Category: Philosophy

Coin Toss in an Alternate Universe

I came across this reddit post a couple years ago and thought it was quite funny. I can see Randall Munroe of xkcd comics drawing up a really good depiction of this imaginary phenomenon too.

“According to the multi-world theory, there is a universe where every flipped coin has landed on heads, completely by chance. Imagine rooms full of machines, just flipping coins with scientists baffled as to why it happens”

According to OP in the comments of the reddit post, this world “would have identical physics, [where] this just happens by chance” and “physics aren’t different in this universe, the incident with coins only landing on heads is pure probability, not a law.” I like to imagine that there would be individuals dedicating their entire research careers to this phenomenon, maybe pulling out their hair as no solid evidence is able to suggest why this happens.

If you, dear reader, felt inspired to fulfill my dream of depicting this scenario in an illustration of this scene, I would excitedly add it to the bottom of this post with full credit to you! Wilfred is tired and would like to retire; in this universe he studied the coin toss phenomenon in his free time.

Works Cited

Philosophy of Humour

When learning about theatre back in high school, my drama teacher mentioned comedy arises from two basic principles:
1. It’s funny because it’s not me
2. It’s funny because it’s true

This has probably been said at one point, but I would like to offer a third principle for consideration:
3. It’s funny because it’s me

Why is this different than the second principle? While there may be some overlap, we often think of ourselves as separate from typical functions which determine truth values. Sure, we are able to run through a list of propositions about ourselves and can evaluate them like any other, but there is something more at play here.

Sometimes our feelings hint at things we aren’t ready to confront. Are you able to look yourself in the mirror and say “it is true that I am ___?” Maybe for certain characteristics this is easy, but others may be more difficult to admit. Our laughter, however, suggests we have understood some property about the world, and may be able to relate it to other things, perhaps to ourselves and others, in ways that are less explicit or unarticulated. We may feel amused for several reasons, one of which may include a certain level of meta-analysis. Perhaps deep down we are aware of one character trait we are not proud of but are able to recognize in a moment of leisure. This openness to information may allow ourselves to acknowledge aspects of our life or personality which we typically tend to hide or fix. Humour, especially reflexive humour, which turns the examination process back to oneself, can be therapeutic insofar as it allows us to understand ourselves without feeling the pressure to do anything about it. The first step to change is the recognition that something exists or must be better understood, and in this way, humour cracks the door to look at aspects of ourselves we wish to turn away from. The pleasure which accompanies laughter and humour allows us to relax and see through feelings of embarrassment or defensiveness.

Internet memes provide us with a way to laugh at ourselves and share our vulnerabilities with others. They serve as a reminder that we are human with troubles, flaws, and fears, but they also remind us that we are not alone. It’s easy to get wrapped up in our work, goals, and expectations as we compare ourselves with others and their accomplishments. As much as these aspects of life are important to some degree, we must always remember that the image others present to us is just a segment of their reality. Humour, especially when shared with others, reminds us to breathe; life is more than a to-do list of tasks.

There is a rich body of philosophical literature on humour that I have not yet had the pleasure of reading, but one day I will. As much as I would like to work on adding more to my Philosophy of Memes page, it’s a slow process because I should be focusing on school work! Until then, these considerations will be relatively uninformed and personal, and I look forward to rereading and laughing at my ramblings in 20 years from now.

Why Science Needs Philosophy

My peers within the department often joke about life after university, considering the whole world seems to scoff at those interested in pursuing arts and humanities (A&H) degrees. This opinion piece by Laplace, however, is an important reminder of the value of our discipline, regardless of how much money we end up making in the future. As institutional funding is reallocated to support students pursuing more profitable degrees like computer science and engineering, A&H departments are likely to suffer, unable to hire new faculty and limiting course selection for example. Unless philosophers can market their skills to assist with projects from a variety of sectors, I don’t see how society will continue to support our endeavours, perspectives and concerns. Although notions of “anti-elitism” seem to continue to grow in the United States, perhaps Canada will challenge my pessimistic attitudes on this subject and find innovative ways to support their A&H graduates, but we will see. This suggests philosophers may need to do their own advocacy demonstrating the financial value of creativity and scepticism, especially within business, science, and technology. Consider this entry as my early attempts at convincing you, dear reader, that philosophy is much more than writing about central figures such as Kant, Aristotle, or Frege.

