I thought working for a reasonably large tech company would be insightful. This would be an opportunity to make leaps and bounds in my knowledge and ability. I expected to learn some “secrets” about how successful companies manage themselves and how employees contribute to their company. I pictured a summer where I got to perform well and feel great while doing so. Unfortunately, I neither felt accomplished, or any more knowledge than before the summer began.
The Experience
I had a lot to do at the beginning of the summer. To become effective on my team I had a lot to learn. Every day consisted of many diagrams, questions, lectures, and a lot of unclear responses that took time to digest. I enjoyed this stage very much. There was always something to do and an obvious path to follow that always led to more work. However, my undying curiosity slowly wore out as I started to see some patterns. Recycling old products results in “fresh” products, revolutionary projects do not meet the “criteria” to be pursued, and priorities do not reflect the mission. The day began to go by a lot faster as less and less got done.
The lack of innovation broke my heart. Recycling ancient product lines takes priority over exploring new technology to develop truly superior products. Instead of discovering future capabilities through research, products created by other corporations are bought for the customer. Better approaches seemed so obvious at first that I began to question the thoughtfulness and standards accepted at the company. Too many deliveries to the customer do not get created internally. Outsourced products cost shocking amounts of money despite the imperfect solutions with unreliable support to fix issues. Management consistently struggles to obtain fixes for systemic problems from outside companies. Implementation of cover ups in internal products takes the place of proper solutions from contracted products.
A handful of projects were exploring the capabilities of the company to advance the industry. However, there were always excuses for why the industry did not accept the new innovations being proposed. Customers can’t move in a more innovative direction without risking safety and reliability. There is no motivation to accelerate the advancement of the industry because every single customer is satisfied with the what exists. The story is that the customer is scared of moving to a radically new product. But I believe no one is willing to go through the hard work of coming up with an improved solution that’s wildly different and provides an amazing experience because it’s so much work. Huge company’s take control of the industry preventing small start-ups to clear a niche.
Almost every day feels like a waste of time despite all of the opportunities I see for my future here. One of the first days a couple of engineers were bullshitting when they got onto the topic of their careers. I started asking some questions when one shared that in hindsight, he would do things a lot differently. This got me thinking a lot about what I really want to do in life and what my future could look like. Weeks into the summer I could not understand his essential role to this company. Seeing someone with no passion perform so well confused me even more. This man developed so much content and supported the company so well it blew my mind. But the company continues to provide just enough to meet the customers expectations.
Reflection
Price’s Law gives insight into large companies: the square root of the employees perform half of the work. For example, a 225 person company likely has 25 people performing half the work. I never fully absorbed this concept until I began to see it in person. Watching smart and talented people slave away for similar compensation as their useless peers destroys my confidence in this system. However, 10-year employees have a significant advantage over new hires. Approaching a problem requires a full understanding of the business dynamics and all the systems at play. Learning the workplace environment takes years longer than it should due to the lack of documentation and tools to properly train employees.
The idea of job security and the promise of a paycheck every two weeks sounds amazing. However, watching smart people with lives dedicated to a company has left me to question this norm. I believe a career all about something other than myself would leave me both painfully unsatisfied and overwhelmingly regretful. Imagining a future in the position of my coworkers terrifies me. Restricted to weekends and a couple hours a day for chasing what I love has led me to search for something better.
Artificial intelligence has been a personal topic of interest for many years now. With arguments ranging from their level of consciousness, superior and inferior abilities, and what affects they will have on the economy, I have always found the subject to be interesting. And it is this last topic that I have prepared to share with you today. I hope to present the debate fairly, 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 has 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 on funding, research, and the development of 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 the 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 perform 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 Ford 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 were the thousands of jobs that were created due to this job displacement. With the invention of the steam engine came the end of the horse cargo 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-fair 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, it opens a whole new sector of better, more efficient jobs.
We see this trend continuing with the emergence of artificial intelligence. 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, job markets are forever changing and should be allowed to maintain a healthy economy.
Yet there remains an 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 their labor. In the same way as a commodity, our workability is sold and bought depending on the supply and demand of that product.
Historically, human labor has always been a superior commodity. One with both a constant demand and supply. The issue 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 workability to A.I. This is an issue because without the demand of human workability 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 workability 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 collision 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 a hundred times better than any human, but that very well may never be a reality. Sadly, we will not know if it is real 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 workers ability altogether. 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 whichever one occurs we will be well suited for.
