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.
Tag: Artificial Intelligence
Podcast | Data & Truth with danah boyd
The topic of this episode is data and truth. There is a popular saying that we live in a data driven world? But where is data driving us? According to some estimates the amount of data generated over the next 3 years will be more than the amount of data created over the past 30 years. We have immersed ourselves in zettabytes of data to minimize uncertainty, make sense of the world around us and validate every step we take. But how reliable is all this data and can it really help us find the truth? In this episode we look for the answers to this and other questions with prominent scholar Prof danah boyd, whose research examines the intersection between technology and society. She’s a partner researcher at Microsoft, the founder of the well-known non-profit research institute Data & Society, as well as a Distinguished Visiting Professor at Georgetown University, where she taught a graduate course on Data and Politics of Evidence.
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.
References
Ashby, R. (1960). Design of a Brain. Butler and Tanner LTD
Ashby, R., & Conant, R. (1981). Mechanisms of Intelligence. Intersystem Publications. http://www.rossashby.info/Ashby-Mechanisms_of_intelligence.pdf
Bell, L. (2016, August 28). What is Moore’s Law? WIRED explains the theory that has defined the tech industry. WIRED UK. https://www.wired.co.uk/article/wired-explains-moores-law
Bostrom, N. (2005). A History of Transhuman Thought. Journal of Evolution and Technology, 14(1). https://www.nickbostrom.com/papers/history.pdf
Dembski, W. A. (1999, October 1). Are We Spiritual Machines? | William A. Dembski. First Things. https://www.firstthings.com/article/1999/10/are-we-spiritual-machines
Descartes, R. (2021). Discourse on the Method Annotated. Independently published.
His famous work, where he proclaims Cogito, ergo sum.
Descartes, R., & Cress, D. A. (1993). Meditations on First Philosophy (Hackett Classics) (3rd ed.). Hackett Publishing Company.
Fieser, J. (2020, June 1). The History of Philosophy: A Short Survey. The University of Tennessee at Martin. https://www.utm.edu/staff/jfieser/class/110/8-empiricism.htm
Kissell, Robert. (2020, September 18). Algorithmic Trading Methods. Academic Press
Hayles, N. K. (1999). How We Became Posthuman. The University of Chicago Press.
Huxley, J. (1942). Evolution. The Modern Synthesis. London: George Alien & Unwin Ltd.
Keeling, D. M. and Lehman M. N. (2018, April 26). Posthumanism. Oxford Research Encyclopedias.
Kurzweil, R. (2006). The Singularity is Near. Penguin Books
Moravec, H. (1988). Mind Children: The future of Robot and Human Intelligence. Harvard University Press
Naftulin, J. (2016, July 14). Here’s how many times we touch our phones every day. Business Insider. https://www.businessinsider.com/dscout-research-people-touch-cell-phones-2617-times-a-day-2016-7
Rushkoff, D. (2019). Team Human. W. Norton & Company
Searle, J. (2013, June 18). Theory of mind and Darwin’s legacy. PNAS. https://www.pnas.org/content/110/Supplement_2/10343
Searle, J. R. (2005). Mind: A Brief Introduction (Fundamentals of Philosophy Series) (Illustrated ed.). Oxford University Press.
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–424. https://doi.org/10.1017/s0140525x00005756
Stanford Encyclopedia of Philosophy. The Chinese Room Argument. (2020, February 20). https://plato.stanford.edu/entries/chinese-room/
Umpleby, S. (1982). Definitions of Cybernetics. American Society for Cybernetics. https://asc-cybernetics.org/definitions/
Weiss, D. M. (1999). Posthuman Pleasures: Review of N. Katherine Hayles’ How We Became Posthuman. University of Chicago Press. https://jcrt.org/archives/01.3/weiss.shtml
Wiener, N. (1968). Cybernetics: or the Control and Communication in the Animal and the Machine: Or Control and Communication in the Animal and the Machine by Wiener (1961) Paperback (2nd Revised edition). MIT Press.