New EU project to reduce discrimination through AI


Nov 17, 2022

MAMMOth calls
the new EU project
and actually faces
a mammoth task.

AI opens up many possibilities. At the same time, it can force discriminatory decision-making – for example, in education, job application processes or advertising. The MAMMOth project aims to change that.

 

CSH scientist Fariba Karimi and her team are developing fairness measurements that take into account not just one attribute, such as skin color, but several overlapping attributes like gender, age and race.

MAMMOth = Multi-Attribute, Multimodal Bias Mitigation in AI Systems

Businesses, politics and many other sectors are increasingly relying on artificial intelligence and making far-reaching decisions for individuals and society based on that. “On the one hand, this opens up enormous opportunities for different sectors such as education, banking or healthcare, as well as on a personal level, for example, in job applications or ad targeting. On the other hand, artificial intelligence (AI) in particular runs the risk of further enforcing discrimination against minorities and marginalized groups in the population – based on so-called protected attributes such as gender, race and age,” explains Fariba Karimi, senior scientist at Computational Social Science at CSH Vienna.

 

By doing so, AI systems reinforce already existing biases and also contribute to the development of new, unknown types of discrimination – so-called black-box biases – instead of using their potential to compensate for inequalities.

 

Capturing discrimination through multiple attributes

 

Over the course of the three-year project, Karimi and her team will develop fairness measurements that go beyond single protected attributes such as gender or skin color. “For example, we want our fairness measurements to work not only for women, but also for women who are immigrants or from disadvantaged ethnic groups,” she says. Her focus is on precisely this multi-criteria fairness in network data – when, for example, inequalities result from people occupying different positions in the context of an underlying network.

 

Minorities should not become invisible in algorithms

 

Discrimination is not a new problem. But the fact that AI technology continues to reinforce discrimination has led to the rise of fairness-aware machine learning (ML) as part of responsible AI. This aims to develop machine learning models that, on the one hand, perform well in terms of prediction, but on the other hand, do not discriminate with respect to protected attributes such as gender or race. „Much effort has been made, but so far the proposed methods have limited impact and do not reflect the complexity and requirements of real-world applications,“ Karimi states.

 

Twelve institutes pull together

 

The new EU project, MAMMOth, aims to change that: In it, experts from twelve different institutions are developing an innovative, fairness-aware, AI data-driven foundation that provides the necessary tools to mitigate discrimination and multi-discrimination and ensure accountability of AI systems. “Through designing and implementing multi-criteria fairness measures and mitigations we want to ensure that minorities do not face any visibility issues in algorithms and treated fairly in sectors that rely on machines in decision-making processes. More fair algorithms means better representation and diversity in society which also means more inclusive and just societies“, Karimi said.

 

To this end, the project will actively target numerous communities of vulnerable and/or underrepresented groups in AI research from the outset. The so-called co-creation approach will ensure that the real needs and hardships of users are at the heart of the research agenda and guide the project’s activities. The solutions developed will then be demonstrated in pilot projects in three relevant areas (finance/loan applications, identity verification systems and academic evaluation).

 

Here you can find more information: http://mammoth-ai.eu/

 

Read more about Fariba’s research on gender inequalities in research here.


People

Nov 30, 2022

Bridging the gap between academia and industry

Publication

W. Schueller, J. Wachs, V. D. P. Servedio, S. Thurner, V. Loreto

Evolving collaboration, dependencies, and use in the Rust Open Source Software ecosystem

Scientific Data 9 (2022) 703

Event

CSH Talk by Zlata Tabachová: "Supply chain shock propagation and financial systemic risk"


Dec 02, 2022 | 15:0016:00

Complexity Science Hub Vienna

Publication

H. Kong, S. Martin-Gutierrez, F. Karimi

Influence of the first-mover advantage on the gender disparities in physics citations

Communications Physics 5 (243) (2022)

Event

CSH Talk by Elma Dervic: "Unravelling cradle-to-grave disease trajectories from multilayer comorbidity networks"


Dec 16, 2022 | 15:3016:00

Complexity Science Hub Vienna

Press

Was crime as bad as it was portrayed [feat.Rafael Prieto-Curiel]


abcNEWS, Nov 18, 2022

Press

A charada do desequilibrio de genero na ciencia [Portuguese] [feat.Fariba Karimi]


