AI Insights Dataset Analysis

AI Insights Dataset Analysis
Colleen McKenzie and J. Bryce Hidysmith
1 AI Insights Dataset Analysis
1.1 Overview
This dataset collects a list of discoveries essential to the development of the current generation
of artiﬁcial intelligence. We trace this development back as early as we have records of relevant
intellectual progress—in this case, to Ancient Greek philosophy—looking for the foundations of
complex new approaches.
Our goal in this project is to present an alternative to an achievement-based timeline of AI de-
velopment. The development of new capabilities in machine intelligence frequently produces ex-
citing tangible results, which dominate public conceptions of progress and are well-remembered
in histories of the ﬁeld, but such results are not always the product of novel technical insight.
Some new abilities rely more on recombination of existing tools or on additional computational
capacity—sufﬁcient to solve complex problems efﬁciently, but not necessarily the most direct pre-
cursors of new tools for further recombination, or of new directions for future work without ad-
ditional increases in computational efﬁciency. Our aim is to augment the current discourse of
historically grounded forecasting by adding a speciﬁc discursive thread that tracks theoretical
discoveries alone, complementing the more capability-focused accounts.
We’ve collected metadata about each discovery (and its discoverers) and looked for trends
in their production. Our own ﬁndings are described below, but we encourage extension and
additional evaluation of the data, and will publish our own ongoing work here.
1.2 Methods & Assumptions
Our metric for what constitutes an insight is an estimate of how novel or surprising the results of
that insight are, using a comparison of LSTM and RNNs as a baseline—that is, given that RNNs
exist, how surprising is the development of LSTM? All discoveries that seem equally or more
surprising were included in our set. This is one of many possible thresholds for signiﬁcance we
could have chosen, and the rationale behind ours is subjective:
Our focus on theoretical progress means that the data do not include progress captured in
implementing an existing theory, or applying it more directly. For example, punched-card pro-
gramming of early computers had clear impacts on the progress of computing, but we attribute
the insight behind that technology to the 18th-century textile worker who developed a punched-
card method for programming looms. From this perspective, the application of punched cards to
electrical computers is a combination of existing theories, not a new development in itself.
We consulted two existing chronicles of the history of AI in an effort to ﬂesh out parts of our
data set that may have fallen in our blind spots: - Nilsson, N. J. (2009). The quest for artiﬁcial
intelligence. Cambridge University Press. - Crevier, D. (1993). AI: the tumultuous history of the search
for artiﬁcial intelligence. Basic Books.
1
A few additional notes on the data:
•First to discover, not ﬁrst to publish: We credit an insight to the ﬁrst person known to have
described it, as best we can determine through reputable sources, not the ﬁrst person to
publish that description. This practice is motivated in part by our understanding that not all
discoverers published work in the academic tradition (e.g. William Newcomb, credited with
the conception of Newcomb’s problem), and in part by some discoveries’ having been kept
conﬁdential, pre-publication, in corporate and state departments.
•Speciﬁc vs. general discoveries: Sometimes an early discovery constitutes a special case of a
later, more general discovery; in this case, we credit the more general discovery. If the special
case itself seems to constitute an inﬂuential insight, we’ll credit it as a separate line item; but
if it was largely ignored, or was unavailable to discoverers of the more general version, we
omit it from this list. For example, ideas from evolutionary biology have been rediscovered
independently by AI researchers through simulationist and purely rationalistic investigation
that were previously discovered empirically through biological ﬁeld research before being
formalized in such a manner that they could be used by AI researchers. We count the usable
formalization, rather than the case studies that could be used as raw material for specifying
the usable formalization.
•Hardware agnosticism: Our focus here is on information theoretical insights, not on in-
sights that aid in the development of new hardware, the rationale being that artiﬁcial in-
telligence is a substrate independent pursuit, provided that the Church-Turing thesis holds.
Futher, charting the history of today’s electronic computers alone would constitute a project
of roughly equal magnitude, and one that aligns less closely with our area of expertise.
1.3 Data & Parameters
The full dataset (as json) and its schema are available at mediangroup.org/research ; this section
provides a brief overview of the data for readers of this report.
The set includes 193 total insights.
For each insight, we record the following information (plus sources for each fact):
•Name
•Year of discovery
•First work in which the insight was referenced or published
•Discoverer(s)
•Institutional afﬁliation of discoverer(s) at time of discovery (if applicable)
•Institution(s) sector and type (see below)
•Nation of origin of discoverer(s)
•Additional notes
Institutions are assigned rough sectors and types from the following lists:
Sectors:
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•Academic
•Military
•Industrial
•State
•Other R&D
•Religious
•N/A
Types:
•Public university
•Private university
•For-proﬁt entity
•Non-proﬁt entity
•N/A
1.4 Analysis
For the purposes of this ﬁrst analysis section, we will discuss the data as we have been able to
make it available to us. Reﬂections on the limitations of the data and the extent to which they are
relevant to readership follow in the Methodological Reﬂections section.
1.4.1 Temporal distribution
3
At a glance, the distribution of insights over time shows an expected uptick in progress con-
temporaneous with the European Enlightenment, followed by a sharp increase in the pace of
discovery at the beginning of the 20th century.
A view of only the most recent centuries provides more detail on the arc of recent progress,
showing a signiﬁcant increase in production with introduction of digital computers available to
major institutions in the late 1940s.
4
A breakdown of insight discoveries by decade clariﬁes the changing rates of discovery.
Historical context The uneven distribution of insights correlates clearly with the trajectory of
Western intellectual and economic history. The theological and philosophical conservatism of the
middle ages matches the ﬂat section of the ﬁrst curve above from c. 500 - 1500 AD. During the mid-
dle ages, there was no sense of how economic or political advantage might be gained from the use
of power not derived from human, animal, or natural sources (e.g. waterwheels applied to rivers).
The media of the middle ages, too, was meant for interpretation by individual human minds, as
opposed to instantiation on larger groups or in artiﬁcial substrates. For example, medieval al-
chemical texts were written with the expectation that the text is exclusively human-readable, and
so the informational payload of the text is found not within the structure of the text as an object
itself, but in the interpretation and implementation of the text by its human reader; this can be
contrasted with the periodic table, which describes a structure already present in nonhuman sub-
strate. This norm continued throughout most of the Enlightenment, perhaps reaching its height
during the efforts of the Encyclopedists led by Denis Diderot.
The philosophical ideas throughout the 18th and the ﬁrst half of the 19th century provided
the foundation for a scientiﬁc community able to take action during the industrial revolution, but
the industrial revolution itself provided the necessary material tools for developing automation
systems capable of directly realizing political, economic, or scientiﬁc goals. The technologies of the
industrial revolution, including the social technologies of the factory and the joint stock company
developed immediately prior during the late Enlightenment, differed from previous technologies
in that they contianed implicit instructions for their operation that were not simply transformations
of a source of physical power such as a horse’s muscles. A joint-stock company’s organization can
be thought of as a primative attempt at a superhuman intelligence implemented on a collection of
individual human beings.
5
The transition to automated systems that lacked a human in their control loop was the ad-
vent of the Jaquard loom (captured in our data as an earlier insight by Basile Bouchon). Earlier
automata in the West, the Muslim World, and China, were limited to toys, and their effects lim-
ited to the thought that they inspired in their viewers. The Digesting Duck, an automaton from
eighteenth century France that crudely pretended the metabolism of a waterfowl, is as inert in its
physical effect on the world as a child’s toy truck or Michaelangelo’s David except by inspiring the
behavior of human agents. The automata of the industrial period became actors in their own right.
The Jaquard Loom or a modern 3D printer takes a machine-readable instruction and produces an
effect that is as physically relevant as if it had been accomplished by human labor.
Though automation systems capable of acting as intelligent agents in their own right, rather
than replacements for physical labor, could have been developed in the 19th century through the
work of Babbage and Lovelace, the uses of cryptography and automatic aiming systems for ar-
tillery during the Second World War provided the industrial basis for their maturation. Blechley
Park’s work in decoding the German Enigma code was perhaps the ﬁrst instance when compu-
tation at a scale not accomplishable in an individual human mind was required to counter an
existential threat to a major power. Previous efforts in state computation by actors such as the
US Government during the censuses of the 1870s and 1880s provided valuable technological pre-
cursors, but these calculating and tabulating machines were not true computers in the modern
sense. Cryptographic and cryptoanalytic efforts during the wars provided the centralization of
capital required to produce an abstract automation system in the form of Colossus, the ﬁrst dig-
ital programmable computing device. Such an automation system that processs and transforms
information rather than simply taking an instruction to produce a physical effect is obviously re-
quired for the development of modern artiﬁcial intelligence. We must further conjecture that the
invention of programmable digital computing devices was required for the psychological con-
ditions necessary for individual scientists and engineeers to experiment in the ﬁelds that would
eventually birth artiﬁcial intelligence. There was only one Turing, publishing his basic princi-
ples of computability in On Computable Numbers (1936), but there are an uncountable number of
individuals able to experiment with the machines derived from these basic insights.
The massive upward trend in insights following the end of the Second World War can thus
be attributed to access to modern computing machines following their invention, as well as the
incentivization of computer science and artiﬁcial intelligence research instrumentally by the states
locked in conﬂict during the Cold War for purposes of military advantage. Artiﬁcial intelligence,
like any intellectual pursuit undertaken as more than a recreation by those with leisure time and
intrinsic interest, advances at pace with its support by institutions tasked with the necessities
security and prosperity.
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The distribution of insights from the beginning of the Cold War to the present shows only a
marginal deceleration after the fall of the Soviet Union, compared to the roughly linear rate of
increase at the beginning of the Cold War. The shallower slopes of curves in the mid-1970s and
the late 80s through early 90s correspond to the two periods now described as AI winters, when
progress slowed.
The former of these two periods appears to be a more substantial decline in insights we mea-
sured. We expect this effect is a result of the 1970s being a period of application and combination
of existing insights to new problem areas, without substantial generation of additional insights, in
addition to the effect of decreased AI-related research during this period.
As Nilsson puts it:
“Until about the early 1970s, most AI research dealt with what Seymour Papert called ‘toy’
problems. . . .However, soon after, AI efforts began a deﬁnite shift towards applications work, con-
fronting problems of real-world importance. . . .One reason for the increasing interest in applica-
tions was that the power of AI methods had increased to the point where realistic applications
seemed within reach.” (Nilsson, 207)
7
1.4.2 Geocultural distribution
(Note: data for “Russia” includes insights produced by Soviet scientists born within Russian
borders and working at historically Russian institutions.)
The distribution of insights by nationality of discover reﬂects a number of well-understood
trends in intellectual history. Ancient Greece provided the intellectual foundations that England
and France then built upon during the Enlightenment, before the rise of Germany as it indutrial-
ized and centralized politically.
During the twentieth century, the rise of both the Russian and American superpowers corre-
lated to substantial advances, but the United States dramatically outcompeted the Soviet Union.
Some of the gains that could be credited to the Soviet Union if one assumes a model based on
spheres of inﬂuence are marked as Hungarian in origin, as well as a few other countries such as
Moldova that did not make it into the top ten. The United States’ position as an aggregator of
immigrants and refugees from Europe during and after the Second World War substantially in-
creases the number of entries counted as American. The circumstances that made such devices
available were not only economic but also politically strategic, as the political aims of military
supremacy by both the United States and the Soviet Union during the Cold War enabled their
local markets to distribute said computing machines. Additionally, given that the state of Israel
was not established until 1949, entries there only date to that time, though many of the scientists
who immigrated to Israel and established the scholarly communities that contributed to AI efforts
originated in Soviet or American territory.
8
1.4.3 Institutional distribution
9
The vast majority of insights in our dataset, unsurprisingly, were discovered and devel-
oped by individuals at academic institutions. Early progress in mathematics and the sciences
was due mostly to unafﬁliated individuals—including most researchers from antiquity and the
Renaissance—but as academic institutions gained prestige and resulting brilliance, they began to
outcompete other institutional types.
Two trends stand out in the latter part of the 20th century: the increase in output from nonaca-
demic R&D institutions, and the slight increase in insights derived within military institutions.
Nonacademic R&D includes institutions such as Bell Laboratories and the RAND Corporation,
and appears in our data ﬁrst in 1947 (an attribution to Bell Labs’s John Tukey). Bell Laboratories
(or Bell Labs) was an unusual institution, in historical context, and in many ways the ﬁrst of its
kind: a result of a step-function increase in the engineering progress needed for telecommunica-
tions infrastructure, Bell Labs was incubated within the monopolistic Bell Telephone Company
before its 1984 dissolution after a successful antitrust suit. Within it, researchers such as Shannon,
Shockley, and Hamming developed some of the core advances of their ﬁelds, and it has continued
to produce novel research for decades: the most recent insight to come out of Bell Labs, in our
data, was from 1995. The RAND Corporation, in contrast, was developed in response to state
ofﬁcials suggesting potential beneﬁts from private involvement in relevant research areas, and
RAND itself developed out of an aircraft company, becoming a separate, nonproﬁt institution in
1948. While insights from RAND represent a shorter timespan in our dataset, limited to just the
decade between 1950 and 1960, they outnumber those from any institution besides Stanford and
Princeton universities, well-known powerhouses of AI development, by the present day. Dynamic
programming (Bellman) and symbolic AI (Newell, Shaw, and Simon) are notable among its body
of production.
The relative scarcity of of military institutions in our data suggests a more indirect role due to
military involvement. The development of artiﬁcial intelligence is deeply entangled with military
concerns, but miliary institutions seem to have been sources of demand for progress, not sources
of progress itself. DARPA, for example, often contracted independent entities such as SRI or teams
of collaborating academics to execute on ﬁnding solutions in its areas of interest. We note when
such entities were afﬁliated with military institutions, though few such instances occur in our
data.
10
A ﬁnal note on the breakdown of insights among institutional entities: while the credit owed
to academic institutions is clear, nonacademic institutions have been contributing an increasing
portion of total progress since the middle of the 20th century. We were surprised to see a near
even distribution of insights between for-proﬁt and non-proﬁt entities—though RAND Corpora-
tion constitutes the bulk of the latter—in recent decades, and we suppose that this supports the
importance of ongoing invesment in independent organizations focused on AI whose mission is
explicitly aligned with public good.
1.4.4 Methodological reﬂections
Our methods generate a view of the past through a particular cultural lens—speciﬁcally, that of
young American computer scientists. This project is not an attempt at the impossible task of ag-
gregating all insights into artiﬁcial intelligence that exist, rather it is an attempt from our position
to aggregate the ones interpretable to ourselves. As we are roughly in the same position socially
as other artiﬁcial intelligence resarchers in the Anglosphere, we expect that the amount of insights
accessible to Anglosphere researchers will be analagous to those accessible to ourselves. There
may be other paths to artiﬁcial intelligence development that are only accessible to individuals
with differing social position, technical knowledge, or linguistic and cultural proﬁciency. Though
it is certainly likely that such paths exist, we can make no comment on their rate of advancement.
Additionally, it seems prudent to make note of the likely presence of survivorship bias: we are
limited to only the information that has survived to the point of being accessible to ourselves. It
is possible that many of the insights of the past that we have analyzed—particularly the distant
past—were developed with the aid of information sources that no longer exist, either dead with
the minds that generated them or lost with the documents that once preserved them. As with any
ﬁeld, this lost information may compromise the ability of individuals in the present to correctly
11
interpret and use past insights. This case of survivorship bias is unavoiable, and mitigatable to the
degree that present researchers remain aware of it. Related work on this topic is available from
Samo Burja of Bismarck Analysis, in his essay Intellectual Dark Matter .
12


