Automated decision-making systems or algorithms are playing an increasingly significant role in public administration and civil rights space. In his book “Voices in the Code: A Story About People, Their Values, and the Algorithm They Made,” David Robinson investigates and contextualizes the story of the Kidney Allocation System, which as a result of cross-disciplinary collaboration among surgeons, clinicians, data scientists, public officials, advocates, and patients, over the course of 10 years, evolved into a relatively inclusive and accountable decision-making technology. Through this story, the author discusses the most fundamental issues related to the design and management of public-interest algorithms.
Category: Artificial Intelligence
On Facial Recognition Technology
Why the US needs federal law on Facial Recognition Technology?
Originally published on Intersect: The Stanford Journal of Science, Technology, and Society
Introduction
Since the beginning of the 2000s, Facial Recognition Technology (FRT) has become significantly more accurate and more accessible. Both government and commercial entities use it in increasingly innovative approaches. News agencies use it to spot celebrities at big events. Car companies install it on dashboards to alert drivers falling asleep at the wheel. Governments have used it to track Covid-19 patients’ compliance with quarantine regimes, or to reunite missing children with their families.[1] However, as the use of technology has become more widespread, the controversies around it have also grown. The technology offers tremendous opportunities, but there are reasons to be concerned about its impact on privacy and civil liberties, if it is not used properly. In this paper, I make a brief introduction to facial recognition technology, look separately at commercial and government applications of it, and present my argument why the US needs a federal legislation on FRT.
1. The Nuts and bolts of FRT
Facial recognition falls under the category of biometric data. The software pinpoints facial landmarks, measures the distance between them, and creates a geometric shape of your face.[2] It is less accurate than other biometric identifiers, such as iris and or fingerprint scanning, because of two reasons. One, facial images are not always of high quality. Two, unlike other biometric identifiers, facial features can change over time, due to aging, plastic surgery, cosmetics, effects of drug abuse or smoking, etc.[3] However, FRT has become a lot more popular, because it can be used remotely and is a lot easier to apply in high traffic places.
Today, facial recognition is used mainly for two reasons. First, face verification, also, known as “one-to-one” matching. It is used to verify that you are who you say you are. It is commonly applied to unlock a smartphone or replace ID checks.[4] Second, face identification, also, known as “one-to-many” matching. Usually used to search for persons of interest, where you start the search with an image of a person you do not know to determine his/her identity.[5]
Another category is facial analysis, where the algorithm analyses facial features to determine “age, gender, ethnicity, emotions, fitness for certain jobs.”[6] For example, McDonald’s has used facial analysis in its Japanese stores to check if the employees are smiling, when assisting the customers.[7] Walmart is working on a facial analysis system that will help to process the shoppers’ mood while they are in a store.[8] There have been numerous reports that China is using facial analysis to track ethnic Uighurs, a largely Muslim group in the western province of Xinjiang. Reportedly, the technology can distinguish “Uighur/non-Uighur attributes”, and allows the Chinese police to track the movements of the minority group.[9] While the reports of the Chinese government crackdown on Uighurs have been confirmed, the credibility of the software distinguishing Uighurs purely on facial features is questionable.[10][11]
These news stories give us a good idea about how the FRT can evolve in the future, but at this point in time, facial analysis software is mainly in the research and trial phase. So, this paper will keep the focus on facial recognition. The truth is even facial recognition technology is prone to mistakes. On several occasions, police have arrested the wrong person, because of a mistake by the FRT. In June 2020, Detroit Police Chief said that the software they use misidentifies 96% of the time, so they use it only to narrow down their search sample.[12] In 2018, American Civil Liberties Union tested the facial recognition software of Amazon to compare the images of members of Congress with a database of 25000 mugshots of convicted criminals.[13] Amazon’s “Rekognition” software falsely identified 28 members of congress as criminals. (Amazon’s software is available for public use and cost the ACLU only $12.33).
The FRT is more likely to make a mistake with women and people with darker skin tones than with white men. In the ACLU test, 40% of the false matches were African Americans, even though they comprise only 20% of Congress. In 2018, MIT study of gender and skin-type bias in commercial artificial-intelligence systems showed a 34.7% error rate for dark-skinned women, and only 0.8% for light-skinned men.[14] There are two likely explanations for this bias: darker skins do not reflect light as well as fair skin tones; 2. smaller sample size of minorities’ images.
