Heuristic

Picasso’s “Le coq saigné”, painted in France in the mid-20th century could be seen as a response to the traumatic events of World War II.

It’s miraculous that after two world wars, a Holocaust, and a cold war, “trauma fiction” was only coined in the 1990’s. Trauma is fascinating, whether it’s sexual, verbal, physical, or another form. It could be a force that captures all parts of an individual. Someone undergoing trauma could have their senses and perceptions changed in such a way they question fundamental tenets of themselves. They may experience distrust, fear, and anxiety throughout other experiences. When one tries to write about trauma, it’s not uncommon that languages fails them. How can someone write about such a paralyzed, numb state? What sort of description can do justice to trauma while remaining objectively detached? And trauma itself can force an individual to re-examine moments of their life that they can’t seem to shake off. For fiction writers searching for narratives and themes, there are ways of identifying key concepts of trauma. Instead of focusing on what happened in the past, it’s important to understand why we remember those things. 

Comparing trauma to a means of survival allows one to view reactions to different psychologically difficult experiences as having some sort of reason to them. Jonathan Foer’s 2005 novel Extremely Loud & Incredibly Close takes a creative, near-experimental approach to the American trauma of 9/11. The novel’s protagonist, a nine-year-old genius Oskar, struggles with the truth of the world after losing his father to the September 11 attack on the World Trade Center. When I read the book in high school, I admired Oskar’s introspective abilities for a child with a severe form of suffering. Yet I felt as though my AP Literature and Composition class didn’t quite capture the true ethical dilemma inherent within Oskar.The magical realism of the novel shows how it is created with techniques that don’t adhere to common realist notions of reality. Instead, the protagonists strategies of dealing with trauma bring him a sense of ethical assertion of the obvious immorality of the terrorist attacks. Oskar’s meaning creates a criticism of political terrorism.

For Foer to write about 9/11, even four years after it happened, was a risk. In the wake of 9/11 many radio stations, television broadcasts, and even movie theaters avoided showing terrorism or terrorism-related media. But Foer’s attempt to capture a mind with post-traumatic syndrome with such detail shows how trauma causes the mind to repeatedly experience and re-experience events of its past until the mind fully understands it. In re-examining the past, the mind enters fantasy and, in this case, a form of magical realism as it relies on memory and repeatedly encountering past events. The reader is left to wonder whether Oskar’s remembrance of the event is real or solely exists in his mind. Foer even uses creative techniques of writing by showing pages that have multiple letters and words written over them (and over them and over them) in such a way they parallel the memories of crashing of the planes into the towers. Or the rumination of trauma. Over and over again. Or the rumination of trauma. Over and over again. Disrupting his sense of time (and possibly space, too), Foer uses a mythic mood reminiscent of modernist literature like T.S. Eliot and Gabriel García Márquez. 

Speaking of time and space, Oskar’s deep interest in theoretical physics lets him draw parallels between the past and the present. In fact, it wasn’t until I entered university and began studying physics and philosophy that I saw the extremely close parallels between physics and trauma. As I read Hawking’s physics “story” A Brief History of Time as well as Alan Lightman’s provocative novel Einstein’s Dreams, I realized the components to the significance of Oskar’s interest in physics. Foer invokes the laws of special relativity and quantum physics to demonstrate that Oskar had a keen interest in the fantasy of what lies beyond our senses. In an effort to unify gravity with quantum mechanics, scientists posited an “imaginary” time that is inherent to the directions of space-time, that is, a way of proceeding through time not with the “classical” conventions of steady, unstoppable, linearity. With this “imaginary time”, you can move in circles, backward, and in whatever direction your mind chooses to. It leads to philosophical questions  such as difficulty in knowing the future while we have complete certainty of the past and what is the true difference between the past and the future. It also creates a form of magical realism in which the features of PTSD become our way of surviving in a chaotic, unforgiving universe. Moreover, Foer shares how Oskar studied the physicist Stephen Hawking and his three arrows of time according to the laws of entropy. The first is the easiest to grasp: our psychological understanding of time from past to future. The second is the thermodynamic arrow of time that moves from the past to the future, which dictates how systems of energy progress as the universe expands. This explains why an ice cube outside in the sun melts or why we need Carnot cycles to create engines to use energy. The third is the cosmological time of how the universe is currently expanding. Oskar draws upon this research to wonder how he may travel backwards in time, but, because the three arrows must point in the same direction, it isn’t possible. Foer is by no means the next Stephen Hawking, but his knowledge of physics allow him to incorporate a sort of “mythic” idea of science fiction – events governed by fantasy elements while still grounded in a reality of scientific inquiry. 

