if imagination rims
it is a model of mind’s running
as much as running
decompletes geometries
and geometries might
lessen lines decomposed
pointing out
higher dimensions
to a dot
•
say dot
convinced as your lover and claimed
to recreate imagination
as if a finding of the century
compared to the greats
equated even
enunciated to inflate
make all believe
sanity is a concentrate
in
you
—animasuri’24
From The Closed World
to The Infinite Universe
from a closed mind
to an enclosed one
at that point where
kinetic elasticity
snaps consciousness
out of place
and yet again
knows but of
expanding,
ex-panding,
ex-pan-ding
to Things Never Seen ping
Thoughts Never Thought
On the Real Space
or the Infinite Being rung
what scientific exploration
speaks one of
where poetics
has no place?
if universes were
such silenced places
matter to waves
would bewilder life
losing their ways
diverging from their root
if universes were predefined
does it wave preference to zero
I mean, or do I,
that type with cubist sharp edges
and deschooled breakage
from meter or measurements
that type escaping clutches
of scholarly veneration
escaping space or place
that type typically touted
by few and written to be unspoken
that type when observed
is altered to serve
meaning what is found
approaching the root
at your pleasure, ah reader, dear.
—animasuri’24—-•
some triggers
Raphson, Joseph. (1702). Analysis Equationum UNIVERSALIS, SEU Ad EQUATIONES ALGEBRAICAS Resolvendas METHODUS Generalis, et Expedita, Ex nova Infinitarum serierum Doctrina, DEDUCTA AC DEMONSTRATA.
Thomas, D. J., & Smith, J. M. (1990). Joseph Raphson, F.R.S. Notes and Records of the Royal Society of London, 44(2), 151–167. http://www.jstor.org/stable/531605
context: Tangermann, Victor. ( Feb 16, 2023). Microsoft: It’s Your Fault Our AI Is Going Insane They’re not entirely wrong. IN: FUTURISM (online). Last retrieved on 23 February 2023 from https://futurism.com/microsoft-your-fault-ai-going-insane
LLM types of technology and their spin-offs or augmentations, are made accessible in a different context then technologies for which operation requires regulation, training, (re)certification and controlled access.
If the end-user holds the (main) weight of duty-of-care, then such training, certification, regulation and limited access should be put into place. Do we have that, and more importantly: do we really want that?
If we do want that, then how would that be formulated, be implemented and be prosecuted? (Think: present-day technologies such as online proctoring, keystroke recording spyware, Pegasus spyware, Foucault’s Panopticon or the more contextually-pungent “1984”)
If the end-user is not holding that weight and the manufacturer is, and/or if training, (re)certification, access and user-relatable laws, which could define the “dos-and-don’ts,” are not readily available then… Where is the duty-of-care?
Put this question of (shared) duty-of-care in light of critical analysis and of this company supposedly already knowing in November 2022 of these issues, then again… Where is the duty-of-care? (Ref: https://garymarcus.substack.com/p/what-did-they-know-and-when-did-they?r=drb4o )
Thirdly, put these points then in context of disinformation vs information when e.g. comparing statistics as used by a LLM-based product vs the deliverables to the public by initiatives such as http://gapminder.org or http://ourworldindata.org or http://thedeep.io to highlight but three instances of a different systematized and methodological approach to the end-user (one can agree or disagree with these; that is another topic).
So, here are 2 systems which are both applying statistics. 1 system aims at reducing our ignorance vs the other at…increasing ignorance (for “entertainment” purposes… sure.)? The latter has serious financial backing, the 1st has…?
Do we as a social collective and market-builders then have our priorities straight? Knowledge is no longer power. Knowledge is submission to “dis-“ packaged as democratized, auto-generating entertainment.
Epilogue-1:
Questionably “generating” (see above “auto-generating entertainment”) —while arguably standing on the shoulders of others—rather: mimicry, recycling, or verbatim copying without corroboration, reference, ode nor attribution. Or, “stochastic parroting” as offered by Prof. Dr. Emily M. Bender , Dr. Timnit Gebru et al. is relevant here as well. Thank you Dr. Walid Saba for reminding us. (This and they are perhaps suggesting a fourth dimension in lacking duty-of-care).
Epilogue-2:
to make a case: I ran an inquiry through ChatGPT requesting a list of books on abuses with statistics and about 50% of the titles did not seem to exist, or are so obscure that no human search could easily reveal them. In addition a few obvious titles were not offered. I tried to clean it up and add to it here below.
bibliography:
Baker, L. (2017). Truth, Lies & Statistics: How to Lie with Statistics.
Barker, H. (2020). Lying Numbers: How Maths & Statistics Are Twisted & Abused.
Best, J. (2001). Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists. Berkeley, CA: University of California Press.
Best, J. (2004). More Damned Lies and Statistics.
Dilnot, A. (2007). The Tiger That Isn’t.
Ellenberg, J. (2014). How Not to Be Wrong.
Gelman, A., & Nolan, D. (2002). Teaching Statistics: A Bag of Tricks. New York, NY: Oxford University Press.