Pesquisa Fapesp, Nov 17, 2022

Publication

N. Pontika, T. Klebel, A. Correia, H. Metzler, P. Knoth, T. Ross-Hellauer

Indicators of research quality, quantity, openness and responsibility in institutional review, promotion and tenure policies across seven countries

Quantitative Science Studies 1-49

Event

CSH Talk by Meike Zehlike: "Beyond Incompatibility: Trade-offs between Mutually Exclusive Fairness Criteria in Machine Learning and Law"


Dec 16, 2022 | 15:0015:30

Complexity Science Hub Vienna

Research News

Dec 6, 2022

Complexity Science meets Digital Humanism

Press

MAMMOth: KI-Tendenz zur Diskriminierung durchbrechen [feat.Fariba Karimi]


Brutkasten, Nov 22, 2022

Spotlight

Dec 2, 2022

Avoiding supply chain bottlenecks with Big Data

People

Nov 30, 2022

Bridging the gap between academia and industry

Publication

W. Schueller, J. Wachs, V. D. P. Servedio, S. Thurner, V. Loreto

Evolving collaboration, dependencies, and use in the Rust Open Source Software ecosystem

Scientific Data 9 (2022) 703

Event

CSH Talk by Zlata Tabachová: "Supply chain shock propagation and financial systemic risk"


Dec 02, 2022 | 15:0016:00

Complexity Science Hub Vienna

Publication

H. Kong, S. Martin-Gutierrez, F. Karimi

Influence of the first-mover advantage on the gender disparities in physics citations

Communications Physics 5 (243) (2022)

Event

CSH Talk by Elma Dervic: "Unravelling cradle-to-grave disease trajectories from multilayer comorbidity networks"


Dec 16, 2022 | 15:3016:00

Complexity Science Hub Vienna

Press

Was crime as bad as it was portrayed [feat.Rafael Prieto-Curiel]


abcNEWS, Nov 18, 2022

Press

A charada do desequilibrio de genero na ciencia [Portuguese] [feat.Fariba Karimi]


Pesquisa Fapesp, Nov 17, 2022

Publication

N. Pontika, T. Klebel, A. Correia, H. Metzler, P. Knoth, T. Ross-Hellauer

Indicators of research quality, quantity, openness and responsibility in institutional review, promotion and tenure policies across seven countries

Quantitative Science Studies 1-49

Event

CSH Talk by Meike Zehlike: "Beyond Incompatibility: Trade-offs between Mutually Exclusive Fairness Criteria in Machine Learning and Law"


Dec 16, 2022 | 15:0015:30

Complexity Science Hub Vienna

Research News

Dec 6, 2022

Complexity Science meets Digital Humanism

Press

MAMMOth: KI-Tendenz zur Diskriminierung durchbrechen [feat.Fariba Karimi]


Brutkasten, Nov 22, 2022

Spotlight

Dec 2, 2022

Avoiding supply chain bottlenecks with Big Data

People

Nov 30, 2022

Bridging the gap between academia and industry

Research News

Dec 6, 2022

Complexity Science meets Digital Humanism

Spotlight

Dec 2, 2022

Avoiding supply chain bottlenecks with Big Data

Research News

Nov 28, 2022

New evidence for possible domino effects in cryptoassets

Spotlight

Nov 28, 2022

BUSTS AFTER BOOMS, BUT WHY?

Research News

Nov 17, 2022

New EU project to reduce discrimination through AI

Research News

Oct 13, 2022

Yes we can -- STEM is also for women

Research News

Oct 13, 2022

Predicting the economic downturn during the pandemic

Press

MAMMOth: KI-Tendenz zur Diskriminierung durchbrechen [feat.Fariba Karimi]


Brutkasten, Nov 22, 2022

Press

Was crime as bad as it was portrayed [feat.Rafael Prieto-Curiel]


abcNEWS, Nov 18, 2022

Press

A charada do desequilibrio de genero na ciencia [Portuguese] [feat.Fariba Karimi]


Pesquisa Fapesp, Nov 17, 2022

Press

COVID : Les animaux peuvent-ils attraper le virus? [French] [feat.Amélie Desvars-Larrive]


News24, Nov 17, 2022

Press

Departure of Tech Workers Weighs on Russian Economy [feat.Johannes Wachs]


The Wall Street Journal, Nov 14, 2022

Press

Männer profitieren stärker vom Pionier-Vorteil als Frauen [feat.Fariba Karimi]


Spektrum Online, Oct 26, 2022

Press

Can your phone tell if a bridge is in good shape?


