Tag Archives: aiethicsliteracy

Letters from Aliens to Aliens, text | wondering, The field of AI

<< I know you not, I know your produce >>


“Full Many a Flower Is Born to Blush Unseen” (Gray 1751)

“Maybe it’s the language that is off-putting. Gray created a heightened diction based in part on classical poetry. Today, formality and artifice strike many as insincere, as though something that’s not colloquial is necessarily suspect. We’re still suffering under an ersatz Romanticism that gives value to the spontaneous and devalues the polished and restrained.“ (La Belle 1994)

I wonder, in the spirit of obsessive innovation, is taking note of dusting off and revisiting acts classified as ‘romantic,’ and yet as easily classifiable as pragmatic contextualization of the incessant “new?” Is it ripping off a style, is it an ode to generating the past generations, is it lacking ingenuity, is it contextualising innovation? Is it, it is all and then some.

Some recent technologies have added a new word into the mix: ‘generative‘ which does sound different from ‘to generate.’ Being ‘generative,‘ to generate, is a form of “creation,” to create, across the generations of human produce. Is a machine that is generative in some (perverting) sense a hyper-romantic dusting of styles of bygone eras, where era might be a time period in a style of yesterday’s meme? Across the polemics of whatever is generated, created or imagined, many a produce are increasingly designated to be democratized on the graveyards of human creation as “Full Many a Flower,” “Born to Blush Unseen.” (Gray 1751)

That brings this writing to further mimicratic note-taking and referencing [*1]: As rays shining brightness on our market-made cultures, there is Samuel W. Franklin with the “Cult of Creativity”(2023). His writing might be unthreading the web of “imagination,” “interpretation” versus “creation,” “production,” (tooled, mechanical, digital or other), and “generation” from an age not too far into the recent past. Creativity –if one could be accepting of a simplified interpretation of the above author’s recent publication– is then possibly a democratization of the output-sell-buy-move-on lineage.

Do I know you or do I know your produce?

There is no “or” through the communal lenses. This might be a subtext symbolized through the passionate, yet society-defining tensions between New York’s Jane Jacobs and Robert Moses.

Both could be equalized as peddling lanes for produce, and yet only one upheld community, relation, and reference to that individual human in the smallness, yet persistence of being, among the vastly architectured physical or digital cityscaping.

“When city planning supremo Robert Moses proposed a road through Greenwich Village in 1955, he met opposition from one particularly feisty local resident: Jane Jacobs. It was the start of a decades-long struggle for swaths of New York.” (Palleta 2016)

The acts of cutting through human creativity-over-time (and that with roads or other and possibly less tangible means) tends to meet with some resistance. Though, is this a romantically fading notion, erased by the statistical structuring and channeling of our produce and fruits of our laboring? In the pragmatics of communal resistance we can take (agency over) produce to proverbial multi-vectored meta-levels.

In that humanly —and at times dehumanizingly— yet created, anthropomorphic environment, have you lately taken a whole day, from before the sun rose until it set, to “unproductively” observe, take note of, one petal —there placed “Between the Commonplace and the Sublime”? (Franklin 2023)

Or, are you predestined to peddle stock in styles appropriated from hushed bygone times to be forgotten the moment you set foot on the (digital) subway, swaying you back to your nightly stead?

Please note, as I too am a peddler, and yet as you can assign time to read this: no counter argument could be that some must, unwaveringly, innovate their produce for a sustainable living. After all, as you observe –as or not as judgement of– lack of beauty “observation can tell more about the observer than about the environment being observed.” (Goldsmith & Lynne 2010)

There is that place between the Franklinses, the Grayses, the Jacobses, the Moseses or the digital versions of Le Corbusierses of our times.

There is non-romanticist beauty in unnoticed smallnesses, you see. In those moments there are no big names, no genius. There is you.

There is the vulnerable yet persistent petal. There is your human-made environment. There are producing generations of cohabitation. And that especially in the solitudes of creative observations.

Epilogue

I was touched by these words by Dr. Tim Williams as a reply to the above writing.

I wish to cherish them here:

“When I read the article, I sensed the tensions of what elements should be included in genuine generative, creative production. And thus, this led to subtle definitions to differentiate between concepts. As such, I felt that each was bringing to light an important nuance; each having its own emphasis on something important. Romanticism with its revolt against the rigid rationalism, reminding us that there are other features beyond what is in the nous; there is the entire phenomena to be considered. But then it too frequently morphs into the abstract and then without purpose (art for art’s sake). And then there is the industrialization of production with its utilitarian focus, almost to the point of killing creativity. And so, I thought a holistic approach looks upon all of these facets — the teleological, the epistemological, and aesthetic perspectives. The entirety of man in all that man is — a being that creates from who he is, limited but profound as that might be.”

Williams, T. (2023, May). “Holistic approach to being really generative.” Online: LinkedIn. Last retrieved 21st May, 2023 from a Dr. Williams comment on a LinkedIn post of the above writing. Thank you, sir.

Attributions, References & Footnote

Header photo: Christopher Michel, CC BY 2.0 https://creativecommons.org/licenses/by/2.0, via Wikimedia Commons. Retrieved from https://commons.wikimedia.org/wiki/File:Generations_%284120355763%29.jpg

[*1] “mimicratic” as from Rampage376·11/22/2020 “mimicratic reflexes (copies moves, techniques and fighting styles like he trained for years)” https://powerlisting.fandom.com/f/p/4400000000000249793 IN: JokuSSJ. (2020, 21 November). If you lived in an Anime World, what would be your life and powers? Online: Superpower wiki.

Franklin, S.W. (2023). “Cult of Creativity.” London: The University of Chicago Press.

Goldsmith, S. A., & Elizabeth, L. (Eds.). (2010). What We See: Advancing the Observations of Jane Jacobs. NYU Press. https://doi.org/10.2307/j.ctt21pxmnw

Gratz, R. B. (2010). The Battle for Gotham: New York in the Shadow of Robert Moses and Jane Jacobs

Gray, Thomas. (1751). Elegy Written in a Country Churchyard. Last retrieved May 18, 2023 from https://poetryarchive.org/poem/elegy-written-country-church-yard/

Jacobs, J. (1961). The Death and Life of Great American Cities. Vintage Books. 

La Belle, J. (1994). Full Many a Flower Is Born to Blush Unseen’ : The echoes of a classic poem about the democracy of death still resonate in our language and literature. Online: The LA Times. Last retrieved on May 15, 2023 from https://www.latimes.com/archives/la-xpm-1994-02-16-me-23414-story.html 

Palleta, A. (2016, 28 April). The story of cities Cities Story of cities #32: Jane Jacobs v Robert Moses, battle of New York’s urban titans. The Guardian. https://www.theguardian.com/cities/2016/apr/28/story-cities-32-new-york-jane-jacobs-robert-moses

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Accountable. Accountability. Accountability (GDPR).


While sharing some attributes, ‘accountability’ is not to be confused with ‘responsibility.’

‘Accountability’ is an allocation of measurement or evaluation (of blame or award)  after a given event, as its outcome is measured or perceived.Following the finalization or interruption of processes that created an event and its results, an individual is held accountable. One then has an obligation to report, to explain, or to justify the effect, the outcome and how these affect or impact.    Accountability relates to one’s commitment, to one’s response and to one taking ownership, with clarity, of the output or result of a given process and its (undesirable or desirable) consequences. It relates to the goodness of the result, and of its consequences. Often accountability is allocated to a single individual (if not, a blame-game could follow). One has accountability, and one is held accountable. An accountable individual, or organzation, is one that is transparent about its decision-making processes, and is willing to explain and justify its actions to others. The measurement of accountability can be done by oversight, by investigating compliance, by analysis of reporting, and by allowing enforcement of reprimands, sanctions or legal steps where judged necessary.

One could distinguish that having the ownership over a task, that must be done, is ‘responsibility.’ Responsibility implies duty of one, or more than one individual, as a team. It relates to the rightness of taking action in completing a task.  One takes responsibility, and one is responsible for doing a task.

Accountability “implies an ethical, moral, or other expectation (e.g., as set out in management practices or codes of conduct) that guides individuals’ or organisations’ actions or conduct and allows them to explain reasons for which decisions and actions were taken. In the case of a negative outcome, it also implies taking action to ensure a better outcome in the future…  In this context, “accountability” refers to the expectation that organisations or individuals will ensure the proper functioning, throughout their lifecycle, of the AI systems that they design, develop, operate or deploy, in accordance with their roles and applicable regulatory frameworks, and for demonstrating this through their actions and decision-making process (for example, by providing documentation on key decisions throughout the AI system lifecycle or conducting or allowing auditing where justified.” (OECD)

References

https://oecd.ai/en/dashboards/ai-principles/P9

European Data Protection Supervisor (EDPS). (n.d.). Accountability. Online. Last retrieved on April, 10 2023 fromhttps://edps.europa.eu/data-protection/our-work/subjects/accountability_en

Pentland, Alex, and Thomas Hardjono. “10. Towards an Ecosystem of Trusted Data and AI.” Works in Progress, n.d., 13. Last retrieved on 26 July 2022 from https://assets.pubpub.org/72uday26/19e47ad0-9cae-4dbf-b2cb-b38cd38d9434.pdf

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Access. Accessible. Accessibility. Right of Access (GDPR).


Through a technological lens, mapped with efficiency and with AI, ‘accessible’ could refer to the ease with which data, applications, and services can be accessed and used by machines, without human intervention. This could imply the absence of a ‘human-in-the-loop.’

Such a system is one that could be optimized for efficiency and that could perform tasks quickly, accurately, and reliably.

From an interface design, mapped with consequentialist ethical perspectives, an accessible AI system could suggest that users, with empowering considerations of their abilities, vulnerabilities or disabilities, could access and use the system with ease or with means nuanced to their specific needs.

It could also refer to the degree to which a product, service, or technology is available, affordable, and designed to meet the needs of all individuals, including those from marginalized or otherwise disenfranchised  communities.

Degrees of accessibility implies that access could not be or be less constraint due to demographics, background, abilities, or socioeconomic status. This definition of accessibility could imply some of the following concepts which could improve due to accessibility, and that to some degree: agency, autonomy, plurality, diversity and diversification, equity, personalization, inclusivity, fairness, mindfulness, and compassion. Through such perspective this could be considered a ‘good’ system design. This could then lead one to consider concepts such as ‘ethical-by-design,’

An accessible AI  system could then also be one that is transparent (the lack of transparency implies a lack of access, even if it is access to the possibility of understanding the inner workings of the AI system), and thus of concepts such as, explainable, and accountable, ensuring that the decisions made by the AI system are fair, unbiased, and aligned with ethical principles.

‘The Right of Access (GDPR)’ is one of the 8 rights of the individual user (also referred to as “data subjects”) as defined within the European Union’s General Data Protection Regulation (GDPR). It is article 15 in the GDPR: “The data subject shall have the right to obtain from the controller confirmation as to whether or not personal data concerning him or her are being processed, and, where that is the case, access to the personal data…” and access to a number of categories of information as further defined in this article.

This policy item aims “to empower individuals and give them control over their personal data.” The 8 rights are “the right of access, the right to rectification, the right to erasure, the right to restrict processing, the right to data portability, the right to object and the right not to be subject to a decision based solely on automated processing.”

References

European Data Protection Supervisor. ( ). Rights of the Individual. Online: (an official EU website). Last retrieved on April 10, 2023 fromhttps://edps.europa.eu/data-protection/our-work/subjects/rights-individual_en

Art. 15 GDPR Right of access by the data subject: https://gdpr-info.eu/art-15-gdpr/

Page, Matthew J, David Moher, Patrick M Bossuyt, Isabelle Boutron, Tammy C Hoffmann, Cynthia D Mulrow, Larissa Shamseer, et al. “PRISMA 2020 Explanation and Elaboration: Updated Guidance and Exemplars for Reporting Systematic Reviews.” BMJ, March 29, 2021, n160. https://doi.org/10.1136/bmj.n160

https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/?template=pdf&patch=17#

https://ethics-of-ai.mooc.fi/chapter-5/3-examples-of-human-rights

text | wondering, The field of AI

<< The Ambiguating Languages of Stat, Status, Statistic >>


To love automation is to love statistics; unwavering, unquestioned, unambiguously and as purely wholesome?

