Context-specific value inference via hybrid intelligence

Human values are the abstract motivations that drive our opinions and actions. AI agents ought to align their behavior with our value preferences (the relative importance we ascribe to different values) to co-exist with us in our society. However, value preferences differ across individuals and are dependent on context. To reflect diversity in...

Designing the Built Environment Through Hybrid Intelligence

There is a lack of an intelligent platform that supports continuous deliberation and captures diverse views and stakeholders’ values during the architectural design process in the early stages. Using hybrid intelligence, this study proposes a method that integrates value, and design pattern theories, to support deliberation during the design...

Advancing Design Approaches through Data-Driven Techniques: Patient Community Journey Mapping Using Online Stories and Machine Learning

Designers are increasingly collaborating with data scientists to apply smart data technologies to understand large-scale user behavior during their design research. This is useful in specific impact domains with vulnerable users and unfamiliar contexts, such as healthcare design. Patient journey mapping is the most common design tool for...

Developing Team Design Patterns for Hybrid Intelligence Systems

With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of...

Value-Based Hybrid Intelligence

In this paper, we argue that the way we have been training and evaluating ML models has largely forgotten the fact that they are applied in an organization or societal context as they provide value to people. We show that with this perspective we fundamentally change how we evaluate and select machine learning models.

Value Inference in Sociotechnical Systems: Blue Sky Ideas Track

As artificial agents become increasingly embedded in our society, we must ensure that their behavior aligns with human values. Value alignment entails value inference, the process of identifying values and reasoning about how humans prioritize values. We introduce a holistic framework that connects the technical (AI) components necessary for...

Inferring Values via Hybrid Intelligence

Values, such as freedom and safety, are the core motivations that guide us humans. A prerequisite for creating value-aligned multiagent systems that involve humans and artificial agents is value inference, the process of identifying values and reasoning about human value preferences. We introduce a framework that connects the value inference...

Artificial Trust as a Tool in Human-AI Teams

Mutual trust is considered a required coordinating mechanism for achieving effective teamwork in human teams. However, it is still a challenge to implement such mechanisms in teams composed by both humans and AI (human-AI teams), even though those are becoming increasingly prevalent. Agents in such teams should not only be trustworthy and...

Abstract Argumentation for Hybrid Intelligence Scenarios

Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. Information in HI scenarios is often inconsistent, e.g. due to shifting preferences, user's motivation or conflicts arising from merged data. As it provides an intuitive mechanism for reasoning with conflicting...

HyEnA: A Hybrid Method for Extracting Arguments from Opinions

The key arguments underlying a large and noisy set of opinions help understand the opinions quickly and accurately. Fully automated methods can extract arguments but (1) require large labeled datasets and (2) work well for known viewpoints, but not for novel points of view. We propose HyEnA, a hybrid (human + AI) method for extracting...

Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs

Centaurs are half-human, half-AI decision-makers where the AI's goal is to complement the human. To do so, the AI must be able to recognize the goals and constraints of the human and have the means to help them. We present a novel formulation of the interaction between the human and the AI as a sequential game where the agents are modelled...

Clustering small and medium sized Dutch enterprises using hybrid intelligence

We are living in a world full of data. Data capture the characteristics of any entity around us, like living species, properties of scientific experimentation, etc. Moreover, data provides a basis for further analysis, reasoning, or decision-making. One of the most common applications of data analysis is to group data into a set of clusters to...

Hybrid Intelligence in Architectural Robotic Materialization (HI-ARM): Computational, Fabrication and Material Intelligence for Multi-Mode Robotic Production of Multi-Scale and Multi-Material Systems

With increasing advancements in information and manufacturing technologies, there is an ever‑growing need for innovative integration and application of computational design and robotic fabrication in architecture. Hybrid Intelligence in Architectural Robotic Materialization (HI-ARM) provides methods and frameworks that target this need. HI-ARM...

A Design Pattern