Huff, D. (1954). How to Lie with Statistics. New York, NY.: W. W. Norton & Company.
Levitin, D. (2016). A Field Guide to Lies: Critical Thinking in the Information Age. Dutton.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York, NY Crown.
Rosling, H., Rosling Ronnlund, A. (2018). Factfulness: Ten Reasons We’re Wrong About the World–and Why Things Are Better Than You Think. Flatiron Books; Later prt. edition
Seethaler, S. (2009). Lies, Damned Lies, and Science: How to Sort Through the Noise Around Global Warming, the Latest Health Claims, and Other Scientific Controversies. Upper Saddle River, NJ: FT Press.
Silver, IN. (2012). The Signal and the Noise: Why So Many Predictions Fail – but Some Don’t. New York, NY: Penguin Press.
Stephens-Davidowitz, S. (2017). Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are.
Tufte, E. R. (1983). The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press.
Wheeler, M. (1976). Lies, Damn Lies, and Statistics: The Manipulation of Public Opinion in America.
Ziliak, S. T., & McCloskey, D. N. (2008). The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives. Ann Arbor, MI: University of Michigan Press.
References
this post was triggered by:
thank you Katja Rausch
and by:
thank you Marisa Tschopp
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21). Association for Computing Machinery, New York, NY, USA, 610–623. https://doi.org/10.1145/3442188.3445922
“Verbatim copying” in the above post’s epilogue was triggered by Dr. Walid Saba ‘s recent post on LinkedIn:
This blog post on LinkedIn
Thinking of what I label as “boutique ethic”, such as AI Ethics, must indeed come with thinking about ethics (Cf. here ). I think this is not only an assignment for the experts. It is also one for me: the layperson-learner.
Or is it?
Indeed, if seen through more-than a techno-centric lens alone, some voices do claim that one should not be bothered with ethics if one does not understand the technology which is confining ethics into a boutique ethic; e.g. “AI”. (See 2022 UNESCO report on AI curriculum in K-12). I am learning to disagree .
I am not a bystander, passively looking on, and onto my belly button alone. Opening acceptance to Noddings’ thought on care (1995, 187) : “a carer returns to the cared-for,” when in the most difficult situations principles fail us (Rossman & Rallis 2010). How are we caring for those affected by the throwing around of the label “AI” (as a hype or as a scarecrow)?
Simultaneously, how are we caring for those affected by the siphoning off of their data, for application, unknown to the affected, of data derived from them and processed in opaque and ambiguous processes? (One could, as one of the many anecdotes, summon up the polemics surrounding DuckduckGo and Microsoft, or Target and baby product coupons, and so on)
And yet, let us expand back to ethics surrounding the boutiqueness of it: the moment I label myself (or another such as the humans behind DuckDuckGo) as “stupid”, “monster”, “trash”, “inferior”, ”weird”, “abnormal;” “you go to hell” or other more colorful itemizations, is the moment my (self-)care evaporates and my ethical compass moves away from the “...unconditional worth of all human beings and the equal respect to which they are entitled” (Rossman & Rallis 2010). Can then a mantra come to the aid: ”carer, return to the cared-for”? I want to say: “yes”.
Though, what is the impact of the mantra if the other does not apply this mantra (i.e., DuckDuckGo and Microsoft)? And yet, I do not want to get into a yoyo “spiel” of:
Speaker 1:“you first”,
Speaker 2: “no, you first”,
Speaker 1: “no, really, you first”.
Here a mantra of: “lead by example, and do not throw the first or n-ed stone” might be applicable? Is this then implying self-censorship and laissez-faire? No.
I can point at DuckDuckGo and Microsoft as an anecdote, and I think I can learn via ethics, into boutique ethics, what this could mean through various (ethical and other) lenses (to me, to others, to them, to it) while respecting the act of the carer. Through that lens I might wonder what drove these businesses to this condition and use that as a next steppingstone in a learning process. This thinking would take me out of the boutique and into the larger market, and even the larger human community.
The latter is what I base on what some refer to as the “ethic of individual rights and responsibilities” (Ibid). It is my responsibility to learn and ask and wonder. Then I assume that, the action by an individual who has following been debased by a label I were to throw at them (including myself), as those offered in the preceding sentence, is then judged by the “respect to which they are entitled” (Ibid). This is then a principle assuming that “universal standards exist” (Ibid). And yet, on a daily basis, especially on communal days, and that throughout history: I hurdle. After all we can then play with words “what is respect and what type of respect are they indeed entitled to?”
I want to aim for a starting point of an “unconditional” respect, however naive that might seem and however meta-Jesus-esque or Ghandi-esque, Dr. King-esque, or Mandela-esque that would require me to become. Might this perhaps be a left libertarian stance? Can I “respectfully” throw the first stone? Or lies the eruption in the metaphorical of “throwing a stone” rather than the physical?
Perhaps there are non-violent responses that are proportional to the infraction. This might come in handy. I can decide no longer to use DuckDuckGo. However, can I decouple from Microsoft without decoupling from my colleagues, family, community? Herein the learning as activism might then be found in looking and promoting alternatives toward a technological ecosystem of diversity with transparency, robustness and explainability and fair interoperability.