The Professional's Dilemma

The Professional's Dilemma

Alan, the executive director of a small nonprofit, is sitting down to dinner with his family.

Responsibility weighs heavily on Alan. It's nearly time to reapply for a grant that's been his

organization's largest source of funds. Alan has carefully cultivated a relationship with Beth, the

program officer for the foundation funding the grant. Beth knows and likes Alan, and is excited

about the work he's doing. If Alan's organization applies for a grant to continue their existing

work, it will almost certainly be approved. But Alan isn't sure what to do.

In the past few months, it's become increasingly clear that his fledgling organization's main

program - the one they were able to write grants for - isn't the best fit for the needs of the people

it's supposed to serve. A bright young intern, Charles, proposed a new program that, as far as

Alan can tell, would be a better fit both for the team and the people they are trying to help. On

the merits, it seems like Charles's idea is the right thing to do.

Alan could, in reapplying, explain the limitations of the existing program, and why the new

program would be better. But that would rock the boat. It would mean challenging the very story

that got last year's grant. There's no guarantee Beth would like the new idea. No one else has

done it. There's no track record to point to.

Alan thinks of what might happen if the grant isn't approved. He'd have to lay people off, good

people, and his organization might not survive. Even if it does, he'd have to take a pay cut,

maybe move to a house in a less expensive neighborhood, pull his kids out of school. It's not

certain this would happen, but can he afford to take that chance?

