Public and private value creation using artificial intelligence: An empirical study of AI voice robot users in Chinese public sector

Despite significant theoretical and empirical attention on public value creation in the public sector, the relationship between artificial intelligence (AI) use and value creation from the citizen perspective remains poorly understood. We ground our study in Moore's public value management to examine the relationship between AI use and value...

Short and long-term innovations on dietary behavior assessment and coaching: Present efforts and vision of the pride and prejudice consortium

Overweight, obesity and cardiometabolic diseases are major global health concerns. Lifestyle factors, including diet, have been acknowledged to play a key role in the solution of these health risks. However, as shown by numerous studies, and in clinical practice, it is extremely challenging to quantify dietary behaviors as well as influencing...

Interpretable confidence measures for decision support systems

Decision support systems (DSS) have improved significantly but are more complex due to recent advances in Artificial Intelligence. Current XAI methods generate explanations on model behaviour to facilitate a user's understanding, which incites trust in the DSS. However, little focus has been on the development of methods that establish and...

Meaningful human control over opaque machines

Digital Excavation of Mediatized Urban Heritage: Automated Recognition of Buildings in Image Sources

Digital technologies provide novel ways of visualizing cities and buildings. They also facilitate new methods of analyzing the built environment, ranging from artificial intelligence (AI) to crowdsourced citizen participation. Digital representations of cities have become so refined that they challenge our perception of the real. However,...

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades. During that period, they have increased in number, complexity, and agility, while their design and development have been processes well kept under secrecy. As a consequence, limited data(sets) regarding these incidents are available. Although various academic and...

Agent-based distributed planning and coordination for resilient airport surface movement operations

Airport surface movement operations are complex processes with many types of adverse events which require resilient, safe, and efficient responses. One regularly occurring adverse event is that of runway reconfiguration. Agent-based distributed planning and coordination has shown promising results in controlling operations in complex systems,...

Hybrid collective intelligence in a human–AI society

Within current debates about the future impact of Artificial Intelligence (AI) on human society, roughly three different perspectives can be recognised: (1) the technology-centric perspective, claiming that AI will soon outperform humankind in all areas, and that the primary threat for humankind is superintelligence; (2) the human-centric...

Sympérasmology: A proposal for the theory of synthetic system knowledge

Owing to the results of research in system science, artificial intelligence, and cognitive engineering, engineered systems are becoming more and more powered by knowledge. Complementing common-sense andscientific knowledge,systemknowledge is maturingintoa crucial productive asset. However, an overall theory of the knowledge of...

Designing for human rights in AI

In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance pricing, and many more aspects of our lives. Artificial intelligence (AI) systems can help us make evidence-driven, efficient decisions, but can also confront us with unjustified...

Deep learning for assessing the corneal endothelium from specular microscopy images up to 1 year after ultrathin-dsaek surgery

Purpose: To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty. Methods: We analyzed 383 post ultrathin Descemet stripping automated endothelial keratoplasty images from...

Embedding Values in Artificial Intelligence (AI) Systems

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how...

Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation...

A Misdirected Principle with a Catch: Explicability for AI

There is widespread agreement that there should be a principle requiring that artificial intelligence (AI) be ‘explicable’. Microsoft, Google, the World Economic Forum, the draft AI ethics guidelines for the EU commission, etc. all include a principle for AI that falls under the umbrella of ‘explicability’. Roughly, the principle states that ...

On domain-adaptive machine learning

Artificial intelligence, and in particular machine learning, is concerned with teaching computer systems to perform tasks. Tasks such as autonomous driving, recognizing tumors in medical images, or detecting suspicious packages in airports. Such systems learn by observing examples, i.e. data, and forming a mathematical description of what types...

AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess...