Systems based on artificial intelligence (AI) are increasingly being used in applications automatically issuing decisions or assessments. They can impact individuals or groups of people with regard to important questions like payments or medical treatment but AI bias can be an issue. The sources of biases of AI decisions can be automatically derived data; algorithms processing data; or use of applications. To eliminate AI biases on all of three stages, the EU-funded NoBIAS project will develop fairness-aware algorithms.
Migration represents a constantly rising social and political concern for many governments. As a result, a better understanding of the drivers and dynamics of migration is important to ensure effective and successful migration governance. The EU-funded HumMingBird project intends to study the origins of migration and their interrelation with the tendency of people to emigrate. In this effort, the role migration data play is instrumental. Data will provide key information concerning drivers, geography, incentives and instruments related to the migration movements.
The emergence of data science has raised a wide range of concerns regarding its compatibility with the law, creating the need for experts who combine a deep knowledge of both data science and legal matters. The EU-funded LeADS project will train early-stage researchers to become legality attentive data scientists (LeADS), the new interdisciplinary profession aiming to address the aforementioned need. These scientists will be experts in both data science and law, able to maintain innovative solutions within the realm of law and help expand the legal frontiers according to innovation needs.
The EU-funded HumanE-AI-Net project brings together leading European research centres, universities and industrial enterprises into a network of centres of excellence. Leading global artificial intelligence (AI) laboratories will collaborate with key players in areas, such as human-computer interaction, cognitive, social and complexity sciences. The project is looking forward to drive researchers out of their narrowly focused field and connect them with people exploring AI on a much wider scale.
Maximising opportunities and minimising risks associated with artificial intelligence (AI) requires a focus on human-centred trustworthy AI. This can be achieved by collaborations between research excellence centres with a technical focus on combining expertise in theareas of learning, optimisation and reasoning. Currently, this work is carried out by an isolated scientific community where research groups are working individually or in smaller networks.
SoBigData++ strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. SoBigData++ is set to advance on such ambitious tasks thanks to SoBigData, the predecessor project that started this construction in 2015.
Black box AI systems for automated decision making, often based on machine learning over (big) data, map a user’s features into a class or a score without exposing the reasons why. This is problematic not only for lack of transparency, but also for possible biases inherited by the algorithms from human prejudices and collection artifacts hidden in the training data, which may lead to unfair or wrong decisions.
The Humane AI Flagship will develop the scientific foundations and technological breakthroughs needed to shape the ongoing artificial intelligence (AI) revolution.
AI4EU is the European Union’s landmark Artificial Intelligence project, which seeks to develop a European AI ecosystem, bringing together the knowledge, algorithms, tools and resources available and making it a compelling solution for users. Involving 80 partners, covering 21 countries, the €20m project kicked off in January 2019 and will run for three years. AI4EU will unify Europe’s Artificial Intelligence community. It will facilitate collective work in AI research, innovation and business in Europe.
PRO-RES project aims to produce a guidance framework regarding the delivery of Responsible Research and Innovation (RRI), which is required from researchers and research funding and performing organizations (RFPO), in order to balance political, institutional and professional contradictions and constraints.
This framework aims to:
• cover the spectrum of non-medical sciences and
• offer practical solutions for all stakeholders, that will comply with the highest standards of research ethics and integrity.