This brings us to the deeper ethical dilemmas of trauma. As part of a greater collection of works Trauma Fiction (by writer Anne Whitehead), Professor of English Cathy Caruth explains that the structure of trauma is a disruption of history or temporality (similar to Oskar’s disruption of space and time) and, as a result, not fully experienced by the victim at the time. For this reason, trauma can cause people to experience persistent and unwelcome thoughts in the future, malignantly effecting recall and recollection. In neurologist Sigmund Freud’s 1939 nonfiction work “Moses and Monotheism”, the  relation between “Man” the problem of becoming human is explored. Freud claims Moses was born to Egyptian nobility and his few followers decided to kill him in rebellion. These rebels would later experience incredible remorse for their action after Moses fused with Yahweh, they would create the “Messiah” in their hopes Moses would return as their savior. This controversial story explores how the material reality of the unconscious can be transmitted from one generation to the next through language in such a way that future generations are forced to deal with an uncomfortable, traumatic knowledge. Yet it would create the language and grounds for discussing trauma and memory for decades to come. In her book, Trauma: A Genealogy, writer Ruth Leys explains that this work by Freud is a place of investigation for memory, trauma, and history that is central to discussions of postmodernism and the Holocaust. By virtue of its inter-textuality and despite its recurrent historicist motifs, Freud’s Moses has also enthralled leading figures in French post-modernist philosophy, who have highlighted its importance for the writing of history, the concepts of suffering and the preservation of experience. Caruth comments, in her her account of psychoanalysis and literature Unclaimed Experience, the story is “a renewal of some of Freud’s earliest thinking on trauma is indicated by his use of the figure of the “incubation period” to describe traumatic latency; Freud had used this figure in his early writing in Studies on Hysteria (1895)”. A sort of incubation period is exactly how Oskar suffers to determine, as a theoretical physicist might, the true nature in our universe. In it, as the deep psychological forces underlying the individual take control, the fear, anxiety, paranoia, obsessiveness, and other dark parts of human nature take root. 

Freud makes the universality of trauma simple: Trauma seals the fate of man. The cause of our individual psychological difficulties have three salient features, Freud argues: they take place in early childhood, they’re generally avoided through other memories (that attempt to “screen” out the individual’s feelings), and traumatic impressions are generally sexual and aggressive as they attack the ego. Whitehead claims that trauma requires a non-linear literary form through abrupt or immediately self-evident methods. This trauma is usually dormant in which the symptoms are not shown until a later traumatic event in the individual’s life. As Caruth writes, “The experience of the soldier faced with sudden and massive death around him, for example, who suffers this sight in a numbed state, only to relive it later on in repeated nightmares, is a central and recurring image of trauma in our century” (in Unclaimed Experience). We’re not only haunted by the events of our past, but our own psychological difficulty in understanding those events.

Similar to Oskar’s detachment and disillusion of the world around him after his father’s death, the protagonist undergoes existential crises through his efforts in school and other areas of life. Foer disrupts space, time, and spacetime to show the obsessive, haunting feelings that plague the psyche. From these understandings of trauma, Caruth argues, with the case of trauma fiction, the individual undergoes a “crisis of truth” that extends to the individual’s society and peers. Whitehead further illustrates trauma fiction with her point that the ethical questions raised by the individual’s testimony have an inherent literary feature to them as a result of these sufferings. 

