volume	20,	no.	24 august	2020 Deepfakes and the Epistemic Backstop Regina Rini York University © 2020 Regina	Rini This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. <www.philosophersimprint.org/020024/> D eepfakes are fabricated video or audio recordings cre-ated through machine learning technology. A computer	program	uses	a large	data set	of real recordings to	build a	model	of	the	facial/vocal	characteristics	of	a	person,	then	superimposes this	onto	recordings	of	another	person.	The	effect is	an	apparent	recording	of	a	well-known	person	doing	or	saying	something	they never	did.	If	you	haven't	seen	a	deepfake,	you	should	probably	stop and	watch	one	before	continuing	with	this	paper;	it's	a	phenomenon that's	hard	to	grasp	without	ostensive	demonstration.1 So far, the output isn't entirely convincing. But that may change, and	soon.	Which	means	we	should	start	asking:	What	could	happen to	our	collective	democratic	processes	of	information-sharing	and	debate	when	our	leaders	can	be	deepfaked	into	doing	or	saying	whatever a	malicious	agent	desires?	Hints	of	this	worry	already	appear	in	journalistic discussions, but outside computer science and legal studies, there	has	been	little	published	by	academics.2	To	my	knowledge,	there is	nothing	yet	from	philosophers	on	the	subject.	So	consider	this	essay	an	exercise in	prophylactic	political	epistemology; I	aim	to	raise worries	about	deepfakes	and	the	erosion	of	knowledge	in	democratic societies	before	it	begins	to	happen. Testimony, Recordings, and the Epistemic Backstop I'll	come	back	to	deepfakes	shortly.	First,	we	need	to	get	clear	on	the epistemic	environment	in	which	they	operate.	I'm	going	to	argue	that audio	and	video	recordings	currently	serve	a	distinctive	role	in	public discourse.	Specifically,	they	regulate	our	testimonial	practices,	providing	what	I'll	call	an	epistemic backstop. Our	collective	epistemic	practices	are	highly	reliant	on	testimony, the transmission of knowledge via say-so. When a credible person tells	me	that	she	has	seen	or	heard	something,	I	am	typically	justified 1. For	an	especially	entertaining	example,	you	can	watch	"Barack	Obama"	insult Donald	Trump	in	a	demonstration	from	Buzzfeed	and	Jordan	Peele.	See	Mack (2018). 2. See	Maher	(2018).	For	legal	academic	perspectives,	see	Chesney	and	Citron (2019);	Silbey	and	Hartzog	(2019);	Pfefferkorn	(2019). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 2 – vol.	20,	no.	24	(august	2020) 	even	those	lacking	in	good	will		a	reason	to	cooperate	with	the norms. An	excerpt	from	Michael	Cohen's	February	2019	testimony	before the	US	House	Oversight	Committee	provides	a	remarkably	succinct illustration of both the ways that bad testimonial practice can blemish	one's reputation.	Cohen	admitted to transmitting	disinformation for his erstwhile client, but claimed a distinction in their respective epistemic	failings: Rep.	Comer:	You	called	Mr.	Trump	a	cheat.	What	would you	call	yourself? Michael	Cohen:	A	fool.5 So	far,	these	are	just	familiar	philosophical	theses	about	the	nature of	testimony.	But	now	I	want	to	draw	attention	to	the	role	of	recordings in	regulating	our	testimonial	practices,	something	rarely	appreciated by	analytic	epistemologists.	Neglect	of	this	role	has	perhaps	been	reasonable	until	now,	but	deepfakes	will	make	it	dangerous. Here	is	the	main	idea:	Video	and	audio	recordings	function	as	an epistemic backstop.	They	regulate	our	testimonial	practices,	sometimes bluntly though more often subtly. The availability of recordings undergirds	the	norms	of	testimonial	practice,	increasing	the	incentive	for testifiers to	speak	with	sincerity	and	competence.	Our	awareness	of the	possibility	of	being	recorded	provides	a	quasi-independent	check on	reckless	testifying,	thereby	strengthening	the	reasonability	of	relying	upon	the	words	of	others. I	think	that	recordings	do	this	in	two	distinctive	ways:	actively	correcting	errors	in	past	testimony	and	passively	regulating	ongoing	testimonial	practices.	I	will	take	these	in	turn. Acute correction	is	the	active	role	recordings	play	in	regulating	testimony.	Think	of	familiar	"let's	check	the	tape"	scenarios:	Someone	has testified	that	an	event	transpired	in	such-and-such	a	way,	but	then	a surreptitious recording reveals otherwise. Perhaps the most famous 5. See	Prasad	and	Matza	(2019). in	believing	the	contents	of	her	claim	simply	on	the	basis	of	her	testifying	to	it.	Of	course,	this	justification	can	be	defeated	by	evidence against	the	proposition,	or	undercut	by	evidence	that	my	interlocutor is	unreliable.	But	absent	those	factors,	I	seem	to	have	a	default	justification	to	accept	testimony	as	evidence,	and	in	many	cases	to	adopt a	belief	simply	on	testimonial	recommendation.	Since	any	individual knower only has so much time and cognition available, our knowledge	of	the	world	would	be	severely	impoverished	if	we	could	not	rely upon	testimony.3 Of course, some philosophers  being philosophers, after all 	have	skeptical	worries	about	our	reliance	on testimony.	But	most theorists accept some form of justification via testimony, and all socially functional humans rely on it in practice, whatever their theoretical	qualms.	A	major	part	of	the	rationality	of	this	practice	comes from	widespread	awareness	of	enforceable	testimonial norms.	When	a person	attempts	to	provide	testimony,	she	is	taken	to	be	implying	that she	is	both	sincere and	competent	about	the	matter	on	which	she	testifies.	Put	simply:	She	really	means	it,	and	she	knows	what	she's	talking about.4	A	person	who	regularly	transmits	misinformation	violates	one or	both	of these	norms	and	will likely	acquire	a reputation	as	a liar or	an idiot.	Fear	of those reputational	consequences	gives	everyone 3. The	philosophical	literature	on	testimony	has	grown	significantly	in	the	last three decades. For important examples, see Coady (1992); Lackey (2008); and	Goldberg	(2010).	Among	philosophers,	there	is	an	active	debate	whether we	should	think	of	testimony	as	a	basic	source	of	epistemic	justification	(a position	sometimes	called	non-reductionism),	or	as	just	one	among	several sources of input to some more basic epistemic capacity (sometimes called reductionism).	I	don't	think	we	need	to	settle	that	debate	here;	so	far	as	I	can tell,	it	won't	matter	to	most	of	my	points	about	how	people	use	testimony	in ordinary	life,	whatever	we	might	say	theoretically.	See	Lackey	(2006)	for	an overview	of	the	debate	and	reasons	to	think	the	dichotomy	itself	may	be	a mistake. 4. Here,	I	am	synthesizing	(and	simplifying)	convergent	points	from	two	different	philosophical	literatures:	the	knowledge	norm	of	assertion	(Williamson 1996;	Lackey	2007)	and	the	nature	of	interpersonal	trust	(Baier	1986;	Jones 1996). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 3 – vol.	20,	no.	24	(august	2020) things:	a	gunshot	echoing	from	here,	another	shot from	there.	Complexities	of	speed,	emotion,	distance,	and	memory	made	it	hard	to	tell which	eyewitness	testimony	to	trust.	The	Zapruder	film	provided	an independent	check	on	all	the	testimonial	noise,	allowing	investigators to calibrate a single narrative (though, of course, not everyone was convinced).8 As	important	as	these	acute	corrections	are,	I	suggest	that	the	passive	regulation	role	of	recordings is	still	more important.	This is the idea: Part of the reason our ordinary testimonial practice allows us to	trust	one	another	to	be	sincere	and	competent	is	that	we	all	know that,	at	any	time,	we	might	be	within	the	range	of	an	audio	or	video recorder,	or	might	be	testifying	about	an	event	that	occurred	near	such a	device.	