Expertise and the Fragmentation of Intellectual Autonomy C. Thi Nguyen (Note:	This	is	a	discussion	of	Elijah	Millgram's	book,	The	Great	Endarkenment:	Philosophy for	an	Age	of	Hyperspecialization.	This	article	appeared	as	part	of	a	symposium	discussion of	that	book,	forthcoming	in	Philosophical	Inquiries.	This	is	a	pre-print	draft;	the	final version	is	available	at	https://philinq.it/index.php/philinq/article/view/224	) Abstract In	The	Great	Endarkenment,	Elijah	Millgram	argues	that	the	hyper-specialization	of	expert domains	has	led	to	an	intellectual	crisis.	Each	field	of	human	knowledge	has	its	own specialized	jargon,	knowledge,	and	form	of	reasoning,	and	each	is	mutually	incomprehensible to	the	next.	Furthermore,	says	Millgram,	modern	scientific	practical	arguments	are	draped across	many	fields.	Thus,	there	is	no	person	in	a	position	to	assess	the	success	of	such	a practical	argument	for	themselves.	This	arrangement	virtually	guarantees	that	mistakes	will accrue	whenever	we	engage	in	cross-field	practical	reasoning.	Furthermore,	Millgram	argues, hyper-specialization	makes	intellectual	autonomy	extremely	difficult.	Our	only	hope	is	to provide	better	translations	between	the	fields,	in	order	to	achieve	intellectual	transparency. I	argue	against	Millgram's	pessimistic	conclusion	about	intellectual	autonomy,	and	against	his suggested	solution	of	translation.	Instead,	I	take	his	analysis	to	reveal	that	there	are	actually several	very	distinct	forms	intellectual	autonomy	that	are	significantly	in	tension.	One familiar	kind	is	direct	autonomy,	where	we	seek	to	understand	arguments	and	reasons	for ourselves.	Another	kind	is	delegational	autonomy,	where	we	seek	to	find	others	to	invest	with our	intellectual	trust	when	we	cannot	understand.	A	third	is	management	autonomy,	where we	seek	to	encapsulate	fields,	in	order	to	manage	their	overall	structure	and	connectivity. Intellectual	transparency	will	help	us	achieve	direct	autonomy,	but	many	intellectual circumstances	require	that	we	exercise	delegational	and	management	autonomy.	However, these	latter	forms	of	autonomy	require	us	to	give	up	on	transparency. Keywords Expertise;	autonomy;	social	epistemology;	trust;	testimony;	epistemic	dependence 2 In	The	Great	Endarkenment,	Elijah	Millgram	offers	a	vision	of	a	very	particular	sort	of intellectual	apocalypse.	This	apocalypse	is	due	to	the	onset	of	intellectual	hyperspecialization.	Human	knowledge	has	splintered	across	a	great	many	distinct	fields	of	inquiry. These	fields	are	mutually	incomprehensible	to	one	another	-	each	field	requires	not	only	its own	technical	jargon	and	specialized	knowledge,	but	its	own	specialized	form	of	reasoning. What	constitutes	a	good	argument	varies	radically	from	field	to	field.	Thus,	even	a	welleducated	expert	in	one	field	will	not	be	able	to	distinguish	real	experts	from	fake	ones	in another	field.	And,	if	it	isn't	already	obvious,	Millgram	thinks	that	this	apocalypse	has	already arrived. Hyper-specialization	presents	an	immediate	problem	for	anybody	who	hopes	to	achieve complete	intellectual	autonomy	-	that	is,	who	hopes	to	understand	and	control	all	the elements	of	their	beliefs	for	themselves.	Moreover,	the	crisis	of	hyper-specialization threatens	successful	practical	activity	itself.	This	is,	says	Millgram,	because	practical arguments	are	draped	across	a	large	number	of	hyper-specialized	areas.	A	single	argument for	a	particular	conclusion	("use	this	kind	of	shielding	in	your	nuclear	reactors")	has	premises in	one	field	(particle	physics),	inferences	from	those	premises	performed	in	another	field (chemistry),	and	then	conclusions	in	a	third	field	(nuclear	engineering).	Thus,	no	single person	has	control	of	all	the	steps	of	the	argument.	This	draping	of	arguments	across	fields gives	us	a	three-pronged	version	of	the	problem	of	intellectual	autonomy.	First,	says Millgram,	no	individual	can	understand	all	the	premises	of	such	a	draped	argument	for herself.	Second,	even	if	we	are	permitted	to	deputize	other	people	in	our	quest	for	knowledge, we	do	so	in	the	hopes	that	they	will	perform	as	we	would	have.	But	experts	in	different	fields go	about	their	intellectual	business	in	such	radically	different	ways	that	autonomous deputization	seems	impossible.	Third,	says	Millgram,	every	argument	has	defeaters,	and	as 3 we	extend	an	argument	over	many	fields,	we	lose	the	ability	to	recognize	when	an	argument has	met	a	defeater.	What	we	need,	says	Millgram,	is	to	manage	the	interface	between different	fields,	and	one	of	the	groups	best	able	to	do	this	would	be	analytic	philosophers trained	in	conceptual	analysis.	Such	conceptual	analysts	could	act	as	the	translators	between different	fields,	easing	the	problems	engendered	by	hyper-specialization	(Millgram	2015:	2744). I'm	going	to	assume	that	Millgram	is	right	about	the	basic	infrastructure	of	his	intellectual apocalypse:	that	there	are	distinct	fields	that	are	mutually	incomprehensible	to	each	other. This	means	that	an	expert	in	one	field	cannot	directly	assess	the	quality	of	an	argument	from another	field.	Are	there	other	means	by	which	we	can	still	come	to	trust	other	experts	and other	fields,	even	if	they	are	incomprehensible	to	us?	I	will	consider	Millgram's	three problems	separately,	and	will	offer	some	solutions	that	might,	when	considered independently,	ease	our	local	worries.	But	these	solutions	will	turn	out	to	run	at	crosspurposes	with	one	another.	Millgram's	account,	I	will	argue,	does	not	show	that	intellectual autonomy	is	impossible.	Rather,	it	will	force	us	to	realize	that	there	are	different	kinds	of intellectual	autonomy,	and	that	they	are	often	in	tension	with	one	another.	To	support	one kind	of	intellectual	autonomy,	we	should	seek	greater	intellectual	transparency	between fields.	But	other	interests	will	call	for	different	sorts	of	intellectual	autonomy,	which,	in	turn, will	call	for	the	opposite	of	transparency:	an	aggressive	compartmentalization	between	fields. What	we	learn	is	that	pressure	from	the	expanding	scope	and	complexity	of	human knowledge	has	fragmented	intellectual	autonomy	-	or	rather,	it	reveals	that	intellectual autonomy	has	always	been	fragmented.	