Planet of the Machines

Abstract

Planet of the Machines According to Jeremy Rifkin in his book, The End of Work, “we are entering a new phase in world history— one in which fewer and fewer workers will be needed to produce the goods and services for the global popu- lation” (1995, p. 16). The rapid advancement of com- puters and machines to do increasingly complex jobs makes his claim palpable. Today, digital technologies are the key drivers of productivity and growth; they are reinventing the world of business and have become one of the most influential forces in the economy. Since June 2009, corporate spending on equipment and software has increased by 26 percent, indicating that corporations have taken advantage of technologi- cal advances. However, payrolls have remained flat for many (Lohr, 2011). In addition, many sectors of society are being influenced by technological displace- ment because it makes the labor of millions of people irrelevant. While some skills have become more valu- able than ever in our society, many more have become easily replaced. Reflected in today’s unemployment statistics, people have little to offer employers that a computer cannot do. Digitization has the unique ability to provide ever-expanding possibilities to com- panies with increasingly rapid advancements. While cyclicality (natural economic fluctuations), out-sourc- ing, off-shoring, and taxes and regulation are certainly important facets of the economy, in this article I will explore the amazing technology that is displacing human labor (Brynjolfsson & McAfee, 2011). Even in fields such as language and writing that are not commonly associated with technological in- novation in the same way that mathematics and the sciences are, profound technological advancements have made their appearance felt. The two most incred- ible examples of this are Geofluent and Livescience, computer software that use algorithms specializing in complex communication to automate the previously exclusive human capability of writing. A translation services company called Lionbridge started using GeoFluent in 2011 to replace their human language translators. GeoFluent’s capabilities are powered by SMT (statistical machine translation) software devel- oped at IBM that uses statistical models derived from Lionbridge’s massive amounts of digital transcripts to generate natural sounding translations. This gives GeoFluent the ability to take online messages and instantly translate them to an unmatched variety of other languages in speech that seems authentically human. In large-high tech companies that are likely to have customers and parties in different countries, this software is replacing the need for human translators and customer service representatives (Brynjolfsson & McAfee, 2011). Several companies have also developed journalism software that can write articles on sports, finance, and real estate, fields whose news stories tend to follow dis- tinct patterns and revolve around statistics. When the numbers are input into the program, the clever software can produce highly readable stories within seconds. The most successful of these companies is Narrative Science, which is employed by Forbes to automatically generate online articles about corporate earnings statements. The B erkeley S cientific J ournal • S ave or D estroy • S pring 2012 • V olume 16 • I ssue 2 • 1 B S J Over two years after The Great Recession official- ly ended in June 2009, the unemployment rate in the United States was at 9.1%, only one percent lower than its peak value. The unemployment statistics are sur- prising considering that other measures of economic growth indicated the economy was recovering. GDP growth, the total of all goods and services produced in the United States, averaged 2.6%, a rate higher than the 1970’s, 1980’s, and 1990’s. By 2010, investment in equipment and software rebounded to 95% of its his- torical peak. According to The New York Times, the companies in the Standard & Poor’s 500-stock index are expected to report record profits this year, and cor- porate profit as a share of the economy is at a 50-year high (Lohr, 2011). With businesses growing, earning profits, and buying equipment, this observation begs the question of why American companies did not begin rehiring workers laid off during the recession as we had anticipated. Tara Landers