However, this is a changing pattern and every year the FRT is getting better at recognizing people of all skin tones. A big reason for this is that both the quantity and the quality of the facial images are going up. According to the National Institute of Standards and Technology (NIST) under the US Department of Commerce, the best face identification algorithm in 2014 had an error rate of 4.1%, while by 2020 the leading algorithm had an error rate of less than 1%.[15]
2. Commercial use of FRT
The market for FRT emerged only around 2001, but it has been dynamically growing ever since. According to various estimates, it is expected to reach somewhere between 7 and 10 billion USD in 2022. More and more organizations are using FRT to replace ID checks. Schools use it to track attendance and/or keep away unwanted people. It is widely used to group and catalog images and video files. We have already mentioned some other innovative ways how FRT can be used. However, it is important to note that not all uses of the technology have equal social impact and the US Congress needs to take action and set legal boundaries for commercial use of the FRT.
If we go back to the two sub-categories of facial recognition we discussed earlier, the main issue in the commercial use of the FRT is around facial identification. In the case of facial verification or one-to-one searches, there is a set limit to the database and everyone involved is usually aware that they are part of a certain facial verification system. Usually, facial features of more people are processed to train the algorithm, but that is less problematic since those images are anonymized. In the case of facial identification or one-to-many searches, there is no set limit to the databank and many people are not aware that their information is on a certain database. So, this raises a question about consent.
Can the companies use the images we share on public platforms online to build their database without asking for permission? On November 2, 2021, Facebook announced that it is shutting down its facial recognition system and deleting “more than a billion people’s individual facial recognition templates”.[16] That is why we no longer see little squares around faces when we scroll over Facebook photos. The decision came 6 months after Facebook had to pay $650 million for violating the Illinois Biometric Information Privacy Act (BIPA), which bans collecting and storing of the facial geometry of Illinois residents.[17] Facebook made an elaborate argument that it inflicted no harm on its users, but still lost the case, since BIPA clearly states that processing the biometric data of Illinois residents without opt-in consent is illegal.[18]
Most big tech companies in the US have or had their own facial recognition software, but following the controversies over the racial bias issue, they have restricted investments in FRT. Within a week in June 2020, IBM announced that it is getting out of the facial recognition business altogether, while Microsoft and Amazon declared a moratorium on selling their facial recognition technology to law enforcement agencies. However, these tech giants are not the biggest in the facial recognition market. Table 1 lists 10 of the biggest companies in the FRT market.
Table 1: Some of the biggest companies in the FRT market
| Company | Country | Founded in | Web info |
| Ayonix | Japan | 2007 | https://ayonix.com |
| Clearview AI | USA | 2017 | https://www.clearview.ai/ |
| Clear Secure | USA | 2010 | https://www.clearme.com |
| Cognitec | Germany | 2002 | https://www.cognitec.com/ |
| iOmniscient | Australia | 2001 | https://iomni.ai |
| Kairos | USA | 2012 | https://www.kairos.com |
| Megvii | China | 2011 | https://en.megvii.com |
| NVISO | Switzerland | 2009 | https://www.nviso.ai/en |
| Oosto* | Israel | 2015 | https://oosto.com |
| SenseTime | China | 2014 | https://www.sensetime.com/en |
In January 2020, The New York Times investigation revealed that a New York based company Clearview AI built a database of 3 billion images scraped from the internet and is selling its software to 600 law enforcement agencies.[19] A month later, BuzzFeed did a follow-up investigation and found that Clearview “had provided its facial recognition tool to more than 2,200 police departments, government agencies, and companies across 27 countries.”[20] Now the company is facing lawsuits in at least 7 countries, including the United States, Canada, Australia, Germany, United Kingdom, France, Italy and Greece.[21] In November 2021, UK government imposed a $23 million fine on Clearview, for violating their national data privacy law. Twitter, Google, and Facebook have also sent cease-and-desist letters requesting it stops using the public information of their users.[22]
When sued under BIPA, Clearview responded that it will delete data of all the residents from Illinois. Currently, on its website Clearview offers an opt-out form for residents of Illinois and California, which also has legislation similar to BIPA.[23] The United States Congress should pass federal law similar to BIPA or California’s Consumer Privacy Act that would introduce clearly defined limits for commercial use of the FRT. However, considering that on the other side of the debate, this technology adds value to the efforts of the security agencies, the federal legislation should not be overly restrictive. An opt-out consent might be a reasonable solution.
