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Personalized and Subjective approaches to Natural Language Processing

Project description

Revolutionary adaptable and accessible language technology

The increased use of AI by different online and social media platforms for moderation, abusive language detection and sentiment analysis has made it challenging to address these issues effectively. Moreover, the high cost and complexity of language technology limit access for many individuals and organisations, exacerbating the problem. The ERC-funded PERSONAE project will enhance access to language technology by advancing research on subjective tasks in natural language processing (NLP). It will focus on abusive language detection and sentiment analysis from the perspective of individual users, leading to better NLP model designs. Additionally, the project will develop subjective language technologies based on this research, ensuring they can adapt to individuals’ needs over time.

Objective

My project, PERSONAE, will make language technology (LT) accessible and valuable to everyone. I will revolutionize research in subjective tasks in NLP such as abusive language detection and sentiment and emotion analysis by developing a new field called personal NLP, yielding new datasets, tasks, and algorithms. This new research area will explore subjective tasks from the perspective of the individual as information receiver, making users active actors in the creation of LTs instead of mere recipients. This will allow for a more tailored, effective approach to NLP model design, resulting in better models overall.

Each person has their own interests and preferences based on their background and experience. These factors impact their views of what makes them happy, angry, or depressed over time. Language technologies (LTs) can consider individual preferences. However, current research presumes a static view of subjectivity: that a single ground truth underlies subjective tasks such as abusive language detection, an assumption that lacks human variability and prevents universal access to LTs.

Language-based AI such as virtual assistants is widely available. But despite significant scientific advances, most LT applications are inaccessible to individuals and their public's opinion has become increasingly negative. GPT-3's 2020 release boosted business-oriented applications such as copywriting and chatbots, yet few that let people improve their lives—for example, by controlling what they see on social media. This gap becomes more pronounced for subjective tasks.

I will design subjective LTs that can be adapted by individuals at will over time. Based on an ambitious meta approach able to generalize from existing, disconnected work, PERSONAE will rely on fully personalizable privacy-aware algorithms that can be used by anyone. It will reveal benefits of LT far beyond those of existing systems, paving the way for future applications.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

(opens in new window) ERC-2023-STG

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Host institution

UNIVERSITA COMMERCIALE LUIGI BOCCONI
Net EU contribution
€ 1 499 775,00
Address
VIA SARFATTI 25
20136 Milano
Italy
Region
Nord-Ovest Lombardia Milano
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 1 499 775,00

Beneficiaries (1)