Susanna	Siegel	*	Explaining	uncertainty 1 How	can	perceptual	experiences	explain	uncertainty?* forthcoming	in	Mind	&	Language Abstract:	Can	perceptual	experiences	be	states	of	uncertainty?	We	might	expect	them	to	be, if	the	perceptual	processes	from	which	they're	generated,	as	well	as	the	behaviors	they	help produce,	take	account	of	probabilistic	information.	Yet	it	has	long	been	presumed	that perceptual	experiences	purport	to	tell	us	about	our	environment,	without	hedging	or qualifying.	Against	this	long-standing	view,	I	argue	that	perceptual	experiences	may	well occasionally	be	states	of	uncertainty,	but	that	they	are	never	probabilistically	structured.	I criticize	a	powerful	line	of	reasoning	that	we	should	expect	perceptual	experience	to	be probabilistic,	given	their	interfaces	with	unconscious	probabilistic	information,	with behavior	responsive	to	it,	and	with	credences. Our	languages	are	full	of	ways	to	express	uncertainty,	such	as	"I	suspect	that...,"	"I am	more	sure	of	X	than	I	am	of	Y,"	"I	can't	rule	out	X	but	I	can't	rule	it	in	either."	You	might feel	doubtful	that	the	cries	you	heard	in	the	desert	were	a	baby	(since	coyotes	can	sound like	that),	yet	not	entirely	comfortable	ruling	out	this	eerie	possibility. Some	hold	that	degrees	of	confidence	are	probabilistically	measurable. Let's	call these	degrees	of	confidence	credences.	If	you	have	a	middling	credence	in	p,	you	are	far from	fully	confident	in	accepting	or	rejecting	it.	To	express	your	opinion	on	p,	you'd	have	to hedge,	by	using	one	of	the	many	locutions	we	have	for	qualifying	an	outright	Yes	or	No. Credences	are	states	of	uncertainty.	How	similar	can	they	be	to	perceptual experience?	If	I'm	not	completely	sure	that	the	cries	in	the	desert	come	from	a	coyote,	can this	be	because	my	perceptual	experience	already	embodies	a	form	of	uncertainty intrinsically,	or	must	my	uncertainty	be	merely	a	contingent	response	to	my	perceptual experience? Uncertainty	intrinsic	to	perceptual	experience	would	supervene	on	the	phenomenal character	of	the	experience.	Anyone	having	a	perceptual	experience	with	that	phenomenal character	would	undergo	that	same	form	of	uncertainty.	As	I'm	using	"perceptual experience",	perceptual	experience	always	feels	like	perception,	which	makes	it	a *	I'm	grateful	for	a	wealth	of	opportunities	to	discuss	the	relationships	between	probability	and	perception, including	invitations	to	give	the	presidential	address	of	the	Association	for	the	Scientific	Study	of Consciousness	meetings,	the	Mind	and	Language	lecture	at	the	European	Society	for	Philosophy	and Psychology,	and	the	Kripke	lecture	at	CUNY,	as	well	as	the	chance	to	speak	at	conferences	at	York, Helsinki,	Cambridge,	and	Bochum	and	give	colloquium	talks	at	Carelton	University,	Glasgow,	and Georgia	State.	Thanks	to	Maria	Lasonen-Aarnio,	Ned	Block,	Alex	Byrne,	Géraldine	Carranante,	David Chalmers,	Rachel	Denison,	Anya	Farrenikova,	Jane	Friedman,	Sam	Gershman,	E.J.	Green,	Gabe	Greenberg, Steven	Gross,	Jakob	Hohwy,	Thomas	Icard,	Geoffrey	Lee,	John	Morrison,	Jessie	Munton,	Nico	Orlandi, Adam	Pautz,	Christopher	Peacocke,	Ian	Philipps,	Stephan	Pohl,	Katia	Samoilova,	Miriam	Schoenfeld, Nicholas	Shea,	Maja	Spener,	Scott	Sturgeon,	Neil	van	Leeuwen,	Jonna	Vance,	Fillippo	Vindrola	and	Ege Yumusak	and	many	others	for	comments	and	discussion. Susanna	Siegel	*	Explaining	uncertainty 2 phenomenal	category.1	Phenomenal	character	is	intrinsic	to	experience.	I'll	sometimes	call it	"experience"	for	short.	If	perceptual	experience	can	ever	be	a	state	of	uncertainty,	then there	is	a	form	of	uncertainty	that	is	intrinsic	to	perceptual	experience. To	illustrate	uncertainty	intrinsic	to	perceptual	experience,	consider	the	following argument	for	it: Face-value	argument P1.	You	can	form	credences	by	taking	an	experience	at	face	value. P2.	If	you	can	form	credences	by	taking	an	experience	at	face	value,	then	the experience	must	be	intrinsically	a	state	of	uncertainty. Conclusion:	Experiences	can	be	intrinsically	states	of	uncertainty. This	argument	develops	the	idea	that	if	the	phenomenal	character	of	your	experience	alone could	guide	you	into	a	state	of	post-perceptual	uncertainty,	then	your	experience	must already	be	its	own	form	of	uncertainty. According	to	the	conclusion	of	the	face-value	argument,	the	phenomenal	character of	experience	is	non-contingently	related	to	uncertainty.	A	stronger,	explicitly	probabilistic version	of	this	claim	would	be	that	the	phenomenal	character	of	experience	can	be	noncontingently	related	to	a	specifically	probabilistic	form	of	uncertainty	–	one	we	might	call perceptual	proto-confidence,	since	it	would	be	a	perceptual	precursor	to	confidence. Both	the	conclusion	and	the	stronger	claim	allow	that	the	phenomenal	character	of perceptual	experience	non-contingently	attaches	a	measure	of	uncertainty	to	information about	the	way	things	are	in	the	environment.2	We	can	say	that	when	an	experience	does this,	it	is	a	phenomenal	hedge-marker.	If	experience	is	a	probabilistic	phenomenal	hedge marker,	then	you	could	read	off	probabilistic	information	from	the	phenomenal	character, as	much	and	in	the	same	way	as	you	could	read	off	any	other	information	that	can	be	noncontingently	related	to	phenomenal	character,	such	as	whether	there's	anything	red	thing to	your	left. In	this	paper,	I	argue	that	taken	on	its	own,	the	conclusion	of	the	Face-value argument	may	well	be	true,	but	that	both	premise	P1	and	the	probabilistic	version	of	its conclusion	are	false.	Some	experiences	are	states	of	uncertainty,	but	none	of	them	are probabilistic:	phenomenal	character	does	not	inherit	probabilistic	information	from	the perceptual	processing	that	produces	it;	it	does	not	convey	probabilistic	information	to 1"Perceptual	experience"	can	alternatively	be	heard	as	denoting	whatever	experience	accompanies perception,	as	opposed	to	the	phenomenological	category	of	experiences	that	feel	like	perception, whether	they	are	perceptions	of	external	stimuli	or	not.	My	use	is	the	phenomenological	reading.	The two	uses	differ	because	as	Perky	(1931)	showed,	experiences	that	accompany	perception	may	feel	like imagination. 2	A	hedge	on	whether	a	worldly	condition	C	obtains	can	take	the	form	of	probabilistic	"worldly"	contents that	assign	a	probability	to	condition	C	obtaining,	or	to	probabilistic	meta-representational	contents	that assign	a	probability	to	the	correctness	of	a	content	that	says	C	obtains.	I'll	count	both	kinds	of	contents as	a	hedge	on	C,	even	though	they	will	be	psychologically	different. Susanna	Siegel	*	Explaining	uncertainty 3 subsequent	states;	and	it	is	not	probabilistically	structured. If	experiences	can	be	states	of uncertainty,	such	states	are	few	and	far	between,	and	contrary	to	P1	it	is	not	possible	to form	probabilistically	measurable	levels	of	confidence	directly	on	the	basis	of	experience. With	a	small	adjustment,	the	Face-value	argument	could	be	modified	to	yield	the stronger	probabilistic	conclusion	that	I'm	arguing	against: Probabilistic	face-value	argument P1.	You	can	form	credences	by	taking	an	experience	at	face	value. P2*.	If	you	can	form	credences	by	taking	an	experience	at	face	value,	then	the experience	must	be	intrinsically	probabilistic. Conclusion:	Experiences	can	be	intrinsically	probabilistic. Morrison	(2015)	offers	an	argument	much	like	this	revised	one.3	In	both	Face-value arguments,	a	host	of	challenges	surrounds	the	premises,	and	recent	discussions	have	made many	of	these	challenges	evident.4 Here	I	assess	the	idea	that	experiences	are	intrinsically	probabilistic	by	engaging with	a	different	route	to	that	conclusion	that	avoids	the	complexities	of	the	Face-value arguments	and	instead	draws	heavily	on	perception	science.	Its	conceit	is	that	in	cases where	behavior	is	sensitive	to	probabilistic	information	that	is	used	in	perceptual processing,	we	should	expect	that	probabilistic	information	to	be	conveyed	by	perceptual experience	as	well. For	instance,	Morrison	(ms)	describes	the	informational	continuity	he	thinks	we should	expect	to	find	reaching	from	sub-personal	processing,	through	experience,	to behavior: "Suppose	we	can	show	that	degrees	of	confidence	that	are	assigned	by	early perceptual	processing	are	also	available	for	behavior. This	is	a	reason	to	think	that the	relevant	degrees	of	confidence	are	assigned	by	the	perceptual	experience	itself. If	that	degree	of	confidence	didn't	arise	until	after	the	perceptual	experience,	we wouldn't	expect	to	find	it	in	the	brain	earlier	than	perceptual	experience. And	if	that degree	of	confidence	were	discarded,	we	wouldn't	expect	to	find	the	same	degree	of confidence	later.	Once	information	is	lost,	it	cannot	be	regained." Probabilistic	experiences,	on	this	picture,	are	part	of	a	continuous	flow	of	probabilistic information	from	sub-personal	perceptual	processing	to	producing	probabilistically	guided behavior.	Such	experiences	safeguard	against	losing	perceptual	information	along	the	way 3	Morrison	formulates	his	argument	in	terms	of	trust	when	he	writes	that	probabilistic	experiences	"best explains	what	happens	when	we	completely	trust	our	experience." 4	Beck	2019,	Cheng	2018,	Pohl	(ms),	Nanay	2020,	Raleigh	and	Vindrola	(forthcoming).	Unlike	these writers,	I	won't	discuss	P2	at	all. Susanna	Siegel	*	Explaining	uncertainty 4 to	behavior	that	they	guide.	And	the	main	alternative	to	probabilistic	experiences,	Morrison goes	on	to	suggest,	is	that	experiences	would	be	epiphenomenal	with	respect	to probabilistic	behavior	–	a	consequence	he	rejects	as	implausible. After	some	preliminary	discussion	in	section	1,	in	sections	2	and	3	I	present	and attempt	to	undermine	the	argument	for	probabilistic	experiences	from	considerations about	the	relationship	between	probabilistic	processing	and	perceptual	experience.	I	then turn	to	assessing	directly	whether	there	are	probabilistic	experiences.	My	strategy	is	to begin	by	considering	the	more	fundamental	claim	that	that	experiences	can	be	intrinsically states	of	uncertainty.	This	claim,	as	we	saw,	is	the	conclusion	of	the	unmodified	face-value argument,	and	I	make	the	case	right	at	the	start	(section	1)	that	it	is	interesting	and important	in	its	own	right,	as	it	challenges	long-standing	and	deeply	entrenched assumptions	about	the	nature	of	perceptual	phenomenology.	I	argue	that	experiences	may well	be	intrinsically	states	of	uncertainty	(section	4),	but	that	they	are	not	probabilistically structured	(section	5). 1.	Why	does	it	matter	if	experiences	can	be	states	of	uncertainty? What	would	it	be	for	a	perceptual	experience	to	be	a	state	of	uncertainty,	and	why does	it	matter	whether	any	of	them	are? In	a	state	of	uncertainty,	one	hedges	on	whether	something	is	or	is	not	the	case.	A hedge-marker	is	something	in	the	mind	that	marks	off	a	content	as	a	way	things	in	the environment	might	but	might	not	actually	be.5	A	probabilistic	structured,	middling	level	of confidence	is	a	paradigmatic	hedge-marker,	but	not	the	only	kind. A	phenomenal	hedge-marker	is	a	phenomenal	feature	of	perceptual	experience	that marks	off	a	content	as	a	way	that	things	in	your	environment	might	but	might	not	actually be. In	phenomenal	hedge-markers,	phenomenal	character	attributes	uncertainty	to information	about	the	external	environment. How	can	a	phenomenal	hedge-marker	attach	uncertainty	to	external-world information	by	virtue	of	its	phenomenal	character?	