In	the	past,	the	relatively	small	size	of	human knowledge	let	us	hold	onto	the	hope	of	achieving	of	a	unified	form	of	intellectual	autonomy. The	rapid	growth	of	the	sciences	forces	us	to	admit	that	there	are	different	forms	of 4 intellectual	autonomy,	that	they	are	in	tension	with	each	other,	and	that	we	must	sometimes choose	between	them. The	problem	of	expert	recognition How	might	we	hang	on	to	some	kind	of	intellectual	autonomy	in	the	era	of	hyperspecialization?	How	much	can	we	really	think	for	ourselves	anymore?	Once	upon	a	time,	we might	reasonably	have	hoped	to	achieve	direct	epistemic	autonomy	-	to	understand	all	the reasons	and	evidence	that	support	our	beliefs	entirely	for	ourselves.	But	the	size	of	human knowledge,	and	the	mutual	incomprehensibility	of	fields,	seems	to	make	direct	epistemic autonomy	impossible.	Complete	intellectual	independence	is	a	pipe	dream	in	any	world	with rich	domains	of	expert	knowledge	(Hardwig	1985).	But	perhaps	we	can	achieve	a	weaker kind	of	autonomy	-	call	it	indirect	epistemic	autonomy,	or	meta-autonomy	for	short.	Metaautonomy	is	a	weaker	requirement;	to	achieve	it,	an	agent	need	not	gather	all	the	evidence and	reasons	directly	for	herself.	She	need	only	autonomously	gather	evidence	and	reasons about	whom	she	ought	to	trust,	and	then	use	that	autonomously	generated	trust	to	filter information	from	the	various	purported	experts. Millgram	allows	that	such	a	distanced	and	indirect	sort	of	meta-autonomy	might	be	worth having.	Says	Millgram:	even	if	we	have	given	up	on	the	hope	of	absolute	epistemic	autonomy, perhaps	we	could	at	least	take	responsibility	for	the	choice	of	experts	(Millgram	2015:	2930).	But,	says	Millgram,	even	meta-autonomy	is	impossible	to	achieve,	since	you	need	to already	be	an	expert	in	order	to	successfully	locate	other	experts	(30,	44-8).	This	sort	of argument	may	be	familiar	from	recent	work	in	the	epistemology	of	testimony,	especially	in moral	epistemology,	where	it	has	been	called	the	credentialing	problem	(though	the	problem is	as	old	as	Socrates)	(Cholbi	2007;	LaBarge	1997;	McGrath	2011).	Here's	the	worry:	an 5 expert	is	marked	by	their	capacity	to	produce	good	arguments	in	their	field;	but	if	we	cannot tell	good	arguments	from	bad	in	some	field,	then	we	cannot	recognize	the	experts	in	that field.	So,	in	precisely	those	cases	in	which	we	truly	need	experts,	we	will	be	unable	to	find them.	And	surely,	in	the	era	of	hyper-specialization,	we	cannot	sort	good	arguments	from	bad in	distant	fields. I	will	argue,	contra	Millgram,	that	we	can,	in	fact,	achieve	certain	forms	of	metaautonomy,	but	that	achieving	it	involves	sacrificing	some	of	the	goods	that	are	traditionally associated	with	direct	intellectual	autonomy.	Let	me	sketch	what	a	reasonable	metaautonomy	might	look	like.	Suppose	that	I	have	no	expertise	in	a	given	field.	How	might	I	go about	finding	the	experts?	Experts	are	not	simply	the	people	that	produce	good	arguments; they	are	the	people	that	reliably	produce	good	results.	In	some	fields,	good	results	are	easy	to evaluate,	even	without	any	expertise.	Those	fields	possess	what	we	might	call	a	litmus	test	- a	success-condition	that's	recognizable	to	the	inexpert.	In	the	most	obvious	fields,	that	litmus test	is	applicable	on	an	individual	and	immediate	basis.	If	you	claim	to	be	an	expert	axethrower,	I	can	test	your	claim	by	handing	you	an	axe	and	indicating	an	appropriate	target.	Of course,	most	fields	are	more	subtle	-	the	expert	is	she	who	produces	a	good	result,	but	the proper	assessment	of	good	results	itself	requires	expertise.	And	pessimists	about	the possibility	of	finding	moral	experts	are	usually	quick	to	point	out	that,	while	many	empirical fields	have	a	clear	litmus	tests,	moral	expertise	does	not	(Cholbi	2007,	325-32;	McGrath	2011, 96-9).	(For	an	extended	discussion	of	litmus	tests,	and	subtle	and	obvious	fields,	see	(Nguyen 2018)). Surely	there	are	litmus	tests	for	the	more	straightforward	empirical	domains.	The	domain of	knowledge	concerning	skilled	axe-throwing	has	a	clear	litmus	test.	But,	just	as	surely,	there are	more	obscure	empirical	domains	that	lack	any	straightforward	litmus	tests.	Good	abstract 6 expressionist	painting,	good	proofs	in	number	theory,	and	good	work	in	particle	physics	are all	incomprehensible	to	the	layperson. Of	course,	such	fields	produce	their	own	internal	rankings.	One	can,	perhaps,	look	to	see who	the	good	economists	are	by	seeing	who	publishes	in	the	most	prestigious	economics journals,	or	has	won	the	Nobel	Prize	in	Economics.	But	this	simply	defers	the	problem	of expert	recognition	from	assessing	individuals	to	assessing	whole	fields,	for	now	we	have	to distinguish	pseudo-fields	from	legitimate	fields.	Fields	can	become	corrupted	and epistemically	wayward.	Think,	for	example,	of	the	experts	that	have	been	selected	and officially	licensed	by	Scientology.	(I	suspect	that	most	academics	would	be	willing,	over	a private	drink,	to	finger	certain	other	academic	fields	as	corrupt.)	But	there	are	ways	around this	problem.	First,	some	fields,	which	do	not	admit	of	individual	litmus	tests,	may	be amenable	to	field-wide	litmus	tests.	I	cannot	understand	the	individual	pronouncements	of an	aeronautical	engineer,	but	I	trust	the	field	of	aeronautical	engineering	in	general	because planes	do	not	generally	fall	out	of	the	sky.	Other	sorts	of	litmus	tests	are	possible	-	whole fields	have	been	discredited	when	top	journals	publish	purposely	fraudulent	gibberish (Millgram	2015:	32).	Some	fields	do	not	admit	of	individual	litmus	tests,	but	do	admit	of collective	ones.	And,	to	the	extent	that	these	fields	have	internal	procedures	for	ranking,	then trust	in	a	whole	field	can	lead	to	trust	in	that	field's	certification	procedures,	which,	in	turn, can	lead	to	trust	in	individual	experts.	In	this	case,	we	have	achieved,	not	direct	autonomy, nor	even	meta-autonomy,	but,	at	best,	meta-meta	autonomy.	But	at	least	that's	something. Furthermore,	though	some	fields	don't	lead	to	a	direct	litmus	test	-	theoretical	physics, for	example	-	we	can	still	perform	what	Philip	Kitcher	calls	"indirect	calibration"	(Kitcher 1993:	320-3).	Fields	overlap.	If	I	trust	the	engineers,	and	engineering	substantially	overlaps with	mathematics,	then	I	can	trust	the	engineers	via	a	litmus	test,	and	then	trust	the 7 mathematicians	via	the	engineers.	Nuclear	engineering	has	a	fairly	vivid	litmus	test,	and	the field	depends	on	the	results	of	theoretical	physics.	