Let's look across the dinner table at Alan's wife, Dana. If Alan tells her about his dilemma, what

do we expect her to feel. What would be the safe option? Disclosing the potentially unsettling

truth to the funder in the hopes of being able to do better work in the future? Or smoothing

things over, tweaking the existing program to try to patch some of the worse gaps, and muddling

on? What will feel to her like the responsible choice for Alan to make, for his family and the

other people depending on him?

In most cases we should expect Alan's wife to feel safer if Alan keeps up appearances. And

that's why vast swathes of our professional society are underperforming their potential: because

playing it safe means covering things up.

Can organizations ever support new ideas?

An organization that's funding outside parties to accomplish certain goals (e.g. a charitable

donor or foundation giving to charities) generally won't fund ideas, even ideas from those people

who are both famous and established experts, unless those ideas start off with a critical amount

of their own money attached.

Either the idea has to be spearheaded by someone who has enough personal funds, or it has to

have raised enough money from donors/investors who no longer have the in-practice authority

to dictate decision making.

(For more detail on this, see Samo Burja’s essay

Borrowed versus Owned Power

. Borrowed

power is granted conditionally -- if your charity is given a “donation” under the condition that you

continue to make the donor happy, that’s borrowed power. If you have the money in your own

personal savings account, or if the charity raised it from so many small donors that none of them

are entitled to make demands about how you spend it, that’s owned power. Borrowed power is

always weaker than owned power.)

It's not generally considered "credible", by big donors, that an initiative will be effective enough

to be worth funding unless the initiative has managed to cross a certain threshold in terms of

acquiring resources.

Moreover, if the grantee meets that threshold, gets funded, and does a good job with that

money, this doesn't necessarily "unlock" disproportionately more resources from the big donor;

the grantee will still have to hustle the same amount, or nearly so, to get the second grant.

They're still running on borrowed power; they still need to keep looking over their shoulder,

worrying about what the funders might think.

The usual paradigm says “if you don’t already have owned power, we’re not going to give you

any owned power, only borrowed power.” A funder won’t give you autonomy; if you don’t

already have autonomy, you don’t deserve it. This means that nobody can gain autonomy

through convincing donors that they should have it. You can only gain autonomy by

taking

it,

surreptitiously, from people who don’t want you to have it.

We know it's possible to do better than this, because this paradigm would never have allowed

the Manhattan Project to get funded. Einstein didn't come with his own money; he was merely a

renowned physicist with a credible proposal. Somebody in the government had to literally

believe his claims that a specific thing that had never been done before could be done.

This kind of belief is crucially different from the sense usually used when we talk about believing

in someone, in that it is about the trusted person's relationship to their field of expertise, not their

relationship to the person trusting them. Not everyone can evaluate every idea, but if a person

reaches a certain threshold of expertise, eminence, reputation for honesty, etc., the funder has

to be able to come to believe that the

content

 of their ideas is more likely than baseline to be

valid and worth pursuing.

As a funder, you have to be able to

believe someone

 -- not everyone, but

someone

 -- when they

say an initiative is worthwhile, enough that

you

 are willing to take the initiative to make it

possible, and you don't expect to regret that decision. Otherwise,

you are not looking for

ideas outside your institution

. You are not a "hub", you are not reachable, you are just doing

your thing with no outside input.

Another way of putting this is that funders need to be able to see potential grantees as

peers

.

Organizations having "friends" -- other organizations or consultants/free-agents that they trust,

are mission-aligned with, and communicate openly with -- is often considered unprofessional

("incestuous"), but is actually a good thing! There needs to be someone outside you (or your

org) whom you trust to be well-informed and value- aligned.

Without the capacity to process genuinely new ideas, it's less effective to have grantees than to

just have employees and decide everything top-down. If you're doing something in a

decentralized fashion, it should be because you actually

value

 the decentralization -- you want

to get an outside perspective, or on-the-ground data, or expertise, or something.

Principal-Agent Problems

How can the principal (the funder) trust the agent (the grantee)?

Most of the incentive systems in the what we hear about in charity are rather primitive; it boils

down to "demand more documentation and proof from grantees."

This is primitive because it tries to

enforce

 honesty by spending resources on detecting

dishonesty, which can be very costly, relative to other ways of incentivizing honesty. It's not

even asking the question "what's the most efficient way to get the grantee to tell me the truth?"

The aesthetic underlying this attitude is called authoritarian high modernism; just trying to add

metrics, not even engaging with the fact that metrics can and will be gamed. The people who

survive in positions of power in such a system are not the ones who naively try to answer

questions they're asked as accurately as possible; they're the ones who keep up appearances.

Conversely, when interacting with someone who keeps up appearances and who has survived

in a position of power in such a system, there is common knowledge only ‘professional’ efforts

will be supported, and that ‘professional’ efforts are efforts that don’t freely reveal information.

You

can

 enforce quality control in a top-down fashion if you have an impartial investigative

process and an enforcement mechanism, but who investigates the investigators? Who judges

the judges? Ultimately somebody has to WANT to give an honest report of what's going on. And

those impartial investigators have to be incentive-aligned such that they

benefit more from

being honest than lying

. Otherwise, even if initially most of the investigators are highly

selected for honesty, by organizational maturity, all will have been selected for ‘discretion’.

To get honest reports, you need a mechanism designed in such a way as to systematically favor

truth, much like auctions designed so the most advantageous price to bid is also each person's

true price. How do you do that?

How to solve the problem

Let's work through a concrete example: Suppose you're considering giving a grant to a

charitable organization. They send you a budget and ask for a dollar amount. How can you

incentivize them NOT to pad the budget?

For instance, if they expect that they might be able to get this grant but they'll have a hard time

getting a second grant, they have a strong incentive to ask for enough money up front to last

them several years, BUT to say that they need it all for this year.

This will happen UNLESS they have reason to believe that you'll frown on budget-padding, BUT

are willing to look favorably on orgs that do well in the first year for subsequent grants.

This requires opening up lines of communication MUCH more for successful/trusted grantees

than for random members of the public or arbitrary grant applicants. It needs to be POSSIBLE

to earn your trust, and for that to unlock a certain amount of funding security. Otherwise,

grantees

must

seek funding security -- for themselves, their families, their employees, their

charitable work -- because without doing so they won’t be able to do their job at all. They'll seek

it through deceiving you,

because that will feel like, and will actually be, and will be seen by

all observers to be, the responsible thing for them to do

.

If you make it seem like "nobody should be able to count on my support, I'll keep 'em on their

toes", they'll find something else they can count on, namely your ignorance of how their project

works. The agent ALWAYS knows more than the principal about the operational details of the

project! They can always keep you in the dark more effectively than you can snoop on them.

So you have to make earning your trust p

ossible, empowering

 and

rewarding

. You can of

course revoke those rewards if they betray your trust, but ultimately you have to be much less

suspicious of your trusted friends than you are of randos. Yes, this means you take on risk; but

the grantees ALSO take on risk by being honest with you. It's symmetric.

Here’s one common failure mode in the conventional paradigm: you can't appear competent if

you reveal the truth that something in your project isn't working at the current funding level and

needs more money. You can't seem "needy" for money, or you'll look incompetent, and you

won't get the money. So instead you try to get the money by inflating your accomplishments

and hiding your needs and trying to appear "worthy."

This is counterproductive from the funder's point of view. As a donor, you want to give money

where it'll do the most good. This means you need accurate info about what it'll be spent on. But

the grantee doesn't necessarily trust you to believe that what they

actually

 need money for is

worthy.

For a well-known instance, many donors think operational costs are "waste", so charities fudge

the accounting to make it seem like all donations go to program expenses, and

still

 underspend

on operational costs like paying their employees.

Or, sometimes part of a charity's actual budget is somewhat unsavory, like bribes to officials in

corrupt countries being a necessary cost of actually operating there.

Or, some costs can be embarrassing to admit, like the costs of learning/mistakes/R&D, if there's

a perceived expectation that you have to get things right the first time.

So the onus is on the funder to make it clear that you want to know what they ACTUALLY need,

what their REAL constraints are, and that you will not pull the plug on them if they have an

awkward funding crunch, once they have earned your trust to an adequate degree.

It has to be clear that CANDOR is an important part of earning your trust. In particular, it needs

to be clear enough to the

third parties

 in the life of the individual you're funding, that being

honest with you will pay off, that

they

 pressure the grantee to be more honest with you, the

funder.

How does their family feel? Is the

spouse

 of the charity's executive director nagging them to be

more honest when fundraising, because that's what'll put their kids through college? Because, if

not, you can bet their spouse is nagging them to be

less

 honest while fundraising, to squeeze

more money out of the donors, because that's the responsible thing to do for their family.

