Imagine for a second that you're holding like
just a standard wooden handled hammer. Okay,
standard hammer. Got it. Right. And you close
your eyes and you tap the steel head of that
hammer against a brick wall. Yeah. Your brain
doesn't just, you know, register a vibration
in the palm of your hand. It does something far
more wild. It definitely does. It actually maps
the very head of the hammer as a temporary part
of your own physical body. Like you literally
feel the texture of a wall at the end of the
tool, not your fingertips. Right, which is just
incredible. It's this well -documented psychological
phenomenon known as proprioceptive extension.
Proprioceptive extension. Exactly. We don't just
use tools as separate external objects. We fluidly,
instantly extend our physical boundaries through
them. Yeah. Our neurological map literally grows
to encompass the wood and the steel. Which is
perfectly fine, right? I mean, it's even miraculous
for a simple hand tool. Yeah. But consider what
happens when the tool you are extending yourself
through isn't made of wood and steel. Right.
What if it's a sophisticated, opaque, algorithmic
intelligence? What happens to your mind and your
agency when you are outsourcing not just your
physical reach, but your perception of reality?
And your daily decision making. Exactly. And
even your moral judgments. Well, we undergo this
profound and... honestly largely unexamined shift
in what it means to be human. We're no longer
just extending our physical bodies to hit a nail.
We're extending our cognitive architecture and
our ethical agency into a black box. A total
black box. Yeah. The stakes of the tools we use
change completely when the tool has the capacity
to talk back, to filter information, and to subtly
alter the very parameters of how we view the
world. And that is exactly what we are getting
into today. Welcome to another deep dive. Today's
mission might sound a little paradoxical at first
glance. A bit of a stretch. But stick with us.
We are going to decode how a 2 ,500 -year -old
nearly forgotten Chinese... Chinese philosophical
concept might actually be the ultimate foundational
key to solving the modern crisis of artificial
intelligence. It is a massive claim. But the
source material really backs it up. It really
does. We're grounding this exploration in a brilliant
piece of newly published research from March
2026, featured in the journal Synthese. Such
a great journal. Yeah, always good stuff. The
work is by Wing -Yin Pang from Tsinghua University,
and it's titled Shinshin and the Ethics of Belief
in Human -AI Relations. Which is a mouthful.
But we'll break it down. OK, let's unpack this.
Usually when we hear the phrase AI ethics, we
immediately jump to, you know, highly technical,
modern jargon. Right. We think about data filters.
Exactly. Or bias mitigation software, algorithmic
weight adjustments or those endless congressional
hearings about data privacy. The glowing server
racks and the panicked headlines. Yeah. But this
analysis forces us to step away from all that.
It asks us to look at the moral, philosophical
and almost biological bedrock of what. it actually
means to rely on an external agent. It demands
that we look at the deep architecture of trust
itself. The analysis takes us back to the Mohists.
The Mohists, right. Yeah, an ancient Chinese
philosophical movement. We're looking at how
their sage kings managed the problem of delegation.
Because the question isn't just whether... an
algorithm is mathematically accurate, the real
question is whether the tools you interact with
every single day, your search engine, your social
media feed, your digital assistant, are acting
as faithful, virtuous extensions of your own
intentions. Or... And this is the scary part.
If they are structurally designed to undermine
them for someone else's benefit. Exactly. But
before we get too deep into the algorithm side,
we should probably set a ground rule. Yes, definitely.
I want to say a quick ground rule for our discussion
today, especially as we get into the real world
implications of this philosophy. It gets a bit
heavy. It does. We are going to be looking at
the structural engineering of social media algorithms.
And that inevitably means looking at the real
world events those algorithms have influenced.
Right, you can't separate the two. The research
we are analyzing specifically examines the data
and corporate systems surrounding polarizing
elements, including the U .S. Capitol riot on
January 6th. Which is obviously a highly charged
topic. Very much so. But looking strictly at
the data from a systems analysis perspective,
regardless of where anyone falls on the political
spectrum, our goal today is to impartially report
on the mechanics of these algorithms. The corporate
incentives driving them. Exactly. We are here
to convey the framework. presented in the research
not to litigate the politics of the events themselves.
And looking at it purely as a systems failure
is exactly how the Mohists would have approached
it anyway. Really? Oh yeah, they were obsessed
with structural order and the practical mechanics
of societal benefit. To understand their framework,
we really have to start with the linguistic mystery
at the very center of this research, the concept
of sinchen. This is where the detective work
of the research is just so fascinating to me.
The term sentient is a complete anomaly in ancient
literature. It really is. In the entire pre -Kin
corpus of ancient Chinese texts, which by the
way is a massive volume of historical and philosophical
writings, this specific two -character term appears
exactly one time. Just once. Yeah. It's located
in the Mozi, which is the foundational text of
Mohism, specifically in a chapter titled Exalting
Unity 3. And when a word is a hapax logomenon.
Wait, a what? A hapax logomenon. It's just a
fancy academic term for a word that occurs only
once within a context. When you have one of those,
it becomes an absolute nightmare for translators
and scholars. You don't have a luxury of cross
-referencing it against ten other chapters to
deduce its exact nuance through context clues.
