– The public sector aims to capture the benefits of using AI.
– The EU AI strategy focuses on trust, excellence, and safeguarding rights.
– Some AI applications in public services have not been developed responsibly.
– The use of AI in public services has increased over the past two years.
– Ensuring explainability of AI systems in public services is crucial.
– There is growing public concern over the development and use of AI.
– The public sector should lead in creating trustworthy AI.
– Different definitions of AI in public services are in use.
– Human responsibility in AI becomes marginalized as complexity increases.
– Automation of decisions or services is an element of human-centeredness.
– Public services include a combination of private and non-profit organizations.
– Pre-procurement can be used to assess the feasibility of AI projects.
– Multilingual datasets are used to train local AI models.
– Access to data for training and testing is a barrier.
– Complex data regulation landscape is a barrier.
– Sharing of best practices is a barrier.
– Alignment of AI strength and digital government goals is a barrier.
– AI can bring efficiency gains and process optimization.
– AI can reduce human error and fraud.
– AI adoption depends on the level of digitization in society.
– AI use in public sector is not lagging behind other sectors.
– Benefits of AI in public sector: efficiency gains, less error/fraud, digitization.
– Recommendations: promote Human Rights Impact Assessment, simplify regulatory landscape.
– AI can improve digital services, predictive services, inclusiveness, and accessibility.
– AI use in direct service delivery needs more evidence.
– The uptake of AI in the EU public sector is not lagging behind other sectors.
– Responsible development of AI in public services is crucial.
– Some AI applications in public services pose unacceptable risks and are forbidden.
– Public investments can accelerate the societal uptake of responsible AI.
– Open Data can be used for AI to improve public services.
– Ensuring explainability and trustworthiness of AI systems is challenging.
– The public sector should lead in creating trustworthy AI.
– Different definitions of AI in public services exist.
– Automation of decisions or services in public services varies.
– Access to data, complex regulations, and sharing best practices are barriers to uptake.
– The paper discusses the benefits and challenges of using AI in public services.
– It emphasizes the importance of responsible and human-centered AI development.
– The public sector aims to lead in creating trustworthy AI.
– The uptake of AI in the EU public sector is not lagging behind other sectors.
– Some AI applications in public services, such as those manipulating human behavior, are considered unacceptable and forbidden.
– Access to data, complex data regulation, and sharing of best practices are barriers to AI uptake in the public sector.
– AI in public services focuses on law enforcement, surveillance, and process optimization.
– The potential for errors and harms increases with the increased use of AI.
– The paper concludes with recommendations for accelerating the uptake of responsible AI in public services.
– Public sector should educate the public about AI through free education.
– Services of general economic interest are subject to European rules.
– Experimentation and regulatory sandboxing are important for developing trustworthy AI.
– Multidisciplinary approach needed for AI development in the public sector.