Thus,	my	trust	in	nuclear	engineering	can be	extended	to	trust	in	theoretical	physics.	It	may	be	that	some	fields	are	not	hooked	up	in this	way	-	that	they	are	cognitively	isolated.	But	Millgram's	primary	concern	is	with	fields that	do,	in	fact,	hook	up	with	other	fields	to	produce,	eventually,	practical	outcomes	-	so	the fields	that	Millgram	worries	about	are	precisely	those	in	which	indirect	calibration	to	a	litmus test	is	possible. For	a	linked	field,	you	don't	need	to	be	an	expert	to	have	some	reason	for	believing another	to	be	an	expert.	You	can	use	a	publicly	available	litmus	test,	and	then	trace	a	line	of trust	through	some	number	of	fields.	Why	does	this	matter?	Well,	it	depends	on	what	you wanted	out	of	autonomy	in	the	first	place.	If	your	goal	was	radical	and	total	intellectual independence	-	well,	then	Millgram's	surely	right,	and	you're	completely	out	of	luck	in	the modern	world.	But	suppose	your	goal	were	more	modest:	it	is	that	you	have	reasons,	of	some sort,	under	your	control	for	your	beliefs,	rather	than	having	to	adopt	them	out	of	unthinking obedience	(Nguyen	2010).	In	that	case,	indirect	calibration	and	litmus	tests	give	us	some reason.	If	the	contrast	class	to	intellectual	autonomy	is	intellectual	servility,	then	there	are more	and	less	intellectually	autonomous	ways	of	going	about	gathering	testimonial knowledge	in	a	hyper-specialized	world.	One	would	have	no	intellectual	autonomy whatsoever	if	one	simply	accepted	claims	to	intellectual	authority	at	face	value	without	any further	reflection	-	this	would	be	complete	intellectual	servility.	In	contrast,	achieving	some degree	of	meta-autonomy	is	surely	better:	one	could	conduct	a	reasoning	process	of	one's own,	in	which	one	thinks	about	the	litmus	tests	and	calibrations	and	comes	to	an	individual assessment	of	entire	fields,	and	then	trusts	those	fields'	internal	rankings.	And	such	a	process is	not	just	rote.	If	one	had	meta-autonomy,	one	could	actively	manage	one's	trust	in	other 8 fields.	One	could	come	to	reject	fields	for	failed	their	litmus	tests,	even	though	they	present themselves	as,	or	are	widely	believed	to	be,	good	fields.	Daphne	Miller,	for	example,	notes that	even	a	layperson	should	have	good	evidence	that	nutrition	science	is	not	a	trustworthy field,	simply	from	the	frequency	with	which	it	reverses	itself	and	condemns	its	own	recent declarations	(Miller	2008). Why	might	we	want	this	form	of	indirect	autonomy?	Perhaps	it	is	a	good	in	and	of	itself. But	one	might	also	think	it	has	practical	epistemic	value.	Philip	Nickel	has	suggested	that	one reason	to	want	intellectual	autonomy	is	adaptability	to	changing	conditions.	When	one simply	accepts	a	belief	on	authority,	one	has	no	grounds	for	adjusting	that	belief	as	conditions change.	If	I	simply,	for	example,	memorized	from	a	textbook	the	belief	that	egg	yolks	were bad	for	you	(as	was	generally	believed	a	few	decades	ago),	my	belief	wouldn't	update	as	new evidence	came	up	in	the	field.	Similarly,	as	Nickel	points	out,	if	I	go	to	a	moral	guru	and	get advice	about	a	moral	dilemma	I'm	in,	and	carry	away	a	simple	directive,	my	actions	won't respond	to	any	changes	in	the	situation.	Individual	contact	with	the	reasons	for	one's	belief provides	one	with	the	capacity	for	adapting	one's	beliefs	(Nickel	2001).	Notice	how	this	plays out	with	distanced	indirect	calibration.	Suppose	there	is	a	field	of,	say,	theoretical	Jungian macroeconomics,	which	I	had,	at	first,	trusted.	After	all,	there	are	whole	academic departments	that	specialize	in	it,	and	even	a	specialty	journal.	As	an	outsider,	I	have	no capacity	to	adjust	my	beliefs	independently	about	individual	pronouncements,	or	even	about the	reliability	of	particular,	within	Jungian	macroeconomics.	But	if	I	eventually	come	to	notice that	all	the	fields	that	draw	from	it	are	starting	to	fail	their	litmus	tests,	then	I	can	let	my distrust	filter	up	and	come,	via	indirect	calibration,	to	distrust	Jungian	macroeconomics.	This is	a	very	distanced	sort	of	autonomous	control,	but	it	may	be	the	best	of	which	we	are capable. 9 We	have	found	the	credentials	problem	is	not	entirely	insurmountable.	We	have	some limited	resources	to	establish	indirect	intellectual	autonomy	-	more,	at	least,	than	Millgram strictly	permits.	Still,	the	distanced	sort	of	meta-meta-meta-etc-autonomy	we	are	actually capable	of	achieving	might	seem	deeply	unsatisfying.	Somebody	who	desired	direct autonomy	for	its	own	sake	have	reason	to	eliminate	the	links	and	bring	those	distant	fields under	their	own	understanding	whenever	possible.	Furthermore,	somebody	who	desired intellectual	autonomy	for	Nickel-style	reasons	would	also	want	to	decrease	the	number	of links.	The	fewer	insulating	layers	between	myself	and	the	argument,	the	more	adaptable	I will	be,	and	the	more	control	I	will	have	over	the	premises	and	steps	of	the	arguments	I	use. How	might	we	decrease	the	indirectness	of	our	autonomy?	Millgram	has	suggested	that	one way	to	ease	the	autonomy	problems	of	hyper-specialization	is	to	set	an	army	of	philosophers at	the	interfaces	between	fields.	They	could	help	experts	to	understand	each	other's	fields	by providing	greater	and	clearer	translations	between	the	fields.	In	short,	a	desire	to	decrease intellectual	distance	will	lead	to	a	desire	for	greater	intellectual	transparency.	Our	army	of philosophers	will,	by	providing	conceptual	translations	and	increasing	intellectual transparency,	serve	to	increase	the	intellectual	autonomy	of	experts	in	one	field	who	needed to	rely	on	the	work	of	experts	in	another	field.	So	long	as	direct	autonomy	is	the	ideal,	and indirect	autonomy	a	mere	compromise,	we	should	seek	more	to	minimize	trust	and	maximize transparency. Intellectual	autonomy	and	proxies Let's	turn	to	the	next	of	Millgram's	problems	for	intellectual	autonomy	-	that	other people	reason	differently	from	ourselves	and	that	this	creates	a	particularly	great	problem 10 for	managing	defeaters	across	fields.	Though	he	broaches	these	topics	together,	I	think	they are	worth	thinking	about	separately.	