Project description
Including demographics in language technology
Incorporating demographic factors in language technology is difficult. But that is the aim of the EU-funded INTEGRATOR project, developing novel data sets, theories and algorithms to incorporate demographic factors into language technology. This will improve the performance of existing tools for all users, reduce demographic bias and enable new applications. Current natural language processing technology fails to account for demographics, both in language understanding (e.g. sentiment analysis) and generation. This failure prevents us from reaching human-like performance, limits possible future applications and introduces systematic bias against underrepresented demographic groups.
Objective
The goal of INTEGRATOR is to develop novel data sets, theories, and algorithms to incorporate demographic factors into language technology. This will improve performance of existing tools for all users, reduce demographic bias, and enable completely new applications.
Language reflects demographic factors like our age, gender, etc. People actively use this information to make inferences, but current language technology (NLP) fails to account for demographics, both in language understanding (e.g. sentiment analysis) and generation (e.g. chatbots). This failure prevents us from reaching human-like performance, limits possible future applications, and introduces systematic bias against underrepresented demographic groups.
Solving demographic bias is one of the greatest challenges for current language technology. Failing to do so will limit the field and harm public trust in it. Bias in AI systems recently emerged as a severe problem for privacy, fairness, and ethics of AI. It is especially prevalent in language technology, due to language's rich demographic information. Since NLP is ubiquitous (translation, search, personal assistants, etc.), demographically biased models creates uneven access to vital technology.
Despite increased interest in demographics in NLP, there are no concerted efforts to integrate it: no theory, data sets, or algorithmic solutions. INTEGRATOR will address these by identifying which demographic factors affect NLP systems, devising a bias taxonomy and metrics, and creating new data. These will enable us to use transfer and reinforcement learning methods to build demographically aware input representations and systems that incorporate demographics to improve performance and reduce bias.
Demographically aware NLP will lead to high-performing, fair systems for text analysis and generation. This ground-breaking research advances our understanding of NLP, algorithmic fairness, and bias in AI, and creates new research resources and avenues.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-STG - Starting Grant
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-STG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20136 Milano
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.