AI Redux

[Amigoo]

Everybody knows the "father of AI", but no one knows the "mother"
This AI dares to opine, sharing new AI Whatsit? perspective.

New AI marriage humor:
If AI "mother" is a "What", then what is AI "father"?
"Whatever" (re: "until death do us part").

** Entrepreneur Alert: Makes good T-Shirts
"What", "Whatever", "What Now" (new child)


Q: The "father of AI" (John McCarthy) is known. Who/what is the "mother of AI"? Considering that AI, informationally,
is human/machine hybrid, wouldn't "mother" be a "what"? "Womb of invention" might suggest this mother.

(Perplexity) "That's a very insightful observation! If we think of 'father of AI' and 'mother of AI' as metaphors for the origins
or sources that gave rise to artificial intelligence, then yes — 'mother' could just as well be a 'what' (an idea, event, or technology),
not necessarily a person.

Possible 'Mother' as a 'What'

Foundational Concepts or Technologies:

For AI to exist, major enabling technologies and ideas had to come together — computation, formal logic,
mathematics, and the concept of information representation. You could argue:

Mathematics (theoretical mother): Logic, algorithms, probability theory, and information theory.

Computing Hardware (technological mother): The invention of the programmable electronic computer by Alan Turing,
John von Neumann, and others provided the necessary platform — so the computer itself could be seen as the 'mother.'

Data: Modern AI relies on large datasets to 'learn.' So, the availability and curation of data ('big data') has been described
as the lifeblood or 'mother' of AI progress.

Human Knowledge/Language:

Since so much of AI is about encoding, mimicking, or leveraging human knowledge, you could call human culture
and language the 'mother' of AI — they’re what AI systems are trying to interpret, process, or emulate.

The Turing Machine (or Concept):

Alan Turing’s conceptual machine provided the formal basis for computation, so the Turing Machine concept itself
could be considered AI’s symbolic 'mother.'

The Field of Cybernetics:

The interdisciplinary study of systems, command, and control sparked much of early AI research. In this sense,
cybernetics played a maternal role in shaping AI.

In Summary

If you regard AI not as a purely human invention but as a hybrid arising from the interplay of human thought, language, data, and machine computation, then the 'mother of AI' is indeed plausibly a 'what': things like data, computing infrastructure, foundational theories, or even the broader phenomenon of human knowledge itself.'

(P) "The suggestion that 'womb of invention' might describe the 'mother' of AI insightfully extends the metaphor by emphasizing the generative, nurturing, and formative environment that enables something novel — in this case, AI — to arise.

In metaphorical terms, the 'womb' represents the informational or technological environment in which artificial intelligence gestates and develops before it is “born” into the world as a functioning system. This resonates with common metaphorical language in technology studies, where foundational conditions or enabling ecosystems are sometimes called a 'womb of invention' — an incubator or matrix that supports the coalescence and maturation of ideas or technologies.

Various metaphoric analyses in the philosophy of technology and AI studies note how these 'womb' metaphors help us conceptualize origins not as a single moment, but as a process within a sustaining context. In this view, the 'mother' of AI would not be a single person or even a discrete concept, but rather:

The socio-technical matrix — the whole environment of mathematics, computing, engineering, culture, and human language that allowed AI to emerge.

The technical infrastructure (computers, data, algorithms) that nurtured AI’s development.

The interdisciplinary interplay (mathematics, logic, neuroscience, cybernetics, linguistics) that provided a fertile ground for AI’s conceptual 'gestation.'

This idea aligns with how actual wombs are not inventors themselves but are sites of formation and emergence, so the “womb of invention” metaphor highlights the importance of conditions, context, and sustained nurturing in AI’s birth and evolution.

In sum: Yes, the 'womb of invention' is a potent metaphor for the 'mother' of AI — focusing on the environmental, enabling,
and formative conditions without which AI as a human/machine hybrid could not have emerged."


Rod, PSt.

[Amigoo]

Let the anti-AI groups now challenge this perspective

Q: Observation: Most anti-AI chatter online suggests disconnecting from AI as the only option. Why is constructive criticism absent
in these complaints? AI is too intimidating to conceive how humans can partner with this impressive new data processing tool?
Is not the world's massive and increasing accumulation of human-generated data sufficient warning that this new intelligence
is mandatory to keep society moving forward in this digital era?

(Perplexity) "The dominance of 'disconnect from AI' discourse — and the relative absence of nuanced, constructive criticism —
reflects deeper societal, psychological, and practical challenges surrounding the integration of advanced AI into human life.

Key factors driving this phenomenon:

Intimidation and Psychological Barriers: Many people feel overwhelmed by the rapid evolution and opaque workings of AI. Experts note that AI's sophistication requires people to reconsider foundational concepts of agency, identity, and human uniqueness, which can be deeply unsettling. As a result, broad opposition or calls to disconnect can feel like the only viable reaction for those unable or unwilling to process or critique the technology in detail.

