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Description
For as long as humans have been working, they have been looking for ways to get that work done better, faster, and more efficient. Over the course of human history, mankind has created innumerable spectacular inventions, all with the goal of making the economy and daily life more efficient. Today, innovations and technological advancements are happening at a pace like never seen before, and technology like automation and artificial intelligence are poised to once again fundamentally alter the way people live and work in society. Whether society is prepared or not, robots are coming to replace human labor, and they are coming fast. In many areas artificial intelligence has disrupted entire industries of the economy. As people continue to make advancements in artificial intelligence, more industries will be disturbed, more jobs will be lost, and entirely new industries and professions will be created in their wake. The future of the economy and society will be determined by how humans adapt to the rapid innovations that are taking place every single day. In this paper I will examine the extent to which automation will take the place of human labor in the future, project the potential effect of automation to future unemployment, and what individuals and society will need to do to adapt to keep pace with rapidly advancing technology. I will also look at the history of automation in the economy. For centuries humans have been advancing technology to make their everyday work more productive and efficient, and for centuries this has forced humans to adapt to the modern technology through things like training and education. The thesis will additionally examine the ways in which the U.S. education system will have to adapt to meet the demands of the advancing economy, and how job retraining programs must be modernized to prepare workers for the changing economy.
ContributorsCunningham, Reed P. (Author) / DeSerpa, Allan (Thesis director) / Haglin, Brett (Committee member) / School of International Letters and Cultures (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
One decision procedure dominates a given one if it performs well on the entire class of problems the given decision procedure performs well on, and then goes on to perform well on other problems that the given decision procedure does badly on. Performing well will be defined as generating higher expected utility before entering a problem. In this paper it will be argued that the timeless decision procedure dominates the causal
and evidential decision procedures. It will also be argued in turn that the updateless decision procedure dominates the timeless decision procedure. The difficulties of formalizing a modern variant of the ”smoking gene” problem will then be briefly examined.
and evidential decision procedures. It will also be argued in turn that the updateless decision procedure dominates the timeless decision procedure. The difficulties of formalizing a modern variant of the ”smoking gene” problem will then be briefly examined.
ContributorsHintze, Daniel Edward (Author) / Armendt, Brad (Thesis director) / Schlee, Edward (Committee member) / DeSerpa, Allan (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor)
Created2014-05
Description
The prospect of anti-aging or life extension technology is controversial in biogerentology but deemed even by skeptical experts to warrant discussion. I discuss the justifications that the probability of life extension technology being developed in the near future is reasonably high and that this research justifies the time and money it receives. I investigate potential ethical and societal issues anti-aging technology might create. This paper addresses inequality of access, economic cost, changes in quality of life, the role of death in human life, if and how the technology should be regulated and how parties who choose not to undergo treatment can be fairly treated, even when they are a minority.
ContributorsGlesener, Julia Hannah (Author) / McGregor, Joan (Thesis director) / DeSerpa, Allan (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05