“Am I a means to their end?” I might ask then “or am I an end in myself?” This then brings me back to the roles of carer. Are, in this one anecdotal reference, DuckDuckGo and Microsoft truly caring about its users or rather about other stakeholders? Through a capitalist lens one might be inclined to answer and be done with it. However, I prefer to keep an openness for the future, to keep on learning and considering additional diversifying scenarios and acts that could lead to equity to more than the happy few.
Through a lens of thinking about consequences of my actions (which is said to be an opposing ethical stance compared to the above), I sense the outcome of my hurdling is not desirable. However, the introduction of alternatives or methods toward understanding of potentials (without imposing) might be. I do not desire to dismiss others (e.g., cast them out, see them punished, blatantly ignore them with the veil of silenced monologue). At times, I too believe that the act of using a label is not inherently right or wrong. So I hurdle, ignorant of the consequence to the other, their contexts, their constraints, their conditions and ignorant of the cultural vibe or relationships I am then creating. Yes, decomposing a relationship is creating a fragmented composition as much as non-dialog is dialog by absence. What would be my purpose? It’s a rhetorical question, I can guess.
I am able to consider some of the consequence to others (including myself), though not all. Hence, I want to become (more) caring. The ethical dichotomy between thinking about universals or consequence is decisive in the forming of the boutique ethic. Then again, perhaps these seemingly opposing ethics are falsely positioned in an artificial dichotomy. I tend to intuit so. The holding of opposing thought and dissonance is a harmony that simply asks a bit more effort that, to me, is embalmed ever so slightly by the processes of rhizomatic multidimensional learning.
This is why I want to consider boutique ethics while still struggling with being ignorant, yet learning, about types and wicket conundrums in ethics , at larger, conflicting and more convoluted scales. So too when considering a technology I am affected by yet ignorant of.
References
Gretchen B. R., Sharon F. R. (2010). Everyday ethics: reflections on practice, International Journal of Qualitative Studies in Education, 23:4, 379-391
Noddings, N. (1984). Caring: A feminine approach to ethics and moral education. Berkeley, CA: University of California Press.
Rawls, J. (1971). A theory of justice. Cambridge, MA: Harvard University Press.
Rossman, G.B., S.F. Rallis. (1998). Learning in the field: An introduction to qualitative research. Thousand Oaks, CA: Sage.
Rossman, G.B., S.F. Rallis. (2003). Learning in the field: An introduction to qualitative research. 2nd ed. Thousand Oaks, CA: Sage.
UNESCO. (2022). K-12 AI curricula-Mapping of government-endorsed AI curriculum.
The New Yorker and NSO in some glorious spy-novel context here
…and further, as a cherry on this cake, one might quickly conjure up Cambridge Analytica , or singularly, Facebook with its clandestine 50000+ or so datapoints per milked data-cow (aka what I also lovingly refer to as humans as datacyborgs) which the company’s systems are said to distill through data collection . Yes, arguably the singularity is already here.
Then, more recently, one can enjoy the application by a facial recognition service, Clearview AI, that uses its data mining to identify (or read: “spy on”) dead individuals; a service which might seem very commendable (even for individuals with no personal social media accounts, one simply has to appear in someone else’s visual material); and yet the tech has been applied for more.
The contextualization might aid one to have the narrative amount to:
“Alienation” and that, if one were to wish, could be extended with the idea of the “uncanny” hinted at with my datacyborg poetics. “Alienation” here is somewhat as meant as it is in the social sciences: the act of lifting the intended use of one’s data, outside of that intended use, by a third party. The questionable act of “alienation” is very much ignored or quietly accepted (since some confuse “public posting” with a “free for all”).
What personally disturbs me is that the above manner of writing makes me feel like a neurotic conspiratorial excuse of a person… one might then self-censor a bit more, just to not upset the balance with any demonizing push-back (after all, what is one’s sound, educated and rational “demos” anyway?). This one might do while others, in the shadows of our silently-extracted data, throw any censorship, in support of the hidden self (of the other), out of the proverbial window.
This contextualised further; related to memory, one might also wish to consider the right to be forgotten besides the right to privacy. These above-mentioned actors among a dozen others, rip this autonomous decision-making out of our hands. If then one were to consider ethics mapped with the lack of autonomy one could be shiveringly delighted not to have to buy a ticket to a horror-spy movie since we can all enjoy such narratives for “free” and in “real” life.
Thank you Dr. WSA for the trigger
Epilogue:
“Traditionally, technology development has typically revolved around the functionality, usability, efficiency and reliability of technologies. However, AI technology needs a broader discussion on its societal acceptability. It impacts on moral (and political) considerations. It shapes individuals, societies and their environments in a way that has ethical implications.”
https://ethics-of-ai.mooc.fi/chapter-1/4-a-framework-for-ai-ethics
…is ethics perhaps becoming / still as soothing bread for the demos in the games by the gazing all-seeing not-too-proverbial eye?