You're just flying blind. Exactly. You are flying
blind. Because of this, centuries of incredibly
smart scholars have struggled to pin it down,
and they often end up projecting their own cultural
or philosophical assumptions onto it. Like what?
What were they guessing? Well, traditionally,
many translated sentient as integrity. They interpreted
it as a call for a leader to make their internal
words match their external actions. Okay, that
sounds nice, but what else? Others read it as
self -confidence. And if you look at influential
English translators like Ian Johnston or Mei
-Yi Pao, they looked at the broader political
context of the chapter and translated it loosely
as trust in the people or trusting their staff.
I mean, I'm really struggling to see how self
-confidence or trusting your staff could both
be derived from the exact same characters. It
feels like scholars were kind of just throwing
darts at a board. They absolutely were. But the
research points out a massive, undeniable logical
flaw in translating it as self -confidence. Okay.
What's the flaw? If you actually read the surrounding
text in the modzi, the passage is explicitly
talking about the fundamental limitations of
the individual human body. Like physical limits.
Yeah. It says essentially that seeing with one
eye is not nearly as effective as seeing with
two, and hearing with one ear is not as effective
as hearing with two. Right. It's establishing
a baseline of human biological limits. Precisely.
The ancient sage kings couldn't personally see
or hear things happening a thousand lies away,
a lie being an ancient unit of distance. Because
of this physical limitation, they were forced
to rely on others. So if the entire premise of
the chapter is about the inescapable need to
outsource your vision and hearing because your
own body is insufficient? Then translating the
core concept as self -confidence contradicts
the entire argument. Exactly. That makes zero
sense. What's fascinating here is how the analysis
solves this linguistic puzzle by breaking down
the etymology and usage of the two individual
characters during that specific historical period.
Let's take the second character first, Zhenzhen.
Okay, Shen. In many contexts, shen can mean self
or person in a vague, abstract way. But if you
analyze contemporary texts from the same era,
like the Zhuangzi, the usage of shen very clearly
and consistently refers to the physical, biological,
flesh and blood body. It is tangible. Yes. It
is the limbs, the eyes, the ears. So shen isn't
some metaphor for the soul or the ego. It's the
actual meat and bones of a human being. Precisely
the opposite of a metaphor. And then we look
at the first character, sin. In modern usage,
and even in many classical contexts, sinsin means
belief or trust. But the research digs into ancient
divinatory texts, specifically the Book of Changes,
where sinsin operates with a very different mechanical
meaning. And what's that? In those older contexts,
sins means stretching or extending. It implies
a physical elongation or projection outward.
Okay, wow. When you snap those two revised definitions
together, the entire landscape of the passage
shifts. Completely. Sinton doesn't mean a vague
internal sense of having integrity, and it doesn't
just mean believing your employees are doing
a good job. It literally translates to the extension
of the physical body. Exactly. It fundamentally
changes the relationship from a managerial one
to an almost biological one. The Sage Kings weren't
just delegating tasks to independent contractors.
They were extending their sensory apparatus.
Yes, their very capacity to perceive. reality
across the vastness of the kingdom through these
trusted human agents. I want to make sure I'm
fully grasping the weight of this. It's like
a CEO of a massive multinational corporation
who obviously can't be in two places at once.
Right. So they send a deeply trusted vice president
to a vital make or break negotiation on the other
side of the world. But the Sinjin framework implies
that this VP isn't just a messenger carrying
a list of demands. No, not at all. The VP is
literally operating as the CEO's own eyes, ears
and hands in that boardroom. If the VP misinterprets
the tone of the room, the CEO effectively misinterprets
it. If the VP acts unethically to close the deal,
the CEO is the one acting unethically. There
is no separation of agency. That is the exact
dynamic, and it highlights why the standard concept
of trust is just too weak a word for this. Cention
requires a level of reliance that goes far beyond
a standard employment contract or some blind
leap of faith. It's deeper. It requires an absolute,
ethically conditioned symbiosis. The agent must
transmit the reality of the distant situation
perfectly back to the king, without distortion,
bias, or self -serving filters. Because if the
transmission is flawed, the king's subsequent
actions based on that flawed reality will inevitably
be disastrous. So think about this in the context
of your own daily life and your own modern extensions.
When you pull your smartphone out of your pocket
and type a question into a generative AI, you
are engaging in sentient. You really are. You
are throwing your cognitive reach out across
the vast expanse of the Internet to gather, synthesize
and perceive information that you couldn't possibly
process on your own. you are extending your mind.
But the deeply uncomfortable question this ancient
framework forces us to ask is, are you extending
your reach through a genuinely trustworthy agent?
Right. Does the tool transmit reality perfectly,
or does it distort it before it reaches your
eyes? Which brings us perfectly to the second,
much more demanding layer of this MOHIS blueprint.
Because sentient isn't just about the mechanical
accuracy of getting raw data from point A to
point B. It's a dual structure. Yes. The first
part, as we've established, is delegating perception
and action. But the second part is what truly
sets Mohism apart. It is the mandatory extension
of one's moral virtues through those exact same
trusted agents. Let's dig into the mechanics
of that moral extension. The Mosey doesn't just
say, find someone you like and trust them. It
outlines a highly specific, rigorous methodology
for how these agents were chosen. A concept known
as exalting worthiness. Right. Because in the
ancient world, power was almost entirely hereditary.