What	I	hope	to	show,	in	these	next	two	sections,	is	that some	interests	we	have	which	bring	us	to	want	intellectual	autonomy	can	only	by	satisfied	by sacrificing	transparency	and	translation. Let's	start	with	the	idea	that	different	specialists	reason	in	radically	different	ways. Millgram	suggests	that	people	in	other	fields	are	"logical	aliens"	–	people	whose	notion	of what	counts	as	a	good	argument	is	different	from	your	own. However,	when	you	delegate	part	of	your	deliberation	to	a	logical	alien	put	less dramatically,	to	a	specialist	whose	idea	of	what	a	good	argument	is	differs	from	yours what	he	comes	up	with	will	not	normally	conform	to	standards	you	accept.	When	an outsider	is	aware	of	another	discipline's	internal	standards,	he	may	well	and	is	even likely	to	think	they	are	wrong	headed...	Because	you're	not	delegating	to	someone who	thinks	as	you	do,	we	no	longer	have	an	explanation	for	how	delegation	of	this sort	preserves	your	autonomy	-	or,	perhaps	more	carefully,	we	haven't	yet elaborated	a	notion	of	autonomy	that	makes	room	for	such	an	explanation.	(Millgram 2015:	33-4) Implicit	in	this	passage	is	an	account	of	how	intellectual	delegation	could	be	autonomypreserving.	If	I	have	good	reason	to	think	that	another	person	would	reason	just	as	I	do,	then offloading	a	reasoning	task	to	them	would	be	autonomy-preserving.	This	condition	is stronger	than	what	has	emerged	previously.	In	the	earlier	discussion	of	meta-autonomy,	we had	sought	only	to	discover	through	our	own	understanding	that	some	other	expert	was reliable;	we	had	not	sought	to	establish	that	they	also	thought	as	we	did.	(The	reason	I	trust my	accountant	is	precisely	because	he	does	not	think	as	I	do,	for	I	am	lousy	at	accounting.) But	this	new	condition	adds	the	requirement	that,	when	we	delegate	our	deliberation	to 11 another,	that	this	other	person	would	must	reason	in	the	way	that	we	would	have	in	order	for that	delegation	to	be	autonomy-preserving.	Let	me	call	this	the	proxy	requirement.1 In	the	science	fiction	novel	Stations	of	the	Tide,	Michael	Swanwick	imagines	a	future	in which	a	bureaucrat,	when	pressed	for	time,	can	create	mental	copies	of	himself,	and	set	each to	its	own	task	(Swanwick	2011).	This	would,	I	take	it,	result	in	the	most	perfect	possible intellectual	proxy.	It's	absolutely	certain	that	the	proxy	would	do	things	as	I	do,	and	it	seems intuitively	plausible	that	the	use	of	such	a	perfect	proxy	would	preserve	my	autonomy.	In	the novel,	the	bureaucrat	absorbs	the	memory	of	each	proxy	once	it	has	finished	its	task.	Let	me modify	the	scenario	a	little	for	my	purposes.	Imagine	that	I	can	make	mental	copies	which	are not	reabsorbed	whole	into	my	mind,	but	simply	present	me	with	their	conclusions,	shorn	of the	evidence	and	reasoning.	There	is,	after	all,	a	limit	to	how	much	my	brain	can	hold.	Even then,	if	my	perfect	proxy	simply	reports	to	me	a	conclusion,	stripped	of	their	reasons	-	still, it	seems	like	intellectual	autonomy	is	preserved.	After	all,	this	is	the	relationship	we	have with	past	versions	of	ourselves.	I	have,	for	example,	decided	for	myself	that	there	is something	deeply	wrong	with	Hegelianism,	though	I	performed	the	reasoning	over	a	decade ago	and	cannot	remember	any	of	the	details.	But	trust	in	my	past	self	still	seems	autonomypreserving.	I	have	good	reason	to	think	that	old-me	would	have	reasoned	quite	similarly	to present-me.	And,	if	I	wanted,	I	could	re-open	my	old	Hegel	books	and	think	it	through	for myself	again.	But	the	fact	that	I	have	not,	and	simply	rely	on	my	memory	of	my	past	self's eventual	conclusion,	without	any	memory	of	my	past	self's	reasoning,	doesn't	undermine	my intellectual	autonomy. 1 Note that Millgram himself, in the quoted passage, floats the proxy requirement and then distances himself from it, allowing, in the end, for the possibility of a reformulated notion of autonomy that might drop the proxy requirement. 12 Leaving	the	science	fiction,	it	seems	plausible	to	think	that	imperfect	proxies	are autonomy-preserving	to	the	degree	that	they	resemble	perfect	proxies.	The	more	I	can	think that	somebody	would	do	something	precisely	as	I	would	do	it,	the	closer	I	can	get	to	that dream	of	complete,	entirely	direct	intellectual	autonomy.	But,	an	important	question:	do	I really	want	perfect	proxies	if	I	am	simply	in	the	business	of	getting	things	right?	That	doesn't necessarily	seem	to	be	the	case.	So	long	as	we	think	that	there	isn't	one	best	way	to	reason	- that	different	ways	of	thinking	might	be	better	adapted	to	different	terrains	-	then,	for purely	epistemic	reasons,	I	might	not	want	to	be	confined	to	using	only	perfect	intellectual proxies.	I	would	not,	for	example,	want	somebody	who	thought	like	a	philosopher	to	give	me marriage	counseling	advice,	oversee	a	non-profit	charity,	or	to	guide	me	through	free	jazz.	In many	cases,	I	don't	seek	anything	like	an	intellectual	proxy	at	all.	I	am,	instead,	seeking somebody	that	I	can	trust	who	is	quite	different	from	me	-	somebody,	in	fact,	that	I	need	to trust	precisely	because	they	are	quite	different	from	me.	The	vast	difficulty	of	intellectual	life in	the	hyper-specialized	world	isn't	simply	that	I	lack	for	time;	it	is	that	different	hyperspecializations	seem	to	require	vastly	different	intellectual	makeups.	If	you	don't	believe	this, then	I	invite	you	to	imagine	a	world	in	which	music,	television,	couples	therapy,	military leadership,	restaurant	cooking,	and	children's	education	were	all	in	the	charge	of	analytic philosophers. What	could	the	basis	for	such	trust	be,	then,	if	not	proxy-hood?	It	may	vary	from	terrain to	terrain.	In	some	cases,	as	with	a	marriage	counselor,	I	trust	that	they	have	my	best interests	at	heart.	With	my	guide	to	the	world	of	free	jazz,	I	trust	that	they	have	good	taste and	are	sensitive	to	the	needs	of	a	newcomer.	But	in	most	academic	and	scientific	terrains,	I am	trusting	in	their	ability	to	get	it	right.	This	may	include	trusting	in	their	intellectual integrity,	sensitivity	to	facts,	intellectual	verve,	or	whatever	characteristics	happen	to	be 13 useful	for	their	field.	Notice	that	if	this	is	true,	then	the	difficulties	of	hyper-specialization	pull us	in	two	very	different	directions.	In	order	to	maximize	our	intellectual	autonomy,	we	would want	to	seek	perfect	proxies,	or	their	closest	available	approximation.	