In extension to my above post (for those who enjoy interpretative poetics):
One might consider that the confusion of a “public posting” being equated with “free for all” (and hence falsely being perceived as forfeiting autonomy, integrity, and the likes), is somewhat analogous with abuses of any “public” commons.
Expanding this critically, and to some perhaps provokingly further, one might also see this confusion with thinking that someone else’s body is touch- or grope-for-all simply because it is “available”.
Now let’s be truly “meta” about it all: One might consider that the human body is digital now. (Ie my datacyborg as the uber-avatar. Moving this then into the extreme: if I were a datacyborg then someone else’s extraction beyond my public flaneuring here, in my chosen setting, could poetically be labeled as “datarape”)
As one might question the ethics of alienatingly ripping the biological cells from Henrietta Lacks beyond the extraction of her cancer into labs around the world, one might wonder about the ethics of data being ripped and alienated into labs for market experimentation and the infinite panopticon of data-prying someone’s (unwanted) data immortality
Over the past 150 years, give or take a year, the most impactful theories of learning have been defined into a few isms. According to UNESCO’s International Bureau of Education, these can be identified as: behaviorism, cognitive psychology, constructivism, social learning theory, socio-constructivism, experiential learning, multiple intelligences, situated learning theory, community of practice, and 21st century learning
Intuitively, one might sense various filtering attributes within the above paragraph. For instance “150 years”, “most impactful”, “theories”, “isms”. While these listed theories might find their roots in yet other pedagogical theories and practices, the constraining parameters might either function as biases and blinders, or rather, might be enriched or contextualized.
Tribal methods of knowledge transfer, for instance, are not mentioned in this list; a list that feels, ever-so slightly, Eurocentric. If one were to imagine a child learning in a “remote” tribe (or various less remote yet self-sustaining communities) where such theories have not penetrated the colorful diverse foliage of community learning, is the child then learning via a less defined or less impactful theory? Strecthing beyond the intended meaning: would learning then be less impactful?
Even within flavors of the New or Old World, there too methods of learning that could be distilled from those described in classical settings, are hidden or perhaps not sufficiently made explicit: Plato (in The Republic) as well as Socrates and their respective methodologies.
Yet another example, stretching both the space and time of impactful theories: the thousands of years of highly elite and selective learning methods in China are neither there, besides its present-day methodological implementation of Labor Education, as one of the five pillars of educational and learning theory and practices in the country.
Then comparison or cross-pollinatable attributes of, for instance, Labor Education with scientifically corroborated methodologies, such as those found with Montessorian methods and theory (or perhaps even links with character-building as hinted at in Plato) are, understandably, neither obvious in such list of the influential few.
The potential of cross-pollination of methodology or theory that explores potentials in-between the impactful theories, is subdued by the mere mentioning of these as segregated in or by their impact. Sure, some might need highly creative or perhaps construing effort to be (partially) combined.
Arguably too imaginative: one could consider that if “the media is the message,” that the technological structures and architectural frameworks could be implied to be a “theory of learning” as well. That is, if a medium (which is implicitly a technology) can define the message, then the structure (again, the technology) influences that what is being learned. One could imagine that structures hence could be designed as such to define a process of learning. Though, do they and are they consciously designed as such, or is the influence on learning often a collateral effect or damage? One might herein consider the field of AI, and Machine Learning and how it is mapped into Edtech.
As Professor Luckin suggested in the Financial Times article of 14 August 2021, “English schools turn to AI to help students catch up after Covid”, AI systems should be challenged by teachers. It is perhaps not too farfetched to assume such challenging might occur through ideological lenses, and secondarily, through pedagogical lenses, or hence through theories of learning, heralded by said teachers.
If, however, the learning theories that are being conjured up are excluding those learning methods that are not recognized as sanctioned theories (conjectured by the idea of being insufficiently “impactful”), then it might again be not too far-fetched to assume that such challenge might be biased and exclusive of those who follow various other methods (or implicit theories, or not yet theorized practices). Here hints of equity or equality or at least some degree of (minor) consideration might be felt.
Is it of high probability that those “others” who do not follow “most impactful” methods, might count into the millions of learners? i.e. China alone accounts for about 200 million students per annum; most of whom are not only influenced by these most impactful theories alone. Who out there, is learning outside of these “most impactful” learning theories?
I can’t help but intuit this group of humans might not be negligibly small. I can intuit, if I were to question the theories that underpinned the majority of our learning, that I would find it educational to see those diversities to be offered at least some footnote in a text that is promoted by a pan-national institution, such as Unesco.