We	can	distinguish	between	two	kinds of	phenomenal	hedge-markers:	intrinsic	and	role-based.	Intrinsic	phenomenal	hedgemarkers	mark	the	hedge	with	intrinsic	features	of	experiences,	whereas	role-based phenomenal	hedge-markers	mark	the	hedge	by	one	or	more	roles	played	by	phenomenal character,	where	the	roles	are	only	contingently	associated	with	the	experience.	For instance,	if	high	pitched	sounds	scare	you,	then	a	role	played	by	your	auditory	experience	is to	cause	fear.	But	this	role	is	only	contingently	related	to	the	auditory	experience,	since someone	might	have	the	same	experience	without	feeling	scared,	and	you	might	cease	to feel	scared	by	such	sounds	after	further	conditioning,	for	instance	if	you	listen	to	a	lot	of 5	The	type	of	contents	relevant	to	this	discussion	are	accuracy	conditions.	As	Morrison	(2015)	points out,	if	experiences	were	structured	in	the	same	way	as	credence	distributions	over	a	hypothesis	set,	with perceptual	seeming	in	place	of	credence	relations	to	each	hypothesis,	then	the	experience	as	a	whole would	not	have	accuracy	conditions	in	any	straightforward	sense.	But	we	can	still	think	of	contents	as the	hypotheses,	and	that's	the	sense	of	"content"	at	issue	here. Susanna	Siegel	*	Explaining	uncertainty 5 operas.	Similarly,	if	an	experience	is	a	role-based	phenomenal	hedge-marker,	the experience	causes	you	to	hedge	on	a	content,	but	its	doing	that	is	a	contingent	feature	of	the experience. If	there	are	role-based	phenomenal	hedge-markers,	then	experiences	are	not necessarily	states	of	uncertainty.	If	there	are	intrinsic	phenomenal	hedge-markers,	then	by definition,	some	experiences	are	states	of	uncertainty	those	with	phenomenal	features that	constitute	hedge-markers. We	can	understand	what	the	intrinsic	variety	of	hedge-marker	would	be	by considering	what	it	would	be	for	intrinsic	features	of	experiences	to	constitute	a	hedge. The	intrinsic	features	of	experience	include	its	phenomenal	character and phenomenal	contents	of	experience	(ie,	contents	that	supervene	on	phenomenal character).6 For	instance,	suppose	the	phenomenal	contents	of	experience	included probabilistic	contents,	such	as	"there's	probably	a	cat	in	front	of	me."	Encoding	this probabilistic	information	would	be	but	one	way	for	experiences	to	be	states	of	uncertainty. If	an	experience	encoded	probabilistic	information	in	its	phenomenal	character,	then	any two	phenomenally	identical	experiences	would	encode	the	same	probabilistic	information. A	different	example	of	an	intrinsic	feature	of	experience	is	the	invariant	phenomenal features	of	experience.	Perceptual	experience,	as	noted	earlier,	always	feels	like	perception, whether	it	is	a	case	of	perceiving	or	not.	It	is	a	phenomenal	category	with	invariant	features that	are	shared	by	all	perceptual	experiences,	whether	those	experiences	are	cases	of perceiving	or	something	else,	such	as	imagining.	Hypotheses	about	the	invariant	features	of perceptual	experience	are	universal	claims	about	all	perceptual	experiences.7 Perception	itself	includes	more	than	perceptual	experience.	Perceiving	can	feel	like imagining,	as	Perky	showed	long	ago.	And	perceptual	experiences	are	not	always	cases	of perception,	as	is	shown	by	immersive	dreaming	and	hallucinating.8 Finally,	the	structure	of	a	perceptual	experience	could	be	a	hedge-marker,	if	by virtue	of	that	structure,	the	experiences	presents	us	with	multiple	incompatible possibilities	at	once,	and	mark	the	possibilities	as	a	way	the	world	might	actually	or	might 6	I'll	leave	it	open	whether	all	phenomenal	features	of	experience	are	also	representational.	Vance (2020),	like	Block	(1996),	suggests	that	some	aspects	of	phenomenal	character	are	manners	of representation	of	contents.	Vance	proposes	that	precision	information	in	perceptual	processing	explains some	manners	of	representation,	such	as	blur,	but	leaves	open	whether	blur	is	intrinsically	a	hedgemarker. 7	There	are	also	arguably	such	things	as	phenomenal	imagining	and	phenomenal	remembering,	and	for each	of	these	phenomenal	states,	we	could	ask	what	its	phenomenal	invariant	features	are.	But	here	I'm concerned	only	with	perceptual	experience	and	whether	it	can	be	a	phenomenal	hedge-marker. 8	Perky	(1931).	Imagining,	in	turn,	can	feel	like	remembering,	as	we	know	from	studies	of	false memories	(Schachter	(2001),	Mazzoni	(2003)),	just	as	remembering	can	feel	like	imagining,	as	Martin and	Deutscher	observed	when	they	developed	their	causal	theory	of	memory	Martin	and	Deutscher (1966).	On	the	phenomenology	of	dreams	see	Hobson	(2005). Susanna	Siegel	*	Explaining	uncertainty 6 not	actually	be.	Section	4.1	makes	the	case	that	such	"multiplex"	experiences	are	the	best candidates	for	intrinsic	phenomenal	hedge-markers,	and	section	5	argues	that	these experiences	are	not	probabilistic:	there	is	no	intrinsic	assignment	of	probabilistic	weights to	each	option. 1.1	The	standard	view	of	perceptual	phenomenology A	first	reason	why	it	matters	whether	perceptual	experiences	can	be	states	of uncertainty	is	that	intrinsic	phenomenal	hedge-markers	are	not	supposed	to	exist, according	to	a	longstanding	view	of	the	phenomenology	of	perception. According	to	the	longstanding	view,	which	I'll	call	the	standard	view,	an	invariant feature	of	perceptual	experience	is	that	it	purports	to	present	us	with	a	unique	way	that things	actually	are	at	the	time	of	the	experience.	This	position	is	often	defended	as	part	of	a scheme	for	differentiating	the	invariant	phenomenal	features	of	perception,	imagination, and	episodic	memory.9	According	to	the	standard	view,	if	you	phenomenally	imagine	an apple	in	front	of	you,	you	can	experience	being	in	the	presence	of	an	apple	as	a	merely possible	way	things	could	be,	or	even	a	way	things	could	be	in	the	future	or	could	have been.	Phenomenally,	this	type	of	experience	is	different	from	episodically	remembering seeing	an	apple.	In	that	case,	even	if	you	picture	an	apple	vividly	in	your	mind,	the experience	is	marked	as	something	that	actually	occurred	in	the	past,	rather	than	as something	imaginary	that	is	not	actually	happening	now. Figure	1	A	standard	view	of	phenomenal	invariances. On	the	standard	view,	phenomenal	perception	contrasts	with	phenomenal	memory	and phenomenal	imagination	by	presenting	things	as	actually	occurring	at	the	moment	of	the experience,	rather	than	as	having	actually	having	occurred	in	the	past	(as	per	phenomenal 9	I	call	the	view	'standard'	because	thinkers	from	different	corners	of	philosophy	and	neuroscience converge	on	it	from	different	places	and	times,	including	Husserl	(1905)	on	memory	vs.	'phantasy',	H. Lau	(2019)	on	perception	as	reality	monitoring,	and	Martin	(2002)	on	perception	vs.	imagination. Husserl's	terminology	does	not	map	on	to	mine,	since	he	draws	finer	distinctions	that	recognize intermediate	states	between	what	someone	might	call	perception	and	memory	(such	as	retention)	and between	perception	and	imagination	(protention).	Husserl's	term	for	the	experiences	that	have	the phenomenology	of	perception	described	here	is	"adumbration".	Note	that	the	chart	leaves	open	whether perceptual	experiences	are	or	involve	representational	states. actual present actual past merely possible (not actual) future perception X memory X imagination X (X) Susanna	Siegel	*	Explaining	uncertainty 7 memory)	or	as	not	actually	occurring	presently	at	all	(as	per	phenomenal	imagination).	On this	view,	there	is	no	way	to	'hedge'	in	perceptual	experience,	no	way	to	mark	off something	we're	perceptually	conscious	of	as	merely	possible,	the	way	we	do	in imagination	and	in	thought. Since	the	standard	picture	is	about	invariance	in	perceptual	experience,	it	makes universal	predictions	about	all	perceptual	experiences. So	if	there	are	intrinsic phenomenal	hedge-markers,	then	the	standard	picture	is	wrong.	I	argue	in	section	4	that the	standard	picture	may	well	be	unable	to	accommodate	some	perceptual	experiences	of wobbly	trajectories,	and	I	suggest	a	different	scheme	for	distinguishing	between phenomenal	perception,	phenomenal	imagination,	and	phenomenal	memory	that	can accommodate	these	odd	experiences. 1.2	How	can	we	discover	whether	there	are	intrinsic	phenomenal	hedge-markers? A	second	reason	to	find	out	whether	perceptual	experiences	can	be	states	of uncertainty	is	that	the	answer	to	this	question	bears	on	how	models	from	perception science	may	map	on	to	visual	phenomenology. Not	all	information	processed	by	our	perceptual	system	ends	up	in	our	perceptual experience.	If	perceptual	experiences	can	be	states	of	uncertainty,	then	the	discovery	of such	experiences	contributes	to	the	science	of	consciousness	by	clarifying	the	options	for how	models	in	perception	science	may	map	on	to	perceptual	experience. How	can	we	discover	whether	any	experiences	are	states	of	uncertainty?	A	method suggested	by	Denison	et	al	(2020)	is	to	start	from	models	of	the	features	detected	in	early vision	that	posit	various	forms	of	uncertainty	in	perceptual	processing,	such	as	signal detection	theory,	drift	diffusion	models,	probabilistic	population	codes,	or	sampling,	and then	try	to	figure	out	which	components	of	those	models	explain	any	phenomenal	features of	perceptual	experience,	such	as	experiences	of	orientation	or	the	direction	of	motion.	If any	of	the	components	that	explain	phenomenology	involve	uncertainty,	uncertainty	in	one way	or	another	will	be	reflected	in	experience.	Once	a	model	is	successful	at	explaining behavioral	data,	further	experiments	can	sometimes	help	rule	out	some	hypotheses	about which	information	represented	by	the	model	gets	inherited	by	experience.10 10	On	their	own,	none	of	the	models	discussed	by	Denison	et	al	determine	which	components	of	the model	maps	to	phenomenology	and	which	don't.	For	instance,	drift	diffusion	models	posit	accumulators that	gather	evidence	and	reach	a	perceptual	decision	when	the	accumulated	evidence	crosses	a threshold,	but	the	decision	threshold	can	be	set	in	different	places	depending	on	other	factors.	Once evidence	accumulates	to	the	decision	threshold	amount,	the	perceptual	system	represents	a	feature, such	as	leftward	direction	of	motion. If	the	phenomenal	character	of	visually	experiencing	leftward motion	is	sensitive	to	whether	the	threshold	is	reached,	then	a	stimulus	will	flit	in	and	out	of	visibility	as the	decision	threshold	moves,	even	if	the	amount	of	accumulated	evidence	stays	the	same.	As	Denison	et al	point	out,	so	long	as	the	decision	variable	can	be	controlled	and	the	evidence	accumulated	can	be measured,	it	is	possible	to	test	this	hypothesis. Susanna	Siegel	*	Explaining	uncertainty 8 This	approach	to	the	science	of	consciousness	involves	reasoning	about	what	else would	be	true	of	experience,	if	one	or	another	mechanism	posited	by	the	model	for perception	of	an	individual	feature	explained	perceptual	experience	of	that	feature.	There is	no	single	method	or	set	of	experiments	underlying	this	approach.	