Although Laplane discusses many important points throughout, the end of the article is quite interesting as it suggests ways to foster the relationship between science and philosophy. Now, I’m not quite sure who said this to me, but they presented the idea that philosophy and science are able to discuss the same topic in different ways. While science may prefer ‘what’ questions, philosophy tends to ask ‘why’ and perhaps even ‘how’ concepts, principles, or processes emerge. Though this generalization may oversimplify the relationship between the two, I merely wanted to point out their approximate differences. Laplane herself states “…we see philosophy and science as located on a continuum.” (3950) which suggests both an overlap and a distinction in the questions each discipline asks. It is important to remember the common ground, in addition to the diversity in perspectives, between science and philosophy as we consider new ways to unite these two fields of inquiry.

While I agree with all six recommendations on page 3951, the fourth and fifth stood out to me as the most important especially when it comes to developing this program in the future. The marriage of science and philosophy can only be as good as its thinkers, where education serves a central role for this relationship to be harmonious and fruitful. From primary school to post secondary, it will become increasingly important to teach both arts and sciences of various types to foster the integration of the two. I say ‘arts’ rather than ‘philosophy’ because developing a love for the arts may inspire individuals in ways philosophy is unable. Artistic expression, regardless of medium, allows one to improve their sense of self, and when combined with educational goals, is likely to facilitate personal and professional growth more effectively than either alone. Whether it is sculpting, poetry, or dance, artistic expression provides mechanisms for new approaches within the sciences as one remains in touch with their creative side. Although it might be difficult to understand how theatre may inspire work in civil engineering, the human brain is quite powerful in its abilities to “fill in the blanks” and synthesize concepts, if the opportunity arises. Most exciting of all is how access to information via the internet and online relationships can further assist individuals in their efforts.

Returning to philosophy though, Laplane makes an important point about why philosophical inquiry is so appropriate for science. On page 3950 after the excerpt mentioned above, she states:

“Philosophy and science share the tools of logic, conceptual analysis, and rigorous argumentation. Yet philosophers can operate these tools with degrees of thoroughness, freedom, and theoretical abstraction that practicing researchers often cannot afford in their daily activities.”

It is exactly this freedom which inspired me to move away from studying psychology to studying philosophy of mind. Of course, too much of a good thing can lead one astray, which is why empirical evidence and the methodologies which produce it must never be overlooked by philosophers. The ability to defer to experts is a powerful bidirectional tool which carries so much potential for the future, and maybe one day those interested in A&H subjects will find their niche within capitalistic economies.

Works Cited

Laplane, Lucie, et al. “Opinion: Why science needs philosophy.” Proceedings of the National Academy of Sciences 116.10 (2019): 3948-3952.

Epistemic Responsibility Today

Section 6 of Miller and Record’s Justified Belief in a Digital Age provides suggestions for responsible belief formation given the role and influence algorithms possess in today’s society. The notions they present, however, are vague and appear to be shortsighted. They suggest “subjects can use existing competencies for gaining information from traditional media such as newspapers to supplement internet-filtered information and therefore at least partly satisfy the responsibility to determine whether it is biased or incomplete” (130), except the nature of ‘traditional media’ (TM) has shifted. Since the widespread adoption of social media platforms and online news streaming, TM has seen an increase in competition as small and independent news websites are also shared between users. Importantly, expectations for endless novel content has pressured TM to keep up by increasingly producing editorials, commentary, and speculation. Pundits receive as much airtime as journalists due to the nature of consumer demand, subsequently influencing belief formation. The notion of political bias in TM is also a large concern, where journalistic integrity and credibility ranges drastically between companies. Additionally, TM is more likely to be subsumed under an umbrella corporation with an agenda of its own, whether political, financial, or religious. Deference to TM has always been associated with epistemic risks, and reasons to be sceptical of stories and information are growing as technology modifies our consumption habits.

