Global artificial intelligence capability is expanding fast, as is the threat of emergent infectious diseases. However, AI is not always used for the benefit of the people. Track-and-trace apps have produced serious concerns and implications for democracy and transparency during national emergencies, and their rolling out has often failed to protect those most at risk of contracting COVID-19. Stephen Roberts, Audrey Prost, and Lele Rangaka find a significant variance in how different populations and communities either benefit from, or are oppressed and disenfranchised by, AI operations aimed at containing COVID-19. The authors argue that for AI to address these inequalities, it must focus on three factors outside of technology: people, processes, and politics

Prost, Audrey

Rangaka, Lele

Roberts, Stephen L.

English

LSE Research Online

Amidst	a	global	pandemic,	who	is	AI	for?	Global	artificial	intelligence	capability	is	expanding	fast,	as	is	the	threat	of	emergent	infectious	diseases.	However,AI	is	not	always	used	for	the	benefit	of	the	people.	Track-and-trace	apps	have	produced	serious	concerns	andimplications	for	democracy	and	transparency	during	national	emergencies,	and	their	rolling	out	has	often	failed	toprotect	those	most	at	risk	of	contracting	COVID-19.	Stephen	Roberts,	Audrey	Prost,	and	Lele	Rangaka	find	asignificant	variance	in	how	different	populations	and	communities	either	benefit	from,	or	are	oppressed	anddisenfranchised	by,	AI	operations	aimed	at	containing	COVID-19.	The	authors	argue	that	for	AI	to	address	theseinequalities,	it	must	focus	on	three	factors	outside	of	technology:	people,	processes,	and	politics.	As	the	COVID-19	pandemic	enters	its	second	year,	little	doubt	remains	regarding	the	unprecedented	andtransformative	role	which	practices	of	artificial	intelligence	(AI)	are	now	positioned	to	play	within	ongoing	efforts	tocombat	the	spread	of	SARS-CoV-2	across	populations.This	crisis	has	become	a	‘prism	and	amplifier	for	anything	data’.	The	intensifying	capture	and	use	of	datathroughout	the	pandemic	has	included	the	unleashing	of	drone	technology	to	enforce	public	health	quarantines,	therise	of	the	COVID-19	robot,	and	the	unfurling	of	pervasive	security	cameras	across	cities	empowered	with	facialrecognition	technologies.	Some	of	these	new	forms	of	data	capture	have	generated	widespread	unease,	asexemplified	by	ongoing	public	debates	over	digital	contact	tracing	strategies	in	the	UK	and	abroad,	and	citizenoutcries	over	the	involvement	of	big	tech	in	public	health	responses.In	contrast,	throughout	stages	of	this	pandemic,	further	applications	of	AI	to	understand	and	shape	responses	to	thespread	of	COVID-19	have	been	met	with	great	interest	and	enthusiasm.	Recent	innovations	and	advancements	inAI,	it	has	been	argued,	have	enabled	state	and	non-state	actors	to	process,	analyse,	and	understand	large	datasetswithin	and	across	populations	to	inform	critical	areas	of	responses	to	the	pandemic,	including		screening,	prediction,forecasting	and	contact	tracing.	Yet,	while	AI-driven	responses	to	COVID-19	have	now	flourished	in	many	countriesacross	the	globe,	this	pandemic	has	also	served	as	a	powerful	illustration	of	ongoing	digital	divides,	and	in	theunequal	degrees	of	access	which	citizens,	not	only	residing	in	low-income	states,	but	also	high-income	ones,	haveto	internet	and	smartphone	usage.Despite	the	celebrated	and	often	controversial	claims	about	what	AI	‘can	do’	in	the	contexts	of	COVID-19,	it	isundeniable	that	emerging	AI	responses	to	this	public	health	emergency	have	also	separated	communities	andpopulations	from	past	experiences	of	responses	to	disease	outbreaks	and	acute	health	episodes,	and	have	furtherdistorted	future	possibilities	of	how	responses	towards	emergent	epidemics	and	pandemics	might	be	shaped	andconceptualised	in	responses	to	future	disease	outbreaks	and	public	health	emergencies.To	this	end,	and	as	discussed	in	a	recent	UCL	roundtable	on	AI	and	emerging	epidemics,	never	has	the	need	for	asustained	examination	and	interdisciplinary	critique	of	the	place	of	AI	in	responding	to	adverse	health	events	beenmore	timely	and	critical.In	a	world	of	advancing	AI	capacities	and	expanding	emergent	infectious	disease	threats,	how	can	AI	beleveraged	for	the	benefit	of	the	people?Our	response?	