Re-Posts: An Untitled Opinion Editorial Piece (October 2017)

Hello! This is a series which I re-upload a number of selected writing assignments I’ve done during my university years to both share them with the world (after some edits here and there, of course) and archive some of my most memorable ones. Enjoy.

The rain is pouring down upon the polluted downtrodden city of Los Angeles. Former LAPD, Rick Deckard has fallen into a tough spot, dangling by only a slippery steel beam and a couple of loose fingers away from a gruesome death by gravity only to be saved by his recent nemesis, Roy Batty. Beaten up, bloodied and soaking wet, Batty crouched down to the speechless Deckard.

Batty coming to terms with his fate during some of the last scenes of Blade Runner (1982)

“I’ve seen things you people wouldn’t believe.” Batty started. “Attack ships on fire off the shoulder of Orion; I watched C-beams glitter in the dark near the Tannhauser Gate. All those moments will be lost in time like tears in rain.” The replicant reminisced in a painful staccato before uttering his last words, “time to die.”

The grand finale of Blade Runner (1982) is definitely one of the timeless masterpieces in all my experience as a personal fan of the cyberpunk genre. ‘Batty’, a biologically fabricated humanoid has portrayed more than enough humanity towards the end of his incredibly short life-span. He sought for survival, meaning and freedom from his inescapable fate as a slave to mankind. Along his journey, the replicant learned hatred, love, sadness, fear, all the very components of which make us all human.

Despite the line being so beautifully written and later expressed by actor Rutger Hauer, the reflection of mankind’s grim endeavor and its ill-fated creations remains. A time will come when our ‘tools’ are developed to the point of near absolute automaton for the sake of usefulness and by then, it would be too late for us all to realize our dependency and social integration with the perfect automata.

At the core of the dark allure of dystopian fiction lies its nature of a realistic cautionary tale. The dystopian setting usually does sound like a dangerous, scary and miserable place to be in. For example, the Hunger Games books and film adaptations had civilian massacres, public executions, famine, extreme prejudice against rebellion forces, you name it. The concept of dictatorial rule and manipulation of media in the Hunger Games are undoubtedly real however, the fictional part of it has been exaggerated to the point that human society became an estranged and unique world. While the hero’s journey of Katniss Everdeen sends a message about resistance against tyranny, the lone Blade Runner discovered empathy for the replicants.

LAPD replicant, Officer K. and his trusty flying police car in Blade Runner 2049. Image taken from Kotaku.com

Fast-forward to 2017, the cyberpunk classic has been reborn. Blade Runner 2049 is the long-awaited sequel to Ridley Scott’s adaptation of Philip K. Dick’s book ever since early 1982. Directed by Denis Villeneuve (Prisoners, Sicario, Arrival), starring Ryan Gosling, Jared Leto, Harrison Ford and Ana de Armas, the first screening on the 6th of October is highly anticipated by enthusiastic fans from around the globe.

While we don’t see either interplanetary colonies or the replicants as of yet despite how the first film was set in the year 2019, subjects such as robotics, advanced artificial intelligence, and the society’s integration with technology have never been so relevant in the history of civilization.

“Every civilization, was built on the back of a disposable workforce. But I can only make so many.” Niander Wallace (Jared Leto) lamented at the sight of the eerily exhibited bodies of Nexus replicant models, spiritual successors to the late Roy Batty in a trailer for Blade Runner 2049.

The obsolete Nexus models on display inside the Wallace Industries Headquarters. Image taken from Engadget.com

The upcoming face of a new workforce is far from rarity. Armies of robotic appendages are used in automobile factories,warehouse bots race around to manage the stock, even your average soda vending machines are, unsurprisingly, robots with simpler minds. The metallic muscles already have superseded their creators in the job market but furthermore, artificial brains are going to knock even more human workers out of the competition. For the cyberpunk enthusiasts, fiction has never been so real today.

The machines are learning fast and not without a good reason. Actually, it is the same reason as why we have replaced manual labor with non-humans in the first place, cost-efficiency. In the United States, the federal minimum wage rage is $7.25 an hour. In a workday, a human worker would still have to take break, eat meals, be insured, and kept productive constantly while still prone to random errors and constant workplace politics. Branch managers, human resource officers, accountants, and other similar tertiary level jobs are also required in order to maintain the well-being of unskilled workers and facilitate business. On the other hand, a self-driving truck or a barista machine could work tirelessly for lesser cost, fewer organizational hassle and significantly higher consistency. For instance, according to an article on Geek.com, the $30,000 burger flipping automaton designed, by Momentum Machines can put together up to 400 freshly grilled burgers in an hour which goes without saying that it will outperform any human cook ever lived.

Repetitive jobs are already condemned to bot takeovers. According to an article by Business Insider, the “degree of automation” refers to the percentage of the job which can be operated by automaton. While fully automated jobs don’t exist just yet, jobs like engraver, crop farm worker, laborer have at least 70% in degree of automation. But the new big leap isn’t about the bots ability to do but rather, their latest ability to make rational decisions and learn how to do variety of tasks. This is an era of machine learning as well as the mechanized market invasion.

The idea of Machine Learning, as an ability of artificial intelligence, was surprisingly not novel. Arthur Samuel, was an American pioneer in the field of computer gaming and artificial intelligence and he coined the term “machine learning” in 1959 which is a concept that focuses on the machine’s algorithms of decision, using provided data rather than having to specifically program everything for the machine.

