Descripción del proyecto
Unos algoritmos justos para la inteligencia artificial
Cada vez se usan más los sistemas basados en la inteligencia artificial (IA) en aplicaciones que proporcionan decisiones o evaluaciones automáticamente. Estas pueden afectar a individuos o grupos de personas respecto a cuestiones importantes como los pagos o el tratamiento médico, pero el sesgo de la IA puede constituir un problema. Las fuentes de sesgos de las decisiones de la IA pueden ser datos derivados automáticamente, algoritmos que procesan datos o el uso de aplicaciones. Para eliminar los sesgos de la IA en estas tres fases, el proyecto NoBIAS, financiado con fondos europeos, desarrollará algoritmos conscientes de lo que es justo. Dichos algoritmos se basarán en principios éticos y jurídicos y estarán diseñados como soluciones técnicas en un esfuerzo multidisciplinar de quince investigadores formados, entre otros campos, en informática, ciencia de datos, aprendizaje automático, derecho y ciencias sociales.
Objetivo
Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impacts on individuals and society. Their decisions might affect everyone, everywhere and anytime entailing risks, such as being denied a credit, a job, a medical treatment, or specific news. Businesses might miss chances, because biases make AI-driven decisions underperform; much worse, they may contravene human rights when treating people unfairly.
Bias may arise at all stages of AI-based decision making processes: (i) when data is collected, (ii) when algorithms turn data into decision making capacity, or (iii) when results of decision making are used in applications. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in the training, design and deployment of AI algorithms to ensure social good while still benefiting from the potential of AI.
NoBIAS will develop novel methods for AI-based decision making without bias by taking into account ethical and legal considerations in the design of technical solutions. The core objectives of NoBIAS are to understand legal, social and technical challenges of bias in AI-decision making, to counter them by developing fairness-aware algorithms, to automatically explain AI results, and to document the overall process for data provenance and transparency.
We will train a cohort of 15 ESRs (Early-Stage Researchers) to address problems with bias through multi-disciplinary training and research in computer science, data science, machine learning, law and social science. ESRs will acquire practical expertise in a variety of sectors from telecommunication, finance, marketing, media, software, and legal consultancy to broadly foster legal compliance and innovation. Technical, interdisciplinary and soft-skills will give ESRs a head start towards future leadership in industry, academia, or government.
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MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)Coordinador
30167 Hannover
Alemania