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Act.AI

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Developing Bias Auditing and Mitigation Tools for Self-Assessment of AI Conformi...

Developing Bias Auditing and Mitigation Tools for Self-Assessment of AI Conformity with the EU AI Act through Statistical Matching The vision behind Act.AI is to utilize statistical matching for mitigating and auditing bias in Artificial Intelligence (AI) models. AI has been rapidly growing in various industries, from financial services to healthcare, educati... ver más

30/11/2025

BCAM - BASQUE CENT...

150K€

Presupuesto del proyecto: 150K€

Líder del proyecto

BCAM - BASQUE CENTER FOR APPLIED MATHEMATICS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5 | 5M€

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-03-04

ERC-2023-POC: ERC PROOF OF CONCEPT GRANTS Objective:Objectives:The ERC Proof of Concept Grants aim at facilitating exploration of the commerci...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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1 Participantes

BCAM - BASQUE CENTER FOR APP...

150.00K€ | Lider

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Duración del proyecto: 20 meses Fecha Inicio: 2024-03-04
Fecha Fin: 2025-11-30

Líder del proyecto

BCAM - BASQUE CENTER FOR APPLIED MATHEMATICS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5 | 5M€

Presupuesto del proyecto 150K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The vision behind Act.AI is to utilize statistical matching for mitigating and auditing bias in Artificial Intelligence (AI) models. AI has been rapidly growing in various industries, from financial services to healthcare, education, and job recruitment. However, as AI algorithms have become increasingly sophisticated and pervasive in decision-making processes, concerns have arisen about their fairness and compliance with regulations. In particular, the EU AI Act requires that AI providers in high-risk applications -- such as employment, credit, or healthcare -- to identify (and thereby address) discrimination by their algorithms against certain demographics of people. However, ensuring compliance with the Act can be challenging, particularly for AI startups that may not have the resources or expertise to fully understand and implement the Act's requirements. Addressing existing disconnects between AI fairness toolkits' capabilities and current practitioner needs, the Act.AI tool can be easily integrated into any AI workflow, in a plug and play fashion, to continuously monitor and improve its fairness. A key aspect of Act.AI is the ability to operate with different types of data (tabular, images, and text) in a variety of contexts (binary and multiclass classification and regression). It is also able to match datasets in different domains including out-of-distribution data even if these datasets have different numbers of variables or features. To ensure usability of Act.AI, it will integrate feedback from relevant stakeholders from two immediate target markets: financial service and healthcare.

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