This	is	especially	true	for	public	figures,	who	can	expect	to acquire	the	interest	of	smartphone-equipped	observers	in	every	room they	enter.	Your	background	awareness	that	the	event	you	are	testifying	about	might	have	been	recorded	is	a	good	reason	to	be	as	sincere and	competent	as	possible,	even	if	you	lack	characterological	honesty or	aptitude. Of	course,	that's	not	always	enough	to	keep	people	from	lying	or overstepping	their	competence.	People	still	do	it,	as	the	Fukuda	case shows.	But	I	suspect	that	our	tendency	to	mis-testify	has	declined	significantly	since	the	arrival	of	widespread	recording.	We	can	see	this passive	regulatory	effect	operating	in	some	complex	examples	played out	in	national	political	life.	In	May	2017,	US	President	Donald	Trump fired	FBI	Director	James	Comey,	who	alleged	this	was	retaliation	for his refusal to help the president suppress an investigation of Russian	interference	in	the	2016	presidential	election.	Responding	to	the 8. The	Zapruder	film	also	provides	instruction	on	the	risks	of	over-reliance	on recordings. According to a modern theory by journalist Max Holland, the investigating	Warren	Commission	was	misled	by	assuming	that	Zapruder's tape	covered	the	entire	assassination,	when	in	fact	the	first	gunshot	(which missed)	was	fired	before	Zapruder	turned	on	his	camera.	Trying	to	interpret all	three	shots	within	the	film's	short	timeframe	led	to	factual	inconsistencies that	were	quickly	seized	upon	by	conspiracy	theorists.	See	Holland	(2014). example	is	Richard	Nixon's	"smoking	gun"	tape.	In	1974,	Nixon	denied for months that he'd had any foreknowledge of the Watergate coverup.	His	aides	testified	to	the	public	that	the	president	was	innocent; they	became	the	outward	links	in	a	testimonial	chain	running	back	to Nixon	himself.	But	it	turned	out	that	the	president's	historical	grandiosity	had	led	him	to	install	a	secret	audio	recording	system	in	the	Oval Office.	After	much	dissembling	and	legal	evasion,	Nixon	turned	over a	June	1972	recording	on	which	he	could	be	heard	ordering	the	CIA to	interfere	in	the	FBI's	Watergate	inquiry.	The	effect	was	devastating; Nixon	was	revealed	to	have	unambiguously	flouted	the	sincerity	norm of	testimony,	and	his	aides	further	down	the	testimonial	chain	were left	out	in	the	cold.	This	last	fact	seems	to	have	been	especially	important,	as	many	of	the	Nixon	true-believers	now	felt	personally	betrayed by	a	president	exploiting	their	testimonial	assistance.	Even	his	innermost	defenders	turned	on	him.	Within	weeks,	the	president	resigned.6 You	might think	modern	politicians	have learned from	examples like this. But recordings still provide acute correction in politics. In spring	2018,	Junichi	Fukuda,	a	senior	official	in	the	Japanese	Finance Ministry,	was	accused	of	sexually	harassing	a	reporter	during	an	interview.	Fukuda	denied	the	allegations		but it then	emerged	that	the reporter	had	pressed the	audio record	button	on	her	mobile	phone. When	she	publicly	released	this	recording,	Fukuda	continued	to	deny the	allegations.	He	admitted	the	voice	in	the	recording	perhaps	sounded	like	him,	but	claimed:	"I	cannot	tell	since	I	can	only	hear	my	voice through	my	own	body."	The	public	was	not convinced.	Fukuda	was quickly	forced	to	resign.7 Recording	can	also	provide	acute	correction	in	cases	of	conflicting or	confused	testimony.	An	extremely	famous	example	is	the	Zapruder	film	of	the	1963	assassination	of	John	Kennedy.	In	this	case,	there were thousands of independent eyewitnesses, an entire crowd in a large	public location.	But	people	were	sure they	witnessed	different 6. Woodward	and	Bernstein	(1976,	308−341). 7. Yamaguchi	(2018). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 4 – vol.	20,	no.	24	(august	2020) effects of recordings. The first known audio recording was made in France	in	1857,	while	the	oldest	extant	visual	recording,	Roundhay Garden Scene,	dates	to	1888.11	A	phenomenon	that	began	to	exist	only	150 years	ago	is	unlikely	to	attract	the	attention	of	a	perspective	attuned	to universal	logical	constants. But	this	is	a	misleading	way	of	thinking.	Though	recordings	are	historically	contingent,	their	role	in	contemporary	social	epistemic	practice	is	pervasive.	Recording	technology	is	older	than	any	currently	existing	person.	Everyone	living	today	(at	least	in	wealthy	countries)	has always lived	with	the	implicit	understanding	that	recordings	provide a check on disputed testimony. Our social epistemic practices have adapted	to	five	generations'	awareness	of	this	possibility.	As	a	result, the	epistemic	role	of	recording	can	be	diaphanous,	since	it	is	hard	to see	a	lens	put	in	place	before	you	were	born. It's worth asking about the scope of these epistemic effects. Is it only	public	figures	who	expect	to	be	regularly	checked	by	recordings? Or do ordinary people living day-to-day lives have similar expectations?	If	it	is	only	public	figures,	then	the	epistemic	backstop	function of	recordings	will	be	much	narrower	than	I've	suggested,	since	testimonial	norms	are	determined	by	the	behavior	of	all people,	not	just the	famous. 12	In	fact,	the	answer	is	a	bit	more	complicated;	I	think	the right	distinction	is	not	so	much	between	public	figures	and	ordinary people, but rather between public events and private lives. It is still true (for	now) that	most	of	us	have	no	expectation that	our	private comments	at	home	are	being	recorded	(unless	you	live	with	TikToking	teenagers).	But	when	we	are	in	public	urban	spaces,	we	know	that we're more likely than not covered by CCTV cameras or traipsing through the background of any number of strangers' selfie-directed phones. So we should indeed expect recordings to regulate our testimony	about public events,	even	if	we	are	not	public	figures	ourselves. The	Zapruder	film,	again,	did	focus	on	some	very	public	figures,	but 11. NPR	(2008);	Smith	(2016). 12. Thanks	to	anonymous	referees	for	Philosophers' Imprint	for	encouraging	me	to clarify	this	point. allegation,	Trump	tweeted:	"James	Comey	better	hope	that	there	are no	'tapes'	of	our	conversations	before	he	starts	leaking	to	the	press!"9 This was a rather insidious exploitation of the testimony-regulating	function	of	recordings.	Trump	was	implicating	that,	like	Nixon,	he keeps	a secret recording	device in the	Oval	Office,	and that	he	had tapes	showing	Comey's	testimony	to	be	false.	But	no	such	tapes	ever emerged. The press, as well as Comey himself, called on Trump to release	the	implied	recordings.	A	month	later,	the	twittering	president followed	up:	"With	all	the	recently	reported	electronic	surveillance,	intercepts,	unmasking	and	illegal	leaking	of	information,	I	have	no	idea ...	[second	tweet]	whether	there	are	'tapes'	or	recordings	of	my	conversations	with	James	Comey,	but	I	did	not	make,	and	do	not	have,	any such	recordings".10 This	is	a	remarkable	illustration	of	the	multiple	roles	of	recordings in	testimonial	practice.	When	Trump	was	unable	to	produce	the	"tapes", many	observers	took	this	as	a	knock	against	his	own	credibility	and further	support	for	Comey's	testimony.	After	all,	the	Director	of	the	FBI was	surely	aware	of	the	Nixon	precedent	for	a	self-bugged	Oval	Office, and presumably experienced passive regulation of his testimony by the thought that tapes might later emerge. Trump's incompetent insinuation	of	challenging	recordings	instead	reminded	the	public	that Comey	had	a	strong	reason	to	be	telling	the	truth. As	these	examples	show,	recordings	(or	the	possibility	thereof)	play several	important	roles	in	supporting	the	rationality	of	our	testimonial practices. It is surprising, then, that epistemologists have not much attended	to	these	roles.	