Human-Development-and-Data-Science

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Self-driving cars are one of the most anticipated innovations of our time. They can assist people by helping them avoid accidents on the road with the development of lidar, which can bounce pulses of light around the vehicle to align the car with lane markings. Another development that can aid in the travel of people from one place to the other is the recurrent neural network, which is said to predict behaviors in the future by implementing past stimuli that the car was exposed to before, making the system exponentially better as it journeys on the roads. This is what helps the system differentiate between a variety of objects that may block the vehicle from its maneuver. The back-propaganda algorithm is mainly responsible for this as it records this data and updates the neural network accordingly, making us one step closer to replicating human behavior.

In terms of the positives and negatives of the advent of self-driving cars, many depend on what people value the most. According to the article, 600,000 lives are projected to be saved by 2045 if the cars are supplied to the public. This can also mean that there will be less congestion on roads and smaller commute times to get to a destination. However, these estimates are not summative of the entire driving experience. It may seem very promising to us now, but these vehicles still require more training of data to reach optimal performance, which means that they are not completely safe just yet. As aforementioned, this car contains a computer that generates multiple outcomes on a case-by-case basis, leading to constant maintenance of the system. Furthermore, the economic consequences of this invention can be destructive for many that work in the transportation industry, such as truck and cabbie drivers. This relates to the question of ethicality in development and how it may be exclusive to certain demographics of the area being affected. The mass deployment of such technology should account for the well-being of all individuals that may be reluctant to be part of this innovation.