Missouri S&T’s Peer to Peer
Abstract
This paper seeks to explore the ways in which machine learning and AI may influence the world in the future and the potential for the technology to be misused or exploited. In 1959 Arthur Samuel defined machine learning as “the field of study that gives computers the ability to learn without being explicitly programmed” (Munoz). This paper will also seek to find out if there is merit to the current worry that robots will take over some jobs based in cognitive abilities. In the past, a human was required to perform these jobs, but with the rise of more complex automation a person may not be necessary. Many of the sources cited throughout this paper focus on the innovation of machine learning and AI and how dangerous the over automation of the world could be. Machine learning and the resulting AI’s have their place in the world and more than likely they will do nothing but push the world towards a more fruitful future. Looking at potential risks of letting lines of code make important decisions is crucial given the consequences that negligence can have. There is a need to explore these topics because losing the human element in decision making can have some big implications if the AI is not programmed correctly. Machine learning has one of the greatest opportunities to impact the world. The need for caution however cannot be understated because of the potential dangers it may pose to jobs, security, and the overall stability of an ever changing world.
Recommended Citation
Skoff, David N.. 2017. "Exploring Potential Flaws and Dangers Involving Machine Learning Technology." Missouri S&T’s Peer to Peer 1, (2). https://scholarsmine.mst.edu/peer2peer/vol1/iss2/4