In 1749 the “Summarisk Tabell” or the first  “systematic collection of statistics” was architectured by the Swedish government and its “Tabellverket” which means ‘tabular work.’ In this context  it became to mean their office for tabulation and was entitled ‘Statistiska centralbyrån’ or the Swedish Central Bureau of Statistics (The Joy of Stats 2010: 12:10)

Spiegelhalter rationally reminds us that statistics used to be called “political arithmetic”. (Ibid: 14:24).

Statistics is etymologically related to the Latin word “status.” In turn, this directly links to the concept of “political state”. The statista, or statesmen, were/are probably more skilled in affairs of state, unveiling and organizing resources for they who were controlling and running the state, than skilled in the measurement or probability via numerical accuracy. They were skilled toward the industrialization of the resources of the state. “In what way is the status ‘a’ changin’?,” might here then be a concern in favor of status rather than too much in favor of change and too many outliers. Is then (social) innovation at all times looked upon with eagerness?

This historical awareness is allowing one possible dimension in continuing processes of (mis)understanding of what was then a drive for increased control and perceived decrease of misunderstanding of (their) populations.

It is however not history alone. Similar centers of power are at play today. They might be nation states. They might be transnational. They might be known as corporate entities or (private) financial institutions. Please note, one does not need to loose track into any conspiracy theorizing to identify these. By the way, the latter I sense as a conspiracy-of-the-self against the self, by using hyperambiguating narratives (aka conspiracies) as a blindfold of what is (is as “realities”) versus what is-imagined. The real(s) is(are) “fantastical” enough (to me).

Returning back to the above referenced video —hosted by the delightful, energetic and sadly late Professor Rosling— it continues in unveiling the 19th century popular excitement for statistical (visualized) facts. Today, with a popular engrossment with distrust as a proverbial spoon, excitement is stirring up and thinning down statistical fact. We could note that by questioning our present-day versions of feudal masters we might also be deconstructing our own tools to enable us to question the same (a “conspiracy of the “self” serving the “self”?). The false linear dichotomy is as disenfranchising as any side of this faux-2D plastic coin: “Ambiguate all and thy shall be ruled through your fog. Disambiguate all and they shall be hammered and tyrannized.“

As with statistics, automation too could be controlling and enabling, rational and mesmerizing. Logos and pathos. Enlightening and clouding. liberating and enshackling; …ad infinitum and gone immediately. While ethos might have been sulking in the corner.

In light of enablement and increasing both awareness and voice, W.E.B Du Bois’ work, for instance, is still an awe-inspiring and humbling exemplar, especially to the statistically-privileged and exnominated samples within the larger and diverse human population.


Automation could be interpreted as an applied extension of statistical control and narrowing of understanding by means of repurposing, appropriating and regurgitating the statistical styles of the most likely/ed (resources).

Automation, as statistics, was initially not invested into with the aim of democratization. It was a matter of control, understanding, and increase of efficiencies toward a more desired return for those who initiated and enabled the creation, architecturing and implementation.

The needed “ambiguation” (here meaning: pluralization, nuancing, modding and jailbreaking of meaning, relation, intent, application, usage, etc.) of initial intent by diversification and decentralization of intent(s), could best be seen as a process rather than an opposition against a more popular idea of a fixed denotation of language (this latter which I would prefer not subscribing to too rigidly either).

Riding yet another vector: statistics applications could be cannibalizing statistics. This could be seen as one type of ambiguation. Clear information through the lens of statistics is undone by automated diffusing statistical probabilities, possibly waging siege (with mal-, mis- and dis-information as arsenals) against initiatives aiming to unveil the incorrect and (almost) unconscious, biased “stats” we impose, as people, onto ourselves (and others). This latter too can be seen as yet another type of ambiguation. Herewith might come to mind such initiatives as Gapminder (see Rosling), Our World in Data, The Deep, etc. These are initiatives in counterattack against conspiracies, scaled bias, systemic mis-, mal- and dis-informing/conception (…and yet, brittle these aforementioned initiatives are as well).

Automation and statistics are not inherently, nor complacently, democratizing, freeing, nor enlightening. There is nothing inherently socio-historically linear nor monolithic about these. They can be and have been historically invented and applied as such though. They are/should neither (be) a fait accompli to defining your acts, relations nor realities. There must be vigilant, at times incessant, work and a labor of citizen love.