But	because	the demands	of	different	fields	are	not	simply	on	our	time,	but	demands	for	different	cognition, then	our	drive	for	the	greatest	accuracy	leads	us	to	seek	something	very	different. To	return	to	Swanwick's	tale:	suppose,	in	the	same	science	fictional	universe,	that	I	was aware	of	the	vast	differences	between	fields	at	a	young	age.	So,	cleverly,	before	I	intellectually specialized,	I	made	many	copies	of	myself,	enough	for	every	intellectual	discipline,	and	sent them	each	to	graduate	school	in	a	different	field,	to	each	be	changed	into	the	kind	of	logical alien	that	their	respective	field	requires.	But	if	my	copies	were	trained	into	different	fields, then	they	would	no	longer	really	be	intellectual	proxies	for	me	-	not	in	Millgram's	sense,	at the	very	least.	They	certainly	will	not	go	about	the	task	exactly	as	I	would	have.	But	what, then,	was	the	point	of	the	exercise?	Perhaps	that	I	know,	at	least,	that	I	can	trust	them	-	I believe	they	are	well-intentioned	in	their	reasoning,	if	not	perfect	proxies	for	how	I	would have	reasoned. Annette	Baier	suggests	that	trust	is	essentially	making	yourself	vulnerable	to	somebody else	-	it	is	entrusting	something	of	yours	to	their	care	(Baier	1986).	When	I	trust	a	doctor,	I make	my	body	vulnerable;	when	I	trust	a	romantic	partner,	I	make	my	emotions	vulnerable. When	I	trust	another	academic	and	rely	on	them,	I	make	my	belief	system	vulnerable.	In	the case	of	perfect	proxies,	the	trust	that	is	required	of	me	is	rather	thin.	I	am	deputizing	those who	think	as	I	do	-	if	they	fail,	they	failed	because	they	haven't	reasoned	well	in	this particular	case,	but	at	least	the	kind	of	reasoning	they	will	engage	in	has	been	chosen	by	me.	I am	only	vulnerable	to	a	simple	failure	of	applied	reasoning.	But	when	I	trust	a	logical	alien, my	trust	is	significantly	thicker.	I	am	trusting	them	not	only	to	reason	well,	but	to	have 14 adopted	the	form	of	reasoning	best	suited	to	the	task,	even	if	that	form	of	reasoning	might	not seem	good	to	me.	This	is	a	vaster	and	more	uncomfortable	form	of	intellectual	vulnerability. But	if	we	do	think	that	different	fields	require	different	reasoning	-	that	is,	if	we	think that	logical	aliens	have	arisen	not	by	accident,	but	because	cognitive	life	demands	significant intellectual	diversity	-	then	this	more	profound	trust	is	actually	requisite	for	getting	things right	in	a	world	of	hyper-specialization.	And,	insofar	as	intellectual	autonomy	consists,	at least	in	part,	in	translating	my	interests	into	suitable	action	through	my	own	activity,	then	the capacity	to	delegate	in	this	manner	is	helps	me	instantiate	a	form	of	intellectual	autonomy. Moreover,	it	is	a	form	of	autonomy	which	runs	counter	to	the	interest	in	approximating	direct intellectual	autonomy	through	perfect	proxies.	A	kind	of	meta-autonomy	is	still	available	here -	I	may	choose	to	trust	people	and	fields	for	good	reasons.	I	might,	for	instance,	choose	to trust	a	logical	alien	because	they	seemed	to	have	some	sort	of	integrity,	or	a	real	love	of	the truth.	But	it	is	a	kind	of	indirect	autonomy	that	is	quite	at	odds	with	any	hope	of transparency,	for	the	very	reason	I	wish	to	trust	them	is	that	their	capacities	and	abilities	are substantially	different	from	my	own. This,	let	me	suggest,	is	significantly	different	kind	of	intellectual	autonomy.	It	is	another way	in	which	we	can	seek	a	relationship	to	knowledge	and	others,	over	which	we	might	a distinctive	form	of	control.	It	is	the	capacity	to	invest	others	with	intellectual	trust,	even	when their	intellectual	work	is	not	transparent	to	us.	Robert	Nozick	has	suggested	that	something very	interesting	happens	in	love	relationships:	we	begin	to	delegate	intellectual	tasks	to	one another.	I	read	all	the	political	news,	and	my	wife	reads	all	the	environmental	news,	and	we report	and	digest	any	extremely	important	information	for	the	other.	And	if	the	other	person doesn't	report	that	anything	interesting	has	happened,	I	trust	them	(Nozick	1990).	Again, here	is	a	kind	of	intellectual	delegation	and	trust,	but	it	doesn't	involve	anything	like	a	perfect 15 proxy.	In	fact,	the	reason	that	I	read	the	political	news	and	my	wife	reads	the	environmental news	is	that	I	am	a	philosopher	and	she	is	a	scientist.	Other	relationships	like	this	can	occur elsewhere.	I	recently	co-authored	an	article	with	an	expert	in	the	field	of	game	design.	I	knew the	philosophical	literature	about	the	nature	of	games	and	play,	and	my	co-author	was	buried in	the	literature	of	computer	game	design.	We	wrote	the	paper	together	precisely	because neither	of	us	had	the	time	to	read	that	other	field	entirely.	The	paper	emerged	out	of	a	long set	of	conversations	between	us,	and	we	both	signed	our	names	to	it.	Now	the	details	of	what happened	there	are	very	complicated,	but	we	could	describe	what's	going	on	as	accessing	a distinctive	kind	of	intellectual	autonomy,	very	different	from	any	of	the	familiar	old individualistic	and	direct	forms.	In	this	kind,	I	am	autonomous	because	I	have	chosen	and delegated	responsibility	to	somebody	out	of	an	active	sense	of	trust	and	because	I	treat myself	as	responsible	for	the	whole.	Let's	call	this	delegational	autonomy. Direct	autonomy	leads	us	to	want	transparency.	When	we	turn	to	meta-autonomy, Millgram	suggests	that	we	ought	to	increase	transparency	as	much	as	possible,	to approximate	direct	autonomy.	But	I've	argued	that,	in	some	cases	of	meta-autonomy,	we ought	not	wish	for	transparency.	We	ought,	instead,	wish	to	have	delegational	autonomy.	We have	delegational	autonomy	in	those	intellectual	processes	which	are	under	our	control,	and regulated	by	our	reasons,	but	during	which	we	place	our	trust	in	people	whose	capacities	are beyond	what	we	can	understand	for	ourselves. The	problem	of	cross-disciplinary	defeater	management Let's	turn	now	to	the	third	of	Millgram's	problems	arising	from	hyper-specialization.	Even if	we	manage	to	locate	the	right	experts,	and	even	if	we	are	empowered	to	trust	them, 16 another	problem	arises:	what	Millgram	calls	the	problem	of	cross-defeater	management. Every	successful	argument,	says	Millgram,	has	its	defeaters	-	conditions	which	would	show the	argument	does	not,	in	fact,	go	through. Doing	a	decent	job	of	thinking	for	yourself	requires	sensitivity	to	the	defeating conditions	of	the	argument	supporting	your	views,	and	if	you	are	not	an	expert	in	the subject	matter	of	those	arguments,	you	do	not	generally	control	those	defeating conditions...	