Work Cited
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
Have you ever taken a second to question where your daily motivation comes from? Ever considered what makes you wake up in the morning and begin another day? I for one have. And honestly, it allowed me to consider some remarkable information and ideas about how and why we function.
The human race has three known motivations, three driving forces that get us to do everything we do every day. The first is our motivation to live. For example, when one is thirsty, he or she is motivated to drink a glass of water. This motivation is rather simple and seemingly self-explanatory. A species unmotivated to live will simply cease to. So, of course, we are motivated to live because if we were not, then we would not have made it this far.
Our second motivation is through rewards and punishments. We see this in any modern, capitalist business. If one works hard, they get a raise. If one works inefficiently, they are fired. This idea has been implemented into the majority of businesses for the last hundred years.
We also see examples of this in how our government runs. When people follow the law, they are provided with rights, such as the ability to vote, health services, and basic freedoms. When people break these laws, all those rights vanish and are replaced with forceful imprisonment. Fear to break the law has been a tactic used for thousands of years and has been working relatively well.
Economies and governments, around the world, use this innate response to get us to do what we are told. It is the current primary tool within most first world countries, which is not terrible. It is a lot better than using the first motivation, I would not enjoy a world where we are starved for going above the speed limit. This is why I do not totally hate our current system, but I also do not totally love it either.
The last of the motivations is our drive to expand the knowledge and skills of ourselves and our community. In an experiment to test this third motivation, researchers gave dozens of chimpanzees a simple jigsaw puzzle once a day. There was no incentive of any sort to do the puzzle, no food attached, no zookeeper pushing the chimps toward the puzzle, nothing. Regardless, every day the chimps would work vigorously to complete the challenge. As each day passed, the chimps became experts at these simple games. On average, they continually beat their times from the day before as the weeks went on.
These results made a firm conclusion that there must be a third motivation since neither of the first two were being fulfilled in this experiment. They found that we are simply motivated to learn, which makes complete sense. By improving our knowledge and skills we are more equipped to handle any future situations presented to us; as well as giving us something to be passionate about. Right now, I am writing, and you are reading, because we want to be more insightful on our motivations. We want to be knowledgeable people because the more knowledge we have, the more we can hopefully help ourselves and others around us.
Therefore, with all of this in mind, I wonder why this isn’t our motivation in society? Why do we rely on rewards and punishment, rather than having people simply fulfill their desire to better themselves? I believe the answer to these questions is outdated.
A separate experiment was later carried out, which can be seen as the battle of the second and third motivation. In this experiment, participants were provided with a box filled with tacks, a candle, and matches. The participants had to find a way to keep the candle lit as it stood off the ground, only using the materials provided. One group of participants were given the same amount of money no matter how long it took them. The other group was told that they would be paid twice as much if they performed in the top twenty-five percent. The results found that the group given no additional reward did much better than the group with a reward.
Now, if you have not already figured it out, the way to solve this problem is to realize that the box containing the tacks can be used as well. So, the participants had to light the candle and tack the box to the wall and then rest the candle in the box. This made the experiment difficult since the tools were not obviously presented. When the second experiment began, the box was left out and explained as a fourth item. This time, the group with the incentive outperformed the other.
The conclusion drawn from this data is that rewards and punishments work better for simple jobs. This makes sense, as we tend to get tunnel vision when we are pressed for time, rather than having all day to carry out an action. The thing is, a hundred years ago, tunnel vision was okay, jobs were simpler back then. In the early 1900s, roughly five percent of jobs used cognitive thinking skills. Now, around thirty-five percent of jobs use those skills, and it is only uphill from here.
Being in the middle of the digital age, the human race has never needed to be as creative as we are now. Jobs are requiring outside of the box thinking, and our current business structure is not built for it. This system uses a form of motivation that is becoming increasingly counterintuitive.
So, which system is better? What structure could allow for the betterment of both laborers and the businesses themselves? And I’m going to do something a bit unconventional here, I’m not going to answer this question. I can not think of a solution that does not require ideal situations or one that is remotely feasible in this day and age.
This is why I will leave you with a question with no answer. Rather than writing a solution I do not totally agree with, or one I do not totally understand, I would like to hear your input. So, please feel free to contact me at [email protected].
