Self-driving cars ethical issues
Computer Sciences and Information Technology
– ethical issue topic :privacy issues , 2-21st emerging century : self driving car
Self-driving cars ethical issues
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In the past five decades, emerging technology has shifted the way we conduct our daily activities, such as communication and transportation. The technology has eased how we do things, thus ensuring convenience and agility. However, emerging technologies have also brought about ethical concerns, such as privacy and security issues. Innovations such as artificial intelligence have changed how we command and interact with computers. Such implementations have been integrated into the transportation systems, thus creating self-driving cars. Self-driving cars are beneficial and convenient, but they also have their problems and challenges. Ethical and privacy issues are among the significant problems of self-driving cars. Privacy issues cause vulnerabilities to users’ data. The paper presented will reflect on the benefits and ethical privacy issues of self-driving vehicles (Williams, 2017).
Autonomous vehicles or self-driving cars have environmental sensors that enable cars to move without human input. The vehicles are equipped with advanced driver assistance systems (ADAS) that allow the vehicles to perceive their surroundings. The control systems and sensors are fitted to identify navigation paths and deal with obstacles. Emerging technologies are leading to autonomous vehicles and extensive road testing to enable them to ensure efficient infrastructure. Self-driving cars have been pursued by mogul companies like Google, Apple, Tesla, Uber, and Lyft. Self-driving vehicles date back to Futurama that was held in 1939 (Williams, 2017). The exhibition predicted that the future would have an automated highway to guide the self-driving cars. The vision has not yet fully manifested. However, vehicles today entail computerized features that are environmentally sensitive, thus providing banking systems and even assisted parking systems.
Autonomous vehicles today are considered semi-autonomous due to their capability to steer, drive, and brake and park themselves. The cars have GPS capabilities and systems that can sense signs, signals, bumps, and obstacles ahead. The emerging technology is expected to take over by 2025.half of the automobiles are expected to be autonomous worldwide. Self-driven vehicles are implemented for their improved safety capabilities on the road. Manual cars have been recorded to cause impaired driving and accidents, especially when under the control of drunk drivers. Autonomous vehicles cannot get drowsy as humans can, nor can they be distracted by their phones (Maurer et al.2016). Therefore, self-driving cars are integrated into their safe qualities. Companies like Ford, Tesla, and Mercedes are investing in autonomous vehicles, thus radically changing the consumer world.
The levels of autonomy range begin at the driver assistance level. The system was used for acceleration and deceleration based on the environment information. However, the human driver was expected to perform all the remaining driving tasks. The partial automation level had an improved system that enabled the driver to relinquish specific controls. The driver can control the acceleration and the steering depending on the information of the driving environment. The system executes by using the monitors as the fallback system (Maxmen,2018). In this system. the driver can perform the rest of the driving aspects. The third level is the conditional automation has an automated system that performs all the driving aspects with minimal human intervention. In this stage, the driver will intervene when needed. The fourth level is high automation, which does not require human driver intervention or response. The fourth level is automated driving in all aspects of the driving tasks. The self-driving vehicle can still perform even when the human driver does not respond to a warning a request (Holstein,2018). Also, the high automation level delivers in either constrained and in defined areas. The fifth level is full automation in all environs and roadway conditions. Vehicles can execute without human intervention because it monitors the driving environment.
Autonomous vehicles are beneficial because of their route optimization. The cars can incorporate real time traffic information. Also, they can connect with the route selection depending on traffic infrastructure, other vehicles, and road conditions. Self-driving cars operate on reduced energy consumption because they consume lesser fuels as compared to conventional vehicles. Autonomous vehicles can maintain lane capacity because they can operate at higher speeds hence increasing lane capacity. Self-driving cars are beneficial for their safety qualities. The vehicles can reduce driving error, which is a significant factor in 94 percent of car accidents (Urmson,2008). The full automation system offers independence to drivers with a disability and the senior members of society. Low fuel costs ensure affordable transportation and mobility. Research shows that autonomous cars will increase productivity because of their timely functionality. Autonomous vehicles are hugely beneficial to the environment because of fewer carbon emissions and fuel use.