When	you	are	assembling	a	defeasible	argument,	you	should	be confident	in	your	conclusions	only	to	the	extent	that	you	control	the	argument's defeasibility	conditions;	in	a	less	fancy	way	of	saying	it,	your	confidence	should	not outrun	your	ability	to	catch	problems	and	bugs	in	your	argument.	(Millgram	2015,	312) The	problem	comes	when	we	take	an	argument	from	a	field	outside	our	expertise	and then	export	it	elsewhere	and	apply	it	on	our	own	recognizance.	An	expert	in	one	field	cannot be	expected	to	control	all	the	defeaters	of	an	argument	from	another	field;	we	should	expect, when	we	export	arguments,	to	miss	applicable	defeaters.	But	modern	practical	arguments	are draped	across	different	fields.	In	order	to	apply	them,	we	must	borrow	chunks	of	arguments from	other	fields	and	apply	them	in	our	own.	But	since	we	know	that	we	will	miss	any defeaters	to	those	exported	chunks	of	argument,	we	should	have	very	low	confidence	in	the success	of	such	cross-disciplinary	arguments.	This	Millgram	dubs	the	problem	of	crossdisciplinary	defeater	management. Perhaps	an	example	will	help.	A	physical	therapist	might	recommend	to	me	the	exercise of	shoulder	dislocates	for	stiff	shoulders,	especially	since	I	cannot	raise	my	hands	directly above	my	heads	(Despite	the	threatening	name,	this	is	simply	a	simple	overhead	rotational movement	with	a	broomstick.)	I	might	find	that	this	exercise	helps,	and	start	teaching	my friends	the	exercise.	However,	I	am	not	aware	of	the	following	defeaters:	the	exercise	is	only useful	for	shoulders	that	are	stiff	from	being	hunched	over	a	laptop,	and	not	useful	for shoulders	that	are	stiff	from	the	impact	of	a	car	accident.	Furthermore,	the	exercise	is	useful 17 for	most	people,	but	in	the	rare	case	of	a	particular	kind	of	nerve	impingement,	will	make	it worse.	My	lack	of	sensitivity	to	defeaters	will	lead	to	misapplications,	but	my	lack	of sensitivity	is	understandable,	since	I	am	not	a	physical	therapist.	Versions	of	this	problem apply,	Millgram	suggests,	whenever	an	expert	in	one	hyper-specialized	domain	has	to	apply results	from	another	hyper-specialized	domain. I	take	the	problem	of	cross-disciplinary	defeater	management	to	be	the	most	threatening of	Millgram's	problems.	Notice	that	none	of	the	potential	solutions	to	the	other	problems	I described	above	will	work	here.	It	does	not	matter	even	if	we	manage	to	identify	true	experts in	other	fields	with	absolute	precision.	Even	if	I	have	found	the	true	expert	and	received	their correct	argument,	the	mere	fact	that	it	is	I,	and	not	the	expert,	that	has	to	apply	that	argument to	new	situations,	leads	to	the	cross-defeater	problem	(32). Mere	translational	work	between	fields	won't	relieve	this	problem.	It	doesn't	matter	if	I understand	the	concepts	from	another	field;	without	actual	expertise	in	that	field,	I	won't control	the	defeaters	from	arguments	from	those	other	fields.	In	fact,	greater	transparency may	simply	exacerbate	the	problem.	Transparency	offers	the	illusion	of	control.	It	offers access	to	seemingly	good	arguments	from	other	fields,	while	hiding	the	complexity	of possible	defeaters.	It	is	an	invitation	to	failure.	Good	delegation	won't	work;	even	if	I	have perfect	knowledge	of	my	field,	and	you	have	perfect	knowledge	of	your	field,	and	we	have chosen	to	trust	each	other	for	very	good	reasons,	the	key	information	is	lost	when	our expertise	is	split	between	two	different	people.	Millgram	suggests	another	solution:	that individuals	be	trained	in	multiple	fields	(280).	If	I,	for	example,	have	a	dual	PhD	in	physics and	in	chemistry,	then	I	may	be	able	to	manage	defeaters	across	both	these	arguments.	But notice	this	only	solves	the	problem	for	those	special	individuals	-	it	does	not	solve	the problem	for	any	of	the	rest	of	us,	who	only	have	been	trained	in	one	field.	We	may	consult	one 18 of	these	special	doubly-trained	individuals	to	look	over	our	arguments,	and	that	may	help	for that	particular	argument,	but	the	moment	they	leave	us,	then	we	normal	specialists	are	still exposed	to	the	original	problem. An	entirely	different	kind	of	solution	instead	suggests	itself:	aggressive compartmentalization.	Here,	I	think	there	is	something	significant	we	can	learn	from	the	field of	computer	programming,	and	especially	the	way	that	computer	programmers	have	learned to	manage	the	connections	between	software	products	made	by	different	teams	and	different companies.	When	learning	programming,	one	learns	to	program	particular	sequences	of instructions	-	called	subroutines	or	functions	-	that	will	be	called	from	different	places	and times.	These	sequences	can	be	triggered	in	various	ways.	For	example,	one	might	have	a subroutine	designed	to	create	a	digital	image	of	Mario	on	a	screen.	The	main	program	will trigger	this	subroutine	over	and	over	again,	each	time	sending	it	a	different	set	of	input variables	indicating	where	on	the	screen	Mario	should	appear.	These	modules	are	called 'subroutines'	when	they	are	simply	sequences	of	instructions,	and	'functions'	when	they	are sequences	of	instructions	that	also	return	information	to	the	main	program.	For	example, many	programs	use	an	"Add"	function	which	takes	any	number	of	input	variables	and	then returns,	as	output,	their	total.	These	functions	often	have	considerable	internal	complexity.	At first,	the	naive	programmer	is	tempted	to	optimize	their	program	by	letting	the	other	parts	of their	program	make	direct	calls	and	modifications	into	the	inner	workings	of	particular functions,	and	let	particular	functions	look	for	all	sorts	of	particular	variables	from	the	larger program	and	from	other	functions.	But	the	naive	programmer	quickly	learns	that	this	degree of	functional	transparency	leads	to	chaos.	Different	programmers	are	always	tinkering	with the	particulars	of	different	functions	and	subroutines.	We	are	taught,	instead,	the	principle	of modularity.	In	modular	programming,	one	tries	to	make	subroutines	entirely	independent 19 black	boxes:	a	fully	modular	subroutine	will	take	an	input	and	generate	an	output,	but everything	that	happens	in	between	is	inaccessible	to	anything	outside	of	that	particular module.	Part	of	the	expectation	of	modular	programming	is	that	a	particular	module	may	end up	being	called	in	all	sorts	of	places	and	for	all	sorts	of	reasons	that	the	programmer	never had	in	mind	when	they	originally	created	it.	