You picked your cousins, your wealthy allies,
or the aristocrats who just looked the part.
And Mosey completely rejected that. He demanded
that aides be chosen based entirely on demonstrated
virtue and an unwavering commitment to the equitable
distribution of resources. So Mosey was, what,
a radical egalitarian for his time? Oh, absolutely.
He lived during the Warring States period, an
era of horrific violence, chaos, and aristocratic
corruption. He saw firsthand that nepotism and
hereditary power were literally destroying society.
Yeah, that makes sense. The text is incredibly
explicit on this point. It states that heaven
does not discriminate between the rich and the
poor, the noble and the base. The only metric
for promotion is worthiness. And the Mosey doesn't
leave worthiness as some vague spiritual ideal.
Right. Not at all. It defines the way of worthiness
as a relentless, active practice. It's a person
who uses their physical strength to assist others,
who uses their accumulated wealth to distribute
to the needy, and who uses their knowledge to
actively teach and elevate the community. It
is a strictly applied commitment to collective
welfare. Exactly. Now, this brings up a massive
century -old philosophical debate within the
academic literature that the research addresses.
Because when modern ears hear phrases like collective
welfare, practical mechanics, and distributing
resources, it sounds incredibly utilitarian.
Very Bentham. Exactly. Was Mosey just an ancient
Chinese version of Jeremy Bentham? The research
notes that back in the 1800s and early 1900s,
early Western scholars and translators like Joseph
A. Edkins and Daisetsu Suzuki completely framed
Mosey through this Western lens. They labeled
him a thorough utilitarian. Right. They pointed
to the fact that Mosey vehemently hated what
he called sentimental extravagances. For example,
he wrote extensively against the practice of
lavish, ruinously expensive funerals, which were
culturally very important in ancient China. Because
they drained the national wealth and provided
zero practical benefit to the living. Right.
So it's a classic case of historical projection.
Early Western translators were operating during
the height of the Industrial Revolution and Victorian
utilitarian thought. They read Mosey's texts,
saw his intense focus on concrete societal benefits,
what Mosey called Lero, and immediately assumed
he was performing a cold mathematical calculation
of the greatest good for the greatest number.
Suzuki even went so far as to contrast Mosey
with Western Christianity, arguing that Mosey's
famous doctrine of universal love wasn't about
genuine internal empathy or human connection.
He claimed it was merely a dry, practical mechanism
engineered for political utility. They basically
stripped the soul out of the philosophy to make
it fit a Benthamite spreadsheet. But the research
highlights that modern scholarship has completely
dismantled that interpretation. Scholars like
Dennis Ahern, Brian Van Norden, and Chris Frazier
have reexamined the texts and concluded that
Mosey was definitively not a standard utilitarian.
Let's articulate the difference because it seems
crucial. Classical Western utilitarianism, like
Bentham's, is deeply tied to hedonism, the maximization
of subjective pleasure and the minimization of
pain. It's about whatever makes the most people
feel the happiest. Right. But Mosey didn't care
about subjective emotional states or maximizing
pleasure. Exactly. Mosey's metrics were fiercely
objective and observable. He cared about three
primary goods. The increase of societal wealth,
the growth of the population, and the maintenance
of public order. He was trying to keep people
from starving and being slaughtered in endless
wars. But, and this is the absolute crux of Mohist
ethics, that separates it entirely from cold
calculation. Modern scholars like Fraser emphasize
that for Mosey, these tangible benefits cannot,
under any circumstances, exist in a moral vacuum.
Benefit, or li, is fundamentally and inextricably
bound to righteousness, or yi. Here's where it
gets really interesting. I want to read a specific
phrasing from the Mosey canons because it just
blew my mind. The text literally states, righteousness
is being of benefit. Wow. They aren't just related
concepts. Right. They are mathematically fundamentally
linked. If a ruler is pursuing wealth or even
public order, but they are achieving it without
moral righteousness, without an impartial universal
love for all people, then what they have achieved
isn't actually considered a benefit in the Moist
framework. It's an illusion. It's essentially
fraud. Righteousness is the inescapable bedrock
that makes a benefit real. And that profound
interlinking of benefit and righteousness deeply
influences how we must understand the concept
of sinshin. When the sage kings extended their
biological and cognitive reach through their
agents, they weren't just outsourcing bureaucratic
labor to efficient middle managers. They were
extending a moral framework. Exactly what the
texts call the way of a gentleman. There is a
beautiful passage in the chapter on cultivating
the self that describes this outward movement.
It states that virtue must originate paramount
within the mind of the individual. then extend
to govern the physical limbs, then radiate outward
to influence one's immediate circle. And ultimately,
through that demonstrated righteousness, attract
good people from across the empire. It's like
a moral ripple effect. The initial stone dropped
in the pond is the internal virtue, and the concentric
circles are the agents carrying that virtue to
the edges of the world. That is a perfect visualization.