Imagine looking into EdTech applications (and their ML-underpinnings) through such lenses of both impactful and other learning (and assessment) theories and practices. Let us just imagine…
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UNESCO. International Bureau of Education. “Most influential theories of learning”. Last retrieved on Monday, November 22, 2021 fromhttp://www.ibe.unesco.org/en/geqaf/annexes/technical-notes/most-influential-theories-learning
Financial Times (14 August, 2021). “English schools turn to AI to help students catch up after Covid”. Retrieved on Monday, November 22, 2021 fromhttps://www.ft.com/content/006ebaf6-a76c-4257-a343-f1db1f7b39e7
Ogilvy, J. (1971). “Socratic Method, Platonic Method, and Authority.” Wiley Online Library. Retrieved on Monday, November 22, 2021 fromhttps://onlinelibrary.wiley.com/doi/abs/10.1111/j.1741-5446.1971.tb00488.x
one could find metaphorical keys to open visualized doors, and activate figurative wobbly wormholes, into proverbial parallel universes, of meaning-making fabric, that might ever so probabilistically, prop-up one’s monoverse/universe of models of thinking; only as if being those “…secretive sides of our nature”
Without the proper keys (imagined by oneself & the many ‘other’) it could make it perceived as impossible to be(come) who one “is” in some of that collection of meaning-making universes, which one might refer to as the ‘social’. The latter is a subset; a noticeable one yet, still a subset
The opening of proverbial doors is not so much an escapism but rather an airing out of stuffiness in one’s thought without having to throw out (while, by less than snap-of-finger, it is an option to simply let go) the proverbial meaning-clinging furniture: a letting in of a breeze of “what ifs” without having to deconstruct one monoverse/universe for another —simply reinstitutionalizing fabric for another patterned fabric
‘Institutions’, of which, e.g., ‘professionalism’ could be one of, are as boxes; are as “monoverses”
These monoverses are examples of what imaginatively could be vast universes (expanding, shrinking, big banging) with surprising metaphorical physical laws
At times, various monoverses are claimed to be incompatible. Yet the act of claiming is the act of entering yet another monoverse, known as Claim-of-Falsity-or-Actuality, and there to hold one’s ground: the falsification or reinforcements of “boundaries”
The decreased agni improperly devensec.com soft cialis mastercard digests the food and this indigested food is sticky in nature and improperly nourishes tissues, causing weakness of body. order cheap viagra http://www.devensec.com/sustain/Welcome_to_Devens.pdf Kamagra is also introduced in the different forms and flavors to use the way you want it. viagra india online Only jelly can be effective in 15 minutes. There is a good news for those ED patients, 100mg viagra effects can be a positive answer.The monoverses, as if wobbly boxes, are found to be silent & beautiful, to those holding the packaging tape; they (“they” is the non-conspiratorial “they” and includes the “you” and the “I”) might be ignoring the imaginable spaces in-between
The interesting (and dare I say, the nurturingly #humane) about these proverbial keys, universes, propping-up one’s monoverse, are not the “keys”, nor the “universes” themselves
The interesting is the in-betweens; those mental spaces in-between the pseudo-quantifiable role, act, persona, character, institution, as if clean datasets
The in-betweens are not revolutionary since they can only exist by not negating, diminishing, ignoring or debasing that what is enabling to be in-between of. That stated, the borderlines are negotiated; feverishly and infinitely
The institutional, the professional & so on, can be dynamically experienced & do not always have to be, as we are experiencing, in the here & now, with this who nor what
‘Ephemerally-adapt’: a new compound word that could be implying the opening of those so-called doors or imagined windows, and letting it imaginatively breeze a bit; only then, and due to whatever impetus toward whichever aim (if any identifiable one at all), could one perhaps imagine of what a healthy, humane multiverse might be.
An enlightened room…is that a non- or de-darkened room, as if a “dark room” that is not a dark room?
An enlightened black color… is that a color that is non-black as if a “black color” that is not a black color? A tromp l’œil or a trick of the brain’s visual cortex’s processes?
An enlightened despot is that a non- or de-psychopathed leader as if a ”psychopathic individual” that is not psychopathic?
Which characters & imaginable (absurd/ funny/ scary/ enlightening/ …) stories does an “enlightened [__________________]” conjure up?
One might like to play with words such as: demon, female bricklayer, husband, angel, giant gnome, virus, blood clot, idiot, belly, fossil fuel vendor, genius, antisocial personality, compassionate moral individual, axolotl, solar panel vendor, robber, bank,…
Knowing that 1 of the denotations for “enlightened” is “freed from #ignorance & #misinformation”, then how might a bright, well-lid room, any tone of white color, or a functional altruist, be differentiated from their somewhat enlightened counterparts, that were played with above?
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“Enlightened room” a superficial online search result
the source for the one of many denotations for “enlightened”
#learning #multidimensionality #complexity #diversity #wink #imagination #nondualist #vectors #continuum
last update: Friday, April 24, 2020
URLs for A “Pre-History” & a Foundational Context:
A “pre-history” and a foundational context of Artificial Intelligence can arguably by traced back to a number of events in the past as well as to a number of academic fields of study. In this post only a few have been handpicked.
This post will offer a very short “pre-history” while following posts will dig into individual academic fields that are believed to offer the historical and present-day context for the field of AI.
It is not too far-fetched to link the roots of AI, as the present-day field of study, with the human imagination of artificial creatures referred to as “automatons” (or what could be understood as predecessors to more complex robots).
While it will become clear here that the imaginary idea of automatons in China is remarkably older, it has been often claimed that the historic development towards the field of AI, as it is intellectually nurtured today, commenced more than 2000 years ago in Greece, with Aristotle and his formulation of the human thought activity known as “Logic”.