What about their other dependents -- employees, collaborators, beneficiaries of charitable

programs -- would THEY put pressure on the executive director to be more forthcoming with the

funder? Or would they say "squeeze those rich morons harder so we can keep the lights on and

help people who need it?" (Or, perhaps, more discretely but synonymously, "don't make waves,

jump through the hoops they're asking you to jump through and tell them what they want to

hear.")

People don't exist in a vacuum; they want to gain the esteem and meet the needs of the people

they care about. We have to be not only rewarding honesty - not only rewarding honesty

more

than smoothing things over - but OBVIOUSLY ENOUGH rewarding honesty that even third

parties know our reputation. Otherwise

everyone who tries to be honest with us will receive

a continuous stream of pressure to stop being so irresponsible

.

"Why are you favoring a rich guy or a huge foundation over your own family and an important

cause?" It's a fair question! And you need to flip it on its head -- you want everyone to be asking

"Why are you forgoing HUGE OPPORTUNITIES for your family and an important cause, just

because you're too insecure to be candid with a rich guy?


Toward A Working Theory of Mind

Toward A Working Theory of Mind This is the first in a series of essays that are meant to lay out the models I’ve developed over the course of the last seven years of my practice. “My practice” is a coaching and guided self development technique, and much of its efficacy relies on the model of mind I use to generate introspective queries. Working with specific assumptions about the basic capacities of mind allows me to note when someone seems to be operating at less than full capacity, and to launch a targeted investigation into why, so that we can work in a structured way toward reclaiming capacity and spurring growth. This is especially helpful in cases where the person feels they’re at a natural ceiling, as it gives us kind of second opinion to work with instead of accepting felt limitations as absolute. While I find the model extremely functional as a framework, I don’t believe it to be at all the last word on the nature or structure of the mind. True accuracy in this domain would be a tall order. I like to tell people that the domain of psychology is all observer effect—the mind is an extremely pliable thing, and this fact combined with the fact that it must be its own observer makes it especially inclined to appear to behave in whatever way one happens to believe it will. Nevertheless, it’s possible to refine theory via application, even in psychology. Applied models of mind can easily generate interface structures that temporarily confirm an incorrect model, but a practice that fails to produce stable and significant experiential and behavioral change must ultimately have its underpinnings revisited. The model that I use now has been developed and clarified by years of application. Its ontological claims are still deeply philosophical in nature—in the limit, they are as much the domain of theology as they are of psychology—but insofar as I have been able to test and develop them practically, I have done so. This is not meant to be a theological document. The framework is merely meant to provide a reference against which one can check one’s psychological position. As far as I am concerned, the truest metric in life of a person’s mental health and internal alignment is the degree to which they are successfully manifesting their desired state of the world. I have found that all purely psychological models of mental health and spiritual advancement are vulnerable to a kind of abuse that I have become very wary of: it is extremely tempting, in a world as difficult as the one we live in, to aim for dissociation and call it enlightenment. Dissociation can come in many different aesthetic skins—irony, positive thinking, yogic bliss, universal love, stoicism—but it is the same de-correlation of psychological state from reality in each case. It can be a very attractive option when it seems that the only other option is the despair and volatility that arise from attachment to the world—in fact, it can be difficult to see how anything other than some form of dissociation could constitute mental health.
 I believe in the possibility of healthy investment in the world. It is what I want for myself and for everyone I work with. The framework that I am about to lay forth, however, offers a purely psychological model of what is possible for a human mind, and makes no claims about what counts as a good state of the world. This makes it vulnerable to the kind of abuse I mentioned above. If you are inclined to take psychological or ethical or spiritual models as your primary prescription—if you are the kind of person who seeks gurus or ideologies, secular or otherwise, in order to attain a moral state irrespective of any material state—please go away. My work is not an invitation to dissociate. It is an invitation to terraform your world. Without further ado, 1. The Fundamental Nature and Ontology of the Mind Let’s start off with something you’ll have heard many times before: that your experience of the world is self-created. You can know that you are experiencing sensations and interpreting them as a tree or a house or a chicken, but you have no way of knowing what the things you’re seeing and hearing and touching actually are, or indeed whether the sights or sounds or feelings actually correspond to anything outside of you at all. The experience of a chicken is an imposed interpretation on a field of sense data. Introductory cognitive science classes like to demonstrate this fact by drawing attention to the ways that interpretations can change or break—for example, simple optical illusions like the Necker Cube provide very mild examples of the way a set of sensations can be multiply interpretable. The examination of processing disorders like aphasia can tell us interesting things about how our conceptual constructions are composed by showing us what happens when different parts of a person’s ability to perceive or interpret sensations break down. You may have encountered a TED talk at some point by Jill Bolte Taylor, a neuroscientist who experienced a stroke and described the experience of losing her ability to interpret her sensations. For Taylor, this was something of a religious experience. This makes sense—many of the forms of enlightenment that meditation traditions pursue include (or just are) the realization that the interpretations are imposed on the sensations, rather than the world actually objectively being the way the person interprets it. “Maya”—the Hindu concept of Illusion—is the interpretation assumed to be reality. The basic ideas of the constructed nature of experience and the unknowability of what’s beyond it are ancient. All good philosophers note the fundamental inability to know that there is anything outside of their experience as their base epistemic position.
 The framework I use in my practice makes distinctions between a few fundamental aspects of mind that provide me with a basis for modeling what is constructed in experience and how. Let’s run through them: The awareness is just experience. You could theoretically have awareness with no sensations, which might be similar to what people imagine the experience of nothing to be—though this would not actually be the experience of nothing, because the awareness would experience itself, and the awareness itself is not nothing. You can’t actually experience nothing. Awareness is not constructed by the mind; it is there whether the mind is constructing interpretations or not. The sensations are experienced by the awareness, but it’s important to make a distinction between the sensations and the interpretations of the sensations—for example, “hand” is not a set of sensations, it’s an interpretation imposed upon some colors and temperatures and proprioceptive data. The colors and temperatures and proprioceptive data are the sensations. You could imagine an awareness that experienced those colors and temperatures and proprioceptive data but did not interpret them as a hand, or as anything. In some sense, the experience of completely uninterpreted sensations might also be similar to some idea of the experience of nothing—you might think of it as “pure noise,” except that even “noise” is a concept, and so the evaluation of the uninterpreted sensations as uninterpreted would not be part of that experience. The question of whether the sensations are constructions of the mind is the same question as “does any of this exist or am I hallucinating all of it?” This is an impossible question to answer with certainty. I happen to believe that sensations do in fact correspond to realities that are (at least partially) independent of the observer. I think it may be the case that all sensations correspond to some reality that is partially independent of the observer, even the imaginations—imaginations may just be very heavy conceptualizations of relatively minimal sets of sensations. That is, the difference between the visual perception of an elephant and the imagination of an elephant may just be that the concept “elephant” is being used to interpret light hitting your eyes after reflecting off of an elephant in one case, and being imposed on a very minimal set of random visual and/or proprioceptive sensations in the other case. In the first case, the sensations being interpreted as “elephant” correspond (potentially) to an actual elephant, and in the second case they are merely part of the default sensation landscape of the body, and it is the body’s state that they correspond to. The concepts are that with which you interpret the sensations. In this document I’m going to talk constantly about concepts, interpretations, models, beliefs, and constructs. These are, roughly speaking, all the same stuff. A concept is like “hand” or “tree” or “house” or “government”; a model is a complex, dynamic, structured interpretation of a dynamic data set, e.g. a model of economics, or a model of your mother. These will be contextually