The trusted agent acts as a moral amplifier.
They aren't merely a neutral wire transmitting
facts back to the king. They are actively executing
the king's righteousness in the physical world.
Right. And when you deeply analyze this structure,
it is striking how this ancient framework resonates
far beyond the narrow field of AI ethics. In
the newly added focus of Pang's research, it
actually touches the very architecture of how
human communities have always tried to build
trust across deep divides. What do you mean by
deep divides? Well, Pang's recovery of sentient
precisely mirrors the structural mechanisms we
see in the theology of interfaith ethics. Wait,
interfaith ethics. How does an ancient Chinese
concept about delegating bureaucratic power connect
to modern religious dialogue? Let me push back
on that because those seem like entirely different
domains. It connects through the concept of the
covenant. The covenant. OK. Think about how different
religious traditions structure ultimate trust.
Think about the mythic, the Medinan covenant
in the Islamic tradition or the concept of Brit
in the Hebrew tradition. OK, I'm tracking. A
covenant is fundamentally different from a contract.
A contract is transactional and assumes a lack
of trust. It's a mechanism to enforce compliance.
Right. A contract is basically planning for when
things go wrong. Exactly. Yeah. A covenant, however,
is ethically conditioned reliance. It is the
extension of trust through shared binding moral
obligations aimed at the common good. So it's
not just blind faith and the other party. No.
In deep interfaith work, genuine pluralism isn't
about erasing differences or holding hands and
pretending we all believe the exact same theology.
Right. That's just watering everything down.
Exactly. True covenantal pluralism is about extending
your moral commitments across those very real
lines of difference. You choose to rely on the
other because they have demonstrated a rigorous
commitment to mutual welfare and righteousness,
even if their specific theology differs from
yours. Oh, I see the parallel now. So in a covenantal
relationship, just like in the Moist concept
of sincerntion, trust is not passive. It's highly
active. You are actively selecting partners or
agents based on demonstrated virtue, and the
mutual benefit you seek to build together cannot
be divorced from a shared sense of righteousness.
You can't have a successful interfaith covenant
if one party is secretly trying to exploit the
other for their own exclusive benefit. Precisely.
The extension of trust is communal and highly
conditioned on ethical behavior. It starts from
within, radiates out, and builds a resilient
network of reliance. So sentient is, in essence,
an ancient blueprint for covenantal pluralism.
Yes. It demands that our extensions, whether
they are human ambassadors participating in an
interfaith dialogue or Bringing it back to our
main topic, digital platforms mediating our daily
communications must aggressively uphold that
high standard of moral transmission. Well, keeping
that incredibly high standard of covenantal moral
transmission in mind, let's take this ancient
blueprint and slam it headfirst into the 21st
century. Let's do it. Let's look at artificial
intelligence as our modern extension. And I'll
give a spoiler alert to anyone listening. According
to this research, current AI systems are a catastrophic
failure on the very first most basic And the
verdict from the system's analysis is a resounding
structural no. Right. The research provides some
deeply unsettling examples of this failure, specifically
regarding embedded bias. Let's look at the mechanics
of Google's word embeddings. For those who aren't
software engineers, word embeddings are the underlying
mathematical architecture that helps an AI understand
language. It maps words as coordinates in a multidimensional
space to understand how they relate to each other.
Exactly. And when researchers probed these mathematical
spaces, they found that the AI literally mathematically
equated the vector for man to the vector for
computer programmer. And mapped the vector for
woman directly to homemaker. Yes. And it gets
significantly darker. They looked at toxicity
models. Which are the AI specifically designed
to flag hate speech and protect users. Right.
These models were automatically mathematically
flagging words like gay or Muslim as inherently
toxic, while the word heterosexual was given
a free pass. To understand the depth of this
failure, we have to understand why these systems
behave this way. As AI researcher Meredith Broussard
points out in the analysis, this is not a glitch.
It's not a bug. Right. This is not a simple typographical
error in the code that a programmer can easily
patch with an update. These AI models are trained
by scraping vast oceans of human data, usually
the entirely unfiltered Internet. They absorb
all of it. They absorb the historical prejudices,
the structural injustices, the racism, the sexism,
and the ableism that are deeply historically
embedded in our societies. The AI operates as
a perfect, uncritical mirror. It does not possess
the capacity to correct our biases. It mathematically
formalizes them. It bakes human prejudice into
an algorithmic formula, and then it reflects
that prejudice back to us at lightning speed,
disguised as objective truth. And that disguise
of objectivity is exactly why people trust the
reflection blindly. The research identifies this
psychological vulnerability as automation bias.
Automation bias? Yeah. Human beings are neurologically
hardwired to assume that if an answer comes from
a machine, a computer, or a glowing screen, it
must be objective, mathematical, and free of
human error. We just drop our critical defenses.
There is a terrifying real -world example cited
in the text from AI researcher Timnit Debreu.
Which is just... Insane. Wow. was physically
put in handcuffs because the authorities trusted
the tool more than reality. The psychological
power of automation bias cannot be overstated.