Instead	what's distinctive	is	the	inquiry	into	what	else	would	be	true	of	the	experiences	of	a	feature,	given assumptions	about	which	part	of	the	model	explains	the	experience. This	approach	has	to	navigate	the	enduring	methodological	challenge	that	since consciousness	involves	a	subject's	perspective,	it	is	hard	to	avoid	relying	on	subjects' reports,	yet	it	is	also	difficult	to	determine	whether	subjects'	reports	are	reporting perceptual	experience	or	merely	judgments	made	in	response	to	them.	This	obstacle	is	not necessarily	insurmountable,	but	it	is	one	place	where	philosophical	analyses	of phenomenology	may	help. A	different	challenge	is	specific	to	the	search	for	phenomenal	uncertainty.	While	it may	seem	clear	enough	what	phenomenal	character	experiences	of	orientation	or	direction of	movement	have,	it	is	much	less	obvious	what	perceptual	experiences	of	uncertainty might	consist	in. Understanding	the	nature	of	phenomenal	uncertainty	in	turn	clarifies hypotheses	about	which	types	of	uncertainty	posited	by	models	could	be	mapped	onto phenomenology,	by	clarifying	the	target	of	such	mappings.11 A	third	reason	to	try	and	discover	whether	experiences	can	be	states	of	uncertainty is	that	it	bears	on	the	roles	of	experiences	in	explaining	behavior.	As	we	will	see	next,	a powerful	argument	for	probabilistic	experiences	depends	on	hypotheses	about	the explanatory	relationships	between	experiences,	the	sensory	systems	that	produce	them, and	behavior	that	is	responsive	to	uncertainty. 2.	If	some	behavior	is	responsive	to	probabilistic	perception,	should	we	expect experiences	to	be	probabilistic? The	sensory	systems	that	produce	perceptual	experience	are	noisy,	since	the	same external	stimulus	causes	different	brain	responses	on	different	occasions.	In	addition, sensory	signals	in	the	brain	are	ambiguous,	in	that	the	same	signal	can	be	caused	by different	states	of	the	environment.	Keeping	track	of	these	two	forms	of	uncertainty	could 11	Another	challenge	concerns	interactions	between	phenomenal	features	of	experience.	The	models discussed	by	Denison	et	al	are	designed	to	explain	perceptual	decisions	about	individual	features	such as	orientation	or	the	direction	of	motion.	Some	aspects	of	perceptual	experience	involve	multiple features	that	interact	phenomenally,	for	instance	if	the	color	of	a	stimulus	depends	on	the	colors	of	the things	around	it,	or	the	sound	of	a	phoneme	depends	on	its	surrounding	phonemes,	or	the	speed	at which	a	thing	looks	to	be	moving	depends	on	the	luminance	features.	Some	cross-modal	effects	have	this structure	as	well,	such	as	the	McGurk	effect	involving	vision	and	audition.	For	many	phenomenal features	of	perceptual	experience,	it	may	not	be	possible	to	leverage	models	of	individual	features	into predictions	about	perceptual	experience. Susanna	Siegel	*	Explaining	uncertainty 9 benefit	the	perceiver,	and	there	is	evidence	that	the	perceptual	system	takes	account	of both	noise	and	ambiguity.12 How	does	the	perceptual	system	take	account	of	uncertainty?	Many	models	of perception	posit	computations	over	probabilistic	information,	or	approximations	of	such computations,	about	both	sources	of	uncertainty.	Such	attributions	of	probabilistic representations	in	the	perceptual	system	are	made	on	the	basis	of	behavior	predicted	by probabilistic	models,	and	in	that	sense	the	behavior	is	sensitive	to	probabilistic information.	In	these	cases,	there	appear	to	be	probabilistic	information	in	perceptual processing	and	behavior	that	is	sensitive	to	that	information,	where	the	behavior	is	also possible	to	rationalize	by	perceptual	experience. For	instance,	Walker	et	al	(2020)	gave	monkeys	a	task	to	decide	which	of	two distributions	over	orientations	a	grating	belongs	to,	where	the	two	distributions	share	a mean	but	differ	in	variance.	Some	orientations	belong	to	both	distributions,	while	others belong	only	to	the	distribution	with	the	wider	variance.	After	training	the	monkeys	to classify	gratings	correctly	by	color	(e.g.,	a	sample	was	colored	red	if	it	belonged	to	the	wide distribution	and	green	if	it	belonged	to	the	narrow	one),	the	color	was	removed	from	the samples,	and	the	monkeys	had	to	decide	which	distribution	samples	belonged	to	without relying	on	color	cues.	This	is	the	behavior	that	turned	out	to	be	sensitive	to	probabilistic information. The	sensitivity	showed	up	on	trials	where	the	orientation	of	the	sample	belonged	to both	distributions,	and	the	sample	was	also	shown	at	low	contrast.	The	low	contrast introduced	noise	in	the	monkey's	measurement	of	the	sample's	orientation.	As	before,	the monkeys	had	to	decide	which	distribution	the	sample	belonged	to.	Their	responses	were predicted	by	a	model	that	combines	information	taking	account	of	the	noise	surrounding the	measurement	of	the	sample's	orientation,	with	information	about	each	distribution over	orientations.	In	a	nutshell,	the	monkey's	behavior	matched	the	behavior	that	would	be produced	if	they	reasoned	that,	for	orientations	that	lie	near	the	intersection	of	the	two distributions,	the	noisier	a	sample	is,	the	more	likely	it	belongs	to	the	narrow	distribution, because	that	distribution	contains	more	orientations	close	to	the	measurement	shown	with noise	attached	to	it. On	this	model,	the	monkeys	behave	as	if	they	are	computing	over	two	kinds	of probabilistic	information:	how	likely	the	sample	is	to	have	various	orientations,	and	how likely	each	of	those	orientations	is	to	belong	to	each	distribution.	Their	behavior	is sensitive	to	probabilistic	information,	and	therefore	to	uncertainty	registered	by	the perceptual	system. Switching	from	monkeys	to	humans,	Walker	et	al's	(2020)	results	belong	to	a	body of	evidence	that	perceptual	systems	take	account	of	uncertainty	by	using	probabilistic 12	Helmholtz	(1856),	Ernst	and	Banks,	Knill	(1996),	Trommerhäuser	et	al	(2011),	O'Callaghan	et	al (2017). Susanna	Siegel	*	Explaining	uncertainty 10 information,	though	it	remains	a	major	question	what	sorts	of	computations	are	involved.13 If	that	suggestion	is	correct,	it	adds	to	the	evidence	that	some	human	behavior	that	we regularly	take	to	be	directly	responsive	to	perceptual	experience	is	also	sensitive	to uncertainty	registered	and	used	by	the	perceptual	system. If	perceptual	experiences	can	be	probabilistic,	then	there	would	be	a	throughway	for probabilistic	information	to	flow	from	sub-personal	perception	to	consciousness,	which could	in	turn	explain	behavior	that	is	sensitive	to	probabilistic	information.	This	picture has	no	need	for	transitions	between	non-probabilistic	perceptual	experiences	and probabilistic	information. This	observation	suggests	the	line	of	thought	that	I	will	criticize	in	section	3. Suppose	that	perceptual	experience	has	no	way	to	express	any	probabilistic	nuance, because	it	cannot	be	a	state	of	uncertainty.	If	behavior	that	we	regularly	assume	to	be guided	by	perceptual	experience	is	also	sensitive	to	probabilistic	information	in	subpersonal	perceptual	processing,	it	becomes	pertinent	to	ask	whether	experience	is	actually epiphenomenal	when	it	comes	to	explaining	behavior	sensitive	to	probabilistic information.	If	the	behavior	is	explained	by	the	probabilistic	information	that	is	left	out	of perceptual	experience,	what	explanatory	role,	if	any,	is	left	for	the	experience	to	play? Some	defenses	of	the	idea	that	probabilistic	perception	reaches	all	the	way	to experience	are	framed	around	the	supposed	choice	between	probabilistic	experiences	and epiphenomenal	ones.	As	noted	earlier,	Morrison	(ms)	argues	explicitly	from	the implausibility	of	epiphenomenal	experiences,	together	with	experimental	support	from Walker	et	al,	to	the	idea	that	perceptual	systems	take	account	of	uncertainty	by	using probabilistic	information.	We	met	this	line	of	thought	earlier,	in	the	introduction.	It	says that	if	perceptual	experience	explains	behavior,	and	some	of	that	behavior	is	sensitive	to probabilistic	information,	then	perceptual	experience	must	be	a	vehicle	for	probabilistic information	to	which	the	behavior	is	sensitive. Munton	(2015)	follows	a	similar	line	of	thought	when	she	defends	probabilistic experiences. She	appeals	to	the	explanatory	role	of	such	experiences	in	forming	and justifying	credences,	which	are	probabilistically	structured	degrees	of	confidence,	rather than	behavior,	but	the	basic	line	of	thought	is	the	same.	The	idea	that	experiences	are probabilistic	is	a	natural	hypothesis,	given	the	assumptions	that	there	are	behaviors sensitive	to	probabilistic	information	that	perceptual	experiences	seem	to	help	explain. Munton	and	Morrison	use	this	line	of	thought	in	defense	of	probabilistic	experiences,	but	it could	also	be	marshalled	in	defense	of	epiphenomenal	ones.	When	we	ask	whether	nonprobabilistic	experiences	could	explain	behavior	that	is	sensitive	to	probabilistic information,	what	kind	of	explanatory	role	is	at	issue? We	can	distinguish	between	a	merely	causal	role	for	experiences	in	explaining behavior,	and	a	role	that	makes	the	behavior	intelligible	from	the	subject's	own 13	For	examples	of	the	vast	discussion	of	this	issue,	see	Griffiths	et	al	2010a	and	2010b,	Icard	2016, Rahnev	2017. Susanna	Siegel	*	Explaining	uncertainty 11 perspective,	which	I'll	call	a	first-person	rationalizing	role	for	experience.	A	different	way for	an	experience	to	be	epiphenomenal	relative	to	a	behavior	is	for	it	to	fail	to	play	any causal	role	in	producing	the	behavior. The	most	robust	explanatory	role	for	experience	would	combine	both	causal	and first-person	rationalization	roles.	I	will	argue	that	perceptual	experiences	can	provide	firstperson	rationalizations	of	probabilistic	behavior,	even	if	the	experiences	are	not probabilistic.	I'll	leave	aside	what	causal	roles	experiences	actually	play	relative	to	such behavior.14	I	focus	on	the	first-person	rationalization	role	because	the	methods	available	to philosophy	are	well-suited	for	finding	out	whether	experience	plays	that	kind	of	role, whereas	discovering	its	causal	role	can	require	experimentation.	A	related	reason	to	focus on	the	first-person	rationalization	role	is	that	it	is	central	to	the	commonsense	assumptions about	experiences	that	the	line	of	thought	favoring	probabilistic	experiences	relies	on. If	my	conclusions	are	correct,	then	experiences	are	available	as	first-person rationalizations	of	behavior	sensitive	to	probabilistic	information,	regardless	of	their	causal role	in	producing	that	behavior. 3. Are	probabilistic	experiences	needed	to	explain	probabilistic	behavior? Suppose	a	subject's	perceptual	experiences	have	no	way	to	reflect	some	of	the information	to	which	their	behavior	is	sensitive.	Would	that	force	the	experiences	to	be epiphenomenal	with	respect	to	that	behavior? No. Perceptual	experiences	can	participate	in	a	division	of	explanatory	labor	with unconscious	perceptual	information,	post-perceptual	information,	or	both. For	instance,	suppose	experience	has	no	way	to	reflect	any	probabilistic	nuance,	but that	it	can	present	a	subject	with	multiple	incompatible	possibilities	at	once,	thereby making	them	salient	to	the	perceiver.	And	suppose	that	post-perceptually,	the	subject attaches	probabilistic	weights	to	each	option.	Here,	one	could	read	off	from	experience	the hypotheses	to	which	probabilistic	weights	are	assigned,	even	if	one	could	not	read	off	the weights	that	are	assigned	to	each	of	them.	