interchangeable, but sloppily speaking my typical usage will be something like—a concept is analogous to a word, a belief is analogous to a sentence and a model is analogous to a book. An interpretation is the use of a particular concept or set of concepts to parse sensations—just as we can theoretically think about about sensations separately from concepts, so too can we think about concepts separately from sensations. Actually, as a pedantic aside, I’m not sure we can literally do that—I work with the assumption that the use conditions for a concept are its application to a set of sensations, and so in order to think about “a concept distinct from sensations,” you must be applying that concept to some set of sensations. The sensations can be extremely minimal—some people who think the thought “a concept distinct from sensations” might generate a visual representation of a conceptual framework in empty space, while others might merely refer to points in proprioceptive space, likely without even noticing they’re doing so. It can certainly seem that nothing is happening except the summoning of the concept, but I currently believe that, even in the least visual, least audial, least verbal thoughts, there are sensations involved in summoning and manipulating the concepts. While it may not be possible to actually think “concept” without applying the concept of a concept to some set of sensations, it is possible to apply the concept “concept absent sensations” to some set of sensations! More importantly, I do believe there is a sense in which we have the concepts even when we’re not applying them to sensations. Which is to say, you’re not reinventing the concept of a rabbit every time you encounter the set of sensations that are best interpreted as “rabbit.” It was there, in some form, ready to be applied. The conceptual content is the construction of the mind, and the way that sensations under-determine their interpretation is what things like the Necker Cube illusion are meant to demonstrate. Most people vastly underestimate the space of possible interpretations of the world around them. Let’s try something: pick a nearby object, like a tree or a pillow. Try imagining that it’s a rabbit. Don’t squint your eyes or imagine that it looks different; just apply the concept “rabbit” to it. Now, try interpreting it as your mom. Now, interpret it as trying to kill you. Now interpret it as secretly dancing. Isn’t it odd that you can do this? Yet you can. Normally, we would think that a person who believed a pillow was their mother or a tree was trying to kill them was insane. I believe that most of us are this insane—that we are misinterpreting the world around us to a comparable degree on a constant basis. But we are only likely to notice our misinterpretations when they diverge wildly from the interpretations of those around us, or when we are so surprised or make an error so obvious that we are forced to re-examine our models. Let’s call the application of conceptual content to sensations the engagement of that content. To engage the concept of a rabbit—that is, to think “rabbit”—one applies the concept “rabbit” to a set of sensations (perhaps a visual image, perhaps light bouncing off a rabbit and
hitting your eyes, perhaps the slight physical memory of something warm and fuzzy, or perhaps to a toothbrush if we’re having some trouble that day or happen to be tripping balls). If one does this consciously, this is attention. One does not have to notice that one is applying concepts for the concepts to be applied. You might drive from home to work, deeply absorbed in some line of thought about a presentations you’re going to give that afternoon, and arrive at your destination with detailed anticipations about how your presentation will go but no memory of the drive. Nevertheless, you were engaging many complex models outside of your attention—your model of the route, of traffic laws and driving hazards, and of how to operate the car, not to mention your models of how to coordinate your body—not only how to sit and move the gear gear shift and the steering wheel but how to breathe and digest and regulate your body temperature and heartbeat. Which models of how to regulate your body you were engaging probably shifted as you thought about standing up in front of everyone and talking. The models you’re engaging outside of your attention are still models, many of them in formats far away from verbal representation, but, I believe, fundamentally no different from your models of the content of your presentation. Attention is a critical idea because attention is what allows you to intentionally change a model. Concepts are formed, shaped and changed by their application. Learning is the formation and changing of concepts. Thus, if you want to improve a concept or a model, you have to obtain its application conditions—that is, you have to use it. If it is to change, it has to be given the opportunity to take new inputs. And if you want to direct the change, you have to figure out a way to get the model in attention. A model’s application conditions are not always easy to obtain; figuring out how to get something into attention is a big part of my practice. We’ll come back to this idea in more detail later. In addition to the conceptual structures themselves, it seems likely that there are constraints on or features of concept formation that aren’t properly categorized as concepts—meaning, they guide or are part of the conceptual formation machinery, but are not produced by and cannot be edited by that machinery. Time and space are likely “built in” in this way, rather than being the products of parsed sensations. It’s possible that there are other “built in” features of the conceiver—things that would be necessary features of all concepts or features of the structure that concepts are built in. I don’t believe that I know what all of these are, but I do believe that one of them—one that is absolutely critical to understand—is Purpose. Purpose/Goal/Telos/Good Concepts are formed for a purpose. This is something that I think modern cognitive science understands only locally and shallowly, and that many of the meditation traditions that
track the constructed nature of experience miss altogether. Cog sci will take a concept like “snake,” note that it’s constructed somehow from visual primitives that pick out a wavy line in a visual field that takes straight lines as default, and make a guess that it’s important to prioritize the recognition of snakes for evolutionary reasons. While that last bit is something of a leap, this is a functional explanation—i.e., the idea is that the concept is formed for the purpose of survival—and so to my mind it has a leg up on a bunch of the nirvana/moksha-seeking traditions, which will say something closer to “the snake is an illusion; let go of your attachment to the snake.” This is bullshit; don’t be a California Buddhist. The snake is an illusion—that is, you are constructing your experience of it—but you have conceptual machinery for a reason. But the reason is not fundamentally survival. If you have to explain all human behavior, survival by itself is pretty unsatisfactory as a motivation. You can sort of do it, at a stretch, and people often try, explaining altruistic behavior as motivated by a species-level survival drive, homosexuality as a glitch or as an obscure form of pro-sociality that somehow contributes to species survival, suicide the same, the purchase of expensive fashionable clothes as an expression of the drive to propagate one’s own genes forward in time. You’d have to do something a little fancier, I think, to explain behaviors like those of terrorists who want to wipe out the human species altogether as expressions of a survival drive, but people have definitely tried. You could take other things besides survival to be the fundamental driver. For many years, I believed that the sole fundamental motivation of mind was to connect to other minds. If you do this, you can do similar antics as one does when trying to cash everything out in survival. I used to be especially focused on explaining violent and manipulative behavior as contorted connection drive—sometimes correctly and sometimes less correctly, as it turned out. That’s its own story, but suffice it to say I’ve updated away from that position. Whatever you choose as a theoretical base motivation, you’re going to have to jump through some hoops explaining the entire space of thought and behavior and preference according to that motivation, because the space is in fact complex and convoluted and full of apparent contradiction. The alternatives to positing a unified fundamental motivation are to posit a fundamentally fragmentary set of drives, or arbitrary motivation. People will often try to explain human motivation as mimetic and/or fully stimulus response, where we can class the action of a fully mimetic mind as a kind of stimulus response, but I hope it will be self-evident why fully environmentally determined motivation and fully imitative motivation are incoherent ideas. We can also discard arbitrary motivation, because clearly there exists some pattern to thought and behavior and preference. As for the option of fundamentally fragmentary drives—for example, the idea that there is a sex drive and a death drive and both exist as incommensurable primitives in the mind, always in competition—all I can say is that I have
never found two apparently separate behaviors or preferences to in fact be based in fundamentally separate or incommensurable drives. If you take someone who on the one hand wants to live and on the other hand wants to die, I predict—and I expect to be right—that the “part” of them that wants to live is focused on one set of information, and the “part” of them that wants to die is focused on a a different set of information. Those sets of information are compartmentalized, which results in functionally separate and conflicting impulses, but they can be de-compartmentalized—and once that happens, some more basic motivation will flow through the combined information landscape and output a coherent and non-conflicting set of preferences. What is the more basic motivation? I don’t know. It is the goal—it is the telos, the will, the fundamental drive; it is value; it is Goodness. Good is only ever coherently definable in terms of the desire of an agent; of the Good, all I can say is that there is that which the agent fundamentally desires, and it is in essence a unified whole. And, since we are discussing not a model of an individual mind but a model of the invariant features of mind in general—a model that is meant to stand independent of individuation or embodiment—the claim is not merely that the individual human has a fundamentally unified or unifiable will, but that at the most fundamental layer, the Goal or the Good is invariant across minds. This is an extremely strong claim. It is not, however, a particularly unusual one—many spiritual traditions make similar claims, usually articulated more fuzzily, along the lines of “we are all one.” But “we are all one” is an extremely strong claim if taken seriously, and can lead people to do really, really stupid and dangerous things. An astounding amount of complexity and divergence can arise from a single algorithm that processes varied inputs, and we will explore that complexity and divergence in depth as we go. For now, just know that the claim of the universality of telos is not an invitation to treat—or to value—everyone the same. So, we have a model of mind—awareness containing sensations, sensations interpreted by concepts, concepts composed within a structured framework and in service of a fundamental Goal. I believe that the ability to make and think through the distinctions laid out above is extremely important, for reasons that will hopefully become clear later in this document. To enable ourselves to make those distinctions, we’ve defined the elements of our ontology, and we’ve clarified our understanding of the elements by imagining them separately from each other—awareness without sensations or concepts, sensations without concepts, and concepts without sensations. In reality, I don’t know which if any such separations ever occur. The idea of sensations or concepts as mental phenomena without awareness is incoherent (in the way that the idea of a thought without a mind is incoherent), so we can rule that one out. Some meditators speak of achieving states of “pure awareness,” where they are not interpreting their sensations