We should, also consider that with every passing day, it is becoming easier to build a search engine for photo matching, like Clearview. Two weeks after the attack on the US Capitol on January 6th, 2021, a website named Faces of the Riot appeared online, which catalogued the faces of 6000 individuals who were present during the incident, extracted from 827 videos posted on social media platform, Parler. The author of the website, who self-identified as a student in the Washington DC area, told the journalists that he intended to help the police investigation and that he used only open-source software.[24] Thus, a heavily restricted legal environment might not achieve the intended purpose, but create a lucrative black market for the FRT. The federal law on commercial use of FRT should define feasible legal boundaries and find the right balance between the right to privacy and public security efforts.
3. Government use
The number of governments using facial recognition is growing every year. They use it mainly for security and traffic control purposes. However, facial recognition technology and the artificial intelligence behind it are very powerful tools that can be used in many different ways that are not always in the public interest. The federal legislative bodies need to intervene and establish certain standards, impose responsibilities and delineate restrictions for the public use of the FRT.
If facial recognition becomes overly pervasive, then independent of the intent, it could lead to constraints on public freedom. It is important for governments to evaluate the potential impact of facial recognition on civil liberties and establish ethical principles and regulatory guidelines before expanding the use of FRT. A privacy impact assessment by The International Justice and Public Safety Network, which is comprised mainly of seasoned law enforcement officers, mentions that “the mere possibility of surveillance has the potential to make people feel extremely uncomfortable, cause people to alter their behavior, and lead to self-censorship and inhibition.”[25] There are various reports that this is happening in China, where facial recognition is very commonplace. German journalist, Kai Stritmatter, who has studied China for more than 30 years writes about the government use of facial recognition in China: “What the Communist Party is doing with all this high-tech surveillance technology now is they’re trying to internalize control. … Once you believe it’s true, it’s like you don’t even need the policemen at the corner anymore, because you’re becoming your own policeman.”[26] In order to provide a better context, I present a brief overview of the government uses FRT in China and the European Union.
China
According to one estimate in 2020, there were around 770 million surveillance cameras installed around the world and roughly 54% of those cameras were in China.[27] Based on the number of cameras per 1000 people 16 out of the top 20 most surveilled cities are in China.[28] Facial recognition technology is omnipresent in most parts of the country and is used by both government and private entities. For example, at KFC China you can pay by smiling into a camera. According to new guidelines passed by China’s Supreme People’s Court, since August 1, 2021, commercial venues, such as hotels, shopping malls, and airports, need to get consent from customers to use facial recognition.[29] The new rules also impose restrictions on the use of the technology and responsibilities for protecting it.[30] The decision of the Supreme People’s Court came about a year after residents in Honk-Kong staged mass protests against the ubiquitous facial recognition and toppled 20 lampposts equipped with cameras.[31] However, there are no restrictions on the government use of the FRC and it continues to be an integral part of the social credit score system. If a Chinese citizen decides to jaywalk on a street equipped with facial identification camera, she will receive a private message with a fine and that will impact negatively on her social credit score.
European Union
Two weeks ago, a coalition in the German parliament, led by the ruling Social Democratic Party said they want to ban “biometric recognition in public spaces as well as automated state scoring systems by AI.”[32] In April of 2021, European Commission proposed a new regulation titled Harmonized Rules on Artificial Intelligence, which also suggests a ban on facial recognition, absent certain exceptions for security purposes. According to the proposed regulation, the use of “real time remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement is prohibited unless certain limited exceptions apply.”[33] Exceptions include: strictly necessary for a targeted search of potential victims of a crime, prevention of a specific imminent threat to life, or the detection or identification of a perpetrator. The act has already been criticized and various improvements have been offered, but is a great starting point on this very important issue.