Scienmag, Nov 3, 2022

Press

Which Animals Catch COVID? This Database Has Dozens of Species and Counting [feat.Amélie Desvars-Larrive]


Scientific American, Oct 19, 2022

Press

Hinweise auf subtile Bevorzugung von Arbeiten von Männern in Physik [feat.Fariba Karimi]


APA Science, Oct 14, 2022

Press

Female representation in physics: Can we fix it?[feat.Fariba Karimi]


Cosmos Magazine , Oct 17, 2022

Press

Hundreds of Russia's top software developers may have left the country [feat.Johannes Wachs]


New Scientist , Oct 19, 2022

Publication

W. Schueller, J. Wachs, V. D. P. Servedio, S. Thurner, V. Loreto

Evolving collaboration, dependencies, and use in the Rust Open Source Software ecosystem

Scientific Data 9 (2022) 703

Publication

N. Pontika, T. Klebel, A. Correia, H. Metzler, P. Knoth, T. Ross-Hellauer

Indicators of research quality, quantity, openness and responsibility in institutional review, promotion and tenure policies across seven countries

Quantitative Science Studies 1-49

Publication

H. Kong, S. Martin-Gutierrez, F. Karimi

Influence of the first-mover advantage on the gender disparities in physics citations

Communications Physics 5 (243) (2022)

Publication

A. Pichler, M. Pangallo, M. del Rio-Chanona, F. Lafond, D. Farmer

Forecasting the propagation of pandemic shocks with a dynamic input-output model

Journal of Economic Dynamics and Control (2022) 104527

Publication

J. Lasser, S. Taofeek Aroyehun, et al.

Social media sharing of low quality news sources by political elites

PNAS Nexus (2022) pgac186

Publication

R. Prieto Curiel, A. Schumann, I. Heo, P. Heinrigs

Detecting cities with high intermediacy in the African urban network

Computers, Environment and Urban Systems 98 (2022) 101869

Publication

T. Reisch, G. Heiler, C. Diem, P. Klimek, S. Thurner

Monitoring supply networks from mobile phone data for estimating the systemic risk of an economy

Scientific Reports 12 (13347) (2022)

Publication

G. De Marzo, F. Pandolfelli, V.D.P. Servedio

Modeling innovation in the cryptocurrency ecosystem

Scientific Reports 12 (12942) (2022)

Publication

A. Nerpel, et al.

SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals

Scientific Data 9 (438) (2022)

Publication

M. Kaleta, J. Lasser, E. Dervic, et al.

Stress-testing the resilience of the Austrian healthcare system using agent-based simulation

Nature Communications 13 (4259) (2022)

Publication

F. Amman, et al.

Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale

Nature Biotechnology (2022)

Publication

J. V. Camp, A. Desvars-Larrive, N. Nowotny, C. Walzer

Monitoring urban zoonotic virus activity: Are city rats a promising surveillance tool for emerging viruses?

Viruses 14 (7) (2022) 1516

Event

CSH Talk by Zlata Tabachová: "Supply chain shock propagation and financial systemic risk"


Dec 02, 2022 | 15:0016:00

Complexity Science Hub Vienna

Event

CSH Workshop: "Innovation and obsolescence in the space of the possible"


Dec 12, 2022Dec 14, 2022

Complexity Science Hub Vienna

Event

CSH Talk by Meike Zehlike: "Beyond Incompatibility: Trade-offs between Mutually Exclusive Fairness Criteria in Machine Learning and Law"


Dec 16, 2022 | 15:0015:30

Complexity Science Hub Vienna

Event

CSH Talk by Elma Dervic: "Unravelling cradle-to-grave disease trajectories from multilayer comorbidity networks"


Dec 16, 2022 | 15:3016:00

Complexity Science Hub Vienna