I	suspect	this	is	because	analytic	philosophers prefer	to	focus	on	necessary	or	conceptual	conditions	for	knowledge transmission,	the	sort	of	factors	you	could	find	at	work	in	the	epistemic practice of any era or any society, unlike the historically contingent 9. @realDonaldTrump Twitter account, May 12, 2017. <https://twitter.com/ realdonaldtrump/status/863007411132649473>. 10. @realDonaldTrump Twitter account, June 22, 2017. Two tweets: <https:// twitter.com/realDonaldTrump/status/877932907137966080>; <https://twitter.com/realDonaldTrump/status/877932956458795008>. regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 5 – vol.	20,	no.	24	(august	2020) One	user		whose	Reddit	handle	"deepfakes"	came	to	stand	for	the phenomenon	itself		provided	a	free	software	tool	("FakeApp")	allowing	anyone	with	a	decent	home	computer	to	make	their	own	videos. Following	media	attention,	Reddit	banned the	deepfake	community for	violating its "involuntary	pornography" rules.15	Of course, the internet	is	a	wide	and	wild	place,	and	deepfake	pornography	is	far	from eradicated. In summer 2019, digital security firm Deeptrace tracked 15,000	deepfakes	on	the	web,	nearly	double	the	number	from	earlier that	year.	96%	of	the	videos	were	porn.16 Obviously,	the	use	of	deepfakes	to	present	people	doing	and	saying things	they	never	did		especially	in	pornography		leads	to	serious ethical	worries.17	But	in	this	paper,	I	will	focus	on	the	risks	of	epistemic mischief.	The	most	obviously	dangerous	applications	are in	politics. Several	journalistic	entities	have	already	published	political	deepfakes, featuring,	e.g.,	Donald	Trump's	face	superimposed	on	Angela	Merkel's body	or	Barack	Obama	appearing	to	call	Trump	a	"total	and	complete dipshit". In	May	2018, the	Flemish	Socialist	Party	posted	a	deepfake video	appearing	to	show	Trump	urging	Belgium	to	withdraw	from	environmental	treaties.	The	Party	later	claimed	that	it	meant	the	video	to be	only	a	provocation	to	conversation,	not	to	fool	anyone	into	believing	its	content.	Yet	some	internet	commenters	appear	to	have	taken the	video	as	real.18 In January 2018, technologist John Wiseman documented what may	have	been the	first attempted deepfake	with a	political motive. The request was posted to the Reddit deepfakes forum (before that forum	was	banned)	and	does	not	appear	to	have	been	fulfilled.	This	is the	text	as	presented	in	a	screencap	Wiseman	posted	to	Twitter: 15. Robertson	(2018). 16. Simonite	(2019). 17. I	have	a	separate	paper,	co-authored	with	Leah	Cohen,	discussing	the	ethics of	deepfakes.	It	is	provisionally	titled	"Deepfakes,	Deep	Harms",	and	you	can email	me	(rarini@yorku.ca)	to	request	a	draft. 18. See	von	der	Burchard	(2018);	Silverman	(2018).; the	testimony	it	corrected	came	from	ordinary	people.	So	it	may	be	that the backstop function of recordings applies only to our testimonial knowledge	of	public	events.	But	that	category	is	already	a	large	and politically	important	one. I	suggest,	then,	that	the	epistemic	role	of	recordings	has	fallen	into a	characteristic	gap in	analytic	philosophers'	attention.	Between the logically	universal	and	the	suddenly	emergent	lies	the	realm	of	historically	entrenched	social	practice.	As	a	discipline,	analytic	philosophy has	tended	to	ignore	that	realm.13	But	this	becomes	dangerous	when social	conditions	suddenly	change.	What	was	diaphanous	while	intact may	become	disorientingly	opaque	once	fractured.	That	is	what	I	fear may	soon	happen	to	the	epistemic	role	of	recordings.	To	see	this	danger,	we	need	to	understand	deepfakes. Deepfakes and Public Deception Deepfakes came to mainstream public attention in December 2017 through	an	article	in	Motherboard	by	tech	writer	Samantha	Cole.14	As with	so	much	on	the	internet,	pornography	was	the	main	vector.	The basic	idea	is	this:	If	you	feed	hundreds	of	hours	of	a	celebrity's	video appearances into a machine learning algorithm, the algorithm will build	an	adaptable	model	of	their	face,	which	can	then	be	digitally	inserted	over	the	face	of	a	different	person	in	a	different	recording.	So	if you	have	a	desire	to	project	your	favorite	actress	into	your	favorite	pornographic	scene,	the	technology	can	make	your	(invasive	and	creepy) dream	come	true.	Connoisseurs	of	the	form	gathered	on	the	website Reddit, where they swapped source images and fabricated outputs. 13. Continental	philosophers,	of	course,	are	much	more	comfortable	in	the	land of historically entrenched social practice. A huge literature of obvious relevance	to	the	topic	of	this	paper	opens	out	from	Walter	Benjamin's	The Work of Art in the Age of Mechanical Reproduction	(1935).	I	am	unaware	of	anything	in continental	work	touching	directly	on	my	argumentative	claims,	though	my own	training	is	mostly	analytic.	In	genuine	social-epistemic	fashion,	I	would be	pleased	if	a	reader	with	better	knowledge	of	other	traditions	pointed	me to	a	close	parallel. 14. Cole	(2017). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 6 – vol.	20,	no.	24	(august	2020) things	while	watching	quickly	on	a	low-resolution	platform,	you	can see	them	if	you	pay	attention.	A	critical	viewer	with	access	to	a	large digital	platform	might	spread	a	debunking	just	behind	the	deepfake itself.21	So	perhaps	deepfakes	won't	be	very	successful	political	tools. The problem with this hope is that, of course, new technology eventually	improves.	To	understand	what	future	deepfakes	will	be	like, we	shouldn't	look	at	Reddit	amateurs.	We	should	look	at	professional computer	scientists.	In	2016,	a	group	of	researchers	in	Germany	and California	presented	a	technique	called	"Face2Face",	which	uses	an	algorithmic	process	to	impose	a	famous	person's	visage	over	an	actor's in real time. You can watch a demonstration online: An actor sits in front	of	a	camera,	moving	his	face	through	various	contortions.	At	the same	time,	the	computer	screen	displays	the	face	of	George	W.	Bush doing	the	same	things.22 You might be tempted to think that fabricated video is of little importance without corresponding audio. Even if a malefactor can make Barack Obama's face do whatever they want, we'll be able to tell	that	it's	not	speaking	with	Obama's	voice.	(The	Obama	deepfake mentioned	earlier	employs	noted	mimic	Jordan	Peele	to	provide	the voice. Not everyone will have access to such effective vocal talent!) Unfortunately, there	are	deepfake	technologies for	voice	as	well.	Researchers	at	Princeton	and	Adobe	(the	makers	of	Photoshop)	debuted a	technique	called	"VoCo"	in	2017.	It	allows	the	user	to	alter	the	content	of	a	spoken	audio	recording	simply	by	typing	new	words	in	the transcript.	The	algorithm	synthesizes	what	the	speaker's	voice	would 21. In	early	2020,	Facebook	announced	that	it	would	"ban"	deepfakes	and	direct resources	toward	automating	their	detection.	However,	the	social	media	firm explicitly	exempts	"parody	or	satire"	from	the	ban,	a	distinction	whose	ambiguity	will	surely	be	exploited	by	malefactors.	See	Shead	(2020). 22. Niessner et al (2016). YouTube video available at <https://www.youtube. com/watch?v=ohmajJTcpNk>. See also the project page at <https://web. stanford.edu/~zollhoef/papers/CVPR2016_Face2Face/page.html>. More recently,	some	of	the	same	researchers	proposed	a	3-D	modeling	technique doing	the	same	with	fabricated	videos	of	a	person's	entire	body.	