One	would	not	be	reasoning	in	the	dark,	if	one assigned	probabilistic	weights	to	multiple	hypotheses	made	salient	by	one's	experience, such	as	the	hypothesis	that	a	darting	butterfly	is	on	a	leftward	trajectory	and	the hypothesis	that	it's	on	a	rightward	trajectory. A	different	way	for	experiences	to	rationalize	behavior	in	light	of	the	contribution from	other	non-experiential	states	is	illustrated	by	behavior	that's	guided	by	the	dorsal stream,	such	as	the	visually	impaired	subject	DF's	ability	to	post	a	card	through	a	slot.15 14	Compare	the	controversies	surrounding	Libet's	conclusions	about	free	will,	which	seem	to	contradict the	commonsense	assumption	the	states	our	brains	were	in	before	we	decide	to	act	do	not	prevent	our decisions	from	being	free	(Libet	1982,	Wegner	2002,	Bayne	2004). 15	Goodale	and	Milner	1992.	Like	many	participants	in	experiments,	DF	is	known	by	her	initials.	See Ganel	et	al	(2019)	for	discussion	of	the	status	of	DF's	experience. Susanna	Siegel	*	Explaining	uncertainty 12 DF's	visual	experience	is	degraded	so	much	that	she	cannot	see	how	the	slot	is	oriented.	Yet she	can	post	a	card	through	it,	successfully	positioning	her	hand	to	match	the	card's orientation	with	the	orientation	of	the	slot.	DF's	sensory-motor	success	is	apparently	not guided	by	any	visual	experience	of	orientation,	but	instead	by	orientation	information	that bypasses	it,	while	remaining	available	for	her	to	use.	Her	visual	system	processes information	about	the	slot's	orientation,	but	her	experience	does	not	inherit	that information. If	the	orientation	information	DF	uses	never	reaches	consciousness,	that	fact	does not	make	her	visual	experience	irrelevant	to	explaining	how	she	posts	the	card	through	the slot.	If	DF's	visual	experience	indicates	the	direction	in	which	the	slotted	surface	is	located, then	it	won't	be	entirely	epiphenomenal.	By	contrast,	if	her	visual	experience	is	too degraded	to	provide	any	information	that	DF	could	use	to	guide	her	card-posting	behavior, then	it	will	be.	The	crucial	factor	in	determining	whether	experience	is	epiphenomenal	is what	information	other	than	orientation	the	experience	conveys,	not	whether	any unconscious	information	guides	behavior. A	special	case	of	unconscious	information	is	unconscious	probabilistic	information. Perceptual	experience	can	retain	a	first-person	rationalizing	role	with	respect	to	behavior, even	when	it	joins	forces	with	unconscious	probabilistic	information	to	which	the	behavior is	sensitive.	Here	are	three	examples. First,	experiences	could	present	a	point	value	estimate	of	a	feature,	such	as	a	degree of	orientation	or	a	distance,	and	then	any	uncertainty	surrounding	that	point	value	could	be encoded	in	the	role	of	experiences	in	subsequent	reasoning	that	uses	probabilistic information.	One	could	not	recover	probabilistic	information	from	the	experience	alone. But	one	could	recover	it	jointly	from	the	experience,	which	phenomenally	presents	a	point estimate	of	orientation,	and	other	perceptual	states,	which	encode	the	variance surrounding	that	point	estimate.	A	proposal	like	this	is	made	by	Shea	and	Frith	(2019).16 Second,	suppose	an	experience	has	the	phenomenal	content	p,	with	which	it phenomenally	represents	an	orientation.	Since	p	is	a	phenomenal	content,	any	two experiences	with	that	orientation	content	p	will	be	the	same	with	respect	to	the phenomenal	character	that	p	helps	characterize.	And	suppose	the	same	experience	also non-phenomenally	represents	a	hedge	on	that	orientation.	For	instance,	the	experience	has non-phenomenal	probabilistic	content	.7p	if	.7	measures	how	strongly	you	are	disposed	to rely	on	this	experience	that	p	in	subsequent	reasoning,	what	confidence	reports	you	are disposed	to	make,	and	whether	you	are	disposed	to	look	again	before	you	act	on	the information.17	But	these	elements	could	be	accompanied	by	a	middling	amount	of	felt 16	For	Shea	and	Frith	(2019),	the	metacognitive	representation	of	the	variance	is	a	phenomenally conscious	and	part	of	perception,	though	its	contents	do	not	co-vary	with	phenomenal	character. 17	Since	these	things	could	in	principle	come	apart,	I'm	idealizing	in	supposing	that	there	is	a	single dimension	of	strength	that	the	probabilities	can	measure	here.	Exactly	what	dimensions	of	perception probabilistic	can	usefully	measure	is	a	central	question	in	assessing	the	general	idea	that	perception	is probabilistic.	I	return	to	this	question	in	section	5.	See	also	Pohl	(ms). Susanna	Siegel	*	Explaining	uncertainty 13 fluency	in	producing	a	report	on	the	orientation,	or	a	feeling	that	the	answer	is	on	the	tip	of the	tongue,	or	a	general	feeling	of	uncertainty.18	Here,	probabilistic	behavior	is	rationalized from	a	first-person	perspective	by	phenomenal	features	that	only	contingently	accompany (non-phenomenal)	probabilistic	contents:	the	phenomenal	content p	of	perceptual experience,	and	the	possibly	non-perceptual	feelings	of	fluency,	etc.	The	perceptual experience	can	still	contribute	to	first-person	rationalizations	of	behavior. Finally,	Vance	(2020)	argues	that	degrees	of	blur	in	experience	rise	and	fall	with degrees	of	precision	registered	in	processes	that	produce	it,	and	that	blur	is	a	manner	of representing	external-world	contents.	If	blur	could	make	it	rational	from	a	subject's	point of	view	to	become	uncertain	about	how	far	away	something	is	or	exact	orientation,	then	we have	another	potential	division	of	labor	in	explaining	behavior	that	is	sensitive	to probabilistic	information.	Blur	would	provide	the	first-personal	rationalization	for uncertainty,	while	unconscious	probabilistic	information	explains	more	fine-grained patterns	of	behavior	(an	example	is	coming	shortly).19 These	examples	show	that	experiences	can	contribute	to	first-personal	rationalizing explanations	of	behavior,	even	when	the	behavior	is	sensitive	to	unconscious	probabilistic information. My	conclusion	so	far	is	an	instance	of	a	more	general	claim:	building	uncertainty into	experience	is	not	needed	to	explain	why	a	subject	ends	up	uncertain	about	something she	consciously	perceives.	Suppose	you	want	to	know	the	age	of	a	person	you're	seeing. The	wrinkles	on	their	hands	suggest	they	are	over	forty,	while	their	hair	color	suggests they	are	under	forty.	So	you	have	two	competing	suggestions,	which	together	leave	you uncertain	as	to	whether	this	person	is	over	forty.	Yet	you	need	not	be	uncertain	about	how wrinkled	or	grey	you	find	their	hands	or	hair.	So	it	is	not	true	in	general	that	a	mental	state that	explains	why	a	subject	ends	up	uncertain	has	to	be	a	state	of	uncertainty	of	its	own. A	final	consideration	against	expecting	continuity	of	probabilistic	information	from perceptual	processing	via	experience	to	behavior	becomes	visible	if	we	look	backward from	perceptual	experience	to	sub-personal	processes	that	produce	it.	Suppose	your	visual system	stores	information	of	the	form:	"under	conditions	C,	it's	80%	likely	that	the important,	valuable	interesting	stimuli	are	to	the	left,"	and	as	a	result,	80%	of	the	time when	you're	in	conditions	C,	you	look	to	the	left.	Then	your	pattern	of	sensory	behavior	is reflecting	uncertainty	registered	by	your	visual	system.	And	since	this	behavior	helps determine	what	you	perceptually	experience,	a	pattern	of	experience	is	reflecting	this uncertainty	as	well. This	kind	of	propensity	to	look	to	the	left	is	a	disposition,	it	can	come	in	different strengths,	and	those	differences	could	be	measured	by	probability	(Icard	2016).	So	here	is a	case	where	probabilistic	information	upstream	of	experience	leaves	its	mark	on	the 18	These	proposals	come	from	Shea	(personal	communication). 19	For	blur	to	provide	a	first-person	rationalization	of	behavior,	must	it	be	an	intrinsic	phenomenal hedge-marker?	No.	This	point	is	discussed	in	section	4.1. Susanna	Siegel	*	Explaining	uncertainty 14 pattern	of	experiences	you	have,	namely	the	experiences	of	whatever	is	on	your	left. But for	all	the	pattern	shows,	you	couldn't	read	off	any	probabilistic	information	from	the phenomenal	character	of	experience,	even	if	you	could	read	off	from	the	frequency	of	such experiences.	In	this	way,	sensory	behaviors	that	are	calibrated	with	probabilistic information	would	provide	a	way	for	non-probabilistic	experiences	to	reflect	uncertainty, without	being	a	state	of	uncertainty. All	of	these	observations	count	against	the	line	of	thought	that	if	perceptual processing	is	probabilistic,	and	if	behavior	is	sensitive	to	any	of	the	probabilistic information	processed,	then	we	should	expect	perceptual	experience	to	be	probabilistic,	so that	a	special	explanation	is	needed	of	why	it	isn't,	if	it	isn't.20	If	there	is	no	reason	to	expect experiences	to	be	probabilistic	just	because	perceptual	processing	is,	then	no	special explanation	is	needed.	What	would	be	needed	instead	is	arguably	an	account	of	how experiences	helps	explain	probabilistically	sensitive	behavior	if	they're	not	probabilistic. I've	given	reasons	to	doubt	that	the	relationships	between	probabilistic	perceptual processing	and	perceptual	experience	and	behavior	support	probabilistic	experiences. I now	consider	the	more	fundamental	question	whether	any	experiences	can	intrinsically	be states	of	uncertainty.	I'll	argue	that	some	experiences	may	well	be	states	of	uncertainty	– contrary	to	the	standard	picture	of	perceptual	phenomenology	described	in	section	1.	In addition	to	challenging	a	longstanding	assumption	about	perceptual	consciousness,	this result	gives	us	some	leverage	on	assessing	whether	any	experiences	are	probabilistic. 4.	The	challenge	from	wobbly	trajectories The	standard	picture	is	that	perceptual	phenomenology,	as	distinct	from phenomenal	imagination	and	phenomenal	memory	purports	to	present	subjects	with	a unique	way	in	which	external	things	are	actually	present	at	the	moment	of	perception. This picture	is	compatible	with	phenomenal	features	that	mark	a	hedge	by	the	roles	they	play	in the	mind,	but	only	when	those	roles	are	only	contingently	played	by	the	experience. For	instance,	earlier	we	discussed	probabilistic	information	taken	account	of	by perceptual	processing	that	remains	unconscious.	Some	philosophers,	including	Shea (2018),	develop	theories	of	content	according	to	which	some	such	probabilistic information	is	represented	in	perceptual	experience,	in	the	form	of	non-phenomenal content	(by	definition,	having	such	content	is	a	representational	feature	that	does	not supervene	on	phenomenal	character). You	could	hold	constant	the	phenomenal	character of	the	experience	and	vary	whether	the	subject	is	related	to	the	environment	in	ways	that would	establish	the	kind	of	representation	relation	that	is	definitive	of	content	as	Shea construes	it. The	standard	picture	is	also	compatible	with	phenomenal	features	that	only contingently	cue	uncertainty.	For	instance,	if	you	learn	to	associate	a	high	pitch	with uncertainty	about	orientation	of	a	line	that	you	see	or	touch,	nothing	intrinsic	to	the	pitch 20	An	evolutionary	explanation	is	offered	by	Clark	(2018),	who	suggests	that	probabilistic	experiences would	be	worse	at	guiding	decisions	than	non-probabilistic	ones	and	therefore	wouldn't	be	selected. Susanna	Siegel	*	Explaining	uncertainty 15 tells	you	about	orientation	or	how	uncertain	you	should	be	about	it.	