The United States
The United States, the world leader in AI industry, does not have a regulation on the fair use of facial recognition either, but the issue is on the agenda of political debates in Congress. In March 2021, National Security Commission on Artificial Intelligence, a bipartisan working group, released its final report, where it recommends the “Congress to require prior risk assessments “for privacy and civil liberties impacts” of AI systems, including facial recognition.” In 2020, “Facial Recognition and Biometric Technology Moratorium Act”, was proposed, but did not pass. Such a moratorium would give time to improve the accuracy of the facial recognition technology and conduct an assessment of its potential implications.
4. Conclusion
One of the biggest concerns in the United States has been the bias of the facial recognition software. As discussed earlier facial recognition systems have been biased against minorities, which has led to several wrong arrests by police. For example, in the summer of 2020 Robert Williams, a resident of Michigan was detained and kept in the police station overnight because a facial recognition algorithm made a flawed match. Usually, these cases get resolved within hours, but it creates a tremendous inconvenience for innocent people and their families. The United States needs a national law that sets out the legal framework for public use of the FRT and addresses all the possible side effects. For example, an effective way to address this issue would be to have third-party testing and approval for the facial software used by police.[34] They would use only the software that is certified by an independent agency. It is also important that police do not use low quality images in their queries.[35]
Facial recognition technology is a powerful new tool that requires a comprehensive approach, which takes into account its impact on the economy, national security, and civic life. It presents incredible opportunities, especially in aiding the work of law enforcement agencies, but finding the right balance between security and civil liberties will be one of the biggest challenges. Federal law is required to regulate both commercial and government use of the FRT and establish quality and credibility standards for the facial recognition software. The law should not force the police to work with analog technologies in a digital age,[36] but they should enforce high ethical standards that will minimize the potentially negative impact on civic life.
[1] Nagaraj, A. (2020, Feb 14). Indian police use facial recognition app to reunite families with lost children. Reuters
[2] Symanovich, S. (2021, Aug 20). What is facial recognition? How facial recognition works. Norton.
[3] Facial Recognition. (2021, October). INTERPOL.
[4] Nature Editorial, & Castelvecchi, D. (2020, Nov 18). Is facial recognition too biased to be let loose? Nature.
[5] Ibid
[6] Ibid
[7] Kaspersky. (2021, August 23). What is Facial Recognition – Definition and Explanation. Kaspersky.Com
[8] Nothing personal? How private companies are using facial recognition tech. (2020, Jun 8). TechHQ.
[9] Mozur, P. (2019, May 6). One Month, 500,000 Face Scans: How China Is Using A.I. to Profile a Minority. The New York Times
[10] Crawford, K., Dobbe, R., Dryer, T., & Fried, G. (2019, December). 2019 Report. AI Now Institute. New York University
[11] Rollet, C. (2019, November 11). Hikvision Markets Uyghur Ethnicity Analytics, Now Covers Up. IPVM.
[12] Koebler, J. (2020, June 29). Detroit Police Chief: Facial Recognition Software Misidentifies 96% of the Time. Vice.
[13] Snow, J. (2018, August 3). Amazon’s Face Recognition Falsely Matched 28 Members of Congress With Mugshots. American Civil Liberties Union.
[14] Hardesty, L. (2018, February 12). Study finds gender and skin-type bias in commercial artificial-intelligence systems. MIT News | Massachusetts Institute of Technology.
[15] Crumpler, W. (2020, April 14). How Accurate are Facial Recognition Systems – and Why Does It Matter? Center for Strategic and International Studies.
[16] Pesenti, J. (2021, Nov 3). An Update On Our Use of Face Recognition. Meta.
[17] 740 ILCS 14/ Biometric Information Privacy Act. (2008, October 3). Illinois General Assembly.
[18] MacCarthy, M. (2020, Aug 20). Who thought it was a good idea to have facial recognition software? Brookings.
[19] Hill, K. (2021, November 2). The Secretive Company That Might End Privacy as We Know It. The New York Times.
[20] Mac, R. (2020, May 8). Clearview AI Says It Will No Longer Provide Facial Recognition To Private Companies. BuzzFeed News.
[21] Webster, S. (2021, May 27). Clearview AI Hit With Dozens of Lawsuit in Europe Over Method of Collecting Data. Tech Times.
