Mind – The Early Days

Artifacts

What does it mean to call something an example of “artificial intelligence” (AI)? There are a few different ways to approach this question, one of which includes examining the field to identify an overarching definition or set of themes. Another involves considering the meanings of the words ‘artificial’ and ‘intelligence’, and arguably, doing so enables the expansion of this domain to include new approaches to AI. Ultimately, however, even if these agents one day exhibit sophisticated or intelligent behaviours, they nonetheless continue to exist as artifacts, or objects of creation.

The term artificial intelligence was conceived by computer scientist John McCarthy in 1958, and the purported reason he chose the term was to distinguish it from other domains of study.¹ In particular, the field of cybernetics which involves analog or non-digital forms of information processing, and automata theory as a branch of mathematics which studies self-propelling operations.² Since then, the term ‘artificial intelligence’ has been met with criticism, with some questioning whether it is an appropriate term for the domain. Specifically, Arthur Samuel was not in favour of its connotations, according to computer scientist Pamela McCorduck in her publication on the history of AI.³ She quotes Samuel as stating “The word artificial makes you think there’s something kind of phony about this, or else it sounds like it’s all artificial and there’s nothing real about this work at all.”⁴

Given the physical distinctions between computers and brains, it is clear that Samuel’s concerns are reasonable, as the “intelligence” exhibited by a computer is simply a mathematical model of biological intelligence. Biological systems, according to Robert Rosen, are anticipatory and thus capable of predicting changes in the environment, enabling individuals to tailor their behaviours to meet the demands of foreseeable outcomes.⁵ Because biological organisms depend on specific conditions for furthering chances of survival, they evolved ways to detect these changes in the environment and respond accordingly. As species evolved over time, their abilities to detect, process, and respond to information expanded as well, giving rise to intelligence as the capacity to respond appropriately to demanding or unfamiliar situations.⁶ Though we can simulate intelligence in machines, the use of the word ‘intelligence’ is metaphorical rather than literal. Thus, behaviours exhibit by computers is not real or literal ‘intelligence’ because it arises from an artifact rather than from biological outcomes.

An artifact is defined by Merriam-Webster as an object showing human workmanship or modification, as distinguished from objects found in nature.⁷ Etymologically, the root of ‘artificial’ is the Latin term artificialis or an object of art, where artificium refers to a work of craft or skill and artifex denotes a craftsman or artist.⁸ In this context, ‘art’ implies a general sense of creation and applicable to a range of activities including performances as well as material objects. The property of significance is its dependence on human action or intervention: “artifacts are objects intentionally made to serve a given purpose.”⁹ This is in contrast to unmodified objects found in nature, a distinction first identified by Aristotle in Metaphysics, Nicomachean Ethics, and Physics.¹⁰ To be an artifact, the object must satisfy three conditions: it is produced by a mind, involves the modification of materials, and is produced for a purpose. To be an artifact, an object or entity must meet all three criteria.

The first condition states the object must have been created by a mind, and scientific evidence suggests both humans and animals create artifacts.¹¹ For example, beaver dams are considered artifacts because they block rivers to calm the water which creates ideal conditions for a building a lodge.¹² Moreover, evidence suggests several early hominid species carved handaxes which serve social purposes as well as practical ones.¹³ By chipping away at a stone, individuals shape an edge into a blade which can be used for many purposes, including hunting and food preparation.¹⁴ Additionally, researchers have suggested that these handaxes may also have played a role in sexual selection, where a symmetrically-shaped handaxe demonstrating careful workmanship indicates a degree of physical or mental fitness.¹⁵ Thus, artifacts are important for animals as well as people, indicating the sophisticated abilities involved in the creation of artifacts is not unique to humans.