Further down on page 130, it is recommended one explore outside their personalized feed by investigating others’ posting history: “Instead he can casually visit their Facebook profiles and see whether they have posted an interesting story that the automatically generated news feed missed.”. While this does improve chances of being exposed to diverse content, it is most effective when one reads the feeds of contrasting personalities. Close friends and family members may hold similar attitudes, values, or perspectives which do not adequately challenge one’s suspicions or beliefs. Opposing views, however, may not be justified or well-formed, and ‘opposing’ is open for interpretation. On page 131 the authors state: “… suggests, internet sites, such as political blogs, may refer their readers to alternative views, for example, by linking to opposing sites, out of a commitment to pluralism.” If this program were to be followed, it would suggest religious individuals with dogmatic beliefs are epistemically irresponsible. This may be an unexciting verdict to a philosopher, but it is difficult to determine whether this normative approach to belief formation is suitable for all humans.

Epistemic justification is complicated in the digital age, and it is unclear how much research is required to fulfill one’s epistemic responsibilities. If one stumbles across a scientific claim, it seems reasonable that one ought to determine whether the news headline matches the outcome of the study. Considering the replication crisis has further complicated this process, how much scientific scrutiny is required at this point? If a reader has an understanding of scientific methodology and access to the article, is it irresponsible if one does not examine the methods section? As ideal as epistemic responsibility seems, it might be unattainable due to the nature of the internet and human emotion. Our ability to access such a wealth of knowledge, even when curtailed by algorithms, generates an infinite regress of duties and uncertainty, a fact unlikely to sit well with the average voter.

Works Cited

Miller, Boaz, and Isaac Record. “Justified belief in a digital age: On the epistemic implications of secret Internet technologies.” Episteme 10.2 (2013): 117-134.

AI and the Responsibility Gap

This week we are talking about the responsibility gap that arises from deep learning systems. We read Mind the gap: responsible robotics and the problem of responsibility by David Gunkel along with Andreas Matthias’ article The responsibility gap: Ascribing responsibility for the actions of learning automata.

It seems the mixture of excitement and fear surrounding the rise of autonomous agents may be the result of challenges to our intuitions on the distinction between objects and subjects. This new philosophical realm can be analyzed from a theoretical level, involving ontological and epistemological questions, but these issues can also be examined through a practical lens as well. Considering there may be a substantial amount of debate on the ontological status of various robots and AIs, it might be helpful to consider issues on morality and responsibility as separate to the theoretical questions, at least for now. The reason for this differentiation is to remain focused on protecting users and consumers as new applications of deep learning continue to modify our ontological foundations and daily life. Although legislative details will depend on the answers to theoretical questions to some degree, there may be existing approaches to determining responsibility that can be altered and adopted. Just as research and development firms are responsible for the outcomes of their products and testing procedures (Gunkel 12), AI companies too will likely shoulder the responsibility for unintended and unpredictable side-effects of their endeavours. The degree to which the organization can accurately determine the responsible individual(s) or components will be less straightforward than it may have been historically, but this is due to the complexity of the tools we are currently developing. We are no longer mere labourers using tools for improved efficiency (Gunkel 2); humans are generating technologies which are on the verge of possessing capacities for subjectivity. Even today, the relationship between a DCNN and its creators seems to have more in common with a child-parent relationship than an object-subject relationship. This implies companies are responsible for their products even when they misbehave, as the debacle surrounding Tay.ai demonstrates (Gunkel 5). It won’t be long, however, before we outgrow these concepts and our laws and regulations are challenged yet again. In spite of this, it is not in our best interest to wait until theoretical questions are answered before drafting policies aimed at protecting the public.

Works Cited

Gunkel, David J. “Mind the gap: responsible robotics and the problem of responsibility.” Ethics and Information Technology (2017): 1-14.

Is Opacity a Fundamental Property of Complex Systems?