Or	if	your	experience leaves	you	disposed	to	make	confidence	reports	partly	based	on	it,	that	disposition,	too, may	be	only	contingently	associated	with	an	experience.	For	instance,	you	might experience	a	line	oriented	at	+5	degrees,	but	in	one	condition	a	subject	might	be	disposed to	report	relatively	less	confidence	that	it	has	that	orientation,	and	in	another	condition	one might	be	disposed	to	report	relatively	more,	even	though	the	phenomenal	character	is	the same	both	times. In	these	examples,	the	roles	of	experience	that	mark	the	hedges	are:	a	disposition	to produce	confidence	reports	in	response	to	experience;	and	being	related	to	the environment	in	a	way	that	establishes	the	experience	as	a	representation	of	probabilistic information. The	standard	picture	is	compatible	with	experiences	that	play	either	of	these roles. By	contrast,	the	standard	picture	is	incompatible	with	phenomenal	features	that	in their	own	nature	(intrinsically)	qualify	information	about	the	external	world.	What	kinds	of phenomenal	features	could	constitute	such	a	hedge? A	first	kind	would	be	a	meta-cognitive	layer	of	representation	about	the	status	of other	contents	of	experience.	For	instance,	an	experience	might	present	a	line	as	oriented ten	degrees	to	the	left,	and	then	include	another	representation	that	the	line	might	be	a	bit more	or	less	than	ten	degrees. The	central	challenge	is	to	characterize	the	phenomenal	hedge,	without	relying	on roles	that	only	contingently	accompany	the	phenomenal	character,	or	on	roles	that establish	non-phenomenal	probabilistic	contents,	or	on	feelings	of	uncertainty	formed	in response	to	perceptual	experience.	It	is	a	difficult	challenge	because	perceptual	experience purports	to	tell	us	how	things	are	in	in	our	immediate	environment,	whereas	uncertainty surrounding	perception	is	about	our	relationship	to	the	information	about	those circumstances.	Is	there	any	hedge	intrinsic	to	perceptual	consciousness? A	natural	suggestion	is	that	in	the	visual	case,	blur	is	an	intrinsic	phenomenal	hedgemarker.	Suppose	that	Vance	(2020)	is	correct	that	degrees	of	blur	rise	and	fall	with	degrees of	precision.	If	there	is	an	informational	throughway	for	probabilistic	information	of	the sort	under	discussion	here,	then	blur	should	be	a	phenomenal	feature	that	conveys probabilistic	information.	A.	D.	Smith	may	have	been	suggesting	as	much	when	he	wrote "the	animal	response	to	blur	is	uncertainty."21	More	exactly,	blur	would	be	an	intrinsic phenomenal	hedge-marker	if	it	were	non-contingently	related	to	a	perceptual	mode	of middling-to-low	proto-confidence. But	what	are	proto-confidences?	The	face-value	argument	may	help	operationalize them.	We	can	ask:	guided	only	by	experience	of	a	feature,	without	relying	on	background beliefs	or	conditioned	habits	(such	as	associating	high	pitch	with	uncertainty	about 21	Smith	(2008) Susanna	Siegel	*	Explaining	uncertainty 16 orientation),	would	it	make	sense	from	a	first-person	perspective	to	end	up	uncertain about	that	feature? We	can	use	this	operationalization	to	assess	whether	blur	is	a	phenomenal	hedgemarker.	To	develop	it	into	a	proposal	about	blur	that's	exact	enough	to	assess,	it	can	be refined: For	any	feature	F	presented	in	experience,	if	you	blurrily	experience	something	as	F, then	going	just	by	experience,	it	would	make	sense	from	a	first-person	perspective to	become	uncertain	about	whether	the	thing	is	F. A	complementary	idea	is	that	degrees	of	blur	rise	and	fall	with	how	uncertain	it	would make	sense	to	be	about	whether	the	thing	really	is	F,	when	guided	just	by	your	experience. Analogous	proposal	could	be	formulated	for	low	contrast.22 These	proposals	seem	to	be	false.	For	many	features	F,	some	amounts	of	blur	need not	leave	person	any	less	uncertain	that	they	would	be	if	they	were	experiencing	something as	F	clearly	instead	of	blurrily.	Blurred	red	can	still	appear	red,	a	blurred	human	form	still appear	plainly	to	be	a	human	form,	and	blurred	things	moving	toward	me	can	still	plainly appear	to	be	moving	toward	me.	Increasing	blur	need	not	leave	me	less	certain	that	the form	is	human,	and	decreasing	it	need	not	increase	my	certainty. Smith's	idea	that	blur	per	se	is	a	phenomenal	hedge-marker	may	arise	from mistaking	it	for	a	different	point:	that	compared	to	clear	vision,	blurred	vision	changes	the information	one	can	get	from	a	scene	by	reducing	spatial	frequencies,	presenting	obstacles to	the	flow	of	some	kinds	of	information.	It	can	be	difficult	to	read	with	vision	so	blurred that	the	lines	distinguishing	the	letters	from	one	another	can't	easily	be	made	out.	But what's	at	issue	here	is	whether	blur	per	se	is	a	hedge	marker,	operationalized	as	rationally generating	uncertainty	if	one	isn't	relying	on	background	information.	The	fact	that	it doesn't	always	play	that	role	shows	that	nothing	internal	to	blur	makes	it	constitute	a hedge	on	external-world	content. Similar	points	hold	for	low	contrast.	Backlit	cubes	can	look	just	as	cubical	as	fullly	lit ones,	and	if	I	end	up	confident	that	it's	a	cube,	I	need	not	be	relying	on	information independent	from	my	visual	experience. These	considerations	reinforce	the	challenge	of	finding	a	pair	of	phenomenal aspects	of	experience,	where	one	aspect	qualifies	the	status	of	what's	presented	in	the other	aspect.	A	way	to	meet	this	challenge	is	to	find	cases	in	which	experiences	present multiple	incompatible	possibilities	at	once,	by	making	such	possibilities	salient	in	the subject's	perceptual	consciousness. We	can	say	that	experiences	structured	in	this	way	are 22	For	example,	"For	any	feature	F	presented	in	experience,	if	you	experience	F	at	low	contrast,	it	would make	sense	from	a	first-person	perspective	to	become	uncertain	about	whether	the	thing	is	F." Susanna	Siegel	*	Explaining	uncertainty 17 multiplex.23	The	structure	of	multiplex	experiences,	I'll	argue,	provide	a	more	promising candidate	for	an	intrinsic	phenomenal	hedge	markers	than	blur. 4.1	Multiplex	experiences Being	multiplex	per	se	does	not	suffice	for	making	experiences	into	a	state	of uncertainty	(or	therefore	into	an	intrinsic	phenomenal	hedge-marker),	because	some multiplex	experiences	present	a	single	object	as	having	incompatible	features,	such	as	the magic	fork	(Figure	2)	which	looks	to	have	two	prongs	at	one	end,	and	at	the	other	end	it looks	to	have	three	prongs.	Just	as	(unfortunately)	there	need	be	no	hedging	if	someone asserts	a	contradiction,	in	principle,	it	seems,	one	could	experience	an	impossible	figure without	one's	experience	hedging	on	whether	the	item	really	has	all	the	features	it	appears to	have.	The	Escher	staircase	is	visually	compelling	to	look	at	because,	amazingly,	it	seems to	keep	going	up	even	while	forming	a	circuit. Multiplex	experiences	will	be	states	of	uncertainty	if	the	possibilities	made	salient are	experienced	as	exclusive.	Can	perceptual	experience	make	a	range	of	incompatible possibilities	salient	to	the	mind,	where	the	possibilities	in	the	range	are	marked	with	a hedge	indicating	that	the	scenarios	presented	are	ways	things	might	be,	but	also	might	not be?24 A	natural	candidate	for	multiplex	states	of	uncertainty	comes	from	the	kind	of	multistable	experiences	typically	caused	by	binocular	rivalry.	If	you	are	shown	a	different stimulus	in	each	eye,	such	as	a	house	and	face,	typically	your	experience	will	flip	between	a house-percept	and	a	face-percept.25	Because	the	information	from	each	side	of	the	flip	is not	easily	integrated,	it	would	be	rational	and	normal	to	remain	uncertain	of	what	you're seeing,	if	you	didn't	know	you	were	getting	different	stimuli	in	each	eye. But	what	if	each	experience	that	you	flip	between	is	a	distinct	experience?	Then	we will	have	alternation	between	non-multiplex	experiences,	rather	than	a	single	multiplex experience	presenting	different	incompatible	possibilities. 23	The	possibilities	are	made	salient	in	the	minimal	sense	that	they	are	present	to	the	subject's	mind.	The experience	has	contents	that	characterize	multiple	scenarios,	making	those	scenarios	present	to	the mind	as	distinct	ways	the	world	could	be. For	a	richer	notion	of	salience	used	to	the	describe	the internal	organization	of	experience	into	things	relatively	more	peripheral	or	central	to	perceptual consciousness,	see	Dicey-Jennings	(2020)	and	Watzl	(2019). 24 In case it helps bring this question into focus, consider a non-perceptual analogy. Suppose that while you're wondering whether the sound you hear in the desert is caused by a coyote or a baby, you imagine that it is caused by a witch disguising herself as a baby. Here you are actively holding in your consciousness these three incompatible options COYOTE, BABY, and WITCH and none of them are marked in your consciousness as "actual". The COYOTE and BABY options are epistemic possibilities for you that pass through your mind while you're in the throes of inquiry, whereas WITCH is an epistemically impossible far-off (logical) possibility brought to mind by your creative imagination. (p is epistemically possible for a subject S iff p is possible, for all S knows.) As this case illustrates, imagination and inquiry can make a range of incompatible possibilities of various kinds salient to you, as can mind-wandering, conversation, and reading. The question here is whether perceptual experience can perform the same function that imagination or inquiry can. 25	In	some	conditions,	there	can	be	fusion	(Klink	2017,	Gershman	2012,	Block	2019.) Susanna	Siegel	*	Explaining	uncertainty 18 In	this	case	individuation	is	a	partly	conceptual	matter.	You	could	hold	constant	the stimuli	and	the	phenomenal	character,	but	change	only	the	theoretical	decision	about whether	the	subject	is	undergoing	a	single	dynamic	experience	or	a	sequence	of	separate ones.26	So	whether	multi-stable	experiences	are	states	of	uncertainty	is	somewhat	up	for grabs.	A	stronger	candidate	would	be	a	multiplex	experience	that	presents	us	with incompatible	trajectories	over	a	short	duration,	but	where	we	have	a	firmer	motivation	to treat	it	a	single	dynamic	experience. The	structure	of	these	cases	is	analogous	to	someone	who	says	on	Sunday	that	since Friday	they	have	uninterruptedly	been	and	are	continuing	on	a	single	career	trajectory:	to become	a	sculptor,	and	then	on	Monday	say	that	since	Friday,	they	have	uninterruptedly been	and	are	continuing	on	a	single	career	trajectory:	to	become	a	lawyer.	Such	a	person's reports	could	not	both	be	true.	Experiences	of	wobbly	trajectories	may	have	this	same structure. 4.2	Butterflies	and	knuckleballs It	is	hard	to	catch	a	butterfly	as	it	darts	and	flutters	because	none	of	its	movements allow	us	to	predict	what	its	next	movement	will	be.	If	we	watch	long	enough,	for	instance for	five	seconds,	we	might	see	its	overall	direction	of	movement,	but	smaller	segments	of this	trajectory	would	offer	competing	cues	to	its	overall	direction. As	in	multi-stable experiences,	the	temporal	segments	of	the	experience	present	incompatible	things.	In	one micro-segment	of	the	experience,	the	butterfly	darts	to	the	left,	and	the	next	micro-segment it	darts	to	the	right.	