Computers and robots are also artifacts given that they are highly manufactured, functionally complex, and created for a specific purpose. Any machine or artifact which exhibits complex behaviour may appear to act intelligently, however, the use of ‘intelligent’ is necessarily metaphorical given the distinction between artifacts and living beings. There may one day exists lifelike machines which behave like humans, however, any claims surrounding literal intelligence must demonstrate how and why that is; the burden of proof is theirs to produce. An argument for how a man-made object sufficiently models biological processes is required, and even then, remains a simulation of real systems.

If the growing consensus in cognitive science indicates individuals and their minds are products of interactions between bodily processes, environmental factors, and sociocultural influences, then we should to adjust our approach to AI in response. For robots intending to replicate human physiology, a good first step would be to exchange neural networks made from software for ones built from electrical circuits. The Haikonen Associative Neuron offers a solution to this suggestion,¹⁶ and when coupled with the Haikonen Cognitive Architecture, is capable of generating the required physiologicalprocesses for learning about the environment.¹⁷ Several videos uploaded to YouTube demonstrate a working prototype of a robot built on these principles, where XCR-1 is able to learn associations between stimuli in its environment, similarly to humans and animals.¹⁸ Not only is it a better model of animal physiology than robots relying on computer software, the robot is capable of performing a range of cognitive tasks, including inner speech,¹⁹ inner imagery,²⁰ and recognizing itself in a mirror.²¹

So, it seems that some of Arthur Samuel’s fears have been realized, considering machines merely simulate behaviours and processes identifiable in humans and animals. Moreover, the use of ‘intelligence’ is metaphorical at best, as only biological organisms can display true intelligence. If an aspect of Samuel’s concerns related to securing funding within his niche field of study, and its potential to fall out of fashion, he has no reason to worry. Unfortunately, Samuel passed away in 1990²² so he would not have had a chance to see the monstrosity that AI has since become.

Even if these new machines were to become capable of sophisticated behaviours, they will always exist as artifacts, objects of human creation and designed for a specific purpose. The etymological root of the word ‘artificial’ alone provides sufficient grounds for classifying these robots and AIs as objects, however, as they continue to improve, this might become difficult to remember at times. To avoid being deceived by these “phony” behaviours, it will become increasingly important to understand what these intelligent machines are capable of and what they are not.

Works Cited

1 Nils J. Nilsson, The Quest for Artificial Intelligence (Cambridge: Cambridge University Press, 2013), 53, https://doi.org/10.1017/CBO9780511819346.

2 Nilsson, 53.

3 Nilsson, 53.

4 Pamela McCorduck, Machines Who Think: A Personal Inquiry Into the History and Prospects of Artificial Intelligence, [2nd ed.] (Natick, Massachusetts: AK Peters, 2004), 97; Nilsson, The Quest for Artificial Intelligence, 53.

5 Robert Rosen, Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations, 2nd ed., IFSR International Series on Systems Science and Engineering, 1 (New York: Springer, 2012), 7.

6 ‘Intelligence’, in Merriam-Webster.Com Dictionary (Merriam-Webster), accessed 5 March 2024, https://www.merriam-webster.com/dictionary/intelligence.

7 ‘Artifact’, in Merriam-Webster.Com Dictionary (Merriam-Webster), accessed 17 October 2023, https://www.merriam-webster.com/dictionary/artifact.

8 Douglas Harper, ‘Etymology of Artificial’, in Online Etymology Dictionary, accessed 14 October 2023, https://www.etymonline.com/word/artificial; ‘Artifact’.

9 Lynne Rudder Baker, ‘The Ontology of Artifacts’, Philosophical Explorations 7, no. 2 (1 June 2004): 99, https://doi.org/10.1080/13869790410001694462.

10 Beth Preston, ‘Artifact’, in The Stanford Encyclopedia of Philosophy, ed. Edward N. Zalta and Uri Nodelman, Winter 2022 (Metaphysics Research Lab, Stanford University, 2022), https://plato.stanford.edu/archives/win2022/entries/artifact/.