See	Liu	et	al (2018). In	Russia	we	have	a	big	problem	with	gay	activist	rights. The governor of Chechnya (region in Russia) Ramzan Kadyrov	supposedly	ordered	the	execution	of	200+	gay people in his region. Vladimir Putin (our president) is a big pussy and doesn't want to do anything with him. Can	someone	please	make	a	gay	video	with	Ramzan	and some other random guy? We can get it viral within his region.	Whatsapp	channels	with	100K+	subscribers	will go	crazy	over	it.	Everyone	will	know	it's	fake,	but	his	reputation	will	be	done.	(but	not	Ramzan	with	Putin	together, because	it	would	just	be	considered	stupid)19 This	was	a	request	to	utilize	the	technology	for	a	political	goal,	trying	to	undermine	a	politician.	In	this	particular	case,	the	politician	is rather	loathsome,	but	of	course	there	is	nothing	confining	the	use	of deepfakes	to	laudable	political	objectives.	And	the	example	points	to something very important. Notice that the Reddit user says, "everyone	will	know	it's	fake,	but	[Kadyrov's]	reputation	will	be	done".	The thought	is	that	a	deepfake	video	needn't	be	positively	believed by	viewers	in	order	to	be	effective.	Merely	getting	a	suggestive	video	into	public	distribution	may	be	enough,	even	if	many	viewers	realize	it	is	fake.20 Still,	we	might	ask:	Just	how	convincing	is	this	technology?	If	you look	at	current	examples	on	the	web,	especially	those	by	Reddit	amateurs,	you	might	be	dubious.	Many	deepfake	videos	have	give-away digital	artifacts.	The	edges	of	the	jaw	are	blurred	unnaturally.	The	eyes don't	blink	quite	as	you'd	expect.	Though	you	might	not	notice	these 19. /r/deepfakes	post	by	Reddit	user	"ethan1el",	as	image-embedded	in	tweet	by John	Wiseman:	@lemonodor	Twitter	account,	January	25,	2018.	<https://twitter.com/lemonodor/status/956652112678551552>. 20.	This	point	is	also	shown	by	another	example,	which	seemed	to	some	observers	to	be	the	first	case	of	an	actual	political	deepfake.	In	late	2018,	Gabonese president	Ali	Bongo	appeared	in	a	video	that	some	opponents	claimed	was machine-generated.	Bongo	had	suffered	a	stroke	months	earlier	and	had	not been	seen	in	public	since;	some	opponents	thought	he	had	in	fact	died,	with the	military	using	his	deepfaked	image	to	maintain	their	power.	It	now	seems unlikely that the	video	was	deepfaked	(Bongo	has reappeared),	but the	accusation	contributed	to	a	failed	coup	attempt.	See	Breland	(2019). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 7 – vol.	20,	no.	24	(august	2020) the internet, being variously championed by partisan communities. Which	returns	us	to	the	central	concern	of	this	paper:	What	will	happen	to	the	backstop	function	of	recordings	once	their	unreliability	becomes	a	matter	of	regular	public	debate? Backstop Crises The	obvious	worry	about	deepfakes	is	that	they	will	be	used	to	propagate	vivid	disinformation.	As	legal	scholars	Bobby	Chesney	and	Danielle Citron (2019) point out in an influential law review discussion, deepfakes are ripe for election interference, corporate malfeasance, psychological	espionage,	and	personal	blackmail. But	I	think	that	the	most	important	risk	is	not	that	deepfakes	will be believed, but instead that increasingly savvy information consumers	will	come	to	reflexively	distrust	all	recordings.	In	other	words,	the backstop	baby	may	get	thrown	out	with	the	deepfake	bathwater. To	see	the	worry,	think	ahead	to	a	day	when	deepfake	technology is	widely	available.	The	problems	will	start	with	events	I	call	backstop crises 	moments	when	the	corrective	and	regulative	functions	of	recordings	are	made	salient,	but	then	quickly	undercut	by	the	spectre	of deepfakery.	Imagine,	for	example,	that	Richard	Nixon	had	said:	"Look, that	wasn't	me	on	the	smoking	gun	tape.	They	used	that	VoCo	technology	to	make	it	sound	like	me	ordering	CIA	interference.	But	it	wasn't!" This	would	not	have	been	a	very	plausible	claim	in	1974.	But	now imagine	that	late	in	the	2020	US	presidential	campaign,	an	audio	recording emerges which certainly sounds like Donald Trump colluding	with	Russian	intelligence	operatives.	Suppose	Trump	insists	that it	wasn't	him,	that	he	has	been	deepfaked	into	an	entirely	fabricated conversation. I	don't	know	how	many	people	would	believe	Trump,	or	how	many would	believe	the	recording.	I	suspect	views	would	break	along	predictably	partisan	lines.	But	I	can	say	this:	Though	not	myself	a	fan	of Donald	Trump,	I	would	have	serious	doubts	about	the	veracity	of	this tape.	Even	with	strong	prior	reasons	to	suspect	that	Trump	would	collude	with	Russian intelligence,	knowing	about	deepfake technology have	sounded	like	with	the	altered	phonemes		as	if	you	can	make any	voice	read	from	any	script	you'd	like.23 You might now say: Okay, this technology is scary, but won't it be	cancelled	out	by	equally	powerful	detection	technology?	Perhaps we	can	turn	machine	learning	loose	on	the	internet	and	have	it	diagnose	characteristic	patterns	in	manipulated	recordings.	Unfortunately, there	are	two	problems	with	this	thought.	The	first	is	technical.	Even	if counter-deepfake	technology	temporarily	overcomes	fakery,	this	may just	be	the	first	move	in	a	machine	learning	arms	race,	where	fakers continually	change	strategies	to	stay	a	bit	ahead	of	detection.	As	digital forensics	expert	Hany	Farid	explains, "Not	only	can	these	automatic tools	be	used	to	create	compelling	fakes,	they	can	be	turned	against our	forensic	techniques	in	the	form	of	generative	adversarial	networks (GANs)	that	modify	fake	content	to	bypass	forensic	detection".24 And	remember	that	we	can	see	only	the	publicly	available	deepfake	research	done	by	universities	and	corporations.	One	must	assume that	several	extremely	well-funded	national intelligence	services	are also	hard	at	work	on	their	own	in-house	versions	of	deepfakery.	For	all we	know,	their	technology	is	already	substantially	improved,	and	they are	simply	waiting	for	the	right	moment	to	deploy	it.	(Would	we	know it	if	they	already	had?)	In	any	case,	the	point	of	this	paper	is	to	think ahead,	perhaps	five	years	or	ten,	to	the	effects	of	an	improved	version of	the	technology		to	allow	us	to	begin	preparing	for	the	epistemic repercussions	before	they	become	dangerously	real. The second problem with technical solutions is more fundamental. It is a problem of social epistemology. Even if we did have reliable	deepfake	detection	technology,	past	experience	with	fake	news suggests that corrections rarely travel as far as initial fakes and are often	not	as	readily	believed. 25	That	suggests	the	best case	scenario	is a	kind	of	epistemic	chaos,	with	corrections	chasing	vivid	fakes	around 23. Jin	et	al	(2017).	You	can	see	a	demonstration	at	<https://www.youtube.com/ watch?v=RB7upq8nzIU>. 24. Farid	(2018,	268). 25. See	Vosoughi,	Roy,	and	Aral	(2018). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 8 – vol.	20,	no.	24	(august	2020) you'll	believe	the	denial.	If	you	don't,	you'll	allege	that	they	are	crying deepfake	wolf	and	hate	them	all	the	more	for	it.27 Regardless	of	the	outcome		whether	we	believe	the	politician	or the	video	 this	process itself is the	backstop	crisis.	We	will	all	confront a suddenly plausible skepticism about the knowledge-bearing potential	of	video	and	audio,	after	lifetimes	of	relying	on	them	as	solid testimonial	anchors.	