At least for me, artificial intelligence is a rapidly growing topic of debate. I have heard arguments about their level of consciousness, superior and inferior abilities, and most of all, what affects they will have on the economy. This last topic is what I plan to share with you today. I hope to present the debate in a fair way, ending with my preferred solution to the growing phenomenon.
Artificial intelligence is commonly referred to as the theory and development of computer systems able to perform tasks that normally require human intelligence (Marr, 2018). No different than any other tool humanity have invented, A.I. is something we have created to modernize and make our lives easier. Its tasks range from recognizing one’s face to unlocking a smart phone’s home screen to helping conduct surgery. Therefore, this tool is helping all around us, even in places we don’t think to look.
The first position worth mentioning is to focus funding, research and development on artificial intelligence. Because of artificial intelligence’s profound ability to perform tasks, policies like ITI Unveils First Industry-Wide Artificial Intelligence Policy have been sprouting up recently (ITI Unveils Policy, 2017). This policy simply advocates to encourage A.I. through funding and research. The policy sees the advantages of A.I. and therefore embraces it no matter the social consequences that may follow. It essentially assumes the benefits will greatly outweigh any problems A.I. may create.
A key point to this debate is noticing what makes A.I. unique. This tool’s uniqueness, and issue, is how efficient it is at its job. Matt Beane, Assistant Professor in the Technology Management Program at University of California, addresses this efficiency in one of his Ted Talks. He explains how surgeons, and residents in particular, are struggling to gain the skills they need to efficiently preform their job. They are lacking the experience they need because A.I. is simply doing it for them. Being programmed to minimize their patient’s risk, these A.I. robots are not allowing the unsteady hand of a young resident anywhere near their operation table (Beane, 2018). This puts humanity in an awkward situation of picking between the inefficient human or the flawless tool. This dilemma of picking between efficiency and humanity leads to the rebuttal of this position.
Quoted from an online Fords article, “Statistics say that 47% of all employment opportunities will be occupied by machines within the next two decades. Statistics also say that about 80% of all Americans believe that they will be able to maintain their livelihood after the prophesized robotic boom,” (Stark, 2017). In other words, within twenty years, starting two years ago, half of all the known jobs that exist today will be occupied by machines. Remarkably, Stark is not alone with this assumption. BBC News reported that eight-hundred million jobs will be displaced by 2030 due to robot automation (2017). Along with a recent poll conducted by The New York Times said that 37 percent of the reason people were unemployed from the age of 25 to 54 was due to technology (Miller, 2014). These extreme numbers are appearing because, as said earlier, A.I. is an efficient tool that can function, in select situations, better than humans. And as A.I. has been developed and improved, their predicted scope of being better than humans has risen accordingly.
Before going too far in this train of thought, one should not forget that this situation has come up before. The Industrial Revolution was a very similar time to this one. Many people feared that their jobs would be displaced, and sure enough, they were. Regardless of the Luddites’ fruitless attempts to smash and burn every machine in existence, the revolution did occur along with the displacement of thousands of jobs. But what many people did not see coming was the thousands of jobs that were created due to this job displacement. With the invention of the steam engine came the end of horse cargoes industry, but also the beginning of railroads. Yes, cargo builders eventually ran out of work, but simultaneously the demand for engineers grew significantly. Going off of basic laisse-faire principles, it would be counter-intuitive to stop the natural flow of the market. With competition among companies also comes competition among sectors, and as one grows in efficiency it should crush the others. The jobs of the old sector are destroyed, but by doing so, opens a whole new sector of better, more efficient jobs.
We see this trend continuing with the emergence of A.I. Dozens of jobs have been created out of seemingly thin air. Titles like data detective, artificial intelligence business development manager and cyber city analyst have all been created because of A.I. (Stillman, 2017). Therefore, it would appear that much like the Industrial Revolution, jobs markets are forever changing and should be allowed to maintain a healthy economy.
Yet there remains any issue at hand. As compelling as this counter statement may be, it neglects two crucial areas when debating the implantation of the A.I. One of which is referred to as the superiority myth by Daniel Susskind. This myth explains our irrational assumption that human beings will always be the dominant workforce (Susskind, 2017). This term essentially says, yes, the markets may change, and jobs may be replaced instead of destroyed. But the issue is that this is only beneficially when assuming that the new jobs are best performed by humans.
Within capitalism a worker sells his or her labor. In the same way as a commodity, our work ability is sold and bought depending on the supply and demand of that product. Historically, human labor has always been the superior commodity. One with a both constant demand and supply. The issues with A.I. is that it may be the first commodity to replace human worker ability. No different than the transition from horse cargoes to the steam engine, we may see the same transition from human work ability to A.I. This is an issue because without the demand of human work ability comes a collapse in capitalism. If the consumers of an economy are not generating revenue to consume with, then no consumption would take place. Which would terminate the cycle of the economy.
