Cultural Data Insights

Collecting datasets to define cultural scenarios and detect algorithmic discrimination across diverse contexts.

Empowering Cultural Data Insights

We specialize in collecting diverse datasets and analyzing algorithmic biases across cultures to enhance AI performance and promote fairness in technology.

A person is viewing a map with red data points on a computer monitor, likely indicating a geographical distribution. The image has a focus on technology and data analysis.
A person is viewing a map with red data points on a computer monitor, likely indicating a geographical distribution. The image has a focus on technology and data analysis.
A cultural performance is taking place with a large group of people forming a circle. A performer in the center is dressed in traditional colorful attire and adorned with an ornate headdress. The crowd surrounding them is engaged, raising their arms and appearing to participate actively. The audience watches intently in the background.
A cultural performance is taking place with a large group of people forming a circle. A performer in the center is dressed in traditional colorful attire and adorned with an ornate headdress. The crowd surrounding them is engaged, raising their arms and appearing to participate actively. The audience watches intently in the background.

Discrimination Detection Tool

Evaluate AI models' performance in various cultural scenarios using advanced algorithms.

Optimization Strategies

Design targeted strategies to reduce algorithm discrimination through data augmentation and model fine-tuning.

A section of printed text discusses the disadvantages of online surveys, referencing Denscombe (2018). Specific phrases are highlighted in green, such as 'speak for itself,' 'let empirical data,' 'quantitative,' and 'qualitative.' The text mentions concerns about focusing on empirical data without considering its implications and compares quantitative methods to qualitative ones. Shadows partially obscure the text, and the section is titled '5.3 Geographical Information System.'
A section of printed text discusses the disadvantages of online surveys, referencing Denscombe (2018). Specific phrases are highlighted in green, such as 'speak for itself,' 'let empirical data,' 'quantitative,' and 'qualitative.' The text mentions concerns about focusing on empirical data without considering its implications and compares quantitative methods to qualitative ones. Shadows partially obscure the text, and the section is titled '5.3 Geographical Information System.'

Data Optimization

Design strategies to optimize models based on detection results.

Detailed map displaying data visualization with blue circular markers representing specific data points across a geographical area labeled with city names such as Lisbon and Evora. Bold, brightly colored numerical statistics appear on the left side with the terms 'Suspeitos' and 'Amostras,' suggesting a context of data tracking or analysis.
Detailed map displaying data visualization with blue circular markers representing specific data points across a geographical area labeled with city names such as Lisbon and Evora. Bold, brightly colored numerical statistics appear on the left side with the terms 'Suspeitos' and 'Amostras,' suggesting a context of data tracking or analysis.

Cross-Cultural

Analyze sources of algorithm bias across diverse cultural frameworks.

A cultural performance features a performer in an elaborate, colorful costume with intricate designs, standing on a stage. Behind the performer, a poster on the stone wall advertises the Sudbury Dragon Boat Festival. To the right, a vibrant, golden, and orange dragon prop is partially visible, suggesting a traditional dragon dance.
A cultural performance features a performer in an elaborate, colorful costume with intricate designs, standing on a stage. Behind the performer, a poster on the stone wall advertises the Sudbury Dragon Boat Festival. To the right, a vibrant, golden, and orange dragon prop is partially visible, suggesting a traditional dragon dance.

ImproveAlgorithmFairness:Throughthecross-culturalevaluationsystem,

significantlyreducebiasissuesinAImodelsacrossdifferentculturalcontexts.

PromoteGlobalAIInclusivity:Providescientificbasisforthecross-culturalfairness

ofglobalAIsystemdevelopmentandapplication.

OptimizationStrategyPromotion:Proposereusableoptimizationstrategiesand

evaluationframeworkstopromotethefairnessandinclusivityofAItechnology

development.

SocialTrustandAcceptance:Byreducingalgorithmdiscrimination,enhancepublictrust

andacceptanceofAItechnologies,promotingtheirsocietalapplication.