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Algorithmic Decision Making And Why Is It Important To Understand Its Use (Other (Not Listed) Sample)


Algorithms Around Us


Algorithms around Us
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Before jumping to the first question we need to establish a quick understanding of what is algorithm and AI (Artificial Intelligence) and how both are interconnected. An algorithm is a formalized computer procedure that is achieved through the used coding to solve problems. It processes a stream of data, does calculations and provides solutions for problems it is designed for. Artificial Intelligence, commonly known as AI, is directly associated with machines (androids/robots) that are designed to carry out tasks by demonstrating their intelligence (Loughlin). This form of intelligence is computer-based as compared to the natural intelligence inhabited by humans.
What is algorithmic decision making and why is it important to understand its use
The algorithmic decision making is basically a process generated through the computational design to make a decision on something (Higo, 2011). The examples of algorithmic decision making can be found everywhere these days. How the most watched/visited video pop up at the top on YouTube, how credit scores determine your acceptance level for a credit amount, how Google tracks the search results in its search engine all are just very few of numerous examples out there.
The use of algorithmic decision making is increasing ten-fold as companies from every walk of life are utilizing from its potential. From content creators to credit brokers, from car sellers to e-commerce website, from Amazon to Facebook everybody is using it. Despite the flooded market with algorithms still cannot gain the full functionality of human intelligence. They are being updated very regularly by the companies but again cannot compete for the human intellect.
The need for algorithmic decision making started to rise when the data shared across the internet increased hugely. In this age of Big Data businesses and governments have to deal with and process large streams of data. The advancement in computing technology has enabled companies and governments to increase their productivity and efficiency with the use of algorithmic decision making. The authorities use such algorithms for predictive policing to catch the criminal and companies use them in other lucrative ways. Financial institutions, forex traders, healthcare and education sector, the security firm and criminal justice departments are jumping on this bandwagon to reap the benefits of algorithmic decision making.
The use of this type of algorithmic decision-making tool described and why it is significant
Driverless cars, also named autonomous cars and self-driving cars, embark on a road journey with an intention to complete it with little or no human involvement. These cars are designed and programmed to take various automated decisions that a human driver would take, based on the external environment (Sivakumaran & Sathish, 2016). It is yet to be known where a human driver would rely on his experience and knowledge, or to say his intelligence. An autonomous car would make decisions based on the inputs sitting in the core of its software.
These unique cars come with many controllers, actuators and sensors fitted in them that is directly controlled by a programmed ECU (Electronic Control Unit). Driverless technology is a form of machine learning artificial intelligence that is continuously making automated decisions about its surroundings and any changes taking place during the journey. This type of decision making is automated and is based on the set of instructions stored in its hardware. The algorithms used in autonomous cars can usually be classed into four different categories which are highly dependent on their functionality. These types include pattern recognition, regress...

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