Presently, with logic, math and data one could make a machine appear to have some degree of “intelligence”. Note, it is rational to realize that the perception of an appearance does not mean the machine is intelligent. What’s more, it could be refreshing to consider that not all intelligent activity is (intended to be seen as) logical.
It’s fun, yet important, to add that to some extent, initial studies into logic could asynchronously be found in China’s history with the work by Mòzǐ (墨子), who conducted his philosophical reflections a bit more than 2400 years ago.
Coming back to the Ancient Greeks: besides their study of this mode of thinking, they also experimented with the creation of basic automatons.
Automatons (i.e. self-operating yet artificial mechanical creatures) were likewise envisioned in China and some basic forms were created in its long history of science and technology.[1] An early mentioning can be found in, Volume 5 “The Questions of Tang” (汤问; 卷第五 湯問篇) of the Lièzǐ (列子)[2], an important historical Daoist text.
In this work there is mentioning of this kind of (imagined) technologies or “scientific illusions”.[3] The king in this story became upset by the appearance of intelligence and needed to be reassured that the automaton was only that, a machine …
Jumping forward to the year 1206, the Arabian inventor, Al-Jazari, supposedly designed the first programmable humanoid robot in the form of a boat, powered by water flow, and carrying four mechanical musicians. He wrote about it in his work entitled “The Book of Knowledge of Ingenious Mechanical Devices.”
It is believed that Leonardo Da Vinci was strongly influenced by his work.[4] Al-Jazari additionally designed clocks with water or candles. Some of these clocks could be considered programmable in a most basic sense.
One could argue that the further advances of the clock (around the 15th and 16th century) with its gear mechanisms, that were used in the creation of automatons as well, were detrimental to the earliest foundations, moving us in the direction of where we are exploring AI and (robotic) automation or autonomous vehicles today.
Between the 16th and the 18th centuries, automatons became more and more common. René Descartes, in 1637, considered thinking machines in his book entitled “Discourse on the Method of Reasoning“. In 1642, Pascal created the first mechanical digital calculating machine.
Between 1801 and 1805 the first programmable machine was invented by Joseph-Marie Jacquard. He was strongly influenced by Jacques de Vaucanson with his work on automated looms and automata. Joseph-Marie’s loom was not even close to a computer as we know it today. It was a programmable loom with punched paper cards that automated the action of the textile making by the loom. What is important here was the system with cards (the punched card mechanism) that influenced the technique used to develop the first programmable computers.
In the first half of the 1800s, the Belgian mathematician, Pierre François Verhulst discovered the logistic function (e.g. the sigmoid function),[1] which will turn out to be quintessential in the early-day developments of Artificial Neural Networks and specifically those called “perceptrons” with a threshold function, that is hence used to activate the output of a signal, and which operate in a more analog rather than digital manner, mimicking the biological brain’s neurons. It should be noted that present-day developments in this area do not only prefer the sigmoid function and might even prefer other activation functions instead.
[1] Bacaër, N. (2011). Verhulst and the logistic equation (1838). A Short History of Mathematical Population Dynamics. London: Springer. pp. 35–39. Information retrieved from https://link.springer.com/chapter/10.1007%2F978-0-85729-115-8_6#citeas and from mathshistory.st-andrews.ac.uk/Biographies/Verhulst.html
In 1936 Alan Turing proposed his Turing Machine. The Universal Turing Machine is accepted as the origin of the idea of a stored-program computer. This would later, in 1946, be used by John von Neumann for his “Electronic Computing Instrument“.[6] Around that same time the first general purpose computers started to be invented and designed. With these last events we could somewhat artificially and arbitrarily claim the departure from “pre-history” into the start of the (recent) history of AI.
As for fields of study that have laid some “pre-historical” foundations for AI research and development, which continue to be enriched by AI or that enrich the field of AI, there are arguably a number of them. A few will be explored in following posts. The first posts will touch on a few hints of Literature, Mythology and the Arts.
[1] Needham, J. (1991). Science and Civilisation in China: Volume 2, History of Scientific Thought. Cambridge, UK: Cambridge University.
