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2022
- Sanchez-Martinez et al., Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
- Duch-Brown et al., New Publication in Research Policy: Market power and artificial intelligence work on online labour markets
- Hupont et al., Monitoring diversity of AI conferences: lessons learnt and future challenges in the DivinAI project
- Fernandez Llorca, D. and Gomez Gutierrez, E., Artificial Intelligence in Autonomous Vehicles: towards trustworthy systems
- Hamon et al., Artificial Intelligence in Automated Driving: an analysis of safety and cybersecurity challenges
- Biparva et al., Video action recognition for lane-change classification and prediction of surrounding vehicles
- Martinez Plumed et al., AI Watch: Revisiting Technology Readiness Levels for relevant Artificial Intelligence technologies
- Izquierdo Gonzalo et al., Testing Predictive Automated Driving Systems: Lessons Learned and Future Recommendations
- Hupont et al., The landscape of facial processing applications in the context of the European AI Act and the development of trustworthy systems
- Charisi et al., Artificial Intelligence and the Rights of the Child: Towards an Integrated Agenda for Research and Policy
- Grunert et al., HumaniTies and Artificial Intelligence
- Escobar-Planas, Towards Trustworthy Conversational Agents for Children
- Izquierdo et al., Vehicle trajectory prediction on highways using bird eye view representations and deep learning
- Chraibi Kaadoud et al., Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI
- Behjati et al., Single Image Super-Resolution Based on Directional Variance Attention Network
- Estevez Almenzar et al., Glossary of human-centric artificial intelligence
- Escobar-Planas et al., Guidelines to Develop Trustworthy Conversational Agents for Children
- Garcia Daza et al., Sim-to-real transfer and reality gap modeling in model predictive control for autonomous driving
- Hernández Martínez et al., Towards view-invariant vehicle speed detection from driving simulator images
- Martín Serrano et al., Insertion of real agents behaviors in CARLA autonomous driving simulator
- Escobar-Planas et al., “That Robot Played with Us!” Children’s Perceptions of a Robot after a Child-Robot Group Interaction
- Escobar-Planas et al., Enhancing the Design of a Conversational Agent for an Ethical Interaction with Children
- Charisi et al., Exploring the Concept of Fairness in Everyday, Imaginary and Robot Scenarios: A Cross-Cultural Study With Children in Japan and Uganda
- Lemaignan et al., UNICEF Guidance on AI for Children: Application to the Design of a Social Robot For and With Autistic Children
- Gomez, R. and Charisi, V., UNICEF Pilot study on Policy Guidance for AI for Children
- Davison et al., Words of encouragement: how praise delivered by a social robot changes children’s mindset for learning
- Portela et al., A Comparative User Study of Human Predictions in Algorithm-Supported Recidivism Risk Assessment
2021
- Grubanov-Boskovic et al., Health and long-term care workforce: demographic challenges and the potential contribution of migration and digital technology
- Charisi et al., The Effects of Robot Cognitive Reliability and Social Positioning on Child-Robot Team Dynamics
- Fernández Llorca et al., Vision-based vehicle speed estimation: A survey
- Tolan et al., Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks
- Charisi et al., What future for European robotics?
- Gomez-Gonzalez et al., Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
- Lorenzo et al., CAPformer: Pedestrian Crossing Action Prediction Using Transformer
- Corrales Sánchez et al., Are We Ready for Accurate and Unbiased Fine-Grained Vehicle Classification in Realistic Environments?
- Izquierdo et al., Vehicle Lane Change Prediction on Highways Using Efficient Environment Representation and Deep Learning
- Hupont et al., How diverse is the ACII community? Analysing gender, geographical and business diversity of Affective Computing research
- Gómez et al., Evaluating recommender systems with and for children: towards a multi-perspective framework
- Hernández Martínez et al., Data-driven vehicle speed detection from synthetic driving simulator images
- Gómez-Cañón et al., Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications
- Quintanar et al., Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information
- Carrasco et al., SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs
- Fernandez Llorca et al., Trustworthy Autonomous Vehicles
- Charisi et al., Designing and Developing Better Robots for Children: A Fundamental Human Rights Approach
- Charisi et al., The Effects of Robot Cognitive Reliability and Social Positioning on Child-Robot Team Dynamics
2020
- Freire et al., Measuring Diversity of Artificial Intelligence Conferences
- Gómez-González et al., Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact
- Samoili et al., AI Watch: Defining Artificial Intelligence
- Charisi et al., Child-Robot Collaborative Problem-Solving and the Importance of Child's Voluntary Interaction: A Developmental Perspective
- Miron et al., Addressing multiple metrics of group fairness in data-driven decision making
- Martínez-Plumed et al., Does AI Qualify for the Job? A Bidirectional Model Mapping Labour and AI Intensities
- Tolan, S., Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges
- Tolan et al., Measuring the Occupational Impactof AI: Tasks, Cognitive Abilitiesand AI Benchmarks
- Gómez-González, E., Artificial Intelligence in Medicine and Healthcare: applications, availability and societal impact
- Miron et al., Evaluating causes of algorithmic bias in juvenile criminal recidivism
- De Nigris et al., Artificial Intelligence and Digital Transformation: early lessons from the COVID-19 crisis
- Shakespeare et al., Exploring Artist Gender Bias in Music Recommendation
- Samoili et al., Setting the Boundaries of the AI Landscape: An Operational Definition for the European Commission’s AI Watch
- Fabra-Boluda et al., Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques
- Hernández-Orallo et al., AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues
- Martínez-Plumed et al., Tracking AI: The Capability is (Not) Near
- Martínez-Plumed et al., CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories
- Martínez-Plumed et al., AI Watch: Assessing Technology Readiness Levels for Artificial Intelligence
- Martínez-Plumed et al., Futures of Artificial Intelligence through Technology Readiness Levels, Telematics and Informatics
2019
- Tolan, S., Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges
- Martens, Bertin and Tolan, Songül, Will This Time Be Different? A Review of the Literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth
- Paniagua, E., El dilema de la tecnología ética – The dilemma of ethical technologies
- Martens, B., The impact of data access regimes on artificial intelligence and machine learning
- Tolan et al., Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia
- Mathioudakis et al., Affirmative Action Policies for Top-k Candidates Selection, With an Application to the Design of Policies for University Admissions
- Paniagua, E., The dismissed cancer tech assessment
- Porcaro L. and Gomez E., 20 Years of Playlists: A Statistical Analysis on Popularity and Diversity
- Porcaro L. and Gomez E., A Model for Evaluating Popularity and Semantic Information Variations in Radio Listening Sessions
- Sturm et al., Artificial Intelligence and Music: Open Questions of Copyright Law and Engineering Praxis
- Sanchez-Martinez et al., Machine Learning for Clinical Decision-Making: Challenges and Opportunities
- Knees et al., Proceedings of the 1st Workshop on Human-Centric Music Information Research Systems
- Gomez et al., Fairness, Accountability and Transparency in Music Information Research (FAT-MIR)
- Meeting Report: PHRP Expert Meeting on Predictive Policing Report
- Alcorn et al., Educators’ views on using humanoid robots with autistic learners in special education settings in England
- Wijnen et al., Now we’re talking: Learning by explaining your reasoning to a social robot
- Workshop report: AI and child rights policy (UNICEF)
