Instead: Notes on the Complexities of Free Will
Remember “The dress”? It was an internet phenomenon that appeared on February 26, 2015, on the social network service Tumblr. Back then, viewers disagreed on the color of a dress: For some of them, it was blue and black, and for others, it was white and gold. The social media reaction to this difference in perception was so significant that it prompted the publication of multiple academic papers on the subject and opened a debate about how people perceive the world. According to cognitive neuroscientist Daniel Yong, humans “experience the world outside [their] heads through the veil of [their] sensory systems.”[1] These faulty and noisy processes are incapable of processing all the information available, forcing the brain to reconstruct what it is experiencing. Therefore, under these circumstances even the simplest object can be perceived differently and cause diametrically opposed reactions, making it hard to establish a clear line between cause and effect. A stochastic world where multiple probable outputs can be the result of a single input.
But what such a world could mean for free-will? In his “What Does It All Mean?” essay, American philosopher Thomas Nagel presented a dilemma about a person going into a cafeteria and, after hesitating between choosing a peach and chocolate cake, decides for the latter just to later regret it and wishing she have had the fruit instead. Nagel wonders whether it is true that the person really had a choice or whether she was deterministically bounded to buy the cake. This dilemma suggests that there was a discrete path of information between previous experiences and the moment when the decision was made, but if it is considered — as Daniel Yong suggests — that what is perceived or recalled from memory is influenced by noise and by the obvious biological limitations of human beings, it is hard to establish a clear line of causation. Yet, it would be possible to say that there was a probability for each one of the outcomes (i.e., there was a probability x that the person decided on the fruit and 1-x that the person bought the piece of cake).
To illustrate this probabilistic approach, it is first necessary to recognize a greater level of complexity in the decision process: Would the decision have been the same if it has been an apple instead of a peach, or if the peach had been a different color? Was the person alone or with a friend? If a friend was present, what did the friend have? What did the person ahead in line order? As the number of factors influencing the decision starts to grow, an identical set of initial conditions can result in different outcomes. What this non-linearity means in practice is that despite the fundamental determinism, no outcome can be predicted with any reasonable precision. Therefore, any “useful conclusions or predictions must be statistical in nature.”[2]
British Empiricists — including John Locke, George Berkeley, and David Hume — adhered to a common empirical standard: that humans do not naturally generate ideas but that “all knowledge comes from experience.”[3] Hume’s version of this standard where he stated that all ideas are products of impressions — known as the “Copy” principle — was rigorously applied to the relationship between causation and necessity in his essay Enquiry Concerning Human Understanding, and it is considered his central empirical axiom.[4] But if any complex idea can be traced back to a set of constituent impressions, then in order to establish causality between them, impressions must be consistently perceived every time. But, as discussed before, the perception process is sensitive to noise and limited by human biology and is therefore erratic by nature and in direct conflict with Hume’s fundamental ideas. This issue seems to be ingrained in the nature of dynamic non-linear systems, as can be seen in the comments of French mathematician Henri Poncairé: “If we could know exactly the laws of nature and the situation of the universe at the initial instant, we should be able to predict the situation of this same universe at a subsequent instant. But even when the natural laws should have no further secret for us, we could know the initial situation only approximately.”[5]
Yet, this chaotic and unpredictable quality of the systems that govern the dynamics of human behavior and the phenomena that emerge out of chaos, although entirely opposed to the deterministic model, could still have similar implications for free will (i.e., if the decision is made randomly, the person never actually makes a conscious choice). Also, and even though it has been rigorously approached mathematically and philosophically over the past few centuries, non-linear models still cannot provide a definitive answer to some of the fundamental questions related with free-will: Do people really have a choice? Could the person in the cafeteria have chosen a peach instead of the chocolate cake? Was there really an option?
In a complex world where behavior can be assumed to emerge probabilistically, the question of choice seems to also require an understanding of how existing impressions affect the process of decision-making: If the line between cause and effect is skewed or interrupted, knowing why and how the disruption happened could be just as important as observing the inputs and outputs. One such possible source of distortion could be biases, known in psychology as the impressions or experiences that influence a person’s attitudes toward or against things or people. They have been the subject of study of behavioral scientists like Daniel Kahneman and Amos Tversky, who have identified how previously conceived ideas affect the mind and the underlying mechanics of human thinking[6] .
At the core of Professor Kahneman’s approach to human behavior, is the division of the brain into two structures identified as System 1 and System 2. The first operates automatically and effortless with no sense of voluntary control, and the second one takes charge of effortful mental activities that are often associated with “the subjective experience of agency, choice, and concentration.”[7] Under this framework, the decision between the peach or the chocolate could have been made automatically — although probably with bias — by System 1 or through a well-structured thinking process by System 2.
What tasks are assigned to the two systems and how exactly they are distributed between them is deeply related to the particular experiences of each individual and can be considered quite subjective. Hence, it would be hard to prove that free will resides in either of these systems or in the interactions between them. Nevertheless, these dynamics can certainly help make a case against determinism. Once the concept of a monolithic mind that follows a discrete, well-defined path of causality can be challenged, the door is opened to a richer, less certain description of reality, full of randomness and emerging behaviors that cannot be unequivocally traced back to a single source or cause.
If an engaged brain — when confronted — can consciously choose between complex options, it can be said that it has exercised free will, even if there was — or will be — an occasion where a similar decision was (or is) made rapidly and automatically based on existing experiences, impressions, and biases. Thomas Nagel’s dilemma presents a direct question looking perhaps for a straight, general solution, but the complex nature of the human mind makes it difficult to provide a simple binary answer. Was the choice actually between peach and cake? Or it was more about healthy vs. unhealthy? Cheap vs. expensive? Peer pressure? Was weather a factor? Or it was perhaps a mix of all of them? If so, did all the factors have the same weight when it came to make a decision? Let’s imagine the decision was not made at the cafeteria but that the person bought both items. Then, she would face the decision in the tranquility of her own house, would the decision have been the same?
There seem to be many scenarios to consider before an acceptable answer can be reached, so perhaps it is just a matter of analyzing all the available evidence and making a reasonable choice. Let’s hope that later in hindsight we would have not preferred a peach instead.
[1] “Now You See it. How Our Brain Sculpts Experience in Line with Our Expectations” Aeon Magazine. July 4, 2019. http://aeon.co/essays/how-our-brain-sculpts-experience-in-line-with-our-expectations
[2] Berliner, L. Mark. “Statistics, Probability and Chaos.” Statistical Science 7, no. 1 (1992): 69–90. http://www.jstor.org.ezp-prod1.hul.harvard.edu/stable/2245991.
[3] C.M. Lorkowski. “David Hume: Causation.” Internet Encyclopedia of Philosophy. //www.iep.utm.edu/hume-cau/.
[4] Ibid.
[5] Berliner. “Statistics, Probability and Chaos”.
[6] Daniel Kahneman. Thinking Fast and Slow. New York: Farrar, Straus and Giroux, 2011.
[7] “Daniel Kahneman Explains The Machinery of Thought.” Farnam Street.