This	has	the	makings	of	an	epistemic	crisis	on	the order	of	beginning	to	suspect	that	a	hallucinogen	has	been	pumped into	the	city's	water	supply. As	backstop	crises	follow	one	on	another,	video	and	audio	recordings	may	lose	their	status	as	acute	correctors	of	the	testimonial	record. Earlier, I stressed that the acute corrective role of recordings is less important than their passive regulatory role. We can see that most clearly	now,	as	we	try	to	imagine	the	long-term	effects	of	highly	public	backstop	crises.	Once	we	know	that	recordings	can	be	deepfaked 	and	that	veridical	recordings	can	be	convincingly	dismissed		our motivation	to	be	responsible	testifiers	may	slowly	erode.	We	no	longer	need	worry	that	someone	might	have	recorded	the	public	events about	which	we	are	testifying.	If	the	recording	goes	against	us,	we	can always	cry,	"Deepfake!"	And	we	might	even	be	right. This	is	the	gravest	danger	of	deepfakes:	not	that	they	will	trick	us into	believing	false	content,	but	that	they	will	gradually	eliminate	the epistemic credentials of all recordings, to an extent that video and audio no longer serve their passive regulative function in testimonial practice. As that happens, the reasonableness of expecting testifiers to be (usually) sincere and competent will begin to diminish. Within	a	few	years,	we	may	have	little	reason	to	trust	the	testimony	of strangers,	as	the	norms	securing	their	anticipated	cooperation	come gradually	undone.	Backstop	crises	triggered	by	deepfakes	may	be	only the	harbingers	of	a	slow-boiling	but	deeply	consequential	epistemic maelstrom. 27. I've	previously	written	about the	similarly troubling	role	of	partisanship-intestimony	reception	regarding	fake	news;	see	Rini	(2017). provides reason to doubt this piece of supposed evidence. After all, many political actors, domestic and foreign, would have strong motives	to	create	such	a	tape,	regardless	of	its	underlying	truth. Notice,	then,	that	the	point	of	this	example	doesn't	require	that	everyone believe a deepfake. The point is the public controversy itself. A backstop crisis implies the sudden public realization that there is no	longer	any	such	thing	as	a	"smoking	gun"	tape.	Even	if	we	end	up disbelieving	our	first	famous	deepfakes,	we	will	all	come	away	with	a growing	sense	of	displaced	epistemic	reality.	Once	everyone	has	seen that a supposedly authoritative recording can be reasonably challenged,	we	will	all	start	to	wonder	about	the	next	recording,	and	the next,	and	the	next... Here	is	another	scenario	to	make	the idea	more	vivid. Imagine	a politician video-calling in to a TV news show and, under pressure from	interviewers,	saying	something	foolish	or	offensive.	Instantly,	the pundits	decree	this	a	deadly	gaffe,	the	beginning	of	the	end	of	the	politician's	career.	But	then,	the	politician's	staffers	claim	that	this	wasn't the	politician	at	all.	They	assert	that	their	politician	was	nowhere	near a	camera	at the time.	Rather, it	must	have	been	an	actor,	using	realtime deepfake technology to steal the image and voice of the poor misrepresented	politician!26 Imagine	the	fallout	from	such	a	spectacle.	Hours	and	hours	of	cable news	fulmination	over	the	plausibility	of	a	guest's	appearance	being "hacked".	Linguists	and	computer	scientists	summoned	to	provide	rival millisecond	breakdowns	of	the	recording:	"See	the	lip	move	like	that, there?	That	can't	be	real!"	Or:	"Look,	that	partial	blink	is	very	hard	to fake	with	an	algorithm.	This	is	the	real	thing!"	Imagine	this	going	on for days or weeks with no clear resolution. In the end, presumably, public	opinion	will	break	along	partisan	lines.	If	you	like	the	politician, 26.	This	scenario	roughly follows	what	Chesney	and	Citron	call the	"liar's	dividend"	implication	of	deepfakes:	"As	the	public	becomes	more	aware	of	the idea	that	video	and	audio	can	be	convincingly	faked,	some	will	try	to	escape accountability	for	their	actions	by	denouncing	authoritative	video	and	audio as	deep	fakes	[sic]"	(Chesney	and	Citron	2019,	1785). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 9 – vol.	20,	no.	24	(august	2020) died	140	years	ago.30	But	the	same	point	comes	through	in	other	ways. Robert Hopkins shifts from the idea that I literally see Looty to the slightly	more	arcane	suggestion	that	a	photograph	can	place	me	in	a necessarily	veridical	seeing-in relation to	Looty.	Assuming the	photograph	was	made	and	reproduced	according	to	standard	photographic norms,	then	my	experience	of	seeing	Looty	in	the	picture	is	roughly as	reliable	as	seeing	Looty	with	my	own	eyes.31	I'm	not	literally	seeing Looty,	but (assuming there	were	no	shenanigans in the	causal	pathway	from	Bambridge's	shutter	to	my	screen)	I	gain	the	same	epistemic access	to	Looty	as	if	I	were. Dan Cavedon-Taylor makes an important related point, claiming the	distinct	epistemic	advantage	of	photographs	over	hand-made	pictures	is	that	the	former	generate	perceptual knowledge,	while	the	latter can	only	support	testimonial knowledge.	When	I	look	at	Keyl's	painting of	Looty,	I	am	relying	upon	the	painter's	skill	and	honesty	in	pictorial representation	just	as	much	as	I	would	rely	upon	his	competence	and sincerity in a verbal testimonial report. By contrast, Cavedon-Taylor argues,	the	photo	is	not	mere	testimonial	evidence;	it	belongs	in	the same	category	as	ordinary	perceptual	experience,	with	the	same	epistemic	immediacy.	He	says:	"When	we	see	a	photograph	that	depicts	x as	F,	say,	our	default	doxastic	response	is	to	believe	that	x	is	F 	and	to only	withhold	assent	if	we	possess	reasons	against	thinking	the	photograph	creditworthy".32 Another example might best illustrate this contrast. Leo von Klenze's	1857	painting	The Temple of Concordia at Agrigento	depicts	the 30.	For	discussion,	see	Cohen	and	Meskin	(2004). 31. Hopkins	(2012).	This	is	a	slightly	compressed	version	of	a	nuanced	view.	One worry	about	Hopkins'	view	is	that	he	appears	to	concede	that	photographs are	only	reliable	when	viewers	see	in	the	photo	"only	facts	consistent	with perfect general knowledge of how things are" (719). Given the difficulty of attaining second-order knowledge that one's judgements cohere with perfect	general	knowledge,	I	worry	that	Hopkins'	proposal	encourages	practical skepticism	regarding	all real-world	photographic	experiences.	But I'll leave that	thought	to	the	side	here. 32. Cavedon-Taylor	(2013,	294). The Epistemology of Recordings: Perceptual versus Testimonial Knowledge My	claims	about	the	consequences	of	backstop	crises	are	speculative and	somewhat	vague. In this	section, I'll	aim	to	be	a	bit	more	philosophically	precise	by	grounding	deepfakes'	challenge	to	the	backstop in	terms	borrowed	from	philosophical	work.	Surprisingly,	there	isn't much philosophical writing on the epistemology of recordings, but there	is	a	substantial	literature	regarding	the	epistemology	of	still	photographs.	When	a	photograph	provides	epistemic	access	to	its	subject, what	sort	of	epistemic	role	is	it	playing? Much	of this literature is framed	in	response	to	Kendall	Walton's transparency thesis, which holds that photographs enable direct, literal perception of their objects.28 Suppose, for instance, that I want to	learn	about	Queen	Victoria's	dog	Looty,	the	supposed	ancestor	of all	Pekingese	in	Britain	and	North	America.	(Looty	was	so	named	because	she		along	with	many	equally	priceless	objects		had	been stolen	from	the	Chinese	Imperial	Summer	Palace	by	rampaging	British troops	during	the	Second	Opium	War.)	First,	I	look	at	an	oil	painting of	Looty,	executed	by	Friedrich	Wilhelm	Keyl	in	1861.	