Modular	programming	becomes	particularly important	the	more	different	programmers'	programs	need	to	interact.	As	soon	as	one	has multiple	programmers	on	a	development	team,	or	programs	interacting	from	different development	team,	modularity	becomes	vital.	Think	again	of	that	Mario	subroutine.	The	main program	fires	off	many	other	subroutines	and	functions,	which	will	tell	the	main	program where	Mario	is,	what	his	vector	is,	and	what	the	player's	last	input	was.	The	main	program would	collect	these	variables	and	pass	them	to	a	Mario	image-generating	function.	And	that image-generating	function	would	take	those	location	variables	as	input,	process	them	inside its	black	box,	output	a	package	of	image	data,	and	send	that	onwards	to	another	subroutine designed	to	communicate	with	a	specifically	physical	display	device	–	like	a	TV	screen, computer	monitor,	or	portable	game-playing	screen.	The	final-stage	programs	that	connect	to actual	specific	physical	output	devices	are	called	'drivers'.	But,	since	programs	are	run	on different	devices,	they	must	be	compatible	with	a	wide	range	of	drivers.	Usually,	a	game development	team	will	write	their	program	so	that	it	might	hook	up	with	any	number	of display	drivers,	for	any	number	of	display	types.	The	game	development	team	actually usually	has	no	idea	what's	going	on	in	the	specific	display	drivers;	in	fact,	the	assumption	is that	drivers	will	change	and	update	many	times	over	the	lifetime	of	their	game,	as	the physical	technology	changes.	So,	game	programmers	and	driver	programmers	can't	rely	on specific	details	of	the	other	programs.	Their	modules	must	only	exchange	a	small	number	of specific	variables,	designed	for	that	exchange.	The	prime	directive	of	modularization	is	the 20 isolation	of	individual	functions,	and	the	stabilization	of	any	information	exchanged	across the	interface	between	functions	(Boudreau,	Tulach	and	Wielenga	2007:	9-19).	Another	way to	put	it	is	that	each	module	should	depend	as	little	as	possible	on	the	particulars	of	any	other module.	It	should	take	an	input,	and	then	work	independently	to	create	the	proper	output, and	other	modules	should	look	only	to	that	particular	output,	and	not	otherwise	peer	inside the	black	box. What	might	this	look	like	applied	to	the	broader	problem	of	hyper-specialization?	Here's an	example:	suppose	you	have	created	a	better	blood	test	for	dopamine.	All	sorts	of	fields have	a	use	for	that	blood	test.	Here	are	two	options:	first,	you	could	translate	-	you	could	try to	explain	how	the	blood	test	works	in	terms	that	any	scientist	could	understand,	as	carefully as	possible,	and	then	let	it	loose	into	the	wider	world.	This	process	is	complicated.	The	initial run	of	the	blood	through	the	analytic	instrument	yields	a	vast	amount	of	data,	which	needs	to be	processed	exactingly	to	yield	a	particular	blood	result.	Then,	animal	researchers,	medical researchers,	biologists,	and	the	like	could	try	to	make	it	work	for	themselves.	This	has	the advantage	of	giving	them	access,	not	only	to	the	dopamine	data,	but	all	the	other	complex instrumental	data.	Or,	second,	you	compartmentalize	and	make	it	into	a	black	box.	You	could set	up	a	laboratory	which	performs	this	blood	test.	The	laboratory	asks	blood	samples	to	be collected	in	a	specific	way,	processes	those	samples	on-site	and	sends	back	a	measurement	of the	dopamine	level,	and	nothing	else. The	first	method	seems	good-hearted,	intellectually	generous,	and	hopeful	in	terms	of supporting	direct	autonomy.	Of	course,	the	first	method	also	invites	hideous	problems	of cross-disciplinary	defeater	management.	The	second	method,	though	perhaps	intuitively repulsive	to	some,	is	an	attempt	to	control	for	defeaters	by	narrowing	the	inputs	and	the outputs.	The	intent	is	to	leave	the	defeasible	innards	of	to	the	appropriate	experts,	and	work 21 to	manage	the	defeasibility	condition	of	the	exports,	by	sharply	limiting	what	is	exported.	One might	think	that	the	second	method	is	intellectually	miserly.	But	another	way	to	put	it	is	that the	second	method	is	more	intellectually	humble.	It	recognizes	the	problem	of	cross-defeater management	and	recognizes	that	different	experts	in	different	fields	simply	to	do	not	have the	sensitivity	to	fully	apply	the	arguments	and	methods	of	other	fields. The	methods	of	modularity	and	isolation	aren't	a	guaranteed	solution	to	the	problem	of cross-disciplinary	defeater	management.	But	they	do	narrow	the	space	of	worries.	Return	to that	blood	test.	If	we	opened	up	the	details	of	that	blood	test	to	all	sorts	of	fields,	then	we would	have	to	worry	about	defeaters	that	might	emerge	at	every	step	-	of	processing	the blood	sample,	of	submitting	it	to	the	instrument,	of	analyzing	the	data	properly.	But	if	we modularize,	we	only	need	to	worry	about	and	manage	the	defeaters	at	two	points	of	contact: input	and	output.	Here's	how	that	might	look:	for	anybody	who	orders	the	test,	they	receive meticulous	instructions	about	how	exactly	to	gather	the	blood	sample.	When	the	test	results come	out,	they	come	with	a	long	list	of	qualifications	about	what	might	have	gone	wrong.	This doesn't	solve	the	problem	of	defeater	management,	but	it	radically	decreases	the	number	of defeaters	we	need	to	manage. When	considering	the	problem	of	intellectual	distance,	we	might	have	thought	that	the right	thing	to	do	at	the	interface	between	the	fields	was	open	the	doors	wider	and	let	more understanding	through.	But	the	problem	of	cross-defeater	management	suggests	the opposite:	that	we	should	narrow	the	opening	between	fields.	Furthermore,	it	suggests	that Millgram's	army	of	philosophers	should	concentrate,	not	on	explaining	the	innards	of	one field	to	another	field,	but	rather	on	ensuring	the	clarity	and	stability	of	any	information exchanged	across	the	interfaces	between	fields,	and	on	otherwise	isolating	the	inner workings	of	one	field	across	another. 22 Of	course,	radical	modularity	is	not	the	only	thing	we	can	strive	for.	Let's	return	to	the blood	case.	As	it	turns	out,	sometimes	blood	test	developers	need	to	export	blood	tests.	