[22] Julia Horowitz (2020, Jul 3). Tech companies are still selling facial recognition tools to the police. CNN Business
[23] Illinois Opt-Out Request Form. (2021). Clearview AI. Retrieved December 9, 2021, from https://clearviewai.typeform.com/to/HDz8tJ?typeform-source=www.clearview.ai
[24] Greenberg, A. (2021, January 20). This Site Published Every Face From Parler’s Capitol Riot Videos. Wired.
[25] Garvie, C., & Moy, L. M. (2019, May 16). America Under Watch | Face Surveillance in the United States. America Under Watch – Real-Time Facial Recognition in America. https://www.americaunderwatch.com
[26] Davies, D. (2021, Jan 5). Facial Recognition And Beyond: Journalist Ventures Inside China’s ‘Surveillance State’. NPR.
[27] Keegan, M. (2020, August 14). The Most Surveilled Cities in the World. US News.
[28] Bischoff, P. (2021, May 17). Surveillance camera statistics: which cities have the most CCTV cameras? Comparitech.
[29] Dou, E. (2021, July 30). China built the world’s largest facial recognition system. Now, it’s getting camera-shy. Washington Post. https://www.washingtonpost.com/world/facial-recognition-china-tech-data/2021/07/30/404c2e96-f049-11eb-81b2-9b7061a582d8_story.html
[30] Ibid
[31] Fussell, S. (2019, August 30). Why Hong Kong Protesters Are Cutting Down Lampposts. The Atlantic.
[32] Heikkilä, M. (2021, November 24). German coalition backs ban on facial recognition in public places. POLITICO.
[33] HARMONISED RULES ON ARTIFICIAL INTELLIGENCE. (2021, April 21). European Union Law.
[34] MacCarthy, M. (2021, May 25). Mandating fairness and accuracy assessments for law enforcement facial recognition systems. Brookings.
[35] Hill, K. (2020, August 3). Wrongfully Accused by an Algorithm. The New York Times.
[36] Porter, T. (2019, March 21). The debate on automatic facial recognition continues. Surveillance Camera Commissioner’s Office.
Can AI be creative?
More than 2000 years ago, Plato made several interesting references to the notion of creativity, in the Socratic dialogues. In Meno, Socrates claims that “when poets produce truly great poetry, they do it not through knowledge or mastery, but rather by being divinely “inspired” by the Muses”. In another dialogue, Socrates contemplates the origins of new knowledge, which can be interpreted as creative thinking. Socrates wondered how can existing knowledge evolve into new ideas. When asked by Meno, “will we say, of a painter, that he makes something?”, Socrates responded, “no, he merely imitates”.
AI can be very good at imitating and learning from the creative works of humans. The below painting of the Healy Hall at Georgetown University, was produced by the Deep Dream Generator, an AI project sponsored by Google. I put in an image of Healy Hall, chose the “Starry Night” painting of Van Gogh as an overlay, and the program put out this painting within a minute. I find it aesthetically pleasing, but I understand it is not a completely original work. Nonetheless, do not all students of art learn by imitation? Can Artificial Intelligence learn to be truly creative?
“Creative souls and glory seem,
Submissive and subtle and soft and serene.”
These two lines were produced by another Google project AI poem generator when I put in my keyword, creativity. The algorithm has learned to write poems “by reading over 25 million words written by the 19th-century poets.” Compare that to the below poem written by Lord Byron in 1816 during the First Industrial revolution.
“As the Liberty lads o’er the sea
Bought their freedom, and cheaply, with blood,
So we, boys, we
Will die fighting, or live free,
And down with all kings but King Ludd!”
– Lord Byron, 1816
Creativity is a challenging concept to define, but it is not difficult to recognize. Clearly, on a creativity scale, AI falls far behind Byron. By the way, Byron was not a Luddite but had sympathies for their cause. (Luddites were a radical anti-technology movement in 19th century England.) Interestingly, Lord Byron is also the father of Ada Lovelace, who is often described as the world’s first computer programmer. Lovelace is credited for creating the first algorithm that was put to use in her friend Charles Babbage’s Analytical Engines. Lovelace also proposed that “until a machine can originate an idea that it wasn’t designed to, it can’t be considered intelligent in the same way humans are.”
