Car accidents are one of the world's leading causes of death in every country. According to several studies that have been conducted all over the world, car accidents rank as the ninth cause of death all over the world but rank as the first cause of death for teenagers and young adults aged between 15 to 29 and the second leading cause of death among children aged 5 to 14. According to some studies that have been done it is approximated that 1.3million people die from road accidents every year. An additional 20 - 50 million are hurt or left disabled by these accidents. Of the 1.3 million that die most of them are young adults who are aged between 15 and 44 years old. These deaths are caused by different factors that were also studied. 32% of these accidents and therefore these deaths are caused by drunk driving, 31% of these accidents are caused by speeding, 16% are caused by texting or receiving calls while driving, and 11% are caused by bad weather. On top of the devastating losses caused by car crashes, there are financial losses as well. It is estimated that car crashes cost a whopping $518 billion per year which is about 1 - 3% of each individuals countries annual GDP. This is expected to cost low and middle-income countries $65 billion which is more than the money they receive for developmental assistance. If the number of car accidents was to significantly decrease then some of this money could be redirected to other causes that would foster not only global but individual development. It is therefore essential that car crash eradication ideas and innovations be made and supplied all over the world. One such innovation is that of computerized car crash avoidance systems that integrate artificial intelligence. This is the system that my team has been working on for some time now.
Car crash avoidance systems also widely known as collision avoidance systems are safety systems whose main function is to detect and prevent or reduce the severity of a collision during an accident. Such systems integrated the use of various mechanisms such as the GPS which is used to detect stationary items such as stop signs or trees that the diver could collide. This system also integrates with radar a system that identifies objects by sending radio waves and can determine the size, angle, range and the velocity if any of different objects. Once the system has detected any of the above, it needs to convey the potential danger to the driver which is where the artificial intelligence system comes in to allow the system to conveniently tell the driver by word of mouth or speech that he/she is approaching imminent danger and should stop. Such a system also need to allow the user to be able to interact with it which is also another reason for the integration of artificial intelligence within the system. Development of the system has been going well, and we had managed to jump over the major hurdles we expected when we began the project. This has led the project manager to think that the system is ready to be unveiled when some minor underlying issues could endanger the lives of people and cost us a fortune in lawsuits from potential victims. I conveyed my concerns about the nonlinear and cognitive dissonance issues with the system, but my team manager did not pay much attention to my concerns which have put me in a tough situation ethically.
Nonlinear problems arise due to some types of limitations within a system (Novak, 211). For example, if the system is unable to distinguish between a typographical error, it may be unable to work and therefore response time may increase, and in a situation as dire as the one the system is being built for this lag may cause an accident rather than stopping it. On the other hand, cognitive dissonance issues arise when the system finds more than one potential solution to avoid a collision or possible causes of an accident (David, 56). These two conflicting thoughts may inhibit the system's ability to come up with an effective course of action for the driver to prevent a collision and can also lead to the accidents itself. This is a harmful position in the legal realm because these systems are teaching humans to rely on them to avoid accidents. Therefore, these systems cannot afford to lag or have conflicting ideas at the same time, because in a situation such as an accident time is of the essence.
Therefore I had to analyze to find out the best course of action. In this situation there are only two plausible solutions; I could both keep quiet about my concerns and let the system be unveiled, or I could follow up the issue with my project manager, and if he were still dismissive of my concerns I would be forced to go above him. Both of these solutions will have repercussions and is therefore important for both of them to be analyzed. If the system is unveiled as it is, the several car companies will have to test it to ensure that it works as it is meant to and as we claim it does. During this testing, these companies may find these issues with the system and report that the system is not fully functional and therefore had to be decommissioned and fixed. This would be the best scenario if I were to choose to ignore my concerns. However, if these car companies were to test the system and find that it was working impeccably and declare it fully functional, the system would be integrated into several vehicles all over the world and could cause millions of deaths if not billions. This would mean a comprehensive investigation would be conducted and when they find that the system is faulty, we will be at fault. The repercussions could include state and individual lawsuits against us and the car manufacturing companies that will have adopted the system. All the cars with this system will be termed unsafe and will lead to losses in the range of billions and severe psychological impacts for me knowing that I could have done something about it, but I choose to ignore the problem.
The option to ignore my concerns would constitute several ethical violations as developed and published by the Institute of electrical and electronics engineering concerning software systems development. These violations include that of the public code, client employer code, and judgment code of ethics (IEEE, 303). The public code states that software engineers should act in the best interest of members of the public. The client employer code states that all software development staff should act in the best interest of their clients or whoever has employed them (the car manufacturing companies in this case). The judgment code stipulates that all s/w developers should maintain integrity in all their decisions.
The other plausible solution would be for me to come up with concrete proof of my concerns and present them to one of my trusted peers to review and if he/she shared the same interests, I would return to the project manager and convince him to hear me out. This could go either of two ways; he could listen to me and present these facts to the team to fix these problems as quickly as possible to prevent the delay of the system's unveiling. However, if he still didn't share my concerns, I would be ethically obligated to go above him. This would undoubtedly put me in bad standing with him but might save the lives of millions of people not to mention billions of dollars. It will also keep me from any psychological issues or guilt brought about by my conscience.
After an analysis of these two options and the consequences of both my options. I concluded that the second choice was in a sense the only option. I would create a comprehensive report detailing my concerns. I would then approach the project manager again with the hope that he would share my concerns and if he did not, I would go to the people whom he reports to with my interests. This would act as a necessary evil that would prevent the potential loss of lives and capital.
David, C V. "Cognitive Dissonance Theory." (David). Print.
"Ieee Code of Ethics." Ieee Transactions on Reliability. 33.1 (1984). Print.
Novak, Bojan. "Reliability and Applicability of Nonlinear Optimization Software." Reliability and Robustness of Engineering Software Ii. (1991): 203-216. Print.
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