Then,	I	look	at	a photograph	of	Looty,	grumpy	on	an	ornate	stiff-backed	chair,	taken	by William	Bambridge	in	1865.29	According	to	Walton's	view,	in	the	latter case	I	am	literally	seeing	Looty	herself,	across	time	via	this	photograph, just	as	surely	as	if	I	were	seeing	her	across	space	via	a	telescope.	By contrast,	when	I	look	at	the	painting,	I	am	not	literally	seeing	Looty	but only	a	pictorial	representation	of	her,	mediated	through	Keyl's	perceptions	and	artistic	expression. Walton's	proposal	has	been	extremely	controversial,	chiefly	due	to the	oddity	of	implying	that	right	now	I	am	literally	seeing	a	dog	who 28.	Walton	(1984).	As	a	referee	for	Philosophers' Imprint	reminds	me,	Walton	himself	was	not	trying	to	make	an	epistemic	point.	But	many	of	the	reactions	to his	article	are	framed	in	epistemic	terms. 29.	Both	the	painting	and	photograph	are	held	by	the	Royal	Collection.	You	can see them online at, respectively, <https://www.rct.uk/collection/406974/ looty> and <https://www.rct.uk/collection/2105644/looty-the-pekingese>. To	learn	more	about	Looty	herself,	see	Haven	(2010). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 10 – vol.	20,	no.	24	(august	2020) We	can	now	recast	the	points	of	the	preceding	sections	more	precisely.	The	danger	posed	by	deepfakes	is	that	successive	backstop	crises	will	gradually	transform	our	attitudes	toward	the	epistemic	status of recordings. In	effect, recordings	will	be	demoted from	sources	of perceptual	evidence	to	sources	of	mere	testimonial	evidence.	And	if they	are	simply	just	another	source	of	testimony,	then	they	cannot	be relied	upon	to	correct or regulate	testimonial	practice.	Recordings	could become	no	more	authoritative	than	paintings,	only	as	reliable	as	the reputation	of	their	creator.	A	recording	is	then	just	another	node	in	the testimonial	web,	equally	subject to	partisan	repudiation	or inflation. And	there	is	less	reason	to	be	responsible	in	one's	testimonial	practices if	recordings	offer	no	more	than	a	source	of	conflicting	testimony. Cavedon-Taylor	and	Hopkins	make	similar	points	about	the	effects of	Photoshop	on	the	epistemology	of	still	photographs.34	Indeed,	this worry	was	raised	by	Barbara	Savedoff	as	early	as	the	year	2000,	not long	after	consumer	digital	photography	first	appeared: If	we	reach	the	point	where	photographs	are	as	commonly digitized	and	altered	as	not,	our	faith	in	the	credibility	of photography	will	inevitably,	if	slowly	and	painfully	weaken,	and	one	of	the	major	differences	in	our	conceptions	of paintings	and	photographs	could	all	but	disappear.35 This	point	raises	a	natural	objection	to	my	worries	about	deepfakes. If	recordings	have	a	perceptual-type	epistemic	role	similar	to	still	photographs,	and	if	the	reliability	of	photographs	has	been	under	assault from	Photoshop	for	two	decades,	why	haven't	we	already	seen	the	sort of	epistemic	catastrophe	I	described	in	the	last	section?	It	seems	like 34. Hopkins (2012, 723). Cavedon-Taylor actually goes further: If our awareness	of	digital	manipulation	thoroughly	erodes	our	trust	in	photos,	then	we might	conclude	that	photographically	based	belief,	in	order	to	be	rationally grounded,	must	be	formed	on	the	basis	of	positive	reasons	for	thinking	the photograph	has	been	reliably	produced.	This	will	have	the	effect	of	rendering photographically	based	knowledge	exclusively	inferential	in	nature,	and	not testimonial.	(Cavedon-Taylor	2013,	296) 35. Savedoff	(2000,	202). eponymous	Sicilian	ruin.	When	I	saw	this	painting	hanging	in	the	Alte Nationalgalerie	in	Berlin,	I	was	confused.	I've	been	to	Agrigento,	and something	about	the	painting	seemed	wrong	to	me,	though	I	couldn't articulate	just	what.	Later,	I	looked	up	a	photo	of	the	temple	and	understood:	The	viewing	angle	Klenze	depicts is	not	actually	possible; the	temple	and	the	city	simply	are	not	spatially	arranged	in	that	way. Klenze	seems	to	have	taken	artistic	license	with	perspective	in	order to	achieve	a	more	pleasing	composition.33 This example shows the different epistemic powers of paintings and photographs. My pictorial experience of the temple in Klenze's painting	was	at	odds	(inchoately)	with	my	perceptual	memory.	I	was unable	to	resolve	this	tension	until	I	examined	a	photo	of	the	same	ruins,	which	quickly	decided	me	in	favor	of	my	memory	and	against	the painting.	This	is	because,	just	as	Cavedon-Taylor	suggests,	paintings provide	only	testimonial	evidence,	which	is	typically	trumped	by	perceptual	evidence	of	the	sort	photographs	provide.	Because	I	know	that Klenze's	aesthetic sensibilities	play	a	crucial role in	his	depiction	of the	temple	-	and	this	is	not	true	to	the	same	extent	in	photographs	-	I treat the	painting	with the	same	merely	provisional	authority	as testimony.	As	Cavedon-Taylor	puts	it:	"The	conditions	under	which	it	is rational	to	believe	the	content	of	another's	testimony	are	stricter	than those	under	which	it	is	rational	to	believe	the	content	of	another's	photograph"	(2013,	288−289). Plausibly,	all	of	the	above	is	just	as	true	for	audio	and	video	recordings	as	it	is	for	still	photographs.	Recordings	provide	us	with	a	form	of perceptual	evidence,	which	enjoys	a	stronger	presumptive	authority than	testimonial	evidence.	And	this	is	exactly	why	recordings	are	so well	suited	to	provide	the	epistemic	backstop.	Their	stronger	evidential	weight	allows	them	to	provide	acute	correction	of	deviant	testimonial	practices	and	passive	regulation	of	trustworthy	testimonial	norms. 33. You	can	see	the	painting	here:	<https://www.smb.museum/en/exhibitions/ detail/concordia-kunst-und-wissenschaft-in-eintracht.html>. Gallery text (on	display	in	May	2018)	confirms	that	Klenze	manipulated	the	temple's	relative	positioning	for	aesthetic	reasons. regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 11 – vol.	20,	no.	24	(august	2020) last	image		Stalin	all	alone		has	been	so	tortured	that	it	is	plainly more	painting	than	photograph.39 So	we	have	known	for	decades	that	photos	can	be	manipulated,	yet our	testimonial	norms	seem	largely	intact.	Why,	then,	should	we	worry much	about	deepfakes?	In	answering	this	objection,	it's	important	to remember	that	our	question	is	not "Why	are	deepfakes	more	likely	to mislead	than	earlier	photographic	manipulation?"	As	I've	stressed,	my main	worry	is	not that	deepfakes	succeed	in	tricking	anyone.	Rather, the	worry	is	that	backstop	crises	triggered	by	contested	deepfakes	will lead	to	erosion	of	the	reliability	that	recordings	provide	to	our	testimonial	practices.	There	are	at	least	four	reasons	to	worry	that	deepfakes are	distinctively	threatening	here. First,	there	is	a	psychological	difference	between	still	photographs and audio-video recordings. Recordings are typically more gripping, perhaps	because they	extend	over time	and	support	articulated	narratives.	People	happily	spend	money	to	gather	in	theaters	and	watch movies,	but	they	don't	do	so	to	view	still	photographs	anywhere	near as frequently. Perhaps recordings simply feel more like reality than photographs.	We	rarely	experience	the	world in	static images,	but	a well-executed recording mimics our everyday perceptual activities. This	suggests	we	may	be	more	psychologically	invested	in	the	reality of	recordings	than	still	photographs.	When	backstop	crises	force	us	to confront	the	growing	unreliability	of	recordings,	the	skeptical	consequences	may	be	amplified	by	their	psychological	power. Second,	deepfakes,	unlike	familiar	Photoshop	images,	are	generated	by	a	machine	learning	process	that	permits	efficient response to	epistemic	challenges.	