While operational opacity generated by machine learning algorithms presents a wide range of problems for ethics and computer science (Burrell 10), one type in particular may be unavoidable due to the nature of complex processes. The physical underpinnings of functional systems may be difficult to understand because of the way data is stored and transmitted. Just as patterns of neural activity seem conceptually distant from first-person accounts of subjective experiences, the missing explanation for why or how a DCNN arrives at a particular decision may actually be a feature of the system rather than a bug. Systems capable of storing or processing large amounts of data may only be capable of doing so because of the way nested relationships are embedded in the structure. Furthermore, many of the human behaviours or capacities researchers are trying to understand and copy are both complex and emergent, making them difficult to fully trace back to the physical level of implementation. When we do, it often looks strange and quite chaotic. For example, molecular genetics suggests various combinations of nucleotides give rise to different types of cells and proteins, each with highly specialized and synergistic functions. Additionally, complex phenotypes like disease dispositions are typically the result of many interacting genotypic factors in conjunction with the presence of certain environmental variables. If it turns out to be the case that a degree of opacity is a necessary component of convoluted functionality, we may need to rethink our expectations of how ethics can inform the future of AI development.

Works Cited

Burrell, Jenna. “How the machine ‘thinks’: Understanding opacity in machine learning algorithms.” Big Data & Society 3.1 (2016).

Addiction by Design: Candy Crush et al.

For class this week, we read the first four chapters of Natasha Schull’s book Addition by Design. I think the goal was to consider the similarities and differences between slot machines and gaming applications on handheld devices.

While the two addictions are comparable despite their differences in gameplay format, apps like Candy Crush have found profitable solutions to their unique problems. Developers expect players to “leave their seats” as cellphone use generally orbits around other aspects of daily life. While “time on device” (58) is surely an important part of app design, creating incentives for users to return are also significant. Though this may be accomplished in a number of ways, a common strategy is to generate frequent notifications to both remind and seduce users back to their flow state (49). Overall, the approach may seem less inviting than sounds and lights but its ability to display explicit directions may be effective. Text has the ability to specify rewards if the user opens the app right then and there. A pay structure involving varying wait times may also push users to pay for the ability to return to “the zone” (2). This may take the form of watching an advertisement or being disallowed to play for intervals from an hour to a day, sufficiently frustrating users to pay to continue playing. Similarly to embedding ATMs in slot machines (72), app stores with saved credit card information allow developers to seamlessly lead users to the ‘purchase’ button, quickly increasing revenue. Financial transactions thinly disguised as a part of the game offer a new way to siphon money from vulnerable individuals, especially parents of children with access to connected devices. Additionally, gaming apps are typically weakly associated with physical money like bills and coins, unlike slot machines from mid 20th century (62), perhaps making it easier for consumers to pay without drawing their attention to the movement of money. This brief analysis suggests the nature of gambling is evolving by modifying existing modes of persuasion and adapting to new technological environments.

One large concern, however, arises from where this money goes; while governmental agencies oversee regulations (91) and collect revenue (5) to fund programs and projects, private companies simply collect capital. This carries severe implications for individuals, communities and economies as this alternative stream of income dries up. Therefore, it could be suggested that state and provincial legislators should consider addressing this issue sooner than later.

Works Cited

Schüll, Natasha Dow. Addiction by design: Machine gambling in Las Vegas. Princeton University Press, 2014.

Algorithmic Transparency and Social Power

This term I’m taking the course Science and Ethics, and this week we read Langdon Winner’s 1980 article “Do Artifacts have Politics?” along with a paper from 2016 published by Brent Daniel Mittelstadt and colleagues titled “The ethics of algorithms: Mapping the debate.” We are encouraged to do weekly responses, and considering the concerning nature of what these articles are discussing, thought it should be presented here. There is definitely a lot that could be expanded upon, which I might consider doing at a later time.