But	unlike	multi-stable	experiences	that	alternate	between	house	and face,	here,	if	we	consider	the	experience	encompassing	both	segments,	we	have	competing cues	as	to	its	trajectory. The	same	situation	on	an	even	smaller	time	scale	can	be	found	in	a	type	of	pitch	in baseball	known	as	a	knuckleball,	one	of	the	most	unpredictable	breaking	pitches. Knuckleballs	dart	and	waffle,	making	it	hard	to	predict	the	ball's	path	and	hit	it.27	Since trajectories	are	plausibly	features	presented	in	experience	over	durations,	these experiences	present	you	with	multiple	incompatible	trajectories	at	once. At	this	point,	one	might	object	that	none	of	these	examples	are	really	experiences	of multiple	options	as	incompatible,	on	the	grounds	that	what's	presented	in	experience	is something	of	the	form	"Possibly	P",	such	as	"it's	possible	that	the	ball	is	on	trajectory	T1" and	"it's	possible	that	it	is	on	T2". And	just	as	you	could	believe	two	claims	of	the	form "Possibly	P"	without	contradiction,	if	you	experienced	both	"possibly	x	is	on	trajectory	T1" and	"possibly	x	is	on	trajectory	T2",	this	would	not	be	a	case	of	experiencing	multiple incompatible	options. The	challenge	might	seem	to	be	deepened	by	comparing	it	to	an	experience	of instability,	a	disposition	of	something	wobbly	to	topple	over.	For	instance,	imagine	a	visual experience	of	a	rock	balanced	precariously	on	another	rock.	Here,	one	is	experiencing	a 26	Lewis	(1986)	makes	a	similar	proposal	about	event	individuation. 27	https://en.wikipedia.org/wiki/Knuckleball Susanna	Siegel	*	Explaining	uncertainty 19 property	(instability)	that	the	rock	actually	has.	The	experience	need	not	be	hedging	on whether	the	rock	is	unstable,	or	on	how	unstable	it	is. In	reply,	the	experiences	described	here	are	hedging	on	which	trajectory	is	currently unfolding.	In	granting	that	the	phenomenal	contents	of	the	experiences	include	"Possibly the	trajectory	is	T",	the	objector	grants	there	is	a	phenomenal	hedge.28 The	experience	of	the	rock	is	different.	This	experience	need	not	be	hedging	on whether	the	unstable	rock	will	actually	fall.	Any	uncertainty	about	that	is	a	response	to	the perceptual	experience	of	instability.29	It	would	be	reasonable	to	be	uncertain	whether	the rock	will	fall	in	response	to	the	experience,	but	if	the	rock	is	balancing	without	moving	at all,	there	is	no	ambiguity	about	its	trajectory	because	it	is	not	on	a	trajectory. If	no	experiences	were	states	of	uncertainty,	then	there	would	be	no	probabilistic experiences	either.	If	some	experiences	of	wobbly	trajectories	are	states	of	uncertainty, then	the	standard	view	would	need	to	drop	the	requirement	that	perceptual	experiences present	a	unique	way	that	things	actually	are. An	adjusted	version	of	the	distinction	might hold	that	perceptual	experiences	purport	to	present	the	subject	with	ways	things	actually are	at	the	time	of	the	experience,	allowing	that	multiplex	experiences	concern	candidates for	how	things	actually	are	at	that	time,	rather	than	ways	things	were	in	the	past	or	could be	at	some	other	time	or	in	some	other	world. My	cases	for	wobbly	experiences	as	states	of	uncertainty	does	not	rule	out	all possibly	alternatives.	In	the	case	of	knuckleballs,	one	might	try	to	argue	that	the	experience presents	shifts	in	the	ball's	direction,	without	specifying	which	directions	these	are.	This analysis	would	not	create	any	need	to	adjust	the	standard	view	at	all.	What's	important	in this	context	is	that	if	some	experiences	may	well	be	states	of	uncertainty,	and	if	any	are, then	that	result	opens	the	question	whether	this	experiential	uncertainty	is	ever probabilistically	structured	or	otherwise	measurable	by	probability. From	here,	I	am	going	to	grant	for	the	sake	of	argument	that	some	experiences	are states	of	uncertainty	and	argue	that	none	of	them	are	probabilistically	structured	or 28	The	kind	of	possibility	would	have	to	be	a	type	of	epistemic	possibility,	so	that	p	is	possible	for	S	in this	sense	just	in	case:	"For	all	S	would	be	justified	in	believing	on	the	basis	of	S's	experience	alone:	p" For	instance,	if	an	experience	of	a	dotted	card	would	give	you	with	immediate	justification	to	think	the card	has	9	dots,	and	would	also	give	you	justification	to	think	it	has	10	dots,	then	"Possibly:	it	has	9	dots" would	be	a	content	of	experience.	In	her	discussion	of	this	example	(which	is	from	Silins	2011)	Munton (2016)	suggests	that	experiences	hedge	in	just	this	way. 29	Compare	McGinn's	(1996)	claim	against	dispositionalism	about	color	that	"You	do	not	see	what	would obtain	in	certain	counterfactual	situations;	you	see	only	what	actually	obtains.	When	you	see	something as	red	you	do	not	see	the	counterfactual	possibilities	that	constitute	its	having	a	disposition	to	appear red.	Your	eyes	do	not	respond	to	woulds	and	might	have	beens."	McGinn	is	moving	illicitly	from	the	plain fact	that	we	can't	perceive	what's	merely	possible	to	the	conclusion	that	we	can't	be	presented	with dispositional	properties.	It	is	part	of	"what	actually	obtains"	that	the	rock	is	disposed	to	topple	over	(ie that	is	unstable),	and	plausibly	this	dispositional	property	can	be	presented	in	experience. Susanna	Siegel	*	Explaining	uncertainty 20 measurable.	Readers	who	are	think	that	no	experiences	are	states	of	uncertainty	will	have reached	the	same	conclusion	already. 5.	Are	experiences	probabilistic?	The	proto-confidence	analysis So	far,	I've	argued	against	the	standard	picture	of	perceptual	phenomenology, according	to	which	all	perceptual	experiences	present	things	as	actually	occurring concurrently	with	the	perception.	I	made	the	case	that	some	experiences	of	conflicting trajectories	falsify	this	universal	claim. A	special	case	of	an	experience	presenting	the	subject	with	multiple	incompatible possibilities	would	be	that	it	presents	possibilities	as	weighted.	Here,	the	phenomenal hedge	would	also	be	weighted	in	a	way	that	forms	a	probability	distribution.	This	picture can	be	developed	into	what	I'll	call	the	proto-confidence	analysis	of	experience. Just	as	the	standard	picture	makes	a	universal	claim	about	all	experiences,	the proto-confidence	analysis	makes	equally	far-reaching	universal	claims.	It	is	an	analysis	of how	phenomenal	character	is	structured.	According	to	version	I'll	consider	here,	it	is structured	by	a	set	of	relations	I'll	call	"perceptual	seeming	relations". A	relation	to	contents	is	a	perceptual	seeming	relation,	if	it	is	a	relation	to	contents by	virtue	of	which	you're	phenomenally	perceptually	presented	with	the	things	the contents	characterize,	and	if	the	relation	is	distinct	from	belief,	judgment,	or	anything	else doxastic.	For	instance,	if	you're	phenomenally	perceptually	presented	with	a	person coming	to	greet	you	and	the	same	person	coming	to	greet	someone	else,	then	on	this analysis,	you'd	stand	in	two	perceptual	seeming	relations,	each	one	to	a	content characterizing	each	of	the	possibilities.	On	this	analysis,	experience	can	make	salient multiple	incompatible	possibilities	at	once. A	further	step	assigns	weights	to	them	that	are	measurable	by	probabilities.	This step	develops	two	ideas:	that	there	are	intrinsic	phenomenal	hedge-markers	in	the	form	of degrees	of	perceptual	seeming	relations,	and	that	these	hedge-markers	are	probabilistically structured. I'll	call	any	degreed	perceptual	seeming	relations	measurable	by	probabilities "proto-confidence	relations."	Just	as	there	are	many	credence	relations,	there	are	many proto-confidence	relations.	In	this	framework,	there	could	be	such	a	thing	as	its perceptually	seeming	to	degree	.7	that	a	sound	is	made	by	a	coyote,	and	its	simultaneously perceptually	seeming	to	degree	.3	that	the	sound	is	made	by	a	human	baby. The	witch hypothesis	from	our	earlier	example	wouldn't	show	up	in	proto-confidences	because	it	is made	salient	by	imagining,	not	by	perceptual	experience.30 30 In illustrating the proto-confidence analysis, I've used an example involving the sophisticated property of being a coyote to maintain continuity with earlier examples. But the proto-confidence analysis does not depend on the idea that such sophisticated properties could not be representable in perceptual experience. Susanna	Siegel	*	Explaining	uncertainty 21 Proto-confidences	would	be	experiences	built	out	of	proto-confidence	relations.	If experiences	are	proto-confidences,	then	they	have	features	that	merit	using	probabilistic formalism	to	describe	them.	Formal	structures	such	as	probability	are	apt	for	analyzing psychological	states	only	when	those	states	independently	have	the	structure	that	the formalism	helps	describe.	The	conceit	of	the	proto-confidence	analysis	is	that	experiences have	such	features. There	is	a	dimension	of	phenomenal	character	of	perceptual experience	that	comes	in	degrees	measurable	by	probability.	Since	nothing	in	the formalism	itself	identifies	what	thing	in	the	mind	the	formalism	measures,	that	task	is	left to	some	other	type	of	analysis,	such	as	phenomenology	for	perceptual	experience,	cognitive modeling	for	perceptual	processing,	or	philosophy	for	credences. It	is	worth	noting	that	in	their	critical	survey	of	the	history	of	attempts	to	analyze the	type	of	confidence	measured	by	probability,	Ericsson	and	Hajek	(2007)	conclude	that none	of	those	attempts	succeed,	and	suggest	that	credences	are	best	taken	as	a psychological	primitive.	Their	discussion	highlights	the	challenge	of	finding	person-level psychological	underpinnings	for	probability	to	measure.	If	Ericsson	and	Hajek's	criticisms of	all	extant	attempts	to	operationalize	credences	are	correct,	it	suggests	that	the	best reasons	to	think	the	mind	is	probabilistically	measurable	will	come	from	other	things	that can	be	explained	on	that	assumption. An	explanation	of	that	sort	is	exactly	what	Munton	and	Morrison	offer	for perceptual	experience.	I've	focused	on	their	strategy	for	defending	proto-confidences because	it	says	proto-confidences	are	needed	to	explain	probabilistic	behavior.	In	section	3, I	criticized	this	strategy.	Munton	also	makes	the	case	that	proto-confidences	can	explain	the formation	of	rational	credences.	I	return	to	this	point	shortly. I	now	to	turn	from	a	strategy	used	to	defend	proto-confidences	to	the	protoconfidence	analysis	itself.	The	key	question	is	whether	there	is	a	phenomenal	dimension	to experience	that	can	be	measured	by	probabilities.	By	using	the	same	formalism	for	a different	purpose,	the	proto-confidence	analysis	commits	to	the	idea	that	experiences	are similar	enough	to	credences	to	merit	probabilistic	analysis,	but	different	enough	from credences	to	be	perceptual	precursors	of	credences,	rather	than	credences	under	another name. Morrison	(2015)	proposes	the	proto-confidence	analysis	as	an	account	of	invariant phenomenal	features	of	perceptual	experience.	When	introducing	the	view	(which	he	calls "Perceptual	Confidence"),	he	writes: "Perceptual	confidence	is	...about	how	your	experiences	present	objects	and properties...[it]	extends	an	earlier	shift	in	our	thinking.	In	the	1960s	...many philosophers	attributed	contents	to	beliefs	but	not	to	perceptual	experiences.	In the	1980s	many	started	attributing	contents	to	experiences...	because	they became	convinced	that	experiences	are	belief-like	in	many	ways...	