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alignAI

financed

value ALIGNed socio technical systems using large language models LLMs

Large Language Models (LLMs) are trained on broad data, using self-supervision at scale, to complete a wide range of tasks. Wider use of LLMs has risen in recent months due to applications such as ChatGPT. Although LLMs bring many... see more

31/08/2028

TUM

4M€

Project Budget: 4M€

Project leader

TECHNISCHE UNIVERSITAET MUENCHEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2024-07-08

HORIZON-MSCA-2023-DN-01-01: MSCA Doctoral Networks 2023 Expected Outcome:Project results are expected to contribute to the following outcomes:

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

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12 Participantes

TUM

1.30M€ | Leader

TECHNION ISRAEL INSTITUTE O...

N.D. | participant

TU/e

1.10M€ | participant

IDIAP

N.D. | participant

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Project duration: 49 months Date Start: 2024-07-08
End date: 2028-08-31

Project leader

TECHNISCHE UNIVERSITAET MUENCHEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 4M€

participation deadline Sin fecha límite de participación.

Project description Large Language Models (LLMs) are trained on broad data, using self-supervision at scale, to complete a wide range of tasks. Wider use of LLMs has risen in recent months due to applications such as ChatGPT. Although LLMs bring many opportunities to improve our everyday lives, the impacts on humans and society have not yet been prioritized or fully understood. Given the rapid development of these tools, the risk of negative implications is significant if LLMs are not developed and deployed in a way that is aligned with human values and responds to individual needs and preferences. To mitigate any negative consequences, academia, in close collaboration with industry, needs to train the next generation of researchers to understand the complexities of the socio-technical implications surrounding the use of LLMs. The alignAI Doctoral Network will train 17 doctoral candidates (DCs) to work in the international and highly interdisciplinary field of LLM research and development. The core of the project focuses on the alignment of LLMs with human values, identifying relevant values and methods for alignment implementation. Two principles provide a foundation for the approach. First, explainability is a key enabler for all aspects of trustworthiness, accelerating development, promoting usability, and facilitating human oversight and auditing of LLMs. Second, fairness is a key aspect of trustworthiness, facilitating access to AI applications and ensuring equal impact of AI-driven decision-making. The practical relevance of the project is ensured by three use cases in education, positive mental health, and news consumption. This approach allows us to develop specific guidelines and test prototypes and tools to promote value alignment. We follow a unique methodological approach, with DCs from social sciences and humanities twinned with DCs from technical disciplines for each use case (9 DCs in total), while the other 8 DCs carry out horizontal research across the use cases.

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