11 James L. Gould, ‘Animal Artifacts’, in Creations of the Mind: Theories of Artifacts and Their Representation, ed. Eric Margolis and Stephen Laurence (Oxford, UK: Oxford University Press, 2007), 249.

12 Gould, 262.

13 Steven Mithen, ‘Creations of Pre-Modern Human Minds: Stone Tool Manufacture and Use by Homo Habilis, Heidelbergensis, and Neanderthalensis’, in Creations of the Mind: Theories of Artifacts and Their Representation, ed. Eric Margolis and Stephen Laurence (Oxford, UK: Oxford University Press, 2007), 298.

14 Mithen, 299.

15 Mithen, 300–301.

16 Pentti O Haikonen, Robot Brains: Circuits and Systems for Conscious Machines (John Wiley & Sons, 2007), 19.

17 Pentti O Haikonen, Consciousness and Robot Sentience, 2nd ed., vol. 04, Series on Machine Consciousness (WORLD SCIENTIFIC, 2019), 167, https://doi.org/10.1142/11404.

18 ‘Pentti Haikonen’, YouTube, accessed 6 March 2024, https://www.youtube.com/@PenHaiko.

19 Haikonen, Consciousness and Robot Sentience, 182.

20 Haikonen, 179.

21 Robot Self-Consciousness. XCR-1 Passes the Mirror Test, 2020, https://www.youtube.com/watch?v= WE9QsQqsAdo.

22 John McCarthy and Edward A. Feigenbaum, ‘In Memoriam: Arthur Samuel: Pioneer in Machine Learning’, AI Magazine 11, no. 3 (15 September 1990): 10, https://doi.org/10.1609/aimag.v11i3.840.

March 6, 2024

Chaos in the System

As an argument against iCub’s ability to understand humans, I wanted to appeal to the work of Robert Rosen because I think it makes for a compelling argument about AI generally. To accomplish this, however, my project would start to go in a new direction which renders it less cohesive overall. Instead, the Rosen discussion is better served as a stand alone project because there is a lot of explaining yet to do, and maybe some objections that need discussing as well. This will need to wait but I can at least upload the draft for context on the previous post. There are a few corrections I still need to make but once it’s done, I will update this entry.

Instead, I will argue that the iCub is not the right system for social robots because its approach to modelling emotion is unlike the expression of emotions in humans. As a result, it cannot experience nor demonstrate empathy in virtue of the way it is built. The cognitive architecture used by iCub can recognize emotional cues in humans, however, this information is not experienced by the machine. Affective states in humans are bodily and contextual, but in iCub, they are represented by computer code to be used by the central processing unit. This is the general idea but I’m still working out the details.

That said, there is something interesting in Rosen’s idea about the connection between Gödel’s Incompleteness Theorem and the incompleteness between syntax and semantics. In particular, what he identifies is the problems generated from self-reference which leads the system to produce an inconsistency given its rule structure. The formal representation of an external referent, as an observable of a natural system, contains only the variables relevant for the referent within the formal system. Self-reference requires placing a variable within a wider scope, one which must be provided in the form of a natural system. Therefore, an indefinite collection of formal systems is required to capture a natural phenomenon. Sometimes a small collection is sufficient, while other times, systems are so complex that a collection of formal systems is insufficient for fully accounting for the natural phenomenon. Depending on the operations to be performed on the referent, it may break the system or lead to erroneous results. The chatbot says something weird or inappropriate.

In December, I presented this argument at a student conference and made a slideshow for it. Just a note: on the second slide I list the titles of my chapters, and because I won’t be pursuing the Rosen direction, the title of Chapter 4 will likely change. Anyway, the reading and writing on Rosen has taken me on a slight detour but a worthwhile one. Now, I need to begin research on emotions and embodiment, which is also interesting and will be useful for future projects as well. The light at the end of the tunnel has dimmed a bit but it’s still there, and my eyes have adjusted to the darkness so it’s fine.