I absolutely despised reading the novel Extremely Loud and Incredibly Close in high school. I felt as though the narrator was too self-absorbed and couldn’t relate to him much. But now I look back on it with fondness. My English teacher emphasized the importance of taking apart an argument with all its assumptions and methods of reasoning when writing. That value and importance he gave me lead me to study philosophy in college as well as taking apart many other truths and ideals of this world. But I still worry that, despite the humanistic visions Foer had for his novel, these methods of literary can leave us staring at mental health patients as though they were fish in an aquarium. We’re distant and detached from their true suffering as we generalize and conceptualize the traumatic framework. For this reason, it’s important for us to remember in all our arguments, there is always a significant subjective, humane element in trauma. People react to problems differently and the way they affect our world views can sometimes be unpredictable and messy. 

No matter our literary, scientific, and philosophical efforts, we can’t turn back time. Foer tries, though, at the end of the novel to share images of a 9/11 jumper in reverse order. This slideshow gives the image that the person is not only moving backwards in time, but flying as though they were an angel ascending in their fantasy. A stark contrast to the horror of witnessing suicide, it at least gives the reader a sort of escapism from the trauma. Like all traumatic events, be them historical, psychological, sexual, or of any form in nature, the past remain unchanged. Still, we can turn to science, literature, and philosophy in creating these narratives for the betterment of the future. I’m not looking back in anger.

“Normal science, the activity in which most scientists inevitably spend almost all their time, is predicated on the assumption that the scientific community knows what the world is like. Normal science often suppresses fundamental novelties because they are necessarily subversive of its basic commitments.” – Thomas Kuhn, The Structure of Scientific Revolutions

My doubts have been getting to me. My questions about the nature of existence and science itself have left me disillusioned and detached from many aspects of my day-to-day routine. I began to slowly and steadily believe that my work as a scientist wouldn’t be valued nor would it be worth doing in any sense. I could barely find answers questions and concerns I wrestled with as a scientist. As I walked through one of the buildings of the National Institutes of Health, I listened to music to drain out the sounds of the world. 

From my view, something caught my eye. A bookshelf. In the middle of the hallway. I stared at it in disbelief took the headphones out of my ears. Anyone could take a book and leave one for others to read. In the middle of the top shelf sat philosopher Thomas Kuhn’s The Structure of Scientific Revolutions. Interesting, I thought. Looks like the scientists at the NIH aren’t completely aloof to the philosophical underpinnings of science. In this post, I hope to discuss the nature of Kuhn’s paradigm shifts and their relevance in the field of Artificial Intelligence (AI).

Kuhn’s opus The Structure of Scientific Revolutions catapulted him to stardom in the world of philosophy. In the work, he presented arguments from the history and philosophy of science to show how science undergoes paradigm shifts. A paradigm shift occurs when a new set of assumptions and values replaces the previous one within a given scientific community. Between the Ptolemaic method of understanding the orbits of planets and the modern ways astronomers use (borrowing ideas from Copernicus and other scientific revolutionaries), we need to pay close attention to the assumptions and arguments that lead to our conclusions. The terms themselves in science would change that complicate the method of comparing scientific theories and evidence between these different paradigms. Kuhn particularly held that scientific theories from before and after a scientific revolution cannot be compared in a straightforward way; they are “incommensurable,” because the meanings of familiar terms change in unexpected ways as scientists go from one mode of description to another. One drastic consequence of incommensurability is that there isn’t any such thing as absolute progress from one paradigm to the next — say from before the Copernican Revolution to after, or from classical physics to quantum physics. A new paradigm may be more complete, or simpler, or more useful for answering certain questions compared to the preceding one, but it is not, strictly speaking and on the whole, objectively better.

There are several examples Kuhn uses to illustrate these paradigm shifts. Kuhn’s analysis of the Copernican Revolution emphasized that, in its beginning, it did not offer more accurate predictions of celestial events, such as planetary positions, than the Ptolemaic system, but instead appealed to some practitioners based on a promise of better, simpler, solutions that might be developed at some point in the future. Kuhn called the core concepts of an ascendant revolution its paradigms and thereby launched this word into widespread analogical use in the second half of the 20th century. Kuhn’s insistence that a paradigm shift was a mélange of sociology, enthusiasm and scientific promise, but not a logically determinate procedure, caused an uproar in reaction to his work. Kuhn addressed concerns in the 1969 postscript to the second edition. For some commentators The Structure of Scientific Revolutions introduced a realistic humanism into the core of science, while for others the nobility of science was tarnished by Kuhn’s introduction of an irrational element into the heart of its greatest achievements.