It might be felt as a real-time theater play with the actors Ambiguous and Disambiguous, in the starring roles portraying luscious eroticism between fact and fuzz, creating worlds as stages for realities re-re-formed.

References

animasuri’23. (2022). Data in, fear and euphoria out. (Blog). https://www.animasuri.com/iOi/?p=3480

animasuri’23. (2023). Learning is Relational Entertainment; … (blog).  https://www.animasuri.com/iOi/?p=4442

Aschenwall, Gottfried. (1748). Vorbereitung zur Staatswissenschaft der heutigen fürnehmsten europäischen Reiche und Staaten.

Battle-Baptiste, W., Du Bois, W.E. B., Rusert, B. (2018). W.E.B Du Bois’s data portraits. visualizing Black America. Princeton Architectural Press.

Dehbozorgi, Alireza. (2023). LinkedIn post: “”Language is an instrument of political and social domination. From ancient China to Europe, the number of words and languages one mastered were signs of belonging to an elite. Artificial intelligence is reshaping the linguistic landscape. An interview with linguist Stefanie Ullmann, machine learning specialist Omolabake Adenle, and philosopher Marc Crepon.” from: ARTE.tv Documentary. (2023). AI and Language

Gapminder  https://ourworldindata.org/

Rosling, H. (2010). IN: Hillman, D, et al. (2010). The Joy of Stats with Professor Hans Rosling.  (Video) BBC & Wingspan Production via Gapminder  last retrieved on May 8, 2023 from https://vimeo.com/18477762

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. editio

Our World in Data. https://ourworldindata.org/

Sustainable Development Goals Tracker (https://sdg-tracker.org/) 

The Deep: http://thedeep.io/

van Bergen, Emille. (20223). quoting Marc Crepon “…we basically need to maintain a relationship with language that resists anything aiming to format it, calculate it or program it…” via Dehbozorgi, Alireza. (2023). LinkedIn post

text | wondering, The field of AI

<< Human-made Outlier Synthesis >>


Some hype and others lament “democratization” (Turing Institute & Seger et al. 2023) and “democracy.” Even though sharing two linguistic roots, the processes to the former can deconstruct the latter. This possibility does not lie in the meaning of the individual words. Nor does it lie in the statistical probability of their appearance, occurring in each other’s proximity. It might partly lie in the lived relationships, triangulated with human interest, incentive, aspiration and application. Or, more pungently, in the absences thereof. Here is an interpretive narrative as illustration: 

The recent report by the CAIDP on Artificial Intelligence and democratic values offers a stage. This publication is an impressive work that heralds policies, frameworks and protections. It echoes the statement that  “Policymakers want an enabling policy environment while mitigating the risks of AI language models”  (OECD).

There is promise of innovation while enabling the commoner to remain free from… ?

The political enablements and constraints imply technological enablements and constraints, while the latter more dominantly implies market influences. Both of them affect social enablements and constraints.  

They affect how the demos (“we”) moves (i.e., agency) and is moved (i.e., “our” wanted or unwitting delegation) within the human polis (i.e., the metaphorical dwelled city). Their mapping, that of polis and tékhnē, are here not a mapping of a linear, one to one, nature. That’s almost so tautological that it is as comforting as listening to and being reminded of  Beethoven’s hair decompositions and of sound into his music, again and again. (Thank you, Dr. Walter Sepp Aigner) 

Simultaneously, these enablements and mitigations create narratives that nurture outliers and entrenchments that are not (and should not at all cost?) be ignored or flippantly dismissed (and we are not only thinking of jellyfish, rhinos or swans of bland monochrome coloring). (Day One Futures) Counter to some scientific and engineering needs, we should not always ignore nor filter away the outliers, either. (Taylor et al. 2016)  

It should be noted that not only technologies and also policies have “omni-uses” or multiple uses users gained access to and have the incentive to tinker or pervert away from the intended or designed usages ( Daniel Schmachtenberger & thank you Liv Boeree). Hence, can protections also be impositions? Yes. 