[2] Liè Yǔkòu (列圄寇 / 列禦寇). (5th Century BCE). 列子 (Lièzǐ). Retrieved on March 5, 2020 from https://www.gutenberg.org/cache/epub/7341/pg7341-images.html and 卷第五 湯問篇 from https://chinesenotes.com/liezi/liezi005.html and an English translation (not the latest) from https://archive.org/details/taoistteachings00liehuoft/page/n6/mode/2up
[3] Zhāng, Z. (张 朝 阳). ( November 2005). “Allegories in ‘The Book of Master Liè’ and the Ancient Robots”. Online: Journal of Heilongjiang College of Education. Vol.24 #6. Retrieved March 5, 2020 from https://wenku.baidu.com/view/b178f219f18583d049645952.html
[4] McKenna, A. (September 26, 2013). Al-Jazarī Arab inventor. In The Editors of Encyclopaedia Britannica. Online: Encyclopaedia Britannica Retrieved on March 25, 2020 from https://www.britannica.com/biography/al-Jazari AND:
Al-Jazarī, Ismail al-Razzāz; Translated & annotated by Donald R. Hill. (1206). The Book of Knowledge of Ingenious Mechanical Devices. Dordrecht, The Netherlands: D. Reidel Publishing Company. Online Retrieved on March 25, 2020 from https://archive.org/details/TheBookOfKnowledgeOfIngeniousMechanicalDevices/mode/2up
[5] Bacaër, N. (2011). Verhulst and the logistic equation (1838). A Short History of Mathematical Population Dynamics. London: Springer. pp. 35–39. Information retrieved from https://link.springer.com/chapter/10.1007%2F978-0-85729-115-8_6#citeas and from mathshistory.st-andrews.ac.uk/Biographies/Verhulst.html
[6] Davis, M. (2018). The Universal Computer: the road from Leibniz to Turing. Boca Raton, FL: CRC Press, Taylor & Francis Group
One could state that Artificial Intelligence (AI) methods enable the finding of and interaction with patterns in the information available from contexts to an event, object or fact. These can be shaped into data points and sets. Many of these sets are tremendously large data sets. So large are these pools of data, so interconnected and so changing that it is not possible for any human to see the patterns that are actually there or that are meaningful, or that can actually be projected to anticipate the actuality of an imagined upcoming event.
While not promising that technologies coming out from the field of AI are the only answer, nor the answer to everything, one could know their existence and perhaps apply some of the methods used in creating them. One could, furthermore, use aspects from within the field of AI to learn about a number of topics, even about the processes of learning itself, about how to find unbiased or biased patterns in the information presented to us. Studying some basics about this field could offer yet another angle of meaning-giving in the world around and within us. What is a pattern, if not an artificial promise to offer some form of meaning?
It’s not too far-fetched to state that the study of Artificial Intelligence is partly the study of cognitive systems[1] as well as the context within which these (could) operate. While considering AI[2], one might want to shortly consider “context.”
Here “context” is the set of conditions and circumstances preceding, surrounding or following a cognitive system and that related to its processed, experienced, imagined or anticipated events. One might want to weigh how crucial conditions and circumstances are or could be to both machine and human.[3] The field of AI is one of the fields of study that could perhaps offer one such opportunity.
A context is a source for a cognitive system to collect its (hopefully relevant) information, or at least, its data from. Cognitive Computing (CC) systems are said to be those systems that try to simulate the human thought processes, to solve problems, via computerized models.[4] It is understandable that some classify this as a subset of Computer Science while some will obviously classify CC as a (sometimes business-oriented) subset of the field of AI.[5] Others might link this closer to the academic work done in Cognitive Science. Whether biological or artificial, to a number of researchers the brain-like potentials are their core concern.[6]
As can be seen in a few of the definitions and as argued by some experts, the broad field of AI technologies do not necessarily have to mimic *human* thought processes or human intelligence alone. As such, AI methods might solve a problem in a different way from how a human might do it.
However similar or different, the meaning-giving information, gotten from a context, is important to both an AI solution as well as to a biological brain. One might wonder that it is their main reason for being: finding and offering meaning.
The contextual information an AI system collects could be (defined by or categorized as) time, locations, user profiles, rules, regulations, tasks, aims, sensory input, various other big to extremely huge data sets and the relationships between each of these data sets in terms of influencing or conflicting with one another. All of these sources for data are simultaneously creating increasing complexities, due to real-time changes (i.e. due to ambiguity, uncertainty, and shifts). AI technologies offer insights through their outputs of the *best* solution, rather than the one and only certain solution for a situation, in a context at a moment in spacetime.
The wish to understand and control “intelligence” has attracted humans for a long time. It is then reasonable to think that it will attract our species’ creative and innovative minds for a long time to come. It is in our nature to wonder, in general, and to wonder about intelligence and wisdom in specific; whatever their possible interlocked or independent definitions might be(come) and whichever their technological answers might be.
In considering this, one might want to be reminded that the scientific name of our species itself is a bit of a give-away of this (idealized) intention or aspiration: “Homo Sapiens.” This is the scientific name of our animal species. Somewhat loosely translated, it could be understood to mean: “Person of Wisdom”.
In the midst of some experts who think that presently our intelligence is larger than our wisdom, others feel that, if handled with care, consideration and contextualization, AI research and developments just might positively answer such claim or promise and might at least augment our human desires towards becoming wiser.[7] Just perhaps, some claim,[8] it might take us above and beyond[9] being Homo Sapiens.[10]
For now, we are humans exploring learning with and by machines in support of our daily yet global needs.
For you and I, the steps to such aim need to be practical. The resources to take the steps need to be graspable here and now.
At the foundation, to evaluate the validity or use of such claims, we need to understand a bit what we are dealing with. Besides the need for the nurturing of a number of dimensions in our human development, we might want to nurture our Technological Literacy (or “Technology Literacy”).[11]
A number of educators[12] seem to agree that,[13] while considering human experiences and their environments, this area of literacy is not too bad a place to start off with.[14] In doing so, we could specifically unveil a few points of insight associated with Artificial Intelligence; that human-made technological exploration of ambiguous intelligence.