Autonomous cars face limitations such as obstacles on the road. Despite their sensors, such as cameras, radars, and lasers that can be used to scan the road for potential obstacles, they cannot be enough to solve the problem. However, smart roads are being explored to solve the problem by communicating with autonomous cars for potential obstacles ahead. Detours and rerouted roads cannot be sensed by self-driving vehicles; hence, thus without advanced communication, accidents can occur. The mapping system is a program to move from point A to point B; therefore, they are not designed to detect detours. Self-driving cars can be limited in inclement weather. During blinding rain, blizzards, and fog, the camera may not communicate accurate visibility. In such situations, the driver may be required to take over the driving aspects of the prototype vehicle.
Privacy issues are a big concern in driverless cars innovation (Holsteir,2018). Just like smartphones, personal information can be derived, thus causing privacy breaches. Autonomous cars entail information that can get hacked and become vulnerable to malice.
The research was conducted where two hackers took control of a Jeep Cherokee vehicle. The possibility was proven to be comfortable and possible. The cars collect information such as locations, behaviors, and preferences that can be used against the user. Driverless car privacy systems have car-sharing features and wireless connectivity that further makes the information vulnerable. The study shows that autonomous car data capabilities generate 100 gigabytes of data per second. The data collected include sensitive data, such as eye scans, fingerprints, and real-time location information. Aggregate data is used to manage traffic vehicles non sensitive days such as mirage information can get used to determine the car performance. The data collected can be used by companies for consumer benefits. For example, none sensitive data can be used in a diagnostic analysis to improve the safety features in a car. However, consumers may not be comfortable with their personal information being sold to third party companies. Also, car sharing connectivity increases the chances of hacking in these vehicles (Urmson,2008). Connected cars create an opportunity for hackers to access more than one vehicle when connected to the internet.
Autonomous vehicles are beneficial and inevitable because they are designed to improve the safety of transportation. Also, they are independent and free from human interference; thus, they can minimize the accidents caused by human error. However, the vehicles have limitations in their designs. They do not have the appropriate sensors to detect obstacles and to navigate through fog weather. Also, the cars pose ethical privacy issues because the information collected can be used for malice or consumer benefits against their consent (.Borenstein,2017). The moral privacy issue in autonomous cars got a response from the Self Drive Act that required the manufacturers to develop cybersecurity systems that can control access and detect vulnerabilities in autonomous vehicles. The information collected by these cars enables personalized services and increased safety. However, such information must be kept safe. Also, the user must be provided with protective guidelines and authentication systems that automate safety. Self-driving vehicles will have a tremendous impact on the automobile industry. However, to achieve this requires the manufacturing companies to tackle technological challenges such as the ethical issues caused by privacy issues. The innovation must be safe to ensure an efficient and straightforward experience.
Urmson, C. (2008). Self-driving cars and the urban challenge. IEEE Intelligent Systems, 23(2), 66-68.
Williams, B. (2017). Self-Driving Cars Will Change Our Lives and Our Cities.
Maxmen, A. (2018). Self-driving car dilemmas reveal that moral choices are not universal. Nature, 562(7728), 469-469.
Borenstein, J., Herkert, J., & Miller, Bihcz., J.K. (2017). Self-driving cars: Ethical responsibilities of design engineers. IEEE Technology and Society Magazine, 36(2), 67-75.
Maurer, M., Gerdes, J. C., Lenz, B., & Winner, H. (2016). Autonomous driving. Berlin, Germany: Springer Berlin Heidelberg, 10, 978-3.
Holstein, T., Dodig-Crnkovic, G., & Pelliccione, P. Walowitz, J.(2018). Ethical and Social Aspects of Self-Driving Cars. arXiv preprint arXiv:1802.04103.