Neither is amplification to be equated with taking note of these outliers. As well is the note-taking not immediately a representation of the note-taker’s outlying, emotional state-of-mind. Note-taking can rhetorically be embellished or muted while having been authored in a state of rational, calm mindfulness while reminding us of a call to innovation to address systemic issues that are ignored or relabeled as if technical outliers or socio-inevitable issues alone; “that’s how it’s always been done”.

And yet, I am utterly excited being alive during these times. This all the whilst I can also think, breathe, reflect and consider the tails of the curve-balls we throw into our underbellies. It does not have to make one despair, nor imagine having reached Nirvana. It could be perceived that such dichotomization and polarization in thinking and working with policy and technology is an act of outlier-creation. In effect this type of creation might mute urgencies related to social minority, and to socially subdued or pressured voices.  Almost paradoxically, these voices are then narrated (by opposing voices) as too extreme and uncomfortable (i.e., as “outliers”), away from a fairness of reparation, and toward a governed solidification of their further biased formatting through models and automation. 

These same outliers and the omni-uses of technology, of information, and of policy, are affecting social relations.  These are as curve-balls into the outlying edges of our playing-field, hitting those of us who are less empowered, those of us who are maintained in iterations of stereotyping and yet more of the same: the antithesis of (social & relational) exciting forms of innovation ( forbes & thank you Prof. Darius Burschka for having pointed at this). Is this antithetical innovation a Wizard of Oz Experiment in the wild, toward large-scale social engineering manipulation?

This seems as an application of an “experiment” which might be seen as an outlier yet at large scale and with serious affective impact. Just as some historic “outliers” (read: biases and bigotries) which are downplayed as ignorable outliers. As if kicking a dead horse, the ignored outliers are then further drowned by some outliers off of the scale of sanity. The insane is given technological form to, as well as given vast policy-making attention, with reduced understanding of both tech and the socio-culturally maintained outliers, who could and should find their place in the middle.

Reflection on the idea of, the lenses to look onto, and the processes that could be constructing, maintaining or muting outliers, and their omni-uses, are as such not a faux-pause, some other acts though might seem reflective and pausing yet smell as if they are not. ( financial times and business insider)

For instance, with The Internet Archive (IA) losing its “lending lawsuit…” (Copyright Lately) should we‘ve cracked down on access to credible and validly verifiable sources? This question is here re-placed in context of opening up the World Wide Web to tsunamis of synthetically-generated content that can’t be corroborated, are based on sources that were taken without consent, nor regard for IPR. .

Is the latter at such vast scale, and with such financial backing, that it’s too large to notice? (Politico) So large it remains hidden? (EUractiv) As a flea in a red carpet not enabled to reflect on its carpet being a carpet? 

So, IA: no, “AI,” yes? Are now outliers and false dichotomies at play?

Synthetic “content” entrenches biases and reinforces boring yet harmful stereotypes. (See recent examples by Abeba Birhane via Twitter). It does the opposite of tackling historic and systemic issues (that have synthetically been kept as outliers across the centuries). These could already be addressed socially, policy-wise and technologically. We even have non-techno cognitive tools. (thank you Alireza Dehbozorgi  for pointing at this) And yet they are stalled by incentives and will, mixed with resources & access.

There lies innovation. In contrast: lie-innovation is instead the stark option we decided exploring feverishly via tech & policy. Here social omni-use is present. Here outliers are reinforced on the scale of the sane.

There is a recent publication entitled “Real World AI Ethics.”Could we now —with digital multiverses, generative AI outputs, & deepfakes— also urge for the nascence of “Fake World AI Ethics,”(6) which could explore outliers that are mixing fakery with the false labeling of actual issues as “fake,” by ignoring what is lived, right now & right there, under extreme conditions? While information is “neither matter nor energy” (Norbert Wiener; Thank you Prof. Felix Hovsepian, PhD, FIMA For reminding us) its creative ugly ducklings named ‘Mis- & Dis-‘ are roughing up lots of dust & partying on vast amounts of energy ( EUractiv )

Innovation is not a one way ticket to bliss, unless we allow asking: “innovative” to whom and with what omni-used meaning making? Repetition and regurgitation, are derivative acts. They are confusing boredom for innovation and could if not handled with care, oppose addressing actual needs. This note-taking here could be interpreted as boring as well, as much as re-reading Beethoven could be. Though, they do not have to be.