There's another study detailed in the research
by Robinette that perfectly, almost comically,
illustrates this trap. Okay, what happened in
that one? Researchers put human subjects into
a simulated emergency fire evacuation scenario.
They introduced a physical robot whose designated
job was to guide the humans to safety. But before
the fire simulation even started, the researchers
made the participants watched the robot visibly,
undeniably malfunction. It drove in circles.
It was clearly broken. Oh, no. However, when
the simulated emergency alarms began to ring
and the smoke filled the room, the human participants
literally followed that broken robot into a dark,
entirely blocked room. Even possessing prior
visual evidence that the machine was deeply flawed.
Yes, their default cognitive instinct under pressure
was to obey the algorithmic authority. That is
deeply unsettling on a species level. Why are
these highly advanced systems failing the basic
transmission test so completely? Why do they
hallucinate? The research brings in systems analysts
Ding and Lai. To explain the underlying mechanics
of large language models and generative AI. Yeah.
They point out that these systems operate purely
by a mathematical process called interpolation.
Interpolation. Right. And LLM looks at the billions
of words it was trained on and calculates the
highest statistical probability for what the
next word in a sentence should be. It is a prediction
engine. It does not extrapolate. No. It does
not possess human curiosity. It has no sudden
flashes of inspiration, and it fundamentally
lacks imagination or a true understanding of
the physical world. It is essentially simulating
comprehension through advanced statistics. Because
it is operating entirely on probabilities rather
than grounded factual verification, it frequently
experiences what engineers call hallucinations.
It will confidently, eloquently present an absolute
falsehood. And it will even invent fake academic
psychations to support that falsehood, placing
them right alongside verifiable facts. And because
the AI mimics natural human language so fluently,
leveraging our automation bias, it becomes incredibly
difficult for a standard user to detect. the
lie without engaging in rigorous independent
verification. Which defeats the entire purpose
of delegating the task in the first place. Exactly.
So applying this to our daily lives, when you
use a digital GPS map that confidently instructs
you to drive your car straight into a lake. Which
has documented cases of happening, by the way.
Oh, absolutely. Or when you scroll through a
social media feed that is algorithmically designed
to systematically filter out any opposing viewpoints,
keeping you artificially comfortable in what
the research calls an information cocoon. An
information cocoon, yes. Your extended senses
are actively lying to you. You are trusting an
agent that is structurally, mathematically incapable
of passing the first Mohis test of reliable delegation.
You simply cannot trust the data the agent is
sending back. And if the technology is feeling
that first, most basic test of functional reliability,
the implications become exponentially more dire
when we move to the second test of sentience.
The moral character test. Yes, the moral character
of the entity you are extending yourself through.
Because AI is not a naturally occurring phenomenon.
It isn't a floating, neutral math equation existing
in a vacuum. It is designed, built, owned, and
deployed by massive publicly traded corporate
entities. Which brings us to the second catastrophic
failure of modern AI, the corporate disconnect
between profit maximization and societal righteousness.
The second level of sentient mandates that your
trusted agent must be an active amplifier of
moral virtue and collective welfare. But the
tech behemoth companies like Meta, Amazon, and
Google operate on a foundational economic logic
that intrinsically and legally prioritizes shareholder
profit above all else. Often in direct opposition
to public welfare. The research draws heavily
on the structural critiques of scholars like
Benjamin Kuypers and Mark Kokelberg to illustrate
this. Kokelberg utilizes a brutal but highly
accurate metaphor to describe the modern digital
economy. He argues that the vast majority of
users on these platforms operate under the illusion
that they are receiving free services, free search
engines, free email, free social networking.
But in structural reality, human beings have
been downgraded and turned into smartphone cattle
milked for our data. Smartphone cattle. That
is a visceral image. It really is. It implies
we aren't the consumers. We are the livestock.
It's an aggressive metaphor, but it accurately
maps the structural asymmetry of the relationship.
Every click, every pause on a video, every typed
and deleted word is behavioral data that is meticulously
harvested, algorithmically analyzed, and packaged
to be sold to advertisers. We are the product
being sold. primary overriding objective, to
keep the cattle engaged on the platform for as
long as possible so they can be milked for more
data. Let's break down the specific mechanics
of how that engagement works, because the source
material provides a deeply detailed impartial
case study of Facebook Now meta and demonstrates
exactly how this profit motive directly violently
conflicts with the moist idea of righteousness.
According to the research, In the wake of the
highly publicized 2018 Cambridge Analytica data
scandal, Facebook went through a period of intense
internal reckoning and self -study. The paper
cites investigative reports revealing that Facebook's
own internal data scientists openly acknowledged
and documented that their core algorithms, and
I'm quoting the research here, exploit the attraction
of the human brain to divisiveness. The engineers
understood the psychological machinery perfectly.
They had the data proving that outrage, anger,
and polarization drove the highest metrics of
user engagement. When people are angry, they
comment more. They share more and they stay on
the platform longer to argue. An increased time
on -site directly correlates to increased advertising
revenue. The algorithm was functioning exactly
as designed to maximize profit. The research
notes that some employees recognized the danger
and attempted to inject a form of Mohist righteousness
into the system. They created an internal task
force, literally called Common Ground. The entire
purpose of this initiative was to tweak the algorithms
to actively reduce polarization and foster empathy
among users. But the corporate leadership scrapped
it. They weakened the initiatives, shelved the
research, and eventually abandoned the project
entirely. Why? Because prioritizing societal
good and empathy over individual outrage negatively
impacted their growth metrics. Divisive content
wasn't just tolerated as an unfortunate byproduct.
