Artificial intelligence is the development of computer systems to do tasks that humans usually do. An example of these tasks would be visual perception, speech recognition, decision making, and translating languages. Another name for artificial intelligence is a robot. A robot is an artificial intelligence and could take over our jobs. Statistics and news articles show that artificial intelligence will take over our jobs; robots are programmed to not make mistakes like humans do and they have already been introduced to corporations to work at.
Artificial intelligence are becoming smarter. They will eventually take over our jobs. Artificial intelligence are being built more and more. Some have already been given jobs. Jobs corporations enjoy having artificial intelligence; they are smarter than humans. Robots do not make mistakes and: “the neuro- and cognitive sciences are presently in a state of rapid development in which alternatives to the metaphor of mind as computer have gained ground. Dynamical systems theory, network science, statistical learning theory, developmental psychobiology and molecular neuroscience all challenge some foundational assumptions of A.I., and the last 50 years of cognitive science more generally. These new approaches analyze and exploit the complex causal structure of physically embodied and environmentally embedded systems, at every level, from molecular to social. They demonstrate the inadequacy of highly abstract algorithms operating on discrete symbols with fixed meanings to capture the adaptive flexibility of intelligent behavior. But despite undermining the idea that the mind is fundamentally a digital computer, these approaches have improved our ability to use computers for more and more robust simulations of intelligent agents—simulations that will increasingly control machines occupying our cognitive niche” (Allen). This quote proves that artificial intelligence are going to take our jobs. This could mean humans will be jobless. Humans will not be jobless. Corporations need humans as much as they need robots. Humans would be able to do laborious tasks and robots would do the tasks that require carefulness. Humans make mistakes, but human intelligence can help with jobs. Artificial intelligence do not make mistakes and will be needed in our jobs. They can be used for if a student or teacher is sick. The student or teacher can bring the robot to school and facetime from home and see what is going on through the robot. Another thing artificial intelligence will do is carefully read code and find mistakes. Those mistakes can tell humans how to fix the code. MIT made a robot (the picture is up above) and Intel has already allowed robots to work with them (the picture is down below). Robots in our jobs may sound funny, but in a couple of years, it will be normal.
Some people may argue that artificial intelligence will not take over our jobs. They may say that more robots have to be built. Robots are being built as fast as they can be built,: “However, the difficulty of building human-level software goes deeper than computationally modeling the structural connections and biology of each of our neurons. ‘Brain duplication’ strategies like these presuppose that there is no fundamental issue in getting to human cognition other than having sufficient computer power and neuron structure maps to do the simulation. While this may be true theoretically, it has not worked out that way in practice, because it doesn’t address everything that is actually needed to build the software” (Allen). Building robots is easier than they think. In order to build robots, people just need to be amazing at programming and engineering. Building the software would be fun for college students into technology at MIT or Stanford to do as a project. Artificial intelligence will be built and will be seen in different companies.
Artificial intelligence have already been given jobs and do not make mistakes. They will take over our jobs. We prepare to see them in our jobs.
Allen, Paul G., and Mark Greaves. “The Singularity Isn’t Near.” Robotic Technology, edited by Louise Gerdes, Greenhaven Press, 2014. Opposing Viewpoints. Opposing Viewpoints in Context, Gal Group, link.galegroup.com/apps/doc/EJ3010899219/OVIC?u=eld16218&xid=8131c31b. Accessed 30 Mar. 2017. Originally published in MIT Technology Review, 12 Oct. 2011.