Currently, if	we	doubt	someone's testimony	about an	alleged	public	event,	we	can	challenge	them	to	produce	a	recording.	And	if	we	doubt	the	first	recording	they	provide,	their	ability	to produce	a	second	corroborating	recording	would	be	strong	evidence in	their	favor.	For	example,	in	2016,	Trump	campaign	manager	Corey 39.	These	images	are	in	the	public	domain	and	may	be	viewed	(as	of	March	2019) at <https://commons.wikimedia.org/wiki/File:Soviet_censorship_with_Stalin2.jpg>. we've	adapted	well	enough	to	widespread	knowledge	that	photos	can be	manipulated		so	why	won't	we	adapt	just	as	well	to	deepfakes? The Distinctive Threat of Deepfakes In	fact,	we've	known	that	photographs	are	vulnerable	to	manipulation since	long	before	Photoshop.	In	1920,	Arthur	Conan	Doyle	published an	article	vouching	for	photographs	of	fairies	taken	by	two	young	girls in	West	Yorkshire.	Of	course, the	creator	of	Sherlock	Holmes	would not	have	done	so	without	ruling	out	alternative	explanations.	First,	he sent	the	negatives	for	inspection	by	Kodak	technicians,	who	refused	to provide	a	certificate	of	authenticity,	though	they	agreed	the	materials "show	no	signs	of	being	faked".36	Conan	Doyle	then	considered	that	the girls	might	have	simply	drawn	the	fairies	on	carboard	and	posed	them very	carefully.	But	he	concluded	that	"the	girl's	own	frank	nature	is,	I understand,	a	sufficient	guarantee	for	those	who	know	her".	To	be	safe, Conan	Doyle's	investigator tested	her	powers	of	drawing,	and	found	that,	while	she could	do	landscapes	cleverly,	the	fairy	figures	which	she had	attempted,	in	imitation	of	those	she	had	seen,	were entirely	uninspired,	and	bore	no	possible	resemblance	to those	in	the	photograph.37 The	fairy	folly	was	only	the	start	of	a	century-long	trend.	Stalin	employed	entire	teams	to	bring	scalpel	and	airbrush	down	upon	the	photographic	records	of	disfavored	comrades.38	In	one	extraordinary	case, the	1926	original	poses	Stalin	alongside	three	others.	A	succession	of retouched	versions	shed	comrades	as	decisively	as	the	Politburo.	The 36.	Smith	(1997,	384). 37. Conan	Doyle	(1920).	Sixty	years	later,	the	women	admitted	this	was	exactly what	they	had	done		though	they	still	insisted	there	really	had	been	fairies around. 38.	See	King	(1997). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 12 – vol.	20,	no.	24	(august	2020) and simply believe whatever conforms to their worldview.41 There is	every	reason	to	expect	such	malefactors	will	use	deepfakes	in	the same	way. Once that happens, we will see the vulnerability of recordings demonstrated frequently and shockingly, in a way that hasn't (yet) happened	to	still	photographs.	Of	course,	it's	possible	that	photos	will also	soon	be	undermined	by	machine	learning	mass-production.	My point	is	only	that	the	machine	learning	technology	behind	deepfakes leads	to	a	predictable	threat	distinct	from	earlier	photo	manipulation techniques. Finally,	and	perhaps	most	importantly,	the	difference	between	Photoshop	and	deepfakes	may	be	simply	this:	Audio	and	video	recordings already	function	as	backstops for	still	photographs.	A	still	photo	of	a single	moment	can	mislead	about	causal	relations	among	objects	in	a way	that	is	often	quickly	resolved	by	a	corresponding	video.	When	a still image	appears	to	show	something	dubitable,	critics	typically	demand	to	see	a	video	of	the	same	incident. For	instance,	in	late	2019,	a	strange	photo	circulated	on	Twitter	appearing	to	show	former	Vice	President	Joe	Biden	sucking	on	his	wife's finger	on	the	stage	at	a	campaign	rally.	Journalist	Luke	Darby	dug	further,	noting it	definitely looks like the former	vice	president	 at	a public	event	and	in	front	of	human	people		is	nibbling his	wife's	finger	like	a	goldfish	at	feeding	time.	But	the	Internet	has	produced	doctored	photos	before,	and	maybe a	video	of	the	event	will	clear	things	up?42 (As	it	turns	out,	the	video	shows	something	only	slightly	less	strange.) 41. See	Tufekci (2018);	Lynch (2016).	For	a	worked	example	of	how the	Putin regime	has	used	this	technique	in	the	past,	see	Snyder	(2018,	chapter	5).	A	related	technique,	which	Margaret	Roberts	calls	"flooding",	is	sometimes	used by	Chinese	internet	censors;	see	Roberts	(2018). 42. Darby	(2019). Lewandowski	was	accused	of	grabbing	the	arm	of	a	reporter	and	pulling	her	away	from	questioning	his	candidate.	The	campaign	quickly dismissed	the	charge,	claiming	that	"not	a	single	camera	or	reporter	of more	than	100	in	attendance	captured	the	alleged	incident".40	Reporters	took	up	the	challenge,	locating	two	different	video	recordings,	from alternate	angles,	showing	Lewandowski	doing	just	what	was	alleged. Part	of	why	the	campaign's	challenge	was	compelling		and	why successfully	meeting	the	challenge	was	even	more	so		is	that	we	currently	assume	that	no	one	will	be	able	to	swiftly	produce	fake	video recordings	tailored	to	novel	(purported)	facts	in	the	way	that	we	know Photoshop is relatively cheap and easy to use. Though Hollywood can	produce	extremely	compelling	videos	of	unreal	things,	we	know that this takes enormous resources of time, money, and human talent.	That's	why	it	is	implausible	to	explain	away	effectively-met	challenges	to	recordings;	currently,	the	idea	of	overnight	faked	recordings sounds	more	like	a	conspiracy	theory	than	a	plausible	debunking.	But this	thought	will	become	less	powerful	after	we	have	witnessed	a	few backstop	crises.	Once	deepfake	technology	is	widely	known,	it	will	be possible	for	public	figures	in	situations	like	Lewandowski's	to	simply insist	that	any	purported	recording	evidence	is	just	more	fakery		and who	will	be	able	to	say	they	are	wrong? Third,	the	efficiency	of	machine	learning	will	enable	mass	production	of	deepfakes	at	a	similar	rate	to	textual	fake	news.	This	will	allow epistemic	malefactors	to	"spam"	the	epistemic	environment	with	conflicting false	videos	of	prominent	events, in	much the	way they	currently	do	with	fake	news.	This	is	an	established	tactic	of	authoritarians seeking	to	disrupt	public	information	channels.	Neutralizing	effective public	epistemology	doesn't	require	tricking	people	into	believe	any particular	falsehood.	It	just	requires	convincing	them	not	to	trust	any information	source.	Once information	channels	are thoroughly	saturated	with	obvious	garbage,	people	fall	into	a	sort	of	epistemic	learned helplessness,	where	they	give	up	trying	to	critically	assess	information 40.	Flores	(2016). regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 13 – vol.	20,	no.	24	(august	2020) I	think	this	is	the	wrong	attitude	to	take.	It	assumes	an	implausibly Spartan	epistemology,	one	where	we	restrict	our	evidence	to	near-infallible	technologies.	I think	this	is	an	unrealistic	epistemic	standard that	would	deprive	us	of	valuable	sources	of	information	quite	often. To	put	it	another	way,	I	think	that	our	epistemic	reliance	on	recordings has been	reasonable,	even	if	it	will	soon	cease	being	so. But	you	don't	have	to	agree	with	me	about	this	to	see	the	danger of deepfakes. Even if abandoning our reliance on recordings might be	epistemically	admirable, there	will	be	serious transition costs,	and these ought to worry everyone. For better or worse, we have developed a web of epistemic norms assuming reliance upon recordings. In	the	developed	world,	there	is	no	one	living	today	who	remembers an	epistemic	environment	preceding that reliance.	Video and	audio recordings,	in	existence	longer	than	any	of	us,	have	always	structured our	lives.	