Few people know that heart comes http://appalachianmagazine.com/2016/12/25/why-stink-bugs-are-taking-over-the-eastern-united-states/ online prescription for viagra under pressure, when stress control of the mind. The uses of alcohol, smoking, tobacco, and http://appalachianmagazine.com/2019/03/10/mountain-tradition-eating-ramps-in-springtime/ super generic viagra illegal drugs have great influence of carrying this sexual complication. You on line viagra can also get discount on bulk order for this product. While viagra lowest prices some states don’t need that this online drug is not good as their branded counterparts are.[1] Sun F., Liu, H., Hu, D. (eds). (2019). Cognitive Systems and Signal Processing: 4th International Conference, ICCSIP 2018, Beijing, China, November 29 – December 1, 2018, Revised Selected Papers, Part 1 & Part 2. Singapore: Springer
[2] DeAngelis, S. F. (April 2014). Will 2014 be the Year you Fall in Love with Cognitive Computing? Online: WIRED. Retrieved November 22, 2019 from https://www.wired.com/insights/2014/04/will-2014-year-fall-love-cognitive-computing/
[3] Desouza, K. (October 13, 2016). How can cognitive computing improve public services? Online Brookings Institute’s Techtank Retrieved November 22, 2019 from https://www.brookings.edu/blog/techtank/2016/10/13/how-can-cognitive-computing-improve-public-services/
[4] Gokani, J. (2017). Cognitive Computing: Augmenting Human Intelligence. Online: Stanford University; Stanford Management Science and Engineering; MS&E 238 Blog. Retrieved November 22, 2019 from https://www.datarobot.com/wiki/cognitive-computing/
[5] https://www.datarobot.com/wiki/cognitive-computing/
[6] One example is: Poo, Mu-ming. (November 2, 2016). China Brain Project: Basic Neuroscience, Brain Diseases, and Brain-Inspired Computing. Neuron 92, NeuroView, pp. 591-596. Online: Elsevier Inc. Retrieved on February 25, 2020 from https://www.cell.com/neuron/pdf/S0896-6273(16)30800-5.pdf . Another example is: The work engaged at China’s Research Center for Brain-Inspired Intelligence (RCBII), by the teams led by Dr XU, Bo and Dr. ZENG, Yi. Founded in April 2015, at the CAS’ Institute of Automation, the center contains 4 research teams: 1. The Cognitive Brain Modeling Group (aka Brain-Inspired Cognitive Computation); 2. The Brain-Inspired Information Processing Group; 3. The Neuro-robotics Group (aka Brain-Inspired Robotics and Interaction) and 4. Micro-Scale Brain Structure Reconstruction. Find some references here: bii.ia.ac.cn
[7] Harari, Y. N. (2015). Sapiens. A Brief History of Humankind. New York: HarperCollings Publisher
[8] Gillings, M. R., et al. (2016). Information in the Biosphere: Biological and Digital Worlds. Online: University California, Davis (UCD). Retrieved on March 25, 2020 from https://escholarship.org/uc/item/38f4b791
[9] (01 June 2008). Tech Luminaries Address Singularity. Online: Institute of Electrical and Electronics Engineers (IEEE Spectrum). Retrieved on March 25, 2020 from https://spectrum.ieee.org/static/singularity
[10] Maynard Smith, J. et al. (1995). The Major Transitions in Evolution. Oxford, England: Oxford University Press AND Calcott, B., et al. (2011). The Major Transitions in Evolution Revisited. The Vienna Series in Theoretical Biology. Boston, MA: The MIT Press.
[11] National Academy of Engineering and National Research Council. (2002). Technically Speaking: Why All Americans Need to Know More About Technology. Washington, DC: The National Academies Press Online: NAP Retrieved on March 25, 2020 from https://www.nap.edu/read/10250/chapter/3
[12] Search, for instance, the search string “Technological Literacy” through this online platform: The Education Resources Information Center (ERIC), USA https://eric.ed.gov/?q=Technological+Literacy
[13] Dugger, W. E. Jr. et al (2003). Advancing Excellence in Technology Literacy. In Phi Delta Kappan, v85 n4 p316-20 Dec 2003 Retrieved on March 25, 2020 from https://eric.ed.gov/?q=Technology+LIteracy&ff1=subTechnological+Literacy&ff2=autDugger%2c+William+E.%2c+Jr.&pg=2
[14] Cydis, S. (2015). Authentic Instruction and Technology Literacy. In Journal of Learning Design 2015 Vol. 8 No.1 pp. 68 – 78. Online: Institute of Education Science (IES) & The Education Resources Information Center (ERIC), USA. Retrieved on March 25, 2020 from https://files.eric.ed.gov/fulltext/EJ1060125.pdf
IMAGE CREDITS:
An example artificial neural network with a hidden layer.
en:User:Cburnett / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/) Retrieved on March 12, 2020 from https://upload.wikimedia.org/wikipedia/commons/e/e4/Artificial_neural_network.svg