and/or not experiencing sensations, and have no will or desire but “just are.” I believe it’s possible to turn one’s attention away from sensations, and I believe it’s possible to dissolve and/or inhibit the application of many, many of one’s conceptual constructs. I don’t believe, however, that it’s actually possible to turn off the will, and I also believe that while all of what people are typically cognizant of as their conceptual content is probably dissolvable, the generator of conceptual content is not. So my actual model is something more like, there exists the “fabric of mind,” which is the awareness-will, which irrevocably contains the parser/conceptualizer/creative apparatus, and through which sensations pass and are responded to by that apparatus in accordance with the will. \* \* \* \* \* Before we continue any further, I want to note something really important: if the model I’ve stated is correct, then your sole purpose in this world is to navigate your way toward what you want—sole purpose not in a moral sense, but in a determinist one, in that if the model above is correct, any idea of morality on which you might have that mission or any other was generated by the function structuring your model of the world in order to pursue your Goal, and thus is superseded by that function. It is not possible to do other than pursue what you want, but there is a truth about what you actually want, and a truth about how to get it, and it’s quite possible to be ignorant or wrong on both counts. We’ll come back to that. Onward. 2. Mind in Environment Think of the model articulated above as a kind of base. These are claims about invariant features of mind; they tell us nothing about any specific aspect of individual or cultural psychology. You won’t get from this model to Oedipal complexes, bipolar disorders, anxiety or depression, childhood trauma, or any of the other structures people typically associate with psychology. Those things are all the result of the mind interacting with an environment. The model of mind outlined so far is so minimal that the description does not even assume it is implemented in a brain; however, if we put that mind into the brain and body of a cat, or a human girl, or an 18th
century French aristocrat, it now has an environment—not merely the environment that the body of the cat or the girl or the French aristocrat inhabits, but the body itself. 1 The body is in some sense the most fundamental part of the mind’s environment, in that it generates—or at least populates—the sensorium. The eyes take in visual sensations, the ears take in auditory sensations, the skin takes in touch sensations, etc. In addition to whatever information is being taken in by the perceptive organs, there is a ton of sensory information corresponding to internal states of the body—the feelings of blood flow, digestion, hormone release, muscular activation and coordination, immune response, etc. Imagine the mind we described—the awareness-will with its creative conceptual apparatus—now flooded with the experience of all of these sensations, and ready to conceptualize them. How is it to do this? Part of the answer is “pattern recognition.” When people talk about pattern recognition, they mean that something is recurring in nature, and it is possible to notice the recurrence. If we are imagining a newborn infant mind conceiving its environment (which, remember, includes its body) we might pick out the combination of the mother’s face plus some warm snuggly feelings as a stably recurring phenomenon. Pattern recognition can’t be the whole story, because pattern recognition ex nihilo is impossible. Computer programs designed to recognize patterns in large data sets must start with some initial set of concepts, some initial dimension or set of dimensions along which it is possible to organize data. If nothing else, it must start with the concept of pattern, some idea of “same” or “match” and some concept like “dimension” (way of matching). Our pattern recognition machinery—the conceiver described in the first section—might have enough “built in” constraints or features of the type we discussed in the first section that conceptual possibility space is fairly determined: put two minds in the world and they will roughly conceptualize it into categories like air, water, trees, animals, parents, etc., absent any other constraints and regardless of whether they can communicate with each other. However, with a conceptual apparatus as minimal as the one I posited earlier—time, space, and Purpose, plus this idea of similarity or recognition—that kind of over-determination seems pretty unlikely. The “Purpose” idea could load a lot of constraints into the parser, but I don’t believe it does. I believe the fundamental drive is so minimally (or broadly) defined that it For now, in order to play with the idea of the mind described above interacting with the body, we are 1going to speak dualistically. Mind-body dualism is the belief that the mind and the body are separate phenomena, with mental phenomena being non-physical and the body and the material world being a separate sphere. I don’t actually believe mind-body dualism, but for the moment it will be cleaner to speak of the mind and body as though they were separate, in order to posit an order of conceptual operations that would be too hard to think about if we started out behaving as though there were no distinction.
doesn’t even have an idea as complex as biological survival. Any function or goal of the body that pertains specifically to the body must on this model be construed as a feature of the mind’s environment. Good as experienced and interpreted through the body is an order more complex than the Good that inheres “fundamentally” in the mind. So it is not just the way that the body generates the sensorium that creates the mind’s environment, but also the body’s functions—things like digestion, reproduction, sleep. These provide constraints on the way that the Good can be pursued, and thus constraints on conceptual formation. The interface between the body’s functions and the mind’s experience is the phenomenology. You experience things pleasure and pain, satisfaction and dissatisfaction, attached to physical experiences like hunger, tiredness, and arousal as the body goes through different states. The mind as described in section 1, minimal parser guided by goal, would not form the concept “food” absent a body; the mind parsing the landscape of sense data that includes simultaneously the smells and tastes and textures of edible substances and feelings of hunger and digestion, co-occurring in a regular way with the experiences of pleasure and pain—that is, tagged as salient—is much more constrained and will reliably construct “food” concepts. You might have noticed a messy implication of this ghost-in-the-shell kind of model: the idea is that the mind has its own goal, and the body has its own goals or at least functions, and these hook up somehow, such that the embodied mind knows that the body’s functions are relevant to or necessary for its goal. Where and how does this hook-up occur? I have no idea as to the details, but the analogy of a car seems apt to me: a car is constructed to be relatively intuitive to the driver that occupies it. Some learning is necessary, different cars are all slightly different, and if a driver has the skill he to do so can customize the car’s internal workings (you’ve probably heard of people training themselves to accomplish strange and usually impossible physical feats—Wim Hof and David Blaine come to mind). However, to avoid responding with the unsatisfying shrug that generally accompanies the mind-body problem, we would have to leave our dualist working simplification, and that is a different topic. So we’re just going to have to bear with our rather implausible ghost in the shell for now. Let’s go back to our infant learning to conceive of his mother and the warm snuggly feelings that accompany her presence. We’ll call this concept Mom + Warm Snuggliness. This is actually a terrible articulation of the idea I’m trying to convey, because linguistically it preserves mom and warm and snuggliness as separate ideas. This is not what’s happening conceptually for our infant. Instead, try to imagine that the infant is forming a concept that tags the entire swath of sensations that accompany his mother’s presence: the visual sensations that correspond to the mother’s face, the temperature sensations that correspond to being held, the proprioceptive and textural and affective sensations that correspond to the release of oxytocin (contentedness,
sleepiness), the olfactory sensations corresponding to her body and physical state and the baby’s own physical state, and more. This concept isn’t nearly as clear as the abstraction indicated by the word “mother”—it’s a single conceptual mashup of a person (though perhaps without the concept of person), the feeling of love and connection, a set of physical states and feelings and actions, etc. I believe this is how early concept formation works. Further distinctions get drawn later, as the different elements of the experience occur and are noticed separately from each other. However, the basic concepts that underpin our more intricate and abstract conceptual structures are deep conflations of the external and the internal. There is no particular reason to start out with the idea of “external” and “internal;” one simply starts with the sensory field, and must parse the sensations in whatever groupings they seem to occur. By the time we are using concepts with verbal correspondents like “mother,” we are working many layers of abstraction and distinction beyond our earliest conceptual foundations. Not only is the normal idea of “mother” a far more specific and distinct occurrence in the sensorium than entirety of the set of sensations that correspond to her presence, the set of sensations that are in fact specific to “mother” are not in the sensorium at all times—that is, her continued existence when she is not sensorily present is an inference. “Mother” as a distinct entity is therefore an abstraction from experience—far more abstract than the earlier concept I tagged Mom + Warm Snuggliness. If this is how concepts are formed, then our most basic and visceral understandings of the world are very different from our verbally communicated concepts, containing what we would consider many strange conflations and disjunctions. If, for example, the base concept that contains (some of) the feelings that later get abstracted into the concept that gets verbally tagged “love” is a concept like Mom + Warm Snuggliness, then really, some semblance of an Oedipal complex might be nigh unavoidable—not because of perversion but merely because of the conditions of the concept’s construction. On the other hand, not all concepts are built in direct reference to clusters of sensory phenomena; some concepts are constructed in reference to something that other people appear to be referring to. When a toddler is told by his mother to be polite, “polite” doesn’t refer to a concrete set of sensations the way that Mom + Warm Snuggliness does; “polite” refers to something mysterious that his mother seems to want. Politeness may well come to be associated with a physical state—whatever physical state garners or coincides with positive feedback from his mother—but the initial referent of the concept was not a naturally arising correspondence between the physical state and/or affect and the world, but rather the apparent desire of another entity. That is, the concept formation was not directly guided by the evaluative apparatus of the child—the one guided but his own Goal—but was indirectly guided by the evaluative apparatus of someone else. This would not occur if the child’s evaluative apparatus did not value the other