To	really	appreciate	what	their	discredit	would	mean	for	our testimonial	practice,	we	must	look	back	to	a	time	when	people	relied solely on the testimony of eyewitnesses and newspapers for knowledge	of	public	events.	If	I	am	right	about	the	effects	of	deepfakes,	we may	be	very	suddenly	plunged	into	just	such	an	environment,	without preparation	or	training.	When	we	fall	into	dispute	about	public	events, there	will	be	no	recorded	backstop	to	resolve	things. There were, of course, testimonial norms before the 19th-century creation	of	recording	technology.	Those	norms	might	be	adequate	if we	could	return	to	them.	But	how	do	we	get	back	there?	None	of	us have	the	benefit	of	life-long	training	in	an	unregulated	testimonial	environment.	We	may	become	dangerously	credulous,	or	perhaps	reactively	paranoid.	I	cannot	predict	the	future,	but	I	am	confident	that	we will	not	quickly rediscover	19th-century testimonial	norms	without	a lot	of	trouble	along	the	way.44 me	of	the	merit	of	this	objection.	Similar	ideas	appear	in	Silbey	and	Hartzog (2019). 44. Among other problems, we should worry about losing the epistemically equalizing benefits of recordings. 19th-century epistemology left members of	marginalized	groups	especially	vulnerable	to	testimonial	injustice	(Fricker 2007). Reliable video recordings have sometimes provided marginalized As this incident suggests, the epistemic authority of still photographs has already been eroded by Photoshop, but our evidential practices around photographs are, like verbal testimony, apparently still undergirded by the epistemic backstop of recordings. Perhaps the	evidential status	of still	photos	has	already shifted from	vehicles of	perceptual	knowledge	to	mere	testimonial	knowledge.	But	so	long as	recordings	still	serve	their	backstop	functions,	they	can	acutely	correct	and	passively	regulate	photographic	evidence	in	the	same	way	as testimonial	practice. However,	if	this	is	true,	then	we	already	implicitly	place	more	epistemic	weight	on	recordings	than	we	appreciate.	The	epistemic	backstop	regulates	not	only	our	testimonial	practices,	but	also	our	use	of other	sorts	of	documentary	evidence,	like	still	photographs.	This	suggest	that	the	threat	deepfakes	pose	to	the	backstop	may	be	even	more consequential,	exposing	neglected	decay	in	our	epistemic	relations	to photos	along	with	undiagnosed	vulnerability	in	testimony. Toward a Worrisome Epistemic Future Where	does	this	leave	us?	If	my	worries	are	right,	then	in	the	near	future,	we	may	face	a	sudden	collapse	of	the	backstop	to	our	testimonial practice,	as	we	can	no	longer	trust	that	recordings	provide	authoritative	correction.	Following	highly	public	backstop	crises,	we	may	find that	our	adherence	to	testimonial	norms	of	competence	and	sincerity becomes	progressively	less	reliable	as	people	realize	there	is	rarely	an independent	check	on	their	testimony.	What	happens	then? One	answer	is	surprisingly	positive.	You	might	think	that	we	never should	have	put	so	much	trust	in	recordings.	After	all,	recordings	have never	been	strictly invulnerable	from	manipulation;	given	extensive time and resources, skilled fakers could produce convincing videos long	before	the	rise	of	machine	learning.	So	it	might	be	a	good	thing if	deepfakes	shake	us	free	from	our	unreasonable	reliance	on	recordings. 43 43. I	thank	audience	members	at	the	2019	Central	APA	in	Denver	for	convincing regina	rini Deepfakes and the Epistemic Backstop philosophers'	imprint – 14 – vol.	20,	no.	24	(august	2020) C.	A.	J.	Coady	(1992).	Testimony: A Philosophical Study. Oxford:	Oxford University	Press. Jonathan	Cohen	and	Aaron	Meskin	(2004). 'On	the	Epistemic	Value of	Photographs'.	Journal of Aesthetics and Art Criticism	62(2):	197−210. Samantha	Cole	(2017). 'AI-Assisted	Fake	Porn is	Here	and	We're	All Fucked'. Motherboard December 11, 2017. <https://motherboard. vice.com/en_us/article/gydydm/gal-gadot-fake-ai-porn>. Arthur Conan Doyle (1920). 'Fairies Photographed'. Arthur Conan Doyle Encyclopedia. <https://www.arthur-conan-doyle.com/index. php?title=Fairies_Photographed>. Luke	Darby	(2019).	'What	Is	Biden	Doing	to	His	Wife's	Hand?'	GQ December	1,	2019.	<https://www.gq.com/story/what-is-biden-doing>. Hany	Farid	(2018).	'Digital	Forensics	in	a	Post-Truth	Age'.	Forensic Science International	289:	268−269. Reena Flores (2016). 'Donald Trump's Campaign Denies Getting Rough with Reporter'. CBS News March 10, 2016. <https://www. cbsnews.com/news/trump-campaign-responds-to-charges-of-getting-physical-with-reporter/>. Miranda	Fricker	(2007).	Epistemic Injustice: Power and the Ethics of Knowing.	Oxford:	Oxford	University	Press. Sanford	Goldberg (2010).	Relying on Others: An Essay in Epistemology. Oxford:	Oxford	University	Press. Cynthia	Haven	(2010).	'Stanford	Historian	Tells	Why	the	West	Rules	- For	Now'.	Stanford News	September	14,	2010.	https://news.stanford. edu/news/2010/september/morris-west-rules-091410.html. Max	Holland	(2014).	'The	Truth	Behind	JFK's	Assassination'.	Newsweek November 20, 2014. <https://www.newsweek.com/2014/11/28/ truth-behind-jfks-assassination-285653.html>. Robert	Hopkins (2012). 'Factive	Pictorial	Experience:	What's	Special About	Photographs?'.	Noûs 46(4):	709−731. Zeyu	Jin,	Gautham	J.	Mysore,	Stephen	Diverdi,	Jingwan	Lu,	and	Adam Finkelstein (2017). 'VoCo:	Text-Based Insertion	and	Replacement in	Audio	Narration'.	ACM Transactions on Graphics	36(4):	96. More fundamentally, I worry that 19th-century testimonial norms simply	won't	work	in	a	modern	world	of	instant	global	communication. We	may	have	been	fortunate	to	enjoy	the	testimony-regulating	effects of	the	epistemic	backstop	during	the	last	150	years	of	rapid	technological	and	social	change.	But	we	may	now	be	forced	to	navigate	future changes without that protection. In a social epistemic environment already	plagued	by	fake	news	malefactors	and	authoritarian	deceivers, I	am	less	than	fully	confident	we	will	weather	the	transition	with	our social	and	political	systems	intact.45 References Annette	Baier	(1986).	'Trust	and	Antitrust'.	Ethics 96(2):	231−260. Walter Benjamin (1935[1969]). 'The Work of Art in the Age of Mechanical	Reproduction'.	In	Illuminations (ed.	H.	Arendt).	New	York: Schocken.	217–251. Ali	Breland	(2019).	'The	Bizarre	and	Terrifying	Case	of	the	"Deepfake" Video	that	Helped	Bring	an	African	Nation	to	the	Brink".	Mother Jones March	15,	2019.	<https://www.motherjones.com/politics/2019/03/ deepfake-gabon-ali-bongo/>. Dan Cavedon-Taylor (2013). 'Photographically Based Knowledge'. Episteme 10(3):	283−297. Robert	Chesney	and	Danielle	Keats	Citron	(2019).	'Deep	Fakes:	A	Looming	Challenge	for	Privacy,	Democracy,	and	National	Security'.	California Law Review	107:	175.	<https://ssrn.com/abstract=3213954>. groups	with	the	means	to	confront	disbelieving	publics,	as	with	recent	smartphone	videos	of	police	brutality	against	Black	people	in	the	US.	(I	owe	this important	point	to	Daniel	Saunders.) 45. I	would	like	to	thank	Daniel	Saunders	for	invaluable	research	assistance	on this	project.	I	also	owe	thanks	to	Leah	Cohen	for	assistance	on	a	related	earlier	project		and	for	first	bringing	deepfakes	to	my	attention.	Thanks	also to	audiences	at	the	2018	"Fake	Knowledge"	conference	at	the	University	of Cologne;	the	2019	Central	APA	in	Denver;	the	2019	"Ignorance	in	the	Age of	Information"	conference	at	Scripps	College;	the	University	of	St.	Andrews; and	the	editors	and	referees	for	Philosophers' Imprint.	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