Overall, the two articles suggested risks of discriminatory outcomes are an aspect of technological advancements, especially when power imbalances are present or inherent. The paper The ethics of algorithms: Mapping the debate focused particularly on algorithmic design and its current lack of transparency (Mittelstadt 6). The authors mention how this is an epistemic concern, as developers are unable to determine how a decision is reached, which leads to normative problems. Algorithmic outcomes potentially generate discriminatory practices which may generalize and treat groups of people erroneously (Mittelstadt 5). Thus, given the elusive epistemic nature of current algorithmic design, individuals throughout the entire organization can truthfully claim ignorance of their own business practices. Some may take advantage of this fact. Today, corporations that manage to successfully integrate their software into the daily life of many millions of users have little incentive to change, due to shareholder desires for financial growth. Until the system which implicitly suggests companies can simply pay a fee, in the form of legal settlements outside of court, to act unethically, this problem is likely to continue to manifest. This indeed does not inspire confidence for the future of AI as we hand over our personal information to companies and governments (Mittelstadt 6).

Langdon Winner’s on whether artifacts have politics provides a compelling argument for the inherently political nature of our technological objects. While this paper may have been published in 1980, its wisdom and relevance can be readily applied to contemporary contexts. Internet memes even pick up on this parallel; one example poses as a message from Microsoft stating those who program open-source software are communists. While roles of leadership are required for many projects or organizations (Winner 130), inherently political technologies have the hierarchy of social functioning as part of their conceptual foundations, according to Winner (133). The point the author aims to stress surrounds technological effects which impede social functioning (Winner 131), a direction we have yet to move away from considering the events leading up to and following the 2016 American presidential election. If we don’t strive for better epistemic and normative transparency, we will be met with authoritarian outcomes. As neural networks continue to creep into various sectors of society, like law, healthcare, and education, ensuring the protection of individual rights remains at risk.

Works Cited

Mittelstadt, Brent Daniel, et al. “The ethics of algorithms: Mapping the debate.” Big Data & Society 3.2 (2016): 1-21.

Winner, Langdon. “Do artifacts have politics?.” Daedalus 109.1 (1980): 121-36.

Update: Phil of Bio

The University of Guelph has a Philosophy of Biology course and it was everything I was hoping it would be. Jointly taught by Dr. Stefan Linquist and Dr. Ryan Gregory, our focus on arguments surrounding epigenetics led many to agree there isn’t really a lot of new information. The book Extended heredity: a new understanding of inheritance and evolution turned out to be hilariously contradictory, as many of the concepts it presented can be easily explained by existing biological theories. I had an opportunity to receive feedback on ideas I have about Chalmers’ “bridging principles” and how biological processes produce subjective feelings. As I suspected, an incredible amount of work needs to be done to get these ideas together, but I have a direction now. The project is being placed on the back burner though and so is my attempt to work on consciousness at school. I’m not too worried, I’ll get to it later.

For now, I’m going to work on an argument for an upcoming need to reconsider our conception of robots and our relationships with them, particularly as they begin to resemble subjects rather than objects. There is a growing demand for robotic solutions within the realm of healthcare, suggesting certain functionality must be incorporated to achieve particular outcomes. Information processing related to social cues and contexts such as emotional expression will be important to uphold patient dignity and foster well-being. Investigating Kismet‘s architecture suggests cognition and emotion operate in tandem to orient agents toward goals and methods for obtaining them. The result of this functional setup, however, is it requires humans to treat Kismet like a biological organism, implying a weak sense of subjectivity. I’m also interested in considering objections to the subjectivity argument and reasons why our relationships with robots will remain relatively unchanged.

My original post on the philosophy of biology cited the entry from the Stanford Encyclopedia of Philosophy which is authored Paul Griffiths. I learned earlier this term that Dr. Linquist studied under Dr. Griffiths, a fact that should not be surprising but is still quite exciting.

I’m looking forward to working on this project and the outcome of the feedback and learning, but I am going to get knocked down many levels over the next six months or so. I mean, that’s why I am here.

Works Cited

Bonduriansky, Russell, and Troy Day. Extended heredity: a new understanding of inheritance and evolution. Princeton University Press, 2018.