...Jumping	to the	present,	many	contemporary	philosophers	attribute	degrees	of	confidence	to beliefs	but	not	to	experiences.	...According	to	perceptual	confidence,	experiences are	belief-like	in	yet	another	way:	they	can	assign	more	or	less	confidence... ...One Susanna	Siegel	*	Explaining	uncertainty 22 could	selectively	endorse	Perceptual	Confidence	in	some	cases	but	not	others.	But it	most	naturally	applies	to	all	or	none."31 The	proto-confidence	analysis	modifies	the	set	of	contrasts	posited	by	the	standard	view.	It says	that	perceptual	experience	can	identify	a	range	of	scenarios	and	presents	each	of	them as	a	way	that	things	might	actually	or	might	not	be,	instead	of	presenting	a	single	way things	are	now. As	noted	a	few	paragraphs	back,	Munton	(2016)'s	defense	of	the	proto-confidence analysis	draws	on	epistemological	considerations.	She	writes: "What	properties	must	our	experience	have	if	it	is	to	account	for	...	fluctuations	in epistemic	power,	even	across	experiences	that	share	epistemically	relevant contents?	I	propose	that	we	should	understand	the	relevant	difference	in	such	cases as	a	change	in	the	certainty	or	confidence	with	which	the	visual	state	presents	its content." Munton	makes	explicit	that	differences	in	proto-confidences	are	also	phenomenal differences: "The	phenomenal	character	of	a	visual	experience	can	change	incrementally.	How things	look	to	you	develops	gradually	as	you	move,	as	the	scene	you	are	looking	at evolves,	or	as	environmental	conditions	change.	Those	changes	in	phenomenal appearance	have	epistemic	upshots:	your	epistemic	position	also	changes	very gradually,	in	line	with	them." The	contents	of	experience	can	stay	the	same,	she	suggests,	as	epistemic	power changes,	which	is	what	motivates	the	idea	that	relations	to	contents	make	a	phenomenal difference	as	well. As	she	puts	it:	"Note	that	at	some	level	the	contents	of	Rey's	and	Elmer's experiences	may	remain	the	same,	even	as	their	phenomenal	character	changes	in	a	way that	is	epistemically	relevant."	(p.	303) Munton	says	one's	epistemic	position	"changes	in	line	with"	phenomenal	changes, which	suggests	that	if	you	are	proto-confident	to	degree	.7	that	it	is	a	tree,	.7	measures	two things	that	rise	and	fall	together: something	phenomenal,	and	something	epistemic.	The phenomenal	thing	is	a	degreed	dimension	of	perceptual	seeming,	and	the	epistemic	thing could	be	a	degree	of	justification	for	believing	that	it's	a	tree,	or	a	level	of	confidence	that	it would	be	rational	to	have,	such	as	credence	.7	in	"It's	a	tree". Munton's	treatment	of	the	tree	example	can	suggest	that	a	subject's	standing	in	a single	proto-confidence	relation	to	a	content,	making	the	analysis	analogous	to	a	point 31	He	adds:	"Perceptual	Confidence	best	explains	what	happens	when	we	completely	trust	our experience...when	you	completely	trust	an	experience	you	endorse	the	way	it	presents	objects." Susanna	Siegel	*	Explaining	uncertainty 23 estimate	rather	than	a	distribution.	Multiplex	experiences	are	also	easily	analyzed	with degreed	perceptual	seeming	relations,	given	Munton's	assumption	that	proto-confidences rise	and	fall	with	epistemic	power.	If	in	looking	at	a	cloth	in	dim	light,	it	would	be	rational to	form	credences	.4	that	it's	blue,	.3	that	it's	green	and	.3	that	it's	purple,	Munton's	analysis can	be	expressed	by	positing	three	corresponding	proto-confidence	relations	that	the subject's	experience	consists	in.32 The	proto-confidence	analysis	can	be	developed	into	either	type	of	theory.	But relative	to	the	goal	of	showing	that	perceptual	experiences	are	intrinsic	phenomenal hedge-markers,	the	distribution	version	is	more	promising.	Compared	to	proto-confidence analyses	of	multiplex	experiences,	the	point-estimate	version	leaves	it	less	obvious	what the	phenomenal	hedge-marker	is.	The	putative	fact	that	having	an	experience	makes	it rational	to	form	one	or	another	credence	could	be	explained	on	the	standard	view	as	well, as	we	saw	in	section	3.	For	instance,	the	experience	of	seeing	a	tree	in	fog	that	occludes	the leafy	part	but	not	the	trunk	might	leave	it	open	whether	it	is	a	tree	or	a	telephone	pole. Here,	the	features	of	experience	that	explain	uncertainty	about	what	one	is	seeing	could	on the	face	of	it	be	explained	without	any	phenomenal	hedging. The	point-value	version	of	the	proto-confidence	analysis	needs	to	specify	which phenomenal	features	constitute	a	hedge-marker.	We	saw	in	section	3	that	there	may	be non-phenomenal	roles	or	representational	features	of	experience	that	probabilities	could measure,	and	something	like	a	point	valued	version	of	the	proto-confidence	analysis	could describe	experiences	in	this	way.	But	those	theories	do	not	posit	any	intrinsic	phenomenal hedge-markers. Given	Munton's	and	Morrison's	goal	to	make	predictions	about	all	perceptual experiences,	there	is	some	pressure	on	their	proto-confidence	analysis	to	posit	multiplex experiences.	We're	then	left	with	a	question:	do	multiplex	experiences	lend	themselves	to probabilistic	analysis? I	argue	next	that	no	experiences	lend	themselves	to	probabilistic	analysis,	and therefore	multiplex	experiences	do	not	either. 5.1	The	anchor	problem	and	superfluous	formalism The	proto-confidence	analysis	proposes	that	all	experiences	are	structured	by degreed	perceptual	seeming	relations. Let's	suppose	for	the	sake	of	argument	that	it provides	an	illuminating	analysis	of	some	multiplex	experiences,	such	as	conflicting trajectories	or	multi-stable	experiences.	Why	should	these	types	of	cases	anchor	a	theory	of the	structure	of	all	perceptual	experiences?	We'd	want	some	reason	to	think	that	these cases	are	the	ones	from	which	we	should	generalize.	Yet	there	doesn't	seem	to	be	anything especially	central	or	fundamental	about	these	cases. Not	every	perceptual	experience	is	an experience	of	a	trajectory,	let	alone	ambiguous	trajectories,	and	hardly	any	experience	are multi-stable.	This	objection	is	the	anchor	problem	for	proto-confidences. 32	Cf.	her	example	of	Silins's	dotted	card	example,	and	Morrison's	(2015)	discussion	of	Jeffrey's	cloth example. Susanna	Siegel	*	Explaining	uncertainty 24 Even	if	we	set	aside	the	anchor	problem,	the	probabilistic	formalism	does	not	seem to	be	tracking	anything	beyond	what	we	can	already	describe	without	it.	By	invoking probability,	the	proto-confidence	analysis	needs	experiences	to	have	just	the	right	set	of features.	There	has	to	be	a	dimension	of	perceptual	seeming	that	comes	in	degrees	in	a	way that	probability	can	measure,	this	dimension	needs	to	have	an	upper	bound,	and	all experiences	must	be	locatable	in	a	linear	order	along	this	dimension,	so	that	any	two perceptual	experiences	can	be	compared. Both	the	upper	bound	nor	comparability	seem	more	likely	artifacts	of	a	formalism than	features	of	phenomena	that	would	make	that	formalism	an	apt	tool	of	analysis. Regarding	the	upper	bound:	What	would	an	example	be	of	maximal	perceptual	seeming? (Is	a	very	vivid	cat	phenomenally	maximal?) In	the	case	of	credences,	it's	possible	to	define	every	credence	in	terms	of	credence 1.	If	credence	1	is	complete	certainty,	the	other	credences	are	progressively	less	than complete	certainty,	and	we	have	a	psychological	underpinning	for	the	formalism.33	By contrast,	in	the	case	of	perceptual	seeming,	if	we	have	no	clear	grasp	of	what	maximal perceptual	seeming	would	be,	then	that	fact	should	leave	us	dubious	that	the	other	values of	perceptual	seeing	are	well-defined. A	proponent	of	proto-confidences	might	reply	to	the	upper-bound	objection	by saying	that	there	is	no	upper	bound	of	proto-confidence.34	But	this	move	introduces	new challenges	to	finding	a	psychological	underpinning	of	proto-confidence.	First,	if	there	is	no perceptual	analog	to	complete	confidence,	it	becomes	obscure	which	proto-confidence value	should	be	assigned	to	epistemically	unproblematic	perceptual	experiences	such	as seeing	one's	hand	while	reaching	for	a	cup.	What	makes	it	less	than	the	maximum?	Without a	clear	definition	of	the	phenomenal	dimension	that	is	getting	measured,	the	adjusted formalism	with	no	upper	bound	is	not	any	better	motivated	than	the	original	formalism. Regarding	comparability,	if	the	proto-confidence	analysis	is	true,	then	there	has	to be	a	fact	of	the	matter	about	which	if	either	of	the	perceptual	seemings	that	result	from seeing	a	backlit	cat	and	the	Idesawa	spiky	sphere	(Figure	3)	are	stronger.	How	would	we locate	a	bang	or	odor	in	relation	to	them?	The	proto-confidence	analysis	forces	questions on	us	that	don't	obviously	have	answers. A	proponent	of	proto-confidences	could	address	this	objection	by	denying	that	there is	an	upper	bound,	or	by	invoking	"fuzzy"	credences,	or	both.	At	that	point,	however,	the motivation	that	comes	from	the	line	of	thought	emphasizing	the	continuity	of	probabilistic information	in	perceptual	processing	gets	lost. In	the	Walker	et	al	study,	there	is	no 33	Another	option	is	to	fix	the	psychological	credence	.5	in	p	as	a	type	of	indifference	between	p	and	notp,	and	then	define	the	other	credences	as	departures	in	degrees	of	asymmetry	between	distributions	of confidence	in	p	and	not-p.	The	main	point	is	that	for	the	formalism	to	be	useful	and	apt	for	analyzing	a set	of	psychological	states,	there	has	to	be	a	psychological	phenomenon	that	it	helps	to	make	exact. 34	This	suggestion	has	been	made	by	Munton	(personal	communication). Susanna	Siegel	*	Explaining	uncertainty 25 indication	that	the	probabilistic	information	guiding	behavior	is	in	the	form	of	fuzzy intervals. This	observation	points	to	a	further	challenge	in	finding	a	phenomenal	subjectmatter	for	probability	that	jibes	with	the	motivation	from	continuity	that	I've	been discussing	in	this	paper.	The	Walker	et	al	study	is	one	of	the	few	studies	that	link probabilistic	information	to	behavior.	In	other	cases	of	perceiving	orientation,	even	if	van Bergen	et	al	(2015)	are	correct	that	probabilistic	information	is	used	by	perceptual processing	of	orientation,	only	the	'winning'	hypothesis	about	orientation	shows	up	in perceptual	experience.35	The	phenomenal	degrees	posited	by	the	proto-confidence	analysis then	have	no	role	to	play.	And	as	I	argued	in	section	3,	non-probabilistic	experiences	can combine	with	probabilistic	information	in	the	rest	of	perception	to	explain	behavior. In	sum,	probabilistic	formalism	may	be	useful	for	measuring	contingent	roles	of experience,	but	this	use	of	it	is	entirely	compatible	with	denying	the	proto-confidence analysis.	That	kind	of	role	would	not	have	the	momentous	consequences	for	the	structure of	experience	that	Morrison	and	Munton	advertise. Conclusion When	Frank	Ramsey	first	proposed	that	our	levels	of	confidence	can	be	measured by	probabilities,	he	took	confidence,	a	phenomenon	that	everyone	can	recognize,	and proposed	that	probability	can	help	us	understand	further	features	it	has,	at	least	in	ideally rational	minds.36	There	is	no	doubt	about	the	existence	of	the	subject-matter	that	the probabilistic	formalism	was	meant	to	help	illuminate. I've	argued	that	there	is	no	phenomenal	dimension	to	perceptual	experience	that gives	proto-confidences	any	analogous	subject-matter.	While	probabilities	may	help	us describe	some	dispositions	and	roles	related	to	perception,	there	appears	to	be	nothing phenomenal	for	probabilities	to	help	us	analyze.	