person’s evaluation—or, perhaps more likely, their happiness or approval—but nevertheless it is a very different order of operations. Thus, as far as we are concerned with how the mind structures itself in response to its environment, we must consider other people and their evaluative frameworks to be critical features of the environment, potentially vastly more weighty than the physical features of the environment in terms of the mind’s architecture. What is likely to be more salient to a child’s evaluative apparatus—the color and texture of the carpet, or his mother’s pleasure and displeasure? For most children, certainly the latter. The parents’ attention directs the child’s attention, and later the child’s friends and teachers direct the child’s attention—which means that whatever is directing their attention is directing his attention. Since we are talking about the ways that psychological structure is determined by the body and the ways it is determined by the social environment—essentially questions of nature or nurture—we should briefly touch on the question of genetic determination. Let’s just explore a couple different ideas of how this might work. You could imagine several different mechanisms, and the fact that a whole host of personal tendencies is extremely likely to be “inherited” from the parents via the attentional direction just described above makes it difficult to tell whether, when we observe what appear to be familial features of a person’s psychology, we’re working with information directly encoded in the body or information transmitted at high fidelity in early life (where early life includes the prenatal environment). On this model, remember, information encoded in the body is still classed as a feature of the mind’s environment, so we’re essentially asking what are the different parts of a mind’s environment that information can come from. If, for example, certain conceptual structures are encouraged or inhibited by chemical tendencies of the body (e.g., testosterone or serotonin production), then what we have is a mind parsing an environment in which phenomenological warmth or relaxation or excitement or whatever else is produced by the chemical tendency co-occurs more or less frequently than average with externally generated sense data, and must be simultaneously explained. That is, mind’s experience of the external world is always being correlated with its experience of the body, and the experience of the body can be genetically influenced, though obviously not fully genetically determined. I have worked with people who appear to access genetic or ancestral memory in the course of introspection—I have seen, for example, one woman appear to recover a memory of what she believed was her grandmother’s village getting bombed in a war that happened before she was born, and I myself have found what appear to be highly specific and fairly ancient cultural models of deportment influencing my behavior. I believe it’s possible to genetically encode fairly complex situationally contingent “plans”—things like, for example, ketosis—and one could imagine an aggressive ketosis contingency encoded into genetic plans as a result of an
ancestor experiencing famine. However, I think that for a modern person’s ketosis contingency to be psychologically associated with the experiential details of the potato famine of 1845, there have to be some non-physiologically encoded attentional things going on. In any case, I have never encountered particularly strong evidence of this kind of thing drastically shaping someone’s psychological structure independent of familial enculturation. One final complicating factor in the nature versus nurture question is that, in addition to the kind of attentional direction we saw in the politeness example, I believe children also learn physiological regulation from their parents, especially their mothers, especially pre- and post-natally. So a physiological tendency that strongly influences the child’s interpretive landscape might be genetically encoded, but might also be learned from physical contact with the parent. For many psychological “family traits,” I think that a wide variety of positions in this nature-and-nurture space are equally plausible causal candidates. I have no ideological attachment to one over the other. Many people who prefer nature-type explanations do so because they are concerned about responsibility being unfairly allocated to those who can’t help their genetic inheritance, or because they want to prove that some group is terminally better or worse than some other group. Conversely, many people who prefer nurture-type explanations prefer them because they want to believe in the power of good parenting or education or therapy to equalize or uplift everyone. To me, nurture does not indicate ease of change—trauma can be insidious in its structuring of the psychology, and those who cling to their fears may as well have been born with them written into their bones. On the other hand, I have no real reason to believe that genetic inheritance is indelibly fixed. Encoding is encoding, even at the physiological level, and if it can be accessed, it can be informed. To me, tractability is less a question of nature versus nurture, and more a question of how early a structure was built or implemented (since this determines how much has subsequently been built on top of it, dependent upon it or patterned on it), how much a person wants to and believes they can change, and how much of the environment around them can be brought to incentivize change by making it evidently the “fit” thing to do (i.e., conducive to the achievement of the Goal in that environment). Having addressed to the extent we can for now the question of nature versus nurture and, broadly speaking, collapsed the two ideas into the broader idea of “environment,” let’s go back again to that idea. Our idea of the mind’s “environment” is unusually broad, including the body, the surrounding physical environment, and the other people it interacts with—everything that produces sense data. Yet we’ve still neglected a critical feature of the mind’s environment: its own conceptual structure. The parsing of the environment affects the environment via the actions it prescribes for the person, and thereby also affects what the mind will encounter in its environment. As the mind builds up conceptual structure, the application of that conceptual structure causes it to recognize things in the environment—i.e., see what it has seen before. And,
as the mind pursues its Goal via the conceptual structure it builds, seek what it has sought before. Thus the conceptualization of the sense data becomes self-reinforcing. This is why the early conceptual structure has an outsize effect on the state of the mind: it is the “parent” of later conceptual structure. As the mind conceptualizes its sense data, it creates its own environment, making it familiar and navigable, but also frequently entrapping itself in the process, as it builds more and more structure that is templated upon early error. We now have the beginning of a basis for a model of structured psychology—the specific sets of sense data provided by the mind’s environment that it then conceptualizes, 3. Agents and the Development of Internal Conflict Earlier, I made a big deal of asserting that the mind’s fundamental drive is unitary. But it seems obvious that within individual people there are different, often conflicting drives. How would it come to be that in a mind with a unified goal, we would experience both the desire to stay in a relationship and to leave it, or the desire to diet and the desire to eat, or the desire to make money and the desire to stop working? The answer lies in the distinction between the Goal and the subgoals that the mind develops in the process of conceptualizing the environment. Internal conflict arises from the fact that distinct subgoals do not necessarily know about each other or know how to share information. They may not know that they are ultimately working toward the same end, or agree about how to get there. In the same way that the reasons behind a foreign cultural practice can be opaque to an outsider, so can one function of the mind be opaque to another function. In some cases, this opacity can even be intentional, either because one part of the mind does not want to understand another, or because it does not want to be understood itself. In other cases, the problem is merely one of failure to communicate. To get a better understanding of this idea of subgoals, let’s go back to our baby with its Mom + Warm Snuggliness concept. Actually, this is not just a concept—it’s a subgoal: something that the baby has conceptualized because it has recognized in the experience a pattern relevant to its Goal. The baby now has a conceptual structure directing its will that not only recognizes Mom + Warm Snuggliness but seeks or anticipates it, and responds with action or impulse when it encounters it. In order to be able to seek and anticipate Mom + Warm Snuggliness, it must be that the conceptual structure (model) pertaining to the subgoal is more complex than just the subgoal itself. It must contain not just the concept of the subgoal but also conceptual structure representing the ways that other things relate to it, e.g. the conditions under which it is more or
less likely to occur (perhaps time of day), or the conditions under which it is more or less important to attain (perhaps hunger versus satiation, or wakefulness versus sleepiness). In this particular example, the action or impulse that occurs in response to the anticipation of Mom + Warm Snuggliness is fairly subtle; perhaps the baby relaxes. But you could imagine a different structure where the person had an extensive model of playground status dynamics, which contained among other things a subgoal like “pursue justice” and concept like “bully,” such that upon recognizing a bully (i.e., applying the concept to a situation where it seemed to fit), the person would punch the bully in the face. I think of this entire structure as a function. The function is the will being channeled through a dynamic conceptual structure (a model) toward a conceptualized aspect of the Goal (a subgoal). The function takes inputs in the form of sense data, parses them in accordance with the conceptual structure, and produces outputs in form of impulse, action, emotion, and/or thought. Outputs may also include amendments to the conceptual structure. I believe that individual functions of the mind come into being where Goal-relevance is perceived in the environment, and conceptual structure is built to pursue that aspect of, or apparently necessary step toward, the Goal. That aspect or step is the subgoal; the function is that which pursues the subgoal. (From here out, I will drop the term subgoal—a function will have a goal and the mind will have its Goal.) Frequently, it makes sense to refer to such functions as agents, or parts of the person. To some of the people reading this, the term “part” will sound familiar from their work with Internal Family Systems, or IFS, which is the only therapy style I’ve encountered that explicitly ontologizes the mind as a multi-agent system, although many others do so implicitly/occasionally/to varying degrees. (If you’re interested in the IFS ontology, you can read more here). To me, the term “part” usually represents the personification of a function; I like to use it when I’m interacting directly with a “part” of someone or otherwise describing it as though it is a person. In other cases, I like to use the term “function” because it emphasizes the idea that the individual function is part of a more general system, rather than being a fundamentally separate entity. And I like to use the term “agent” when I want to capture the idea of intentionality in a way that the term “function” doesn’t, but want to remain impersonal-sounding so as to seem abstract and cool. Anyway. Now that we have a clear idea of agents/functions/parts, we can look at the conditions under which they come into conflict. Let’s start with a “simple” case, by which I mean a case in which there is no intentional obfuscation, merely a failure of communication. Earlier, I made the analogy between a conceptual model and a book. This is actually not a great analogy for several reasons. For one thing, a book is static, while a model evolves as it is applied, and even begets “offspring” as new situations are encountered that can be parsed with