The second crucial point to recognize in this debate is that even if jobs are successfully replaced with human beings, there is still a probable decrease in unit labor cost. Referring to the picture I took in my sociology economics class to the right, as technology has skyrocketed, so has productivity. Yet what has essentially stayed the same is worker hourly compensation. Therefore, even the workers that have successfully maintained their jobs, have found themselves grossly underpaid. This is not only morally incorrect, because with underpaid workers comes overpaid bosses, but also detrimental to the economy. With this being one of the major causes of income inequality, the economy is struggling to maintain consumption with such limited demand. If we see A.I. continue its trend of “efficiency”, then we may develop into a grossly unstable and unequal economic structure.
These concluding points have brought me to my preferred position on the matter. I find it naïve to assume that A.I. will only displace as many jobs as it creates. Yet I also find it counter-intuitive to become a luddite and attempt to stop technological modernization. At the end of the day it is a safer world when we have A.I. surgeons who never mess up, compared to human surgeons who sometimes mess up. Therefore, I find it ideal to allow the growth and modernization of A.I. if we also implement policies that will support and prepare humanity for economic and societal change.
Attempting to not stray too far from the main subject, it should also be noted that the predictions of job displacement and artificial intelligence’s ability to outperform human work ability are only predictions. Quoted from Scientific America when referring to self-driving cars, “But to me, as a human factors researcher, that’s not enough information to properly evaluate whether automation may actually be better than humans at not crashing. Their respective crash rates can only be determined by also knowing how many non-collisions happen. For human drivers is it one collision per billion chances to crash, or one in a trillion?” (Hancock, 2018). Hancock explains how it is very difficult to measure collusion rate and therefore it is only through hopeful assumption that we expect autonomous cars to outperform human drivers. Being a historically accurate trend, human desires tend to cloud reality. It would be great if we could have self-driving cars that functioned hundred times better than any human, but that very well may never be reality. Sadly, we will not know if it is reality until it happens, and only then will it be too late to take action without issues arising. Hence why policies like the A.I. in the UK: Ready, Willing and Able are critical to our future (Authority of the House of Lords, 2018). This policy looks at the possible issues that may arise with A.I. and raises awareness of them. Essentially preparing for the probable societal and economic issues ahead. It is not limiting A.I. development, but instead preparing for it.
A.I. is becoming increasingly important in today’s debates. Its significance is rising as it outperforms humans in more and more tasks. As of now there is no clear distinction when this tool will plateau, therefore it would be wise to build awareness and preparation for the future. By doing so we will not be limiting the arguably inevitable but will instead plan for how to maximize our benefits associated with it. Artificial intelligence may replace human worker ability all together. It may also plateau and allow for a shift in the workforce rather than the destruction of it. Until that day all we can do is prepare for either option and hope which ever one occurs we will be well suited for.
Rise of Robot Work Force Stokes Human Fears (2014, December 15). Retrieved March 4, 2019, from https://www.nytimes.com/2014/12/16/upshot/as-robots-grow-smarter-american-workers-struggle-to-keep-up.html
Miller The Build-up: Good and Ready: After Slow Beginnings, a Big Push in Robotics now seems Imminent. (2014, March 29). Retrieved March 4, 2019, from https://www.economist.com/special-report/2014/03/29/good-and-ready
Marr The Key Definitions Of Artificial Intelligence (AI) That Explain Its Importance. (February 14, 2018) Retrieved March 4, 2019, from https://www.forbes.com/sites/bernardmarr/2018/02/14/the-key-definitions-of-artificial-intelligence-ai-that-explain-its-importance/#5fe2e5594f5d
News Releases – ITI Unveils First Industry-Wide Artificial Intelligence Policy Principles. (October 24, 2017) Retrieved March 4, 2019, from https://www.itic.org/news-events/news-releases/iti-unveils-first-industry-wide-artificial-intelligence-policy-principles
Robot automation will ‘take 800 million jobs by 2030’ – report (November 29, 2017) Retrieved March 4, 2019, from https://www.bbc.com/news/world-us-canada-42170100
Stillman, Jessica 21 Future Jobs the Robots Are Actually Creating (December 6, 2017) Retrieved March 4, 2019, from https://www.inc.com/jessica-stillman/21-future-jobs-robots-are-actually-creating.html
Hancock, Peter Are Autonomous Cars Really Safer Than Human Drivers? (February 3, 2018) Retrieved March 4, 2019, from https://www.scientificamerican.com/article/are-autonomous-cars-really-safer-than-human-drivers/
Authority of the House of Lords AI in the UK: ready, willing and able? (April 16, 2018) Retrieved March 4, 2019, from https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf
Stark, Harold As Robots Rise, How Artificial Intelligence Will Impact Jobs (April 29, 2017) Retrieved March 4, 2019, from https://www.forbes.com/sites/haroldstark/2017/04/28/as-robots-rise-how-artificial-intelligence-will-impact-jobs/#a10638f7687d
TED Matt Beane (2018, November). How do we learn to work with intelligent machines? Retrieved from https://www.ted.com/talks/matt_beane_how_do_we_learn_to_work_with_intelligent_machines?language=en#t-10332
TED Daniel Susskind (2017, December). 3 myths about the future of work (and why they’re not true) Retrieved from https://www.ted.com/talks/daniel_susskind_3_myths_about_the_future_of_work_and_why_they_re_not_true?language=en#t-640007