Another amazing example of a paradigm shift would be the shift from Aristotelian to Newtonian physics (classical mechanics). Despite the cleverness and elegance of Aristotle’s antiquated observations (that objects have mass and can be governed by forces), scientists found themselves with a fundamental difference in how they regarded what is knowledge and how it can be found. With the groundbreaking discoveries of Newtonian physics, physicists could create rules to describe intrinsic behavior of objects. Through obesrvation and refinement of theory and evidence, Newtonian physics laid the foundation for much of the rest of physics for centuries to come. 

Vertical section drawing of 18th-century British scientist Henry Cavendish’s torsion balance instrument including the building in which it was housed. This apparatus was used to measure the gravitational constant by observing the force of gravity between two masses. The large balls were hung from a frame so they could be rotated into position next to the small balls by a pulley from outside. Despite how sensitive the experiment was, it did not cause a shift in the understanding of the constant of gravity as other experiments did.

As a student with deep interests in philosophy and discerning truth in all its forms, I began to ponder and reflect upon the ways Kuhn’s writing would affect my work. I sought to bring the value and meaning of this scientific work in a context such that I could benefit most from it as immediately as possible in my life. Through several weeks spent digging away at philosophical writings by Kuhn, Feyerabend, and Popper, even searching for original papers in physics and chemistry by scientists like Newton, Cavendish, and Archimedes. I began interpreting their arguments and pitting some against others. To put myself in the shoes of these thinkers, I sought to defend and attack their views. Kuhn’s response to philosopher Karl Popper’s notion of falsificationism (the doctrine that falsifiability is the most important feature to determine what is scientific), in particular, is essential to understanding Kuhn’s paradigm shifts. Kuhn emphasizes the importance of verificationism, a philosophical movement that emerged in the 1920s among logical positivists. The verifiability principle claims that meaningful statements must be supported by empirical evidence or logical requirements.

One may argue AI started at Dartmouth in the 1950’s. Students and professors (among them Allen Newell, Herbert Simon, and John McCarthy) created computers that could function using programs. On both hardware and software sides, computers developed their own ways of playing games such as checkers, solved algebraic problems, and showed proof of logical theories. The moments were spurred with optimism and a bright-eyed look at the future for computer science in general. 

AI has undergone similar transformations since its creation in the 1950’s. The emergence of data-driven approaches over the past few decades has allowed for more detailed, refined approaches for computers to complete machine learning tasks. This means computers can behave in ways similar to humans in solving complex problems and making decisions about the world in ways unparalleled since the field’s inception. A paradigm shift using the conceptual tools of Thomas Kuhn are very implicit in the field. And one needs to sense and determine the structure of the reovlutions in the field (as Kuhn did for physics) on the fundamental level on which knowledge is acquired. Looking at the successes of the field over the past 70 years, the replacement of these exemplar stories to more corresponds to a shift in goals, methods, and expectations. 

Understanding the appropriate methods used by those scientists, I began to form a greater, more expressive appreciation of scientific research in general. There’s an objective truth out there, and I don’t interpret Kuhn’s writing as a challenge to that nor do I interpret his work as evidence of relativism in the philosophy of science. Given the growing initiative and significance of AI research, I hope I can elucidate what sort of paradigm have occurred in the field over the past few decades.

There is a beautiful account of what it means to be doing research in this new paradigm. It can be found in the article “The unreasonable effectiveness of data” published in 2009 by three leading scientists working within Google Research. It reads like the perfect manifesto of a scientific paradigm in Kuhn’s definition, containing success stories, recommendations and directions of expansion.