In 2001, this approach inspired a group of engineers led by Selmer Bringsjord to come up with the Lovelace test, which many computer scientists consider a better replacement for the outdated Turing test. A computer can pass the Lovelace test only if it produces an outcome it was not programmed to. For example, a novel idea or an original painting. However, there is one more condition of the Lovelace test: the software output should surprise the human designer of the program. She should not be able to tell how the program achieved that outcome.
To this day, it is an open question whether any AI can pass the Lovelace test. In 1997, World Chess Champion Garry Kasparov (originally from my hometown Baku) lost to chess-playing supercomputer Deep Blue. Many people believe that mastering chess is associated with creative thinking. Deep Blue was calculating between 100 and 200 million positions on a 64-square chessboard, but it was following grammatical boundaries prescribed by its designers. The scientists behind Deep Blue at Carnegie Mellon University cannot beat the world champion in chess, but their brainchild can. Deep Blue’s victory over Kasparov marked a major milestone in the development of AI, but it did not prove that AI can be creative.
Maybe the challenge is that creativity belongs in the arts domain, and we are trying to explain it scientifically. Albert Einstein famously said “It would be possible to describe everything scientifically, but it would make no sense. It would be a description without meaning—as if you described a Beethoven symphony as a variation of wave pressure.” The founder of psychoanalysis, Sigmund Freud believed that pain and repression are necessary ingredients for creativity. Does this mean we will have to teach AI to experience pain, so it can be creative?
Humans have been creative since the beginning of days, but across the globe, ancient cultures did not have a word to express creativity. The modern notion of human creativity emerged only in the age of Enlightenment in Europe, and it became a popular catchfrase during the 20th century. People applied it to the course of history and identified it as one of the driving forces behind our evolution. Various studies have demonstrated that even some animals have creative potential, but none of them can be a rival to human creativity. Now, recent breakthroughs in technology have inspired many ideas about the prospective of machines to compete with human creativity. However, there is no conclusive answer due to two reasons: there is no clear philosophical definition of creativity and AI is rapidly evolving.
References
Devlin, E. (2019, May 2). Create a personalized poem, with the help of AI. Google. https://www.blog.google/outreach-initiatives/arts-culture/poemportraits/
Kaufman, S. B. (2014, May 12). The Philosophy of Creativity. Scientific American Blog Network. https://blogs.scientificamerican.com/beautiful-minds/the-philosophy-of-creativity/
Miller, A. I. (2020, February 1). Machines have learned how to be creative. What does that mean for art? Salon. https://www.salon.com/2020/02/01/machines-have-learned-how-to-be-creative-what-does-that-mean-for-art/
Pearson, J. (2014, July 8). Forget Turing, the Lovelace Test Has a Better Shot at Spotting AI. Vice. https://www.vice.com/en/article/pgaany/forget-turing-the-lovelace-test-has-a-better-shot-at-spotting-ai
Plato. The Republic. (1998). The Project Gutenberg. https://www.gutenberg.org/files/1497/1497-h/1497-h.htm
From cybernetics to posthumanism: Biological humans vs synthetic machines
Cyberspace, cybersecurity, cyberinfrastructure and cyborg are some of the most popular words in modern vocabulary. If we look up the etymology of the prefix cyber, it is an abbreviation of cybernetics, which in turn traces its roots back to a Greek word “kybernētēs” that means steersman, governor or pilot. In the mid XX century cybernetics emerged as a transdisciplinary scientific approach, which applies to engineering and computer science, as well as to philosophy and psychology. One of its many definitions is that cybernetics is “the study of systems of any nature which are capable of receiving, storing, and processing information so as to use it for control” (Umpleby, 1982). Since its first public introduction, cybernetics paved a new path of research comparing human mind and computer machines. Over the decades, this line of inquiry has evolved and gained new layers as both the computer and cognitive sciences have advanced and reached new frontiers. By now there is a substantial scientific literature, which argues that in the near future we will be able to upload human mind onto computers, the line between biological human and synthetic machine will dissolve, and humans will no longer be identified by their physical bodies.