This shift in directions makes me think about the relationship between chaos and order, and systems that swing between various states of orderliness. Without motion there would be rest and stagnation, so as much as change can be challenging, it can bring new opportunities. There is a duality inherent in everything, as listed as one of 7 Hermetic Principles. If an orderly, open system is met with factors which disrupts or disorganizes functioning, the system must undergo some degree of reorganization or compensation. The explanatory powers of the 7 Principles are not meant to relate to the external world in the way physics does, but relate to one’s perspective of events in the outside world. If one can shift their perspective accordingly, they operate as axioms for sense-making, their reality pertaining more to epistemology than ontology. We can be sceptical as to how these Principles manifest in the physical universe while feeling their reality in our lived experience of the world. They are to be studied from within rather than from without, and are thus more aligned with phenomenology than the sciences.

Metaphorically speaking, chaos injected into any well-ordered system has the potential to severely damage or disrupt it, requiring efforts to rebuild and reorganize to compensate for the effects of change. The outcome of this rebuilding process can be further degradation and maybe even collapse, however, it can lead to growth and better outcomes than if the shift had not occurred. It all depends on the system in question and the factors which impacted it, and probably the specific context in which the situation occurred, but it might depend on the system in question. Anyway, we substitute the idea of ‘chaos’ for ‘energy’ as movement or potential, thus establishing a connection to ‘light’ as a type of energy. Metaphorically, ‘light’ is also associated with knowledge and beneficence, so if the source of chaos is intentional and well-meaning, favourable changes can occur and thus a “light bringer” or “morning star” can be associated with positive connotations. Disrupting a well-ordered system without knowledge or a plan or good reasons is more likely to lead to further disorder and dysfunction, leading to negative or unfavourable outcomes. In this way, Lucifer can be associated with evil or descent.

This kind of exercise can help us make sense of our experiences and understanding, but they also give us into a window into the past and how other people may think. Myth and legend from cultures all over the world portray knowledge in metaphors which inspire those who come upon them for generations since. The metaphysics are not important, it’s the epistemology from the metaphors which can explain aspects of how the world works or why people think certain things or act in certain ways. It exists as poetry which needs interpreting and there is room for multiple perspectives, so not everyone appreciates it which is understandable. It is still valuable work to be done by someone though, and the more people the better.

★★★

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February 6, 2024

Moving On Up

Given my last post, I should probably explain myself. I still don’t know what I’m doing but maybe simple acceptance isn’t all it’s cracked up to be. We have the power to change our circumstances, so why not give it a go? A saying I often think about is “ships aren’t built to sit in harbours” and while one can avoid risk this way, you also don’t get to see far off lands either.

Time to rebuild. What do I know? I know what I feel; phenomenology is a good place to start. I still stand behind everything I stated regarding qualia. There may be aspects to my hypothesis that might change or there might be something I’m missing, however, to state that the entire idea is wrong is a hastily generated conclusion.

There is probably more to consciousness than can be captured by our current scientific understanding, however, one must tread very carefully when moving in this direction. Figuring out what this involves and how it works is my new pet project and hopefully I can make some headway. I’m not in a rush though.

Here’s the big reveal: I read the CIA document titled Analysis and Assessment of Gateway Process in addition to Itzhak Bentov’s book Stalking the Wild Pendulum. Luckily for us, Thobey Campion has done some very important investigative journalism regarding the missing page 25 from the CIA document; thank you very much for your work Thobey. I strongly encourage you to read the Vice article about it while it’s still available. I have a hunch that this article won’t be around for a long time but hopefully I’m wrong.

I want someone to explain the physics to me like I’m 5 and stick around for a lengthy Q&A session. I want to know how this works in a way that connects to our current understanding of physics. Bentov’s book seems to get about halfway there but doesn’t explain all the details necessary to generate a full explanation of the phenomenon. If you know of anyone who has written about this, please email me because I’m very interested in exploring this further.