Things have changed since then. Emphasis moved from knowledge, logic and reasoning to data, learning and statistics. Information seemed to triumph over wisdom and gratification of immediate results over epistemic truths. Success stories like the ones mentioned in the “Unreasonable Effectiveness” paper started being passed on, from teachers to students, more often than stories involving rules, theorems and logical deductions. Data became central in the new narrative, intelligent behavior was acquired by the system through automatic analysis of vast amounts of data. The results of the analyses on these enormous amounts of data has allowed AI to conquer a multitude of problems in computer vision, text processing, speech recognition, and so forth. And because of this centrality of data, machine learning became the lingua franca of AI researchers, and increasingly this was true for the specific version of learning that had enabled all those success stories: statistical learning. The languages of statistics and of optimization took hold of discourse in the AI literature, replacing that of logic. After all, the stories seemed to be based on modeling the problem of intelligent inference as an inverse problem, solved by maximization of some probabilistic quantity.

Throughout the decades since then, AI’s research has extended to amazing results in spelling correction, facial recognition, machine translation, information retrieval, and theoretical problems we believed were unsolvable decades ago. Machines can now correct their own spelling and grammar of writers even without knowing the rules on which to act beforehand and, instead, by learning those rules themselves. We’ve moved from emphasizing the importance of a particular domain knowledge to the availability of data and the ability to draw trends and conclusions from that data. This allowed for a paradigm shift (in the words of Kuhn) to occur in which we can adequately and appropriately discuss the AI findings of today. 

In the 2010’s, AI research to a great degree defined its ability to process large amounts of information and to learn new theories and rules by advances in computer science and mathematics. A series of breakthroughs in applications created a strong business model for a part of AI. It is now possible to transcribe speech, translate text and recognize faces, to a sufficient extent that this can be used in real applications. The stories of current AI do not involve sentient robots or Turing tests, but rather efficient processing of digital content, or the modeling of its consumers and producers. They don’t even dig into details about investigation of general cognitive capabilities. Instead, they’re more focused on the reproduction of very specific behaviors. This is precisely the kind of shift that Kuhn talks about and it has far reaching consequences. Success stories tend to act as templates for future research, to define for new researchers which new puzzles should be solved and how. The adoption of new stories changes the definition itself of the scope of a research field. And, most strikingly, all these breakthroughs were achieved by the use of the same set of techniques and by the same overall approach: the methods of statistical AI.

Despite what the arguments about paradigms and the relative nature of them to scientific research, Kuhn is not a relativist. Kuhn admits there’s something objectively out there. But he qualifies that this thing-in-itself, like German philosopher Immanuel Kant described, as ineffable and undiscussable. Instead, we need to focus on our approach. 

We speak as though we could bring ourselves closer and closer to this truth. Like diving deeper into a dark abyss (similar to the way philosopher Friedrich Nietzsche might have warned us about), we can only see some of what is in front of us. And, until we can figure out how to interpret these mysteries in science, we must make sure our methods of speculation and evaluating claims are as close to the objective truth as we can possibly get. Through each shift of a paradigm, we soak in new sources of light and adjust our vision accordingly. Only then can we understand the importance of our current paradigm in artificial intelligence. Through that, we can inch closer to the elusive objective truth as Kuhn envisioned. 

“Truth, it is said, consists in the agreement of cognition with its object. In consequence of this mere nominal definition, my cognition, to count as true, is supposed to agree with its object. Now I can compare the object with my cognition, however, only by cognizing it. Hence my cognition is supposed to confirm itself, which is far short of being sufficient for truth.” – Immanuel Kant, Logic Lectures

Unfortunately, I still find myself bogged down by technical details and issues of my work in such a way that these philosophical insights come few and far between. Despite how skeptical and relativistic Kuhn may appear, I believe his methods hold insight for the nature of research in biology and neuroscience is conducted at the NIH. As I dig into the methodology behind recent advances in bioinformatics, machine learning, and computational neuroscience, I became more keen to the rhetoric and logic underlying the insights we derive. Though I stare into the abyss with wonder and fascination at how AI research has evolved since it’s inception, I don’t look back in anger. Only the solemn hope that we’re making the right decisions in our current paradigm.

I sit at my laptop staring at a black box on dimly lit screen. In it run all my programming commands and shell scripts for carrying out my analyses. I can imagine how my methods of carrying out analyses using scripts in Python would form part of this bigger search for an objective truth. I sit back and speculate on the future of the field and especially the results for computational neuroscience. For Kuhn, Kant, and everyone else, I hope to continue this inquiry.