake technologies are still being explored. Theories range from the possibility of constructing life-like artificial patients to guiding reconstructive surgery for burn patients.
Unfortunately, it is easier to imagine more nefarious uses of the technology, and they are already here. There exist real-world examples of how Deep Fake technology can be used to create fraudulent videos of world leaders in conflict. As science in this area progresses, we risk losing faith in the authenticity of the visual world if our ability to detect wrongdoing cannot keep up.
Artificial Intelligence has long enjoyed a promise of being the marker of the future. In many ways, that future is already being beta-tested by the forces of industry and individuals of excellent means for the greater good of humanity. However, it is wise for all those concerned with how technology influences our world to remain educated on how deep learning mechanics are being incorporated into our everyday lives – some methods are happening without much notice.