Modern cybernetics emerged in the post-World War II period, as a result of the Macy Conferences, but first scholarly works comparing humans to machines go back to the philosophers of the French Enlightenment in the 18th century. For example, in 1748 Julien Offray de La Mettrie published the book “Man a Machine”, where, as the title suggests, he argued that humans are basically machines. However, neither La Mettrie, nor his like-minded contemporaries such as Pierre Cabanis, and Baron d’Holbach had the depth and breadth of knowledge that the scientists attending Macy’s conferences had. Held in New York between 1941 and 1960, Macy Conferences aimed to stimulate a cross-disciplinary scientific discussion. The conferences were attended by the most influential scientists of the century including physicists John von Neumann and Heinz von Foerster, mathematicians Norbert Wiener and Claude Shannon, neurophysiologists Warren McCulloch and John Young, anthropologist Margaret Mead, psychologist Heinrich Klüver and psychiatrist Ross Ashby, sociologist Paul Lazarsfeld, ecologist George Hutchinson, among many others. This created a rare opportunity for the emergence of a transdisciplinary concept like cybernetics.
Norbert Wiener first introduced the cybernetics to general public in 1948 in his seminal book “Cybernetics: Or Control and Communication in the Animal and the Machine.” Wiener was a child a prodigy, who earned his BA in mathematics at the age of 14 and enrolled in graduate studies in zoology at Harvard, but a year later transferred to Cornell, where he completed a graduate program in philosophy by the age of 17. This background explains how in his research Weiner is able to intertwine mathematical formulas with philosophical ideas. His first book on Cybernetics includes chapters “Computing Machines and the Nervous System”, “Cybernetics and Psychopathology”, “On Learning and Self-Reproducing Machines”, where one of the underlying themes is the comparison of human mind and computing machines. For example, Wiener writes that “a very important function of the nervous system, and, as we have said, a function equally in demand for computing machines, is that of memory, the ability to preserve the results of past operations use in the future” (Wiener, p. 121).
Another giant in the field of cybernetics is Ross Ashby, whose books “Introduction to cybernetics” published in 1956 and “Design of a Brain” from 1960, made him one of the most influential voices in the field of cybernetics. Psychiatrist by profession, Ashby analyzed the human mind as a complex system, and proposed to simplify it to well-defined constraints, rules and algorithms that shape our thinking and behavior. Ashby believed that cybernetics lifted the mystery of “brain and its higher functions” (Ashby, R. Mechanisms of Intelligence, p. 334) and that if properly taught future scientists will be able to “to demonstrate that the science of brain-like mechanisms is essentially clear, practical and useful” (Ashby, R. Mechanisms of Intelligence, p. 334).
From the perspective of cybernetics human mind is a complex system, that receives, stores, and processes information, which makes it essentially similar to a computing machine. The main issue is to find the right code and build a machine that is powerful enough. In many ways, the computational power of modern artificial intelligence can surpass that of a human brain, but can it replace the human mind completely is another question. One of the most outspoken scholars, who argues that computers can only simulate certain functions of a human brain, but never replace it entirely is John Searle (Searle, 1980). Searle is the author of the well-known thought experiment Chinese Room Argument. Searle imagines himself alone in a room, where he is supplied with a string of Chinese characters and numerals under the door and expected to answer queries in Chinese language, even though he does not speak the language. Searle says that with the help of a rule book (with the right code in case of machines), he could produce the right answers to the questions, but yet not understand a word of it (Stanford Encyclopedia of Philosophy). Searle’s famous proposition is that a computer can learn the syntax but it is not sufficient for semantic content.
Katherine Hayles took this debate to a whole new level in her book “How we became post-human,” where she suggests that not only computers have consciousness, but we can upload a human consciousness onto a machine. She builds on the findings of the cyberneticians, to propose that we are the information we have constructed and our body is just a prosthesis that stores and processes that information. According to Hayles, the creation of cyborgs “as a technological artifact and cultural icon” in the post-World War II years, is not a coincidence, but a sign of the direction we are heading to. Hayles proposes that we are already in the middle of a historical process that is transforming the conventional definition of human to a new construct called the post-human (Hayles, p. 2).
Hayles offers 4 characteristics for her definition of post-human: first, it privileges “information pattern over material instantiation”; second, it identifies the human solely with the consciousness; third, our physical body is “the original prosthesis we all learn to manipulate”; fourth, there are no fundamental differences between physical existence and computer simulation, “cybernetic mechanism and biological organism” (Hayles p. 2-3). Basically, Hayles argues that an individual is not a physical body, but a cloud of information that could be transferred from one prosthesis to another. Hayles, cites a poignant quote from the influential study of the relation between humanism and anorexia by Gillian Brown, “you make out of your body your very own kingdom where you are the tyrant, the absolute dictator” (Hayles, p. 5).