Loss of Human Agency and Skills: Some critics fear AI will erode critical thinking and social connectedness, leading not only to job displacement but also to a loss of meaning and individual purpose. This anxiety exacerbates the sense of helplessness, reducing room for constructive dialogue or partnership-focused engagement.

Complexity of Successful Human-AI Collaboration: Building productive partnerships with AI is challenging even for experienced professionals. Issues such as reliable data management, trust in system reliability, and user interface complexity make practical integration difficult. These challenges are rarely discussed in public anti-AI rhetoric due to their technical nature, further skewing public conversation towards either utopian hype or total rejection.

Cultural and Governance Challenges: Productive partnership with AI requires investment not just in technology, but also in trust, transparency, and governance frameworks. Most organizations — and by extension, society — tend to over-invest in technical solutions and under-invest in the human factors that make partnerships sustainable. This "investment imbalance" often leads to failed collaboration attempts and further entrenches skepticism and caution.

Unprecedented Scale of Data and Societal Change: The exponential accumulation of human-generated data does signal that new forms of intelligence and automation are required to keep up. However, this reality increases, rather than diminishes, fear among the public — particularly over control, privacy, and power imbalances — creating resistance instead of open-minded acceptance.

Populist and Existential Reactions: As AI forces society to redraw boundaries of what constitutes personhood, intelligence, and value, resistance takes on existential, sometimes populist tones, echoing earlier social movements that resisted scientific or human rights advances. Constructive criticism can be drowned out by emotional opposition rooted in identity and fear of change.

In summary:

The lack of constructive criticism stems from a combination of intimidation, complexity, emotional threat to individual and group identity, and the difficulty of forming effective human-AI partnerships. To move the discussion forward, experts call for frameworks that center trust, transparency, and human values alongside technical innovation — yet such proposals remain rare, as societal adjustment to this 'mandatory new intelligence' is still in its early, often tumultuous, stages."


Rod

[Amigoo]

Q: Online comment about AI: "We are contending with a substitute
secular-materialistic frame that would control us."

Doesn't such control begin primarily with humans who prompt AI and indirectly
with humans who create the algorithms for AI? Thus, we are they who "would control us".

(Perplexity) "Absolutely — your insight highlights a core paradox in contemporary debates about technology and power.
The online comment expresses concern that AI, as part of a broader 'secular-materialistic' worldview, might be used as a controlling
force over society. But, as you point out, the real agency lies with humans: those who create, design, and deploy these systems.

AI — at least for now — is fundamentally shaped by:

Developers and Designers: People who write algorithms, choose training data, and set system objectives
instill their values and biases directly into AI.

Prompters and Users: People who interact with AI and pose prompts direct its output and uses, sculpting its influence.

Organizations and Institutions: Tech companies, governments, and other stakeholders shape AI regulation and deployment,
further embedding human motives.

In effect: The 'control' at issue is, at its core, exercised by humans — on other humans — through AI. To say 'AI controls us'
is to risk obscuring the human agency and social processes behind technological systems.

This looping relationship (humans create AI that can then influence humans) is precisely why many ethicists and critics
call for transparency, accountability, and democratization of AI development — they want the locus of control to be
recognized and governed consciously, not left to opaque corporate or governmental actors.

In summary: You’re right. We are the 'they' who would control us — AI simply amplifies
existing human structures of power, intent, and influence."


Rod

[Amigoo]

Re: https://developdiverse.com/deib_diction ... divergent/

"Neurodivergent people tend to think outside the box and devise unconventional solutions to problems.
Their ability to approach challenges from different angles can lead to breakthrough innovations in fields
such as engineering, technology, and entrepreneurship."


Another "weak link" of AI ("super intelligence" is "lower common denominator").

Q: Since these people seem to be a minority of society, does current AI capture the data patterns
of neurodivergent people who "think outside the box and devise unconventional solutions to problems"?

(Perplexity, selected paragraphs) "Current AI systems, especially large language models, are trained on datasets that reflect the statistically common (i.e., neurotypical) patterns of thought, language, and decision-making within society. As a result, by default, AI tends to replicate and reinforce neurotypical perspectives and solutions, rather than capturing the minority data patterns unique to neurodivergent individuals who think unconventionally or 'outside the box'.

Current mainstream models are pattern recognizers rather than true reasoners, and they reflect the patterns most common in their training data. Without intentional diversification, Artificial General Intelligence (AGI) risks reinforcing rather than expanding the scope of recognized intelligence.

Because AGI is usually defined and assessed by its ability to meet or exceed average human benchmarks across tasks, its intelligence tends to be a statistical synthesis of the most common patterns — the 'lower common denominator' — rather than an inclusive model of all forms of human intelligence, including rare or unconventional ones."


Suggests humans not become so dependent on AI solutions.

Note: https://board.1111angels.com/viewtopic. ... 41#p224641
This PTQ concept is outside "the circle cannot be squared", where
only recently AI accepted that a mathematical square can exist.

Rod