CRITICAL ALGORITHM STUDIES

CRITICAL ALGORITHM STUDIES

The Social Media Collective (SMC) is a network of social science and humanistic researchers, part of the Microsoft Research labs in New England and New York.

https://socialmediacollective.org/reading-lists/critical-algorithm-studies/

CRITICAL ALGORITHM STUDIES

The Social Media Collective (SMC) is a network of social science and humanistic researchers, part of the Microsoft Research labs in New England and New York.

https://socialmediacollective.org/reading-lists/critical-algorithm-studies/

AS A RESULT, OUR LIST DOES NOT CONTAIN MUCH WRITING BY

COMPUTER SCIENTISTS

AI AND BIAS

A 30,000 FT VIEW OF THE ALGORITHMIC SOCIETY

AUDITS AND ACCOUNTABILITY

VALUES SOCIETY AND CULTURE

LEGAL FRAMEWORKS POLICY RECOMMENDATIONS

“FAIR” SYSTEMSCURRENT

AUTOMATION INFRASTRUCTURE

CRITICAL AND REFLECTIVE PROCESSES

ROLE OF THE COMPUTER SCIENTIST

A 30,000 FT VIEW OF THE ALGORITHMIC SOCIETY

AUDITS AND ACCOUNTABILITY

VALUES SOCIETY AND CULTURE

LEGAL FRAMEWORKS POLICY RECOMMENDATIONS

“FAIR” SYSTEMSCURRENT

AUTOMATION INFRASTRUCTURE

CRITICAL AND REFLECTIVE PROCESSES

CRITICAL PERSPECTIVES IN CS

Friedman/Nissenbaum 1997

Rogaway 2015

Selbst/boyd/Friedler/V/Vertesi 2019

Barabas/Doyle/Rubinovitz/Dinakar 2020

V/Bliss/Nissenbaum/Moses 2020

Crypto for the people

Kamara 2020

VALUE-LADEN EVALUATION OF A SYSTEM

REVEAL THE VALUES IMPLICIT IN AN ALGORITHMIC

FRAMEWORK

DEMONSTRATE THE INABILITY OF AN

ALGORITHMIC FRAMEWORK TO SPEAK TO SPECIFIC

NORMATIVE CONCERNS

DESIGN NEW FRAMEWORKS THAT CAPTURE NORMATIVE CONCERNS MORE CLOSELY

JUST INFRASTRUCTURES

Values SYSTEMS

JUST INFRASTRUCTURES

Values SYSTEMS

REVEAL THE INJUSTICES IMPLICIT IN AN

ALGORITHMIC FRAMEWORK

DEMONSTRATE THE INABILITY OF AN ALGORITHMIC

FRAMEWORK TO SPEAK TO CONCERNS AROUND JUSTICE AND EQUITY

DESIGN NEW FRAMEWORKS THAT SEEK TO MOVE US

CLOSER TO EQUITY

THE PROBLEM OF ACCESS

ALLOCATION VS ACCESS

Allocation

ALLOCATION VS ACCESS

Allocation

How do we ensure ‘fair’ access to resources?

ACCESS AS CLUSTERING/FACILITY LOCATION

What does it mean to have equity, or fairness?

BALANCE

Ensure that each cluster “represents” the whole [CKLV17]

BALANCE

Ensure that each cluster “represents” the whole [CKLV17]

Balance doesn’t provide fair access

EQUITABLE ACCESS

Given groups of points<latexit sha1_base64="3RE3+mQJ/GmfV5PsQdYBdnaaLu4=">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</latexit>

X1, X2, . . . , Xk

Cost of clustering X into clusters C is<latexit sha1_base64="RkIBjkCdHmHP3DQLzU/qf/lqoJU=">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</latexit>

costC(X)

minimize the maximum average access cost across groups

<latexit sha1_base64="0FvM4hLLPMrrBnRUFQXlxURM8Zg=">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</latexit>

arg minC2C

max✓

1|X1|

costC(X1), . . . ,1

|Xm|costC(Xm)

◆

EQUITABLE ACCESS


X1, X2, . . . , Xk


costC(X)



arg minC2C

max✓

1|X1|

costC(X1), . . . ,1

|Xm|costC(Xm)

◆

Define cost in different ways<latexit sha1_base64="d4LgMDEJIYC7MfhwJhuUbwkso08=">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</latexit>

AbsErrorC(X) = Âx2X

d(x, C)

<latexit sha1_base64="G/b0O0/qX5hnQ+c/W/Uw9U41XX4=">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</latexit>

RelErrorC(X) =Âx2X d(x, C)

Âx2X d(x, OPT(X))

EQUITABLE ACCESS


X1, X2, . . . , Xk


costC(X)



arg minC2C

max✓

1|X1|

costC(X1), . . . ,1

|Xm|costC(Xm)

◆

Define cost in different ways<latexit sha1_base64="d4LgMDEJIYC7MfhwJhuUbwkso08=">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</latexit>

AbsErrorC(X) = Âx2X

d(x, C)

<latexit sha1_base64="G/b0O0/qX5hnQ+c/W/Uw9U41XX4=">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</latexit>

RelErrorC(X) =Âx2X d(x, C)

Âx2X d(x, OPT(X))

THE TWO NOTIONS COINCIDE ONLY

WHEN EITHER THE CLUSTERINGS ARE PERFECT

OR BOTH GROUPS HAVE THE SAME “BASE COST”

ALGORITHMSThere is a natural LP-relaxation of k-median clustering for this problem

Yields a bicriterion approximation • at most clusters • each group has cost at most