A hospital	may	perform	so	much	of	a	particular	blood	test	that	they	wish	to	perform	it	in-house. If	it's	economically	feasible,	blood	test	developers	will	actually	create	literal	black	boxes	- machines	that	can	be	sold	to	hospitals	and,	with	minimal	training,	will	take	a	blood	sample and	spit	out	a	result.	But	we	could	also	attempt	to	break	out	of	modularity	by	double-training an	individual.	A	zoologist	who	needed	to	adapt	that	blood	test	to	gorillas	might	temporarily apprentice	themselves	to	the	blood	test	developer	in	order	to	learn	the	details	of	the	blood test	and	optimize	it	for	their	needs.	But	this	requires	a	massive	expenditure	of	human	time and	effort	-	months	if	not	years.	Modules	can	be	customized	and	custom-fit,	but,	as elsewhere	in	life,	custom	work	is	mighty	expensive.	We	could	also	do	this	with	whole	fields; as	Millgram	suggests,	we	can	take	individuals	and	train	them	in	two	fields	simultaneously, and	those	individuals	can	tend	to	the	connection	between	those	two	fields.	But	this	is	likely only	worthwhile	when	the	two	fields	are	deeply	and	frequently	connected.	For	example,	the relationship	between	aeronautics	and	the	chemical	engineering	involved	in	jet	engines	likely has	been	tended	to	by	a	large	number	of	specialists	who	are	double-trained,	as	has	the relationship	between	ethical	theory	and	legal	theory.	To	press	the	analogy	further:	in	most	of industrial	life,	we	use	modular	parts.	Sometimes,	for	a	special	purpose,	we	may	customengineer	a	part,	or	custom-modify	two	parts	for	a	better	and	more	integrated	fit.	But	that	is time-consuming	and	expensive.	Most	of	the	times,	we	simply	use	modular	parts	and	assemble them	as	needed. In	fact,	one	might	start	to	suspect	that	modularity,	while	it	depresses	the	traditional	sort of	direct	autonomy	of	every	individual	piece	of	evidence,	encourages	yet	another	sort	of autonomy:	the	ability	to	manage,	for	oneself,	the	overall	shape	of	large	systems	of	knowledge. 23 Let's	call	this	management	autonomy.	Given	that	we	are	cognitively	finite	human	beings,	it seems	like	we	have	a	choice:	we	can	either	know	for	ourselves	all	the	details	of	a	small system,	but	have	little	idea	of	where	the	inputs	for	that	system	come	from	or	where	the outputs	for	that	system	go	-	or	we	can	step	back	and	modularize,	and	get	a	glimpse	of	the whole.	This	permits	us	to	autonomously	consider	the	structural	relationships	of	the	various domains	of	knowledge.	When	human	knowledge	was	small,	it	was	possible	to	have	all	these forms	of	autonomy	for	oneself.	But	as	human	knowledge	grows	larger,	it	seems	that	we	must choose	between	them.	Direct	autonomy,	and	its	interest	in	transparency,	is	at	odds	with delegational	autonomy's	need	to	trust	logical	aliens	and	management	autonomy's	need	to encapsulate	fields	in	black	boxes. Conclusion There	is	a	tension	between	different	potential	reactions	to	the	difficulties	of	hyperspecialization.	First,	to	increase	the	familiar	sort	of	intellectual	autonomy,	we	might	want	to open	the	borders	between	the	fields,	translate	the	concepts.	But	this	solution,	though	it increases	our	direct	autonomy,	will	also	exacerbate	the	problem	of	cross-disciplinary defeater	management.	To	manage	that	second	problem,	we	ought	to	narrow	the	interface between	the	fields,	and	compartmentalize	instead	of	translate.	That	choice	increases intellectual	distance	and	decreases	adaptability,	and	it	requires	greater	trust	and	creates greater	intellectual	vulnerability,	but	increases	our	capacity	for	management	autonomy. Furthermore,	the	drive	to	transparency	presumes	that	we	would	wish	to	do	all	the	thinking for	ourselves,	or	employ	somebody	sufficiently	like	ourselves.	But	in	some	cases	our 24 intellectual	interests	call	us	to	place	our	trust	in	those	significantly	unlike	ourselves.	In	that case,	we	want	the	capacity	for	delegational	autonomy. Are	these	forms	of	intellectual	autonomy	always	going	to	stand	in	tension?	Perhaps,	in some	sense,	we	can	move	towards	transparency	and	modularity	at	once.	Again,	return	to	the computer	programming	example.	It	is	possible	for	us	to	be	simultaneously	transparent	and modularized,	in	at	least	once	sense.	Large	swathes	of	the	computer	programming	world	are open-source	-	what's	inside	each	program	is	available	to	anybody	else,	as	source	code.	Any programmer	can	see	what's	inside	any	open	source	black	box,	and	lift	out	the	code	and	tinker with	it.	But,	that's	a	matter	of	source	code.	When	the	programs	are	actually	running,	they behave	as	modules.	If	we	export	this	analogy	to	the	academic	world,	what	this	looks	like might	be	a	distinction	between	reporting	and	use.	For	example,	it's	perfectly	fine	for	our blood	test	designer	to	publish	her	research	and	let	other	experts	look	under	the	hood.	What functional	modularity	demands	is	that	when,	say,	specialist	in	cell	cancer	wants	to	use	that blood	test,	she	ought	to	order	the	modularized	blood	test	rather	than	try	to	adapt	the	original research	for	her	ends.	If	we	are	worried	about	cross-disciplinary	defeater	management,	then in	actual	use,	modularity	trumps	transparency.	If	I	am	not	a	blood	testing	expert,	then	I	may have	a	go	at	that	research	data	in	my	own	spare	time,	but	when	push	comes	to	shove,	I	need to	order	the	blood	testing	package	and	trust	it,	and	defer	to	that	trust,	over	my	own	shaky attempt	at	thinking	through	how	that	test	works. This	may	require	that	we	abandon	the	familiar	desire	for	complete	direct	intellectual autonomy	and	its	concomitant	fetishization	of	complete	personal	understanding	and	control. It	might	require,	instead,	trading	off	direct	autonomy	for	trust	in	others,	and	for	the	capacity to	manage	large	scale	structures.	What	we're	starting	to	uncover	here	is	the	fact	that intellectual	autonomy	fragments	under	the	pressure	of	the	increasing	size	of	human 25 knowledge.	Or,	perhaps,	it	was	fragmented	all	along,	and	that	fragmentation	was	hidden	due to	the	relatively	small	size	of	human	knowledge.	But	as	the	amount	of	human	knowledge increases,	the	forms	of	intellectual	autonomy	separate,	and	come	into	tension,	and	we	must sometimes	choose	between	them. Bibliography Baier,	Annette,	1986,	"Trust	and	anti-trust,"	in	Ethics,	96,	2:	231-260. Boudreau,	Tim,	Jaroslav	Tulach,	and	Geertjan	Wielenga,	2007,	Rich	Client	Programming: Plugging	Into	the	Netbeans	Platform,	Prentice	Hall	Press,	Upper	Saddle	River. 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