elements of existing models. For another thing, a book is meant to be read. A model is meant to be applied, but is not necessarily formatted to be understood or communicated. Thus, a person can end up in a position where they seem not to be able to “access” information they know they have. Imagine someone trying to eat healthy. She “knows” she should eat vegetables, but she craves ice cream instead. So we have two functions at work here—one that wants vegetables and one that wants ice cream. Let’s think about the differences between these functions’ models. In some sense, the two models contain very similar information—at least, they purport to model the same domain. The function that wants the ice cream probably has a model of the caloric and chemical content of both ice cream and vegetables, formatted as an understanding of how they taste and how it will feel to eat them—their felt effects on the person’s energy levels and digestion, and the emotional states associated with those. The function that prescribes vegetables probably also has a model of the the caloric and chemical content of both ice cream and vegetables, formatted more abstractly, perhaps recalled as visual/audial imaginations—perhaps a memory of a conversation the person had with her mom or a health article she once read. (The latter function’s model may not be very precise—it might be as simple as “ice cream is fatty and sugary and vegetables have nutrients and vitamins.” But even in the case where the person is counting calories and tracking specific nutrients, it’s worth noting that the abstract model of the caloric and chemical contents of food is almost definitionally nowhere near as detailed as the model generating the craving.) So, two models of the caloric and chemical contents of food. To expect to be able to use the ice cream-craving function’s model to write down the chemical composition or number of calories of the ice cream, however, is obviously ridiculous (at least without training). In that sense, the information in the model of ice cream that generates the craving is not at all the same information as the information in the explicit model (the one that wants the person to eat vegetables). Both models contain descriptions of ice cream, but the formatting of the information is so different that the two can only be said to be the same information in a very abstract sense. Simply put, they’re not. However, the two functions are attempting to model the world and produce action in the same domain, and thus are coming into conflict. The vegetable-prescribing function can’t “talk to” the ice cream-seeking function, because when it says “that ice cream doesn’t have any nutrients,” the ice-cream seeking function not only has no idea what it’s talking about—it may have no idea that it’s talking at all. So the person tells herself, “I should eat vegetables,” and this affects the status of her ice-cream craving not one iota. You could imagine her integrating the two models, building a translation between them by creating a highly detailed mapping between her sensory experience of food and her explicit understanding of nutrition. (You could even imagine her getting good enough to be able to
approximately guess a food’s caloric and nutritional content from taste and digestive feel.) In the world where both parts shared similar goals or recognized the validity of each other’s goals, this would resolve the conflict—the person might crave ice cream, then be able to propose the idea of vegetables to herself via visceral imagination, at which point the craving might shift. Or perhaps she might get a feeling in response to the visceral imagination of eating vegetables that she could understand as “no, I’m not really hungry, I just want to feel comfort right now.” At that point she might decide to that comfort was a good idea, and eat the ice cream without feeling guilty about it. Or, she might be able to counter-offer with something healthier but equally comforting. If the relationship between the two parts is good enough that both recognize the Goal-relevance of each other’s goals, and her counter-offer is good, the counter-offer will not only be acceptable but may present as viscerally superior to the part that was previously craving ice cream, since it will value attaining both comfort and health. Such successful communication between parts, however, depends on their willingness to understand or attend to each other’s information, and/or value the achievement of their goals. You could easily imagine a person with a pair of functions similar to the ones we just described, except where the vegetable-prescribing function strictly cared only about following an explicit set of nutritional rules and didn’t care about the other function’s nutritional models or desire for comfort. This version of the vegetable-prescribing function instead would actively ignore and do its best to override all of the other function’s signals. Obviously, in this scenario, the communication channel we imagined above would never get built. Imagine yet another variation: the vegetable-prescribing function is willing to make some allowances for ice cream cravings, but only where they’re properly justified. Imagine that it only gives the green light to eat ice cream if it’s been a really, truly hard day. Now imagine that the ice cream-craving function is experiencing a certain type of hunger and wants the sugar and fat that the ice cream contains, but has learned that it’s only going to get them if it can make the case that things are going sufficiently poorly. Now, when the person is debating with herself about whether to eat the ice cream, she finds herself imagining all the worst aspects of the day, dwelling on and amplifying the difficult parts, spending a lot of attention catastrophizing. This is happening because the available rationale for ice cream is determined by the constraints she has set on what counts as acceptable; the ice cream-craving function has an incentive to obfuscate its models, instead fabricating information that will pass a filter. Thus the possibility of accurate introspection is compromised. This kind of thing happens all the time. People who believe they shouldn’t ask for care if they’re healthy and able to care for themselves will often find themselves feeling mysteriously sick. People who believe they can only be loved if they’re sufficiently moral will fabricate altruistic justifications for their behavior that obscure their real reasons. A lot of internal
fragmentation—that is, the state of different parts of the mind being unable to share information, or more simply put, the inability of a person to know themselves—is created and stabilized by parts of the mind inadvertently setting up adversarial incentives for others, where both are vying to produce action in a shared domain. Setting up good communications between functions, however, can be easier said than done. A function with a directly adversarial relationship to another function is often configured that way because it came into being for the express purpose of fighting or compensating for the first function. Take our ice cream-craving function and our vegetable-prescribing function. It’s possible that the vegetable-prescribing function developed when the person read a book on nutrition and decided it would be a good idea to try to eat more healthily. I should mention, by the way, that calling these guys the “ice cream-craving function” and the “vegetable-prescribing function” is a silly simplification, and I’m not at all implying that ice cream and vegetables are their only or their primary goals. In the scenario we’re describing now, where the vegetable-prescribing function arises from an encounter with a nutrition book, it’s much more likely that the person already had an elaborate self-management and information-gathering function, and the plan to encourage herself to eat vegetables was a simple addendum developed by a function that knew how to seek and integrate a wide range of information into its plans. It’s also possible, however, that the vegetable-seeking function arose specifically in response to some terrible failure of the ice cream-seeking function. If the person’s cravings were pretty out of whack and generating some externalities that it didn’t seem to be able to take into account, and she found herself eating until she felt sick or gaining weight she didn’t want to gain, the second function might have come into being specifically to rein in the first. If this is the case, we can say that the ice cream-craving function is prior to the vegetable-prescribing function. The vegetable-prescribing function has the goal of being healthy, but is largely concerned with correcting the ice cream-craving function. If we see this, we know something about the responsive evolution of the person’s psychological structure. Psychological structure develops over time in response to perceived error or incompleteness in existing structure, when the mind observes its actions and forecasts its own failure to achieve its Goal. In my experience, common functional growth over time looks much like the branches of a tree—tapering from extremes into nuance as the person’s different functions get increasingly refined in their mutual compensation patterns. In some cases, people with deeper than average understandings of their own inner workings are able to more frequently understand and amend the original function generating an error rather than develop a separate compensating function, and so experience more integration and less “branching.” Dysfunctional development, on the other hand, is more “bipolar,” with the different parts of the mind each refusing to accept the
realities of the other and instead implementing more and more extreme compensations and repressions on both sides, until functional sustained action becomes virtually impossible. At this point, we have a working model of psychological structure, sufficiently detailed to allow a huge amount of navigation, correction and development. We have a base ontology of mind that lets us understand the distinction between reality and interpretation, and maintain an understanding of the commensurability of goals; we have the understanding of the interpretive apparatus building conceptual structure in response to its environment; and we have the understanding of that same interpretive apparatus building further conceptual structure in response to its projections of its own behavior in its environment. This lets us understand the general pattern of psychological genesis, and, with good introspective training, also lets us trace the genesis of a specific psychological structure, which lets us understand its subjective environment and primary concerns, its checks and balances, and thus positions us to be able to communicate with it in a targeted manner and help it develop positively. Please use these models gently—don’t over-impose them where they don’t actually seem to fit, and don’t expect to be able to immediately solve all your problems with them. Building relationships takes time and care, and applying these models well means building strong relationships, with anyone you are trying to understand but especially with yourself. Bon V oyage!