Democratizing “solidarity” (thank you Michael Robbins) via wanting Beethoven, or social relational care into diversities of lived, local and global needs, can symbolize omni-innovation in tech and policy.

some highlighted References

OECD (2023), “AI language models: Technological, socio-economic and policy considerations”, OECD Digital Economy Papers, No. 352, OECD Publishing, Paris,https://doi.org/10.1787/13d38f92-en.

Seger, Elizabeth, Aviv Ovadya, Ben Garfinkel, Divya Siddarth, and Allan Dafoe. “Democratising AI: Multiple Meanings, Goals, and Methods,” March 27, 2023. https://doi.org/10.48550/arXiv.2303.12642.

Taylor, J. et al. (2016 ). Alignment for Advanced Machine Learning Systems . Last retrieved on April 15, 2023 from here


text | poetry, text | wondering, The field of AI

<< The Tàijí Quán of Tékhnē >>


•

Looking at this title can tickle your fancy, disturb your aesthetic, mesmerize you into mystery, or simply trigger you to want to throw it into the bin, if only your screen were made of waste paper. Perhaps, one day.

<< The Balancing Act of Crafting >>

Engineering is drafting and crafting; and then some. Writing is an engineering; at times without a poetic flair.

One, more than the other, is thought to be using more directly the attributes that the sciences have captured through methodological modeling, observing, and interpreting.

All (over)simplify. The complexities can be introduced, when nuancing enters the rhetorical stage, ever more so when juggling with quantitative or qualitative data is enabled.

Nuancing is not a guarantee for plurality in thought nor for a diversity in creativity or innovation.

Very easily the demonettes of fallacy, such as false dichotomy, join the dramaturgy as if deus ex machina, answering the call for justifications in engineering, and sciences. Language: to rule them all.

Then hyperbole joins in on the podium as if paperflakes dropped down, creating a landscape of distractions for audiences in awe. Convoluting and swirling, as recursions, mirrored in the soundtrack to the play unfolding before our eyes. The playwright as any good manipulator of drama, hypes, downplays, mongers and mutes. It leaves audiences scratching at shadows while the choreography continues onward and upward. Climax and denouement must follow. Pause and applause will contrast. Curtains will open, close.

<< Mea Culpa>>The realization is that it makes us human. This while our arrogance, hubris or self-righteousness makes us delusionary convinced of our status as Ubermensch, to then quickly debase with a claimed technological upgrade thereof. Any doubt of the good and right of the latter, is then swiftly classified as Luddite ranting;<</Mea Culpa>>

While it is hard to express concern or interest without falling into rhetorical traps, fear mongering, as much as hype, are not conducive to the social fabric nor individual wellbeing.

“Unless we put as much attention on the development of [our own, human] consciousness as on the development of material technology—we will simply extend the reach of our collective insanity….without interior development, healthy exterior development cannot be sustained”— Ken Wilber

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Reference:

Wilber, K. (2000). A theory of everything: an integral vision for business, politics, science, and spirituality. Shambhala Publications

Fromm, E. S. (1956). The Sane Society. “Fromm examines man’s escape into overconformity and the danger of robotism in contemporary industrial society: modern humanity has, he maintains, been alienated from the world of their own creation.” (description @ Amazon)

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#dataliteracy #informationliteracy #sciencematters #engineering #aiethics #wellbeing #dataethics #discourseanalysis #aipoetics

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<< Learning is Relational Entertainment; Entertainment is Shared Knowledge; Knowledge is... >>

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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.

#entertainUS

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:

https://www.linkedin.com/posts/katja-rausch-67a057134_microsoft-its-your-fault-our-ai-is-going-activity-7034151788802932736-xxM6?utm_source=share&utm_medium=member_desktop

thank you Katja Rausch

and by:

https://www.linkedin.com/posts/marisa-tschopp-0233a026_microsoft-its-your-fault-our-ai-is-going-activity-7034176521183354880-BDB4?utm_source=share&utm_medium=member_desktop

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:

https://www.linkedin.com/posts/walidsaba_did-you-say-generative-ai-generative-ugcPost-7035419233631039488-tct_?utm_source=share&utm_medium=member_ios

This blog post on LinkedIn