Ontic Structural Realism

John Worrall’s paper “Structural realism: The best of both worlds?” mostly outlines the debate occurring within the Philosophy of Science surrounding whether scientific realism or anti-realism best captures our intuitions and intentions regarding the scientific process and its history. Although this topic on its own is a fascinating discussion, it will not the focus of this article. Instead, I’d like to explore Worrall’s reply and its implications when approached from a metaphysical perspective. At the end of his paper, Worrall concludes that combining an aspect of realism with an anti-realist attitude produces a potential solution to the dilemma. Structural realism describes a perspective which can account for the predictive success of science while also explaining how scientific revolutions changed theories and research practices throughout history (Worrall 123). Structural realists believe that when scientific theories undergo conceptual change, their form or structure remains constant while the content of a theory may be modified based on new empirical findings (Worrall 117). He believes this account is able to explain how scientific theories are able to undergo both growth and replacement over time (Worrall 120).

However, structural realism can be further divided into two different categories which support differing views. The epistemic structural realist (ESR) believes all we can learn through scientific inquiry is the accuracy of a theory’s inherent structure, and not the concepts or entities themselves (Ladyman SEP). The more extreme version, ontic structural realism (OSR), states that there are no objects or things, and the universe is only comprised of structures, forms, and relations (Ladyman SEP). Van Fraassen describes this position as “radical structuralism” (van Fraassen 280) and appeals to science’s use of mathematical formulas to serve as motivation for this view (van Fraassen 304). Since physics uses math to describe how the physical world operates, and complex bodies of organic machinery operate based on the rules of physics, objects found in nature can theoretically be explained in mathematical terms. Although our conceptions of these entities may change dramatically over time, their mathematical descriptions and relations tend to expand as new discoveries are incorporated into existing theories (van Fraassen 305).

Although the discussion surrounding structural realism originally aimed to answer problems in the philosophy of science, OSR eventually became its own metaphysical view. This is partly due to discoveries made in physics over the previous century, shaping how we think about the natural world, especially in the subatomic domain (Ladyman SEP). At one point, an atom was thought to be the smallest unit of matter in the universe, with its original Greek word atomos meaning ‘indivisible’ (merriam-webster.com). Today however, we are able to run tests which not only divide atoms, but smash them together in order to inspect the pieces which make up the subatomic particles themselves. Furthermore, as our understanding of quantum physics grows, the less neat-and-tidy the world seems to be packaged.

My goal here is not to convince you to fully adopt the OSR perspective, but to consider it as a tool for drafting instances of artificial general intelligence and artificial consciousness. Personally, I find this approach to understanding reality very interesting and am compelled by the notion of “structures all the way down.” However, some may find this problematic as the relata seem to be missing. What is the ‘stuff’ that the structure is made out of? What exactly is being organized in a structural way? In a nutshell, segments of miniature structures. An example of this is the relationship between chemical bonds and the physical laws which binds them together. Or a Swiss army knife made of small metal parts, where these pieces consist entirely of a combination of metal atoms arranged into shapes. But these atoms themselves are just structures of subatomic particles, consisting of protons, neutrons, and electrons. Moreover, if we continue to zoom in, it turns out that these particles are just comprised of other particles arranged in different relations. Each contemporary understanding of “matter” and “mass” changes based on  technological improvements, assisting in the production and interpretation scientific experiments. It may turn out that OSR becomes a useful perspective for conceptualizing our universe, especially as old assumptions are reworked to include new and possibly contradictory empirical discoveries.

Speaking of perception, if there are no objects, then does everything exist in the mind like Berekely thought? I think the answer to this is a little ‘yes’ and a little ‘no’: the brain creates representations of concepts which are based on learned regularities from interacting within an environment. From an evolutionary perspective, the brain adapted to help promote an individual’s survival by learning to recognize patterns and recall previous events. As neuronal structures developed to support new and more complex functions, the individual’s subjective awareness of their abilities grew as well, eventually producing mental concepts and linguistic labels. For example, neurons in the primary auditory cortex are arranged tonotopically, where particular cells responding to specific frequencies are arranged by pitch from low to high (Romani, Williamson, and Kaufman 1339). In this sense then, a C major scale played on a piano can be viewed as isomorphic to the way these frequencies are physically realized in the brain. Rather than the world or universe containing ‘a C major scale’, from an OSR perspective, reality only contains the laws which govern how sound pressures and vibrations must exist and operate such that a musical scale can be realized in a human brain. From an individual’s perspective however, this type of stimuli is represented as ‘music’ or ‘the sound of a piano’.