<latexit sha1_base64="a8IVXR38MQYTL2JX0zwPTUunNJA=">AAAC9nicbVJda9RAFJ1N/Wjj166+CL4EF6GCrokg9rHUFx8ruG1hE5bJ5GZ32PliZrJ1OwT6R+qb9lX8H/4AwR/jZFOkm3ph4HDuuffcuTO5YtTYOP7dC7Zu3b5zd3snvHf/wcNH/cHjIyMrTWBMJJP6JMcGGBUwttQyOFEaMM8ZHOeLD03+eAnaUCk+25WCjOOZoCUl2Hpq2h8s3uwmr9Ml1qAMZVK8nPaH8SheR3QTJFdguP/07M/O+c+Dw+mg9ystJKk4CEsYNmaSxMpmDmtLCYM6TCsDCpMFnsHEQ4E5mMytZ6+jF54polJqf4SN1uz1Coe5MSueeyXHdm66uYb8X25S2XIvc1SoyoIgrVFZscjKqFlEVFANxLKVB5ho6meNyBxrTKxf14ZL01vhM1lverOZ9GVz/uofosRLBJwSyTkWhUtzzNQc1x5IVjS3kMylLddRWm8MXth4SeVSzSOrG5GG67IlkHqSZC4FYSoNjbqtyUs3TOpu15xXHXNPdDRLKRpj39n5BmEY+g+QdJ/7Jjh6O0rejeJP/ifsoTa20TP0HO2iBL1H++gjOkRjRNApukDf0WXwJfgafAsuW2nQu6p5gjYi+PEXgID7MQ==</latexit>

k/(1 � #)<latexit sha1_base64="Y08EgEHrMphXOsTCp/e7GVny6Ok=">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</latexit>

2l/#

Similar result hold for • k-means clustering • facility location • clustering/facility location with capacity constraints

Abbasi/Bhaskara/V 2021

Ghadiri/Samadi/Vempala 2021

Makarychev/Vakilian 2021

VOTING ACCESS PROJECTAbbasi, Barrett, Friedler, V

We collected voter demographics and addresses, and early voting polling locations.

We geocoded the addresses and ran an analysis.

EQUITABLE INFORMATION FLOW IN

NETWORKS

SOCIAL CAPITAL [COLEMAN]

• Social standing within a network confers utility on an individual.

• Social “position” in a network is a class marker defined by the network, not the individual.

• Should we be considered about discrimination based on social position? [boyd, Marwick and Levy]

We must rethink our models of discrimination and our mechanisms of accountability. No longer can we just concern ourselves with immutable

characteristics of individuals; we must also attend to the algorithmically produced position of an individual, which, if not acknowledged, will be used to reify

contemporary inequities.

INFORMATION ACCESS

• Social networks grow through recommendations as well as organically

• Network position confers advantage ([Granovetter])

• Access to information that improves network position relies on …. network position

• “edges in social network” == “biased input data”

INFLUENCE MAXIMIZATION

Given a graph, a mechanism for spreading information and k seeds, how many nodes can be

be influenced?

WELFARE FUNCTIONS

Probability that v gets the information.

Welfare function

Welfare of vertex set in graph G with seed set S:

f<latexit sha1_base64="viODc+H7PrdU3eZYovOUDsa9A10=">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</latexit>

-mean

ACCESS GAPS

Definition: Access gap of a partition V, V’ of G with seed set S is

Definition: In a graph G, the rich get richer if there is a partition (V, V’) such that the optimal intervention S* satisfies

The access gap increases after intervention

Fish/Bashardoust/boyd/Friedler/Scheidegger/V 2019

THE RICH ALWAYS GET RICHER

Proposition

A RELAXED CRITERION

A RELAXED CRITERION

REQUIRE THAT ANY INTERVENTION THAT MAXIMIZES UTILITY MUST

ENSURE THAT ANY GROUP UTILITY MUST IMPROVE

BALANCE IS FEASIBLE

Minimax welfare is balanced make sure that the node with the worst access is improved

BALANCE IS FEASIBLE

Minimax welfare is balanced make sure that the node with the worst access is improved

Then is -imbalanced

other ways of maximizing utility don’t work

COMPLEXITY OF COMPUTING BEST MINIMAX INTERVENTION

• This problem is not submodular (aka “it’s not nice to optimize”)

• Finding the best intervention is quite hard and even heuristics are not that great …. yet.

REFLECTIONS



FRAMEWORK



NORMATIVE CONCERNS




FRAMEWORK



NORMATIVE CONCERNS


Choice of optimization Choices in representation

Choices in what data to collect….


VALUES + ALGORITHMS

FRAMEWORKS + NORMS

FRAMEWORKS + NORMS


VALUES + ALGORITHMS

FRAMEWORKS + NORMS

FRAMEWORKS + NORMS

Analyze Introspect

Build

ACKNOWLEDGEMENTS

“the band” Sorelle Friedler (Haverford)

Carlos Scheidegger (Arizona)

“special guests” Andrew Selbst (UCLA)

danah boyd (Data & Society)

“collaborators” Janet Vertesi (Princeton)

Karen Levy (Cornell) Mark Alfano (Macquarie)

Neal Patwari (Washington U) Kristian Lum (Penn)

Aaron Horowitz (ACLU) Berk Ustun (UCSD)

Students Josephine Moeller

Mohsen Abbasi Lizzie Kumar

Ashkan Bashardoust Pegah Nokhiz

Chitradeep Dutta Roy Scott Neville

Danielle Ensign

Funders NSF

Mozilla Foundation

CRITICAL ALGORITHM STUDIES

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