Never	forget	the	3Ps:	people,	processes,	and	politics.LSE Business Review: Amidst a global pandemic, who is AI for? Page 1 of 3		Date originally posted: 2021-02-17Permalink: https://blogs.lse.ac.uk/businessreview/2021/02/17/amidst-a-global-pandemic-who-is-ai-for/Blog homepage: https://blogs.lse.ac.uk/businessreview/People-centred	thinking	must	be	paramount	in	ongoing	assessments	of	the	role	of	AI	practices	in	responding	tooutbreaks	during	and	after	COVID-19.	This	calls	for	a	robust	intersectional	and	interdisciplinary	analysis	of	howdifferent	groups	of	people	experience	and	are	empowered	or	disenfranchised	by	the	employment	of	AI-drivenresponses	during	national	emergencies.	While	governments	around	the	world	have	sought	to	present	AI-supportedcontact-tracing	apps	as	instrumental	to	exiting	imposed	national	lockdowns,	evidence	increasingly	suggests	that	theglobal	proliferation	of	these	‘track-and-trace’	apps	ushered	forward	by	big	tech	have	produced	serious	concerns	andimplications	within	certain	contexts	for	democracy	and	transparency	during	national	emergencies,	while	researchelsewhere	has	demonstrated	how	the	rolling	out	of	these	apps	has	often	failed	to	protect	those	most	at	riskof	contracting,	spreading,	and	dying	of	COVID-19.In	2020,	a	year	which	saw	global	resistance	against	systemic	racist	violence	and	structural	inequities,	critical	publichealth	research	has	also	drawn	attention	to	the	ways	in	which	the	increased	insertion	of	AI	practices	into	COVID-19responses	has	provided	new	opportunities	for	the	intensification	of	algorithmic	oppression	and	discriminatory	designagainst	already	marginalised	or	racialised	communities.	Equally	important	discussions	have	also	emerged	on	theinclusion	or	exclusion	of	social	determinants	of	health	indicators	for	modelling	the	spread	and	impacts	of	COVID-19,and	how	such	assumptions	used	in	modelling	techniques	might	potentially	deepen	health	inequities	among	alreadyvulnerable	populations	including	racialized	and	Indigenous	populations,	as	well	as	economically	disadvantagedgroups.These	examples	bring	into	critical	focus	the	significant	variance	in	how	different	populations	and	communities	eitherbenefit	from,	or	are	oppressed	and	disenfranchised	by,	advancing	AI	operations	launched	in	efforts	to	containCOVID-19	and	to	‘police	the	pandemic’.	Beyond	a	narrow	focus	on	technical	solutionism	in	leveraging	AI	to	reduceinfection	rates	and	increase	clinical	diagnostic	precision,	work	that	considers	AI	for	the	people	must	recognise	theeveryday	complexity	in	the	lived	experiences	of	individuals	and	communities,	intermeshed	within	racial,	economic,social,	historical,	and	political	injustices	and	within	relationships	to	infection,	containment,	and	contagion.A	people-centred	vision	that	addresses	the	challenges	of	intensifying	AI	practices	in	pandemic	response	must	alsoconsider	the	central	role	of	communities	and	government	in	addressing	and	understanding	drivers	of	vulnerabilityand	ill	health	during	and	beyond	outbreaks,	and	in	continually	reviewing	parameters	against	the	encroachment	andunintended	impacts	of	AI-supported	public	health	interventions.Understanding	and	evaluating	processes	also	matters	greatly	in	considering	how	evolving	systems	of	AI	in	publicand	global	health	can	be	leveraged	for	the	benefit	of	the	people.	While	advancing	practices	of	AI	are	infamouslyassociated	with	complexity	and	opacity,	it	is	also	vital	to	remember	the	human	face	behind	processes	of	AIknowledge	production.	Already,	important	conversations	are	deepening	on	recruiting	more	diverse,	interdisciplinaryAI	talent	in	the	forms	of	programmers,	engineers,	and	analysts	to	address	bias	and	to	build	principles	of	diversity,representation	and	lived	human	experiences	into	the	development	culture	of	AI.	