Page 25 is truly the most important page in the CIA document because it reiterates a certain truth that serves as the bedrock for creating the Philosopher’s Stone: self-awareness. Unwavering, unfiltered, unapologetic self-awareness.

“It was axiomatic to the mystic philosophers of old that the first step in personal maturity could be expressed in the aphorism: “Know thyself.” To them, the education of a man undertook, as its primary step, achievement of an introverted focus so that he learned what was within himself before attempting to approach the outside world. They rightly assumed that he could not effectively evaluate and cope with the world until he fully understood his personal psychological imbalance. The insights being provided by Twentieth Century psychology in this context through the use of various kinds of personality testing seem to be a revalidation of this ancient intuition. But no personality test, or series of tests, will ever replace the depth and fullness of the perception of self which can be achieved when the mind alters its state of consciousness sufficiently to perceive the very hologram of itself which it has projected into the universe in its proper context as part of the universal hologram in a totally holistic and intuitional way. This would seem to be one of the real promise of the Gateway Experience from the standpoint of its ability to provide a portal through which, based on months if not years of practice, the individual may pass in his search to find self, personal effectuality, and truth in the larger sense.”

The appeal to holograms here might rub some the wrong way, however, I think this has something to do with Kantian metaphysics. Specifically, that everything is just sense data, and while we don’t necessarily need to go full Berkeley, we must always remember that our experiences are simply appearances, not objective data. Where does certainty come from? The synthesis of a first-person perspective and third-person perspective. Do not simply defer to what everyone else says but do not ignore it either.

This I know. As do many others, many (most?) of which have lived before I or Bentov or anyone else around today. What I might add, though, is that it always takes two to tango. Men and women together as fully-developed agents even when it generates a conflict. When done in good faith, the outcome is so much more, so much greater, than either one alone.

July 21, 2023

Implicit Argument for Qualia

Steven Harnad provides an embodied version of the Turing Test (TT) in Other Bodies, Other Minds by using a robot instead of a computer, calling it the Total Turing Test (TTT). He states that to be truly indistinguishable from a human, artificial minds will require the ability to express embodied behaviours in addition to linguistic capacities (Harnad 44). While the TT implicitly assumes language exists independently from the rest of human behaviour (Harnad 45), the TTT avoids problems arising from this assumption by including a behavioural component to the test (Harnad 46). This is due to our tendency to infer other humans have minds despite the fact individuals do not have direct evidence for this belief (Harnad 45). This assumption can be extended to robots as well, where embodied artificial agents which act sufficiently human will be treated as if it had a mind (Harnad 46). Robots which pass the TTT can be said to understand symbols because these symbols have been grounded in non-symbolic structures or bottom-up sensory projections (Harnad 50–51). Therefore, embodiment seems to be necessary for social agents as they will require an understanding of the world and its contents to appear humanlike.

These sensory projections are also known as percepts or qualia (Haikonen 225), and are therefore required for learning language. While Harnad’s intention may have been to avoid discussing metaphysical properties of the mind, for the sake of discussing the TTT, his argument ends up providing support for the ontological structures involved in phenomenal consciousness. Although I didn’t mention it above, he uses this argument to refute Searle’s concerns about the Chinese Room, and the reason he is successful is due to the fact he is identifying an ontological necessity. Robots which pass the TTT will have their own minds because the behaviours which persuade people to believe this is the case are founded on the same processes that produce this capacity in humans.

Works Cited

Haikonen, Pentti O. ‘Qualia and Conscious Machines’. International Journal of Machine Consciousness, Apr. 2012. world, www.worldscientific.com, https://doi.org/10.1142/S1793843009000207.

Harnad, Stevan. ‘Other Bodies, Other Minds: A Machine Incarnation of an Old Philosophical Problem’. Minds and Machines, vol. 1, no. 1, 1991, pp. 43–54.

February 9, 2022