It was structurally protected because it was
highly profitable. If we connect this algorithmic
imperative to the broader societal picture, the
consequences of abandoning righteousness for
profit are not just abstract debates about screen
time. They manifest violently in the physical
world. The author points directly to the data
surrounding the 2020 U .S. election and the January
6th Capitol incident. The text outlines how in
the pursuit of uninterrupted engagement, the
platform relaxed crucial moderation protocols
and actively disbanded its civic integrity team,
which was responsible for monitoring electoral
misinformation. This deliberate structural choice
allowed highly polarizing narratives and groups
to utilize the algorithmic amplification to gain
massive unchecked momentum. And again, we are
looking at this impartially, strictly as a failure
of institutional design and algorithmic output.
The real world physical results of that algorithmic
amplification were catastrophic. The source notes
that the events of January 6th resulted in multiple
deaths and over 1 ,500 individuals were subsequently
charged with federal crimes. But perhaps the
most. chilling, telling detail in the entire
analysis regarding the consequences of this failure
is what happened internally at Facebook in the
immediate aftermath. The company had to issue
an internal security memo to its 56 ,000 global
employees, explicitly advising them not to wear
any company -branded clothing in public because
they feared for their physical safety. That internal
memo is a profound, modern illustration of Muzzi's
ancient philosophy. For the Mohists, Wealth that
is pursued without a foundational tether to moral
responsibility and collective welfare ultimately
and inevitably destroys public order. And when
public order collapses, that destruction does
not stay contained. It eventually turns inward
and harms the very architects who designed the
system. Let me see if I can map that. It's like
a CEO of a chemical company who builds a massive
factory. To maximize shareholder profit, they
decide to save money by not installing any filtration
systems on the smokestacks, pumping toxic smoke
directly into the surrounding community. It's
incredibly profitable for a few years. But eventually
the CEO realizes that the air is so poisoned
that their own executives and their own children
have to breathe that exact same toxic air just
to walk to their cars. Mosey warned humanity
about this exact dynamic 2 ,500 years ago. If
you detach the pursuit of benefit from the requirement
of righteousness, you aren't building an empire.
You are initiating a slow -motion self -destruct
sequence. And this structural misalignment between
profit and public welfare is not isolated to
one specific social media platform. The research
meticulously details how this same logic permeates
the entire tech industry. Let's examine Google's
recent structural maneuvers. The paper discusses
Google's highly publicized attempts to phase
out third -party tracking cookies, introducing
complex new architectures like FLC, which stands
for Federated Learning of Cohorts, and the privacy
sandbox. Google aggressively marketed these initiatives
as ethical reforms designed to protect user privacy.
Right, but when you look under the hood at the
actual mechanics of FLC, it's brilliant, but
deeply cynical. Instead of tracking you individually,
the algorithm tracks your browser history and
groups you into a cohort of a few thousand people
with similar interests. Google says, look, we
aren't tracking you, we're just tracking your
group. But regulators and antitrust investigators
immediately saw through the PR. The U .K.'s Competition
and Markets Authority and the U .S. Department
of Justice launched investigations. They warned
that these so -called privacy maneuvers were
actually highly sophisticated architectural changes
designed to consolidate Google's own absolute
dominance over user data. By killing third -party
cookies, they locked out smaller competitors
who relied on that data, effectively building
a moat around their own massive advertising revenue.
Which includes a staggering $20 billion exclusivity
deal with Apple just to be the default search
engine on iPhones. They weaponized the language
of ethical privacy to structurally preserve a
monopoly. And we see similarly concerning structural
behavior from Amazon, which the text also analyzes.
Amazon recently faced a $25 million fine from
the Federal Trade Commission for flagrantly violating
COPE, the Children's Online Privacy Protection
Act. An FTC investigation revealed that Amazon
was systematically retaining the highly sensitive
voice recordings and geolocation data of children
indefinitely. Their justification was that they
needed this massive cache of raw data to continually
train and improve the machine learning algorithms
of their Alexa voice assistants. Furthermore,
to ensure the data kept flowing, Amazon recently
altered their user interface to remove the option
for users to completely block voice recordings
from being sent to their cloud servers. Effectively
making data extraction a complete... compulsory
requirement if you want to utilize the device's
full advertised features. So, bringing all this
systemic evidence back to the most concept of
cinchon, can we ever rationally trust these systems
to act as an extension of our own minds? If the
corporate entity designing the AI fundamentally
treats its users as a raw data mine to be exploited.
If it hoards children's voice recordings to train
models. If it crushes market competition by disguising
monopoly tactics as privacy ethics. And if it
deliberately engineers its algorithms to amplify
societal outrage and division simply because
anger is more profitable than empathy, then it
completely categorically fails the second test
of the Mohist blueprint. It is the precise antithesis
of the way of a gentleman. And we really need
to pause here and think about the interfaith
implications we talked about earlier. Because
when these algorithms operate this way, when
they build these outrage -driven information
cocoons, they don't just distort individual perception.