An unpublished article by Brian Cantwell Smith called Non-Conceptual World discusses a similar perspective to structural realism, claiming that concepts only exist in the mind (Cantwell Smith 8). One example Cantwell Smith mentions is the aftermath of the volcanic eruption which occurred in ancient Pompeii (see photo below). While he uses this as an example of how object recognition is an intentional process (Cantwell Smith 16), I was reminded of an optical illusion which shares important similarities to depictions of Pompeii. The Dalmation Illusion (see photo below) is just a series of black and white dots, yet somehow the brain manages to pick out the form of a dog. In reality however, there is no dog and the image is deemed an illusion. However, the image of the Pompeii disaster indicates that there really is a person amidst the variety of grey blotches. In both instances, the incoming visual information seems to be quite similar at first, but the stored contextual information associated with the visual stimuli creates a contrast in the conceptual representation of each “object”. I tend to agree with Cantwell Smith when he says “there aren’t any objects out there” (8) because an evolutionary perspective suggests the brain generated object-based concepts, not the universe.

If this is so, what can be said about human consciousness? Natural selection is the process of increasing genetic diversity through reproduction, as well as constraining it through environmental pressures, producing a mechanism for building and refining chemical and physiological structures. It seems likely that psychological structures are also subject to this same type of development, or at least impacted by it. Random genetic mutations may produce functional changes which impact neighbouring structures, requiring other neurons to update their internal and external organization as a result. If this change produces a large enough effect, a small patch of cortex or connected regions may also be impacted, leading the individual to notice alterations in their motor or perceptual abilities. By viewing the brain as a structure of networks and configurations, it can be suggested that consciousness may have emerged as a result of one or more self-organizing structures interacting within both internal and external environments over time.

Therefore, consciousness is an emergent property of the brain, but there may be more to this story, as will be discussed in future articles. Briefly though, consciousness, or some version of intelligent self-awareness, may be a direct result of the self-organizing system which constitutes evolution. Furthermore, could consciousness be an inevitable outcome of an instance of natural selection? Is there a threshold in the variables which makes this outcome necessity to occur, like an action potential in a neuron? I am also looking forward to discussing Dynamical Systems Theory and Information Theory as they relate to these ideas as well.

The reason OSR is important for designing artificial minds is because of its power to generate isomorphic versions of laws from the natural world. If an object or entity can be conceptualized as a series of structures with functional regularities, machine code and mathematical systems may be able to generate models which produce similar behaviours or results. Since neural networks and deep learning have found success in perceptual recognition, perhaps it will be beneficial for taking a developmental approach to artificial consciousness as well.

Edited version:

Works Cited

“Atom.” Merriam-Webster.com. Merriam-Webster, n.d. Web. 26 May 2018.

Blauw, Laura. Bodies in Pompeii. 2008, digital photograph. https://lauraotms.deviantart.com/art/Bodies-in-Pompeii-83587124

Ladyman, James, “Structural Realism”, The Stanford Encyclopedia of Philosophy (Winter 2016 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/win2016/entries/structural-realism/>.

Romani, Gian Luca, Samuel J. Williamson, and Lloyd Kaufman. “Tonotopic organization of the human auditory cortex.” Science 216.4552 (1982): 1339-1340.

Van Fraassen, Bas C. “Structure: Its shadow and substance.” The British Journal for the Philosophy of Science 57.2 (2006): 275-307.

Worrall, John. “Structural realism: The best of both worlds?.” Dialectica 43.1‐2 (1989): 99-124.