Post-humanism has a different meaning in social philosophy, but the definition of a cyborg-like posthuman emerged shortly after the invention of cybernetics. Around the 1960’s a new philosophical movement emerged, called transhumanism, which represents the people, who firmly believe in the coming of a posthuman and identify themselves as transitional between human and posthuman. Today, most influential transhumanists like Ray Kurzweil, Hans Moravec, Vernor Vinge, believe that sometime between 2030s and 2040s, humanity will reach the point of technological singularity, when humans will no longer be able to either control or contain the artificial intelligence. They believe machines will outsmart humans, and then build even smarter machines. For example, Kurzweil writes that beyond that point of singularity, we, the humans, will be able to scan our brains and upload them onto a computer, and thus Human Body Version 3.0 will emerge. Human 3.0 will be able to transfer from one body to another, and will not be constrained by biological weaknesses characteristic to humans of our time. According to Kurzweil individuals will be compelled to upgrade to 3.0, in order not to lose in competition either to machines or other humans (Kuzweil, p. 310).
From this perspective of post-humanists and transhumanists the information stored in human mind captures the entirety of our consciousness and it is possible to separate the consciousness from physical body. This is a contentious topic that relates to the centuries old mind-body problem in philosophy. One of the earliest and most influential thinkers who discussed this subject is 17th century French philosopher Renee Descartes, who rejected Aristotelian school of thought that all knowledge comes from our sensory experiences and started his philosophical investigation with external world skepticism (Fieser, 2020). Some observers compare Descartes to the protagonist of the Matrix film series Neo, for this form of methodological skepticism, which is called Cartesian doubt in philosophy.
Descartes proposed that an evil demon could be misleading us, so we cannot blindly trust our sensory experiences. However, then Descartes concluded that, if he can doubt the world around him, question the potentially evil plot, then he can think and has an independent mind. Descartes famously proclaimed “I doubt therefore I think, I think therefore I exist” and developed on this premise to achieve that consciousness is distinct from the body and can exist on its own. Descartes was a devout Christian, who believed only the soul can be conscious neither the physical body nor brain. It is hard to tell now, whether Descartes would agree that the conscious soul would follow the memory, if it is ever possible to transfer all the information on human mind onto a machine.
Conversely, scholars like John Searle believe that “conscious states are entirely caused by lower-level neurobiological processes in the brain” and “they have absolutely no life of their own” (Searle, Mind: A brief Introduction. P. 113). Searle argues that consciousness is a purely biological phenomenon, the same as “photosynthesis or digestion” (Searle, Theory of mind and Darwin’s legacy). From this perspective, even if you have the most powerful computers, you cannot separate the consciousness from physical body, since the first cannot exist without the latter.
Conclusion
Human mind is a very complex system and claims that we will be able to upload our consciousness onto machines are open to discussion. However, with regards to the dawn of artificial intelligence and its impact on our collective identity as human species, there are certain trends that are easily observable and undeniable.
First, as transhumanists like to emphasize, technology is developing very rapidly. Moore’s law, which basically proposed that the computing power you could fit in a certain device (number of transistors in a circuit) would double every 2 years (initially it was every 1 year), has proven true for more than 50 years now. Second, we are growing increasingly dependent on technology. It is already turning into a basic necessity both for our mundane daily lives and professional industries. An average cell phone user touches his/her phone 2617 times a day (Lee). A 2019 study demonstrated that algorithms are responsible for 92% of trade in the Forex market (Kissel). Third, evolution is a scientific fact. It might be hard to imagine that our species could change, but in the big scheme of things evolution is inevitability, not just a possibility.
Given these trends, I also believe that fundamental changes are in the making for our species. Changes so big that they will transform our very essence as a species. However, I think these changes will take a little more time than one or two decades. Also, I find it plausible that in that future, it will be possible to scan a human mind and upload it onto a computer, but I do not think that will be the same person. At best it will be a very good clone that will not be able to associate with the human feelings of its original copy.
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