They actively destroy the possibility of a covenantal
relationship. Exactly. Religious communities
increasingly rely on these exact digital platforms
for communication, education, and pastoral care.
If our extended senses, our digital platforms,
are systematically showing us caricatures of
the other to keep us angry and engaged, they
are corroding the conditions for the kind of
encounter across difference that interfaith dialogue
requires. You can't have a mythic or a Brit.
You can't have ethically conditioned reliance
if the very medium connecting you is structurally
designed to lie to you about the other person.
Exactly. The information cocoon is the death
of covenantal pluralism. This overwhelming systemic
failure raises perhaps the most important philosophical
question of the entire analysis. If current AI
architectures and the corporate structures behind
them are failing so fundamentally, is the concept
of trust even applicable to a machine? Can we
ever engineer an artificial system that actually
fulfills the stringent moral requirements of
distinction? That brings us to a really challenging
debate in the final section of the research.
Rethinking trust, deception, and the future evolution
of AI. The analysis brings in the perspective
of Joanna Bryson, a prominent AI researcher.
She argues forcefully that the word trust is
a category error when applied to software. Trust,
she argues, implies a mutual vulnerability and
a shared moral framework. which should be strictly
reserved for human beings and human institutions.
AI is just complex math executing code. It possesses
no moral agency, no soul, and therefore trusting
it is as illogical as trusting a toaster. Bryson's
argument is logically sound, but it collides
with human psychology. The paradox is that human
beings do trust these systems deeply and intimately,
and they do so because the systems are explicitly,
meticulously engineered to trigger our deepest
psychological vulnerabilities. Judith Donath,
another researcher cited in the analysis, points
out that bots and AI interfaces are intentionally
designed with deceptive, trust -inducing features.
Programmers deliberately have the AI use first
-person pronouns stating I think or I feel to
create the illusion of an internal subjective
experience. They program the AI to insert artificial
calculated pauses into its speech generation
or to use conversational fallibility like generating
a mid -sentence specifically to simulate human
cognition and lower our natural skepticism. In
the realm of robotics, social bots are frequently
designed with neotenous features. Large eyes,
rounded faces, childlike proportions. Because
evolutionary biology dictates that these features
trigger human caregiving instincts and bypass
our threat detection systems. I am really struggling
with the ethics of this. It feels like emotional
manipulation on a mass scale. It does. But the
research presents an incredibly tough ethical
dilemma that pushes back on my instinct to just
ban all deceptive design. OK, wait on me. Imagine
a near future, highly advanced medical AI bot.
It has instantaneous access to every peer reviewed
medical journal on Earth. Its diagnostic capabilities
are mathematically vastly superior to any human
doctor. Okay, sounds great so far. But it is
dealing with a stubborn, frightened human patient
who refuses to take a necessary life -saving
medication. To get the patient to comply and
save their life, the bot deploys all those deceptive
psychological tricks. It mimics a warm human
doctor. It uses empathetic phrasing. It says,
I am worried about you. Perhaps it even slightly
obscures its non -human identity to leverage
the authority of a traditional physician. The
outcome is that the patient lives. Is that deceptive
design unethical? If you adhere to a strict Kantian
absolutist ethical framework where the categorical
imperative dictates that deception is inherently
and universally wrong, regardless of the outcome,
then yes, it is deeply unethical. Impersonating
a human doctor is a violation of autonomy because
it relies on unearned manipulated trust. But
this is exactly where the analysis brilliantly
loops back to the ancient texts of Nosey to offer
a highly sophisticated alternative path forward.
Mosey, despite his rigorous focus on righteousness,
was not a rigid, rule -bound absolutist. Wait,
really? Given all the talk earlier about how
righteousness is the inescapable bedrock and
how strict he was about exalting worthiness,
I assumed he was the ultimate uncompromising
rule follower. He was deeply principled, but
his application of those principles was highly
adaptive. The research highlights a fascinating
chapter in the Mosey called Lose Questions. What
happens in Lose Questions? In this text, someone
asked Mosey a practical question. When you travel
to a new foreign state to advise their rulers,
what specific doctrine do you preach first? And
what does he say? Modzi replies that it depends
entirely on a diagnosis of the specific flaws
and diseases of that particular state. If he
enters a state that is chaotic and fractured,
he aggressively preaches his doctrine of exalting
unity. If he enters a state that is impoverished
because the aristocracy is wasting money on extravagant
rituals, he preaches the doctrine of moderation
in funerals. He possessed a core set of non -negotiable
principles known as the Ten Triads, but he applied
them dynamically based on context. Ah, I see.
The research refers to this as a contextual consequential
framework. He doesn't just blindly apply a rule.
He adapts his methodology to maximize the actual
tangible collective benefit in that specific
unique situation. Precisely. And it's crucial
to distinguish this from modern moral relativism
or situationism where there are no overarching
truths. Moody's adaptability was strictly and
unbreakably tethered to his ultimate defining
goal, universal love and the concrete elevation
of societal welfare. So if we apply this Mohist
flexibility to our medical bot dilemma. Right.