Arthur Samuel Playing checkers on the IBM701 (1956.) Image taken from IBM.com

The 1960s however, wasn’t at all a great year for computerized automatons, the decade was more about rock and roll music, hippies and the cold war. It was until the World Wide Web was first launched by English scientist Tim Berners-Lee in 1989. Suddenly, the Information era blew up. Computers of various sizes and capacity were the gateway and they do collect tariffs in bits of personal information. According to the Internetlivestats.com, there were 3 billion Internet users around the world in 2014. Now combine that with the advent of Apple iPhone in 2007, 2.1 billion smartphone users in 2016 and we now have an immense amount of data generating in every minute. Outside of the numerous professionally published information like opinion editorials, research statistics and business reports, hashtags, tweets, likes, comments, shares, subscriber numbers, the social media is some of the biggest archives, made exactly for the machines to study human sociology and in many cases, install consumer influences (still under the command of human supervisors of course.)

Search engine suggestions, targeted ads follow each and every online consumer around everywhere. These are some of the visible executions by robotic marketers, derived from habits and behavioral trends. The input of your Facebook post about #RunBKK or #Marathon could lead the advertising bot to categorize you as an active runner and bombard you with Nike, Adidas, Puma products. That one time you went through an album by Muse on Spotify might have opened a floodgate of Muse ads on merchandise, collectibles, fan meets and concerts. The en masse database of what we all feel, see and do ironically becomes a trend, both predictable and controllable by marketers like a huge consumption machine itself. With the correct sample size and criteria, the analytical minds of business professionals could also be rendered obsolete soon after the human workers.

Outside of the impersonal, numbers and percentages logic in commerce, artificial intelligence researchers today are already expecting the man-made minds to effectively engage in moral dilemmas and decide upon the matter of life and death within split seconds. Almost like a homage to Isaac Asimov’s work, scientists at the MIT set up a peculiar website called the Moral Machine in previous year. There, a video introduction greets the visitors, its title consisting of an odd concept, the idea of Machine Ethics. On the Moral Machine, questionnaires with two choices in each are given to the participating guests and while they all feature cartoon-ish depictions of the average pedestrians, the content is absolutely gruesome. In each and every scenarios presented, a self-driving with a sudden brake failure would crash into either a concrete barrier, killing the passengers or swerve away into a crowd of pedestrians. Our job here is to help guide the artificial intelligence through the ethical dilemma and judge who lives and who dies. For example, letting the car run straight ahead without any intervention means mowing down two parents and a child but choosing to ram into a nearby concrete barrier instead would murder five innocent elders in the car’s passenger seats. Similar to the famous “trolley problem” thought experiment, the participants have shown a variety of difference values and verdicts via the scenarios involving inevitable killings. The difference between the trolley and the self-driving car is that the online participants or the judges are giving massive data input which would be analyzed and potentially utilized later on in order to improve the machine ethics in real-life situations like these.

“Who lives and who dies?” The user interface for the Moral Machine in action. Image taken from TrendHunter.com

Crowd sourced morality “doesn’t make the AI ethical,” said James Grimmelmann, a professor at Cornell Law School who studies the relationships between software, wealth, and power. “It makes the AI ethical or unethical in the same way that large numbers of people are ethical or unethical.” According to its given samples, the Moral Machine AI would decisively kill the least number of people as possible, it would also kill a criminal instead of a non-criminal, and it would always choose to kill a homeless person rather than a person who is not homeless. A death by democracy. It is terrifying to imagine how machines could possibly become an embodiment of humanity not only in the aspects of love and harmony but also those of discrimination and prejudice.

In this era of rapid technological advancements, it seems as though the many parts of a singular machinery are scattered throughout the latest history of scientific innovation. One by one, the pieces of humanity are fabricated and improved beyond its original version.The brain is the massive cyber network and handheld devices. The body could be drones, self-driving cars and robotic arms. With more and more humans leaving the job market and relevant fields of expertise, all that’s left to begin the replicant revolution is merely an assembly required.

In the futuristic world of human desolation, the creator and God to the replicants, Eldon Tyrell of the Tyrell corporation stated his Impressum and slogan, “more human than humans.”

Sources:

https://www.adeccousa.com/employers/resources/job-market-update/

http://reports.weforum.org/future-of-jobs-2016/employment-trends/

https://insidebigdata.com/2016/12/14/how-machine-learning-is-changing-the-way-the-back-office-does-business/

https://en.wikipedia.org/wiki/Machine_learning

https://www.forbes.com/sites/bernardmarr/2016/12/06/what-is-the-difference-between-artificial-intelligence-and-machine-learning/#4bd95a862742

http://www.businessinsider.com/jobs-replaced-by-robots-2017-9

https://www.geek.com/tech/400-burger-per-hour-robot-will-put-teenagers-out-of-work-1703546/

http://www.internetlivestats.com/internet-users/

http://www.huffingtonpost.com/dave-astor/why-do-we-like-dystopian-novels_b_1979301.html

http://moralmachine.mit.edu/

https://theoutline.com/post/2401/what-would-the-average-human-do

Beans juice enthusiast and feline management expert. Currently in Bangkok, Thailand. My opinions are my own.