Perceptual	representations	of	pointestimates	may	be	accompanied	by	blur	or	feelings	of	uncertainty,	but	these	phenomenal feelings	are	not	plausibly	measurable	by	probabilities.	The	proto-confidence	analysis seems	to	lack	a	phenomenal	subject-matter. 35	A	point	emphasized	by	Clark	(2018),	Block	(2018),	and	Gross	(2019). 36	Ramsey,	"Truth	and	Probability"	(1926/1931).	As	Ramsey	recognized	when	he	founded	formal epistemology,	the	kind	of	confidence	that	has	the	best	chance	of	being	analyzed	probabilistically	are dispositional	states	of	mind,	rather	than	mental	occurrences	like	feelings:	"We	have	therefore	to	find	a process	of	addition	for	degrees	of	belief...	to	determine	a	numerical	scale.	Such	is	our	problem;	how	are we	to	solve	it?	There	are,	I	think,	two	ways....	We	can,	in	the	first	place,	suppose	that	the	degree	of	a belief	is	something	perceptible	by	its	owner;	for	instance	that	beliefs	differ	in	the	intensity	of	a	feeling	by which	they	are	accompanied...	This	view	would	be	very	inconvenient,	for	it	is	not	easy	to	ascribe numbers	to	the	intensities	of	feelings;	but	apart	from	this	it	seems	to	me	observably	false,	for	the	beliefs which	we	hold	most	strongly	are	often	accompanied	by	practically	no	feeling	at	all;	no	one	feels	strongly about	things	he	takes	for	granted.	We	are	driven	therefore	to	the	second	supposition	that	the	degree	of	a belief	is	a	causal	property	of	it,	which	we	can	express	vaguely	as	the	extent	to	which	we	are	prepared	to act	on	it..." Susanna	Siegel	*	Explaining	uncertainty 26 What	is	the	deepest	reason	why	perceptual	experiences	are	not	probabilistic?	I suspect	it	is	that	the	core	phenomenal	features	of	perceptual	experience	is	to	tell	us	how things	are	in	in	our	immediate	environment,	whereas	uncertainty	surrounding	perception is	about	our	relationship	to	the	information	about	those	circumstances.	Perceptual experience	feels	like	a	tribunal	against	which	we	can	compare	hypotheses	about perceptible	things.	For	many	reasons,	perceptual	experience	cannot	always straightforwardly	play	that	role.37	But	basic	questions	about	our	surroundings,	such	as	(as Austin	asked)	whether	the	pig	is	in	the	pigpen,	normally	seem	to	be	us	to	be	questions	that perception	can	settle.38 If	this	conclusion	is	correct,	then	contrary	to	premise	P1	of	the	face-value arguments,	one	can't	form	credences	by	taking	experiences	at	face-value,	simply	importing a	probabilistic	structure	of	experience	to	the	doxastic	level,	changing	only	the	nature	of	the relations	one	bears	to	the	contents.	Credences	would	have	to	be	formed	other	ways,	such	as forming	them	by	inference,	or	by	adjusting	your	mind	to	match	(what	you	take	to	be)	the objective	chances. Perception	science	can	tell	us	much	about	which	behavior	is	sensitive	to probabilistic	information.	But	the	conclusions	here	suggest	that	phenomenological considerations	may	be	better	than	perception	science	is	at	assessing	whether	experiences are	phenomenally	probabilistic.	If	my	conclusions	are	correct,	models	from	perception science	may	be	mapped	on	to	states	of	uncertainty,	but	not	on	to	any	states	that	are phenomenally	probabilistic. Figure	2.	The	magic	fork. 37	I	discuss	these	reasons	in	Siegel	(2017). 38	Austin	(1962). Susanna	Siegel	*	Explaining	uncertainty 27 Figure	3.	Idesawa	spiky	sphere. Bibliography Austin,	J.L.	(1962).	Sense	and	Sensibilia,	ed.	G.	J.	Warnock.	Oxford:	Oxford	University	Press. Bayne,	T.	(2004).	Phenomenology	and	the	feeling	of	doing:	Wegner	on	the	conscious	will.	In Susan	Pockett	(ed.),	Does	Consciousness	Cause	Behaviour?	Cambridge:	MIT	Press. Beck,	J.	(2019)	On	Perceptual	Confidence	and	'Completely	Trusting	Your	Experience'.	In,	pp 121. Block,	N.	(1996)	Mental	paint	and	mental	latex.	Philosophical	Issues	7:19-49. Block,	N.	2018.	If	perception	is	probabilistic,	why	does	it	not	seem	probabilistic? Philosophical	Transactions	of	the	Royal	Society	of	London	B:	Biological	Sciences,	373(1755), 20170341.	doi:10.1098/rstb.2017.03 Cheng,	T.	(2018).	Post-perceptual	confidence	and	supervaluative	matching	profile.	Inquiry. DOI:	10.1080/0020174X.2018.1562370 Christensen,	David	(1992).	Confirmational	holism	and	bayesian	epistemology.	Philosophy of	Science	59	(4):540-557. Clark,	A.	2018.	"Beyond	the	Bayesian	Blur:	Predictive	processing	and	the	nature	of subjective	experience.	Journal	of	Consciousness	Studies,	25(3-4),	71–87. Denison	R.	et	al	(2020)	"What	do	models	of	visual	perception	tell	us	about	visual phenomenology"?	In	F.	De	Brigard	&	W.	Sinnot-Armstrong	(Eds.),	Neuroscience	and Philosophy.	Cambridge:	MIT	Press. Dicey-Jennings,	C.	(2020)	The	attending	mind.	Cambridge	University	Press. Susanna	Siegel	*	Explaining	uncertainty 28 Eberhardt,	J.	2004.	Seeing	Black:	Race,	Crime,	and	Visual	Processing.	Journal	of	Personality and	Social	Psychology,	87(6),	876-893. Ernst,	M.,	Banks,	M. (2002)	Humans	integrate	visual	and	haptic	information	in	a statistically	optimal	fashion.	Nature	415,	429–433.	https://doi.org/10.1038/415429a Francis	G.	(2015).	Excess	success	for	three	related	papers	on	racial	bias.	Frontiers	in psychology,	6,	512.	https://doi.org/10.3389/fpsyg.2015.00512 Ganel,	Tzvi,	and	Melvyn	A.	Goodale.	(2019).	'Still	Holding	after	All	These	Years:	An	ActionPerception	Dissociation	in	Patient	DF'.	Neuropsychologia,	Neural	Routes	to	Awareness	in Vision,	Emotion	and	Action:	A	tribute	to	Larry	Weiskrantz,	128:	249–54. doi.org/10.1016/j.neuropsychologia.2017.09.016 Gershman,	S.	et	al	2012	Multistability	and	perceptual	inference.	Neural	Computation	24,	1– 24 Griffiths,	T.	et	al	2010a.	Probabilistic	models	of	cognition:	exploring	representations	and inductive	biases.	Trends	in	Cognitive	Science	14	357–364.	doi:10.1016/j.tics.2010.05.004 Griffiths,	T.	et	al	2010b.	Exemplar	models	as	a	mechanism	for	performing	Bayesian inference.	Psychonomic	Bulletin	&	Review	17	(4),	443-464	doi:10.3758/PBR.17.4.443 Goodale	and	Milner	1992.	Trends	in	Neuroscience	15(1),	20-5. Gross,	S.	(2020)	"Probabilistic	Representations	in	Perception:	Are	There	Any,	and	What Would	They	Be?"	Mind	and	Language.	https://doi.org/10.1111/mila.12280 Helton,	Grace	(2018).	Visually	Perceiving	the	Intentions	of	Others.	Philosophical	Quarterly 68	(271):243-264. Helmholtz,	H.	(1856)	Treatise	on	Physiological	Optics:	Thoemmes	Continuum. Hobson,	A.	2005.	Dreaming:	A	very	short	introduction.	Oxford:	Oxford	University	Press. Husserl,	E.	2005,	Phantasy,	Image-Consciousness,	and	Memory,	in	Edmund	Husserl: Collected	Works.	Vol	11,	ed.	Rudolf	Bernet,	Dordrecht:	Springer,	22. Icard,	T.	2016.	Subjective	probability	as	propensity	sampling. Review	of	Philosophy	and Psychology.	7(4),	863–903.	doi:10.1007/s13164-015-0283. Klink,	C.,	Boucherie,	D.,	Denys,	D.,	Roelfsema,	P.	and	Self,	M.	(2017).	Interocularly	merged face	percepts	eliminate	binocular	rivalry.	Scientific	Reports,	7,	7585.	doi:10.1038/s41598017-08023-9 Susanna	Siegel	*	Explaining	uncertainty 29 Knill	DC,	Richards	W,	eds	(1996)	Perception	as	Bayesian	Inference.	Cambridge,	UK: Cambridge	University	Press. Lau	H	(2019)	Consciousness,	metacognition,	&	perceptual	reality	monitoring.	PsyArXiv Lewis,	D.K.	(1986).	Events.	In	_Philosophical	Papers	Vol.	II_.	Oxford	University	Press.	pp. 241-269. Libet,	B.	;	Wright,	E.	&	Gleason,	C.	(1982).	Readiness	Potentials	Preceding	Unrestricted Spontaneous	Pre-Planned	Voluntary	Acts.	_Electroencephalography	and	Clinical Neurophysiology_	54:322-325. Madary,	M.	(2012)	How	would	the	world	look	if	it	looked	as	if	it	were	encoded	as	an intertwined	set	of	probability	density	distributions?	Frontiers	in	Psychology.	October	2012, Volume	3,	Article	419. Madary,	M.	(2016)	Visual	Phenomenology.	Cambridge:	MIT	Press. Martin,	Michael	G.	F.	(2002).	The	transparency	of	experience.	_Mind	and	Language_	17 (4):376-425 Martin,	C.	B.	&	Deutscher,	Max	(1966).	Remembering.	_Philosophical	Review_	75 (April):161-96 Mazzoni,	G.,	Memon,	A.	(2003).	'Imagination	can	create	false	memories'.	Psychological Science,	14,	2,	186-188. McClelland,	T.	(2020)	"The	mental	affordance	hypothesis"	Mind volume	129,	Issue	514, April	2020,	Pages	401-427 https://doi.org/10.1093/mind/fzz036 McGinn,	C.	(1996).	Another	look	at	color.	Journal	of	Philosophy	93	(11):537-53. Miller,	Brian	T.	(2016).	How	to	Be	a	Bayesian	Dogmatist.	_Australasian	Journal	of Philosophy_	94	(4):766-780 Morrison,	J.	2015.	Perceptual	confidence.	Analytic	Philosophy,	57	(1),	pp.	15–48. ---------------(ms.)	Third-personal	evidence	for	perceptual	confidence. Moss,	S.	2019.	Probabilistic	Knowledge.	Oxford	University	Press. Munton,	J.	2016.	Visual	confidence	and	perceptual	justification.	Philosophical	Topics	44:2 Ma	W.	(2012)	Organizing	probabilistic	models	of	perception.	Trends	in	Cognitive	Sciences Nanay,	B.	(2011).	Do	we	see	apples	as	edible?	Pacific	Philosophical	Quarterly	92:3	(305-22). Susanna	Siegel	*	Explaining	uncertainty 30 Nanay,	B.	(2020)	Perceiving	Indeterminately.	Thought:	A	journal	of	philosophy.	1-7. 10.1002/tht3.454 C.	O'Callaghan,	K.	Kveraga,	J.	Shine,	R.	Adams,	M.	Bar	(2017)	Predictions	penetrate perception:	Converging	insights	from	brain,	behaviour	and	disorder	Consciousness	and Cognition	47:63-74 Perky,	C.	1910.	An	Experimental	Study	of	Imagination.	American	Journal	of	Psychology	(21) 422–52 Pohl,	S.	(ms)	Perceptual	representations	are	not	probabilistic. Raleigh,	T.	and	Vindrola,	F.	(ms)	"Perceptual	experience	and	degrees	of	belief" Ramsey,	F.	(1926/2010)	Truth	and	probability.	In	Antony	Eagle	(ed.),	Philosophy	of Probability:	Contemporary	Readings.	Routledge.	pp.	52-94. Schacter,	D.	L.,	&	Dodson,	C.	S.	(2001).	Misattribution,	false	recognition	and	the	sins	of memory.	Philosophical	transactions	of	the	Royal	Society	of	London.	Series	B,	Biological sciences,	356(1413),	1385–1393.	https://doi.org/10.1098/rstb.2001.0938 Shea,	N.	2018.	Representation	in	Cognitive	Science	Oxford	University	Press. Shea,	N	and	C.	Frith,	2019	"The	global	workspace	needs	metacognition"	Trends	in	Cognitive Science. doi.org/10.1016/j.tics.2019.04.007 Shea,	N.	2019	Replies	to	Egan,	Gallistel,	and	Gross. Mind	and	Language. Siegel,	S.	2017.	The	Rationality	of	Perception.	Oxford	University	Press. Silins,	N.	2011.	"Seeing	through	the	'Veil	of	Perception'."	Mind	120(478):	329–67. Smith,	A.	D.	(2008)	Translucent	experiences.	Philosophical	Studies_	140	(2):197--212. Sturgeon,	S.	2020.	The	Rational	Mind.	Oxford	University	Press. Trommershäuser	J,	Kording	K,	Landy	MS,	eds	(2011)	Sensory	Cue	Integration.	Oxford: Oxford	University	Press. van	Bergen,	RS.	et	al	2015.	Sensory	uncertainty	decoded	from	visual	cortex	predicts behavior.	Nat.	Neurosci.	18,	1728	–	1730.	(doi:10.1038/nn.4150) Vance,	J.	(2020)	Precision	and	perceptual	clarity.	Australasian	Journal	of	Philosophy. doi.org/10.1080/00048402.2020.1767663 Susanna	Siegel	*	Explaining	uncertainty 31 Watzl,	Sebastian	(2017).	Structuring	Mind.	The	Nature	of	Attention	and	How	it	Shapes Consciousness.	Oxford,	UK:	Oxford	University	Press Wegner,	Daniel	M.	(2002).	The	Illusion	of	Conscious	Will.	MIT	Press Weisberg,	Jonathan	(2009).	Commutativity	or	Holism?	A	Dilemma	for	Conditionalizers. British	Journal	for	the	Philosophy	of	Science	60	(4):793-812. Weiss,	Y.	et	al	2002. Motion	illusions	as	optimal	percepts.	Nature	Neurosci.	5,	598–604.