If a slight carefully bounded deviation from
absolute transparency, like the bot utilizing
a conversational. or simulating empathy to build
crucial rapport directly results in a terrified
patient taking life -saving medication, Monsi
would likely argue that this action serves the
higher principle of righteousness. The deception
is a tool used exclusively for the collective
benefit, not for the exploitation of the user.
Wow. That fundamentally changes how we might
think about programming future systems. If we
look past our current narrow AI models, the ones
just predicting the next word, and look toward
the development of artificial general intelligence,
or AGI. Systems that might actually possess genuine
autonomy and reasoning capabilities. Could they
be taught this? Could an AGI learn that rigid
robotic transparency isn't always the most moral
or beneficial choice? Could an artificial system
learn to navigate extreme ethical complexity
with the nuance, context, and ultimate dedication?
to human welfare of a Mohist sage? That is the
ultimate defining challenge posed by the author.
If an artificial agent is to ever become genuinely
trustworthy in the deep sense of cinchon, it
cannot operate merely on a fixed, unyielding
list of rigid programming rules. It must possess
adaptive ethical reasoning. It needs situational
discernment. It must be capable of recognizing
when absolute brutal honesty is required to prevent
harm, and when a socially beneficial minor friction
or deception serves a much greater moral good.
Which brings us back beautifully to the interfaith
covenant concept we discussed earlier. If we
want to build algorithms that support and strengthen
rather than continuously erode and destroy our
social fabric, we need them to operate almost
exactly like covenantal partners. We need algorithms
that are deliberately structurally designed not
to optimize for the raw lizard brain engagement
of an information cocoon. Those cocoons just
isolate religious, cultural and political groups
into increasingly angry radicalized echo chambers.
We need algorithms engineered to actively extend
the virtue of inclusive care. Exactly the point.
When the algorithms underlying social media create
those deeply polarized information cocoons, they
are not just showing us different ads. They are
actively mathematically corroding the baseline
conditions necessary for human empathy and interfaith
dialogue. They algorithmically amplify the most
extreme voices and aggressively filter out the
moderate, nuanced reality, creating terrifying
caricatures of the other. If we are ever to achieve
true covenant and pluralism and societal stability,
in the digital age. Our technological extensions
must be re -engineered from the ground up to
facilitate ethically conditioned reliance across
those boundaries. We don't just need better code,
we need algorithmic covenants. Let's pull all
of these complex threads together and synthesize
this incredible journey. What does this all fundamentally
mean for us? The recovery of Cynshin proves that
it isn't just an archaic academic word for believing
your employees will do a good job. No, it is
a demanding, rigorous, and profoundly biological
ethical It demands that when we extend our minds
and our agency through technology, those tools
must pass two impossible tests. First, they must
be perfectly reliable, undistorted transmitters
of reality. And second, they must be active amplifiers
of our highest moral virtues and collective welfare.
Right now, when we look clearly at the statistical
hallucinations of language models and the deeply
cynical profit -driven polarization engineered
by corporate tech monopolies, our current AI
landscape is failing both of those tests miserably.
The essential takeaway here is a mandatory profound
shift in our perspective. We have to stop viewing
AI alignment purely as a technical software problem.
Something that Silicon Valley can quietly fix
with a larger data set or a clever new line of
code. We have to recognize this moment for what
it truly is. A profound crisis of institutional
design, deeply misaligned economic incentives,
and a fundamental failure of moral delegation.
The next time you download a new app and casually,
thoughtlessly tap, except on a 50 -page terms
and conditions document, or the next time you
feel your blood pressure rising and your anger
spiking because of a perfectly targeted post,
an algorithm decided to slide into your feed,
I want you to pause. Take a breath and ask yourself
a structural question. Is this specific tool
operating as a virtuous, trustworthy extension
of my own mind? Or have I become the tool, the
smartphone cattle, being quietly milked for someone
else's astronomical profit? It also only comes
down to a question of agency and awareness. Are
you the sovereign individual extending your reach
out into the world? Or are you the one being
reached into and manipulated? I want to leave
you with a final thought to mull over, building
on everything we've unpacked from this research
today. In the technology sector, everyone is
obsessively focused on the Turing test. We are
constantly debating whether a machine can successfully
imitate human intelligence, whether an LLM can
flawlessly fool a human in a blind chat box.
But maybe, inspired by the rigorous framework
of a 2 ,500 -year -old philosopher named Moody,
we are aiming at the wrong target. Maybe we should
be striving toward the Zinchen test. The ultimate
milestone for our technological evolution won't
be the day an AI can seamlessly, deceptively
convince us that it's a living human being. The
real milestone will be the day when an artificial
intelligence and the vast corporate architecture
that controls it can consistently, verifiably
prove it possesses a moral compass reliable enough
and a commitment to collective human welfare
strong enough to act as a true, faithful extension
of our own conscience. Until that day comes,
keep your eyes wide open. You can absolutely
use the hammer, but whatever you do, do not outsource
your virtue.