We	are	also	witnessing	a	newfound	value	for	interdisciplinary	queries	on	approaches	to	AI,	with	calls	for	increased	social	science	investigationson	systems	design,	errors	and	oversights	not	only	flourishing	outside	and	in	reference	to	the	system,	but	also	fromwithin.For	global	health	systems	important	interdisciplinary	evaluations	of	the	processes	which	constitute	AI	operations,and	their	impacts	must	be	foundational	in	navigating	incidences	where	AI-supported	or	assisted	interventions	mighthave	observable	benefits	for	global	health	communities.	These	evaluations	should	consider	the	actors	involved	inAI	development	processes,	the	values,	and	worldviews	which	such	actors	promote,	and	how	proposed	initiativesmight	advance	or	undermine	global	health’s	commitments	to	social	justice	and	equity.Lastly,	it	is	critical	to	consider	the	importance	of	politics	in	ongoing	efforts	to	leverage	AI	for	the	benefits	of	thepeople,	for	social	justice	and	for	global	health	equity.	While	COVID-19	is	one	of	the	most	severe	health	crises	indecades,	it	is	also	an	opportunity	and	diagnostic	for	understanding	and	evaluating	the	ongoing	crisis	of	internationalpolitics.	Political	decisions	have	driven	responses	to	the	spread	of	COVID-19	with	varying	degrees	of	success,	andthe	increasing	application	of	AI-responses	cannot	be	divorced	from	the	political	contexts	and	visions	in	which	suchresponses	have	originated.LSE Business Review: Amidst a global pandemic, who is AI for? Page 2 of 3		Date originally posted: 2021-02-17Permalink: https://blogs.lse.ac.uk/businessreview/2021/02/17/amidst-a-global-pandemic-who-is-ai-for/Blog homepage: https://blogs.lse.ac.uk/businessreview/There	is	a	striking	contrast	between	the	UK’s	mounting	failures	to	effectively	and	transparently	harness	AI-capacities	in	its	pandemic	response	operations,	and	the	ways	in	which	other	states,	including	Taiwan,	which	hasoperated	effective	AI-powered	participatory	surveillance	methods	within	an	integrated	response	systememphasizing	free	and	early	testing,	extensive	and	effective	social	care,	paired	with	high	levels	of	trust	ingovernment	authorities.	An	understanding	of	politics,	as	it	intersects	and	interweaves	into	public	health	operationswill	therefore	be	essential	in	any	comparative	cross-country	learning	exercise	and	sharing	of	best	practices	whichseeks	to	understand	the	effectiveness	of	varying	national	responses	to	this	pandemic	and	to	future	adverse	globalhealth	episodes.In	navigating	future	assessments	of	the	impacts	of	new	AI-powered	responses	to	emerging	outbreaks,	politicalengagement	will	be	further	essential	in	providing	context	for	how	different	political	and	governance	structures	mayenlist	digital	interventions	for	varying	objectives	and	ends	which	may	run	counter	to	public	health	goals	and	healthequity,	especially	during	epidemics	and	pandemics.	Engaging	with	politics	will	also	help	understand	and	chart	howcritical	elements	of	trust,	compliance,	and	resistance	within	populations	may	shape	the	outcome,	uptake,	andeffectiveness	of	these	advancing	digital	practices	during	health	emergencies.Seen	collectively	then,	an	emergent	and	interdisciplinary	agenda	of	research	and	action	which	incorporates,understands,	evaluates,	and	centralises	the	3	Ps	–	people,	processes,	and	politics	–	all	too	often	obfuscatedwithin	overly	technical	contemporary	discussions	of	AI,	is	not	only	salient	and	timely,	but	also	practical,	andultimately,	humane.♣♣♣Notes:This	blog	post	is	based	on	ongoing	discussions	from	UCL’s	AI	&	Policy	Roundtables,	which	bring	togetherleading	voices	in	policy,	industry,	third	sector	and	academia	to	stimulate	dialogue	and	forge	consensus	onhow	to	deliver	“AI	for	people	and	planet”.	The	post	expresses	the	views	of	its	author(s),	not	the	position	of	LSE	Business	Review	or	the	London	Schoolof	Economics.Featured	image	by	Maria	Oswalt	on	UnsplashWhen	you	leave	a	comment,	you’re	agreeing	to	our	Comment	Policy		LSE Business Review: Amidst a global pandemic, who is AI for? Page 3 of 3		Date originally posted: 2021-02-17Permalink: https://blogs.lse.ac.uk/businessreview/2021/02/17/amidst-a-global-pandemic-who-is-ai-for/Blog homepage: https://blogs.lse.ac.uk/businessreview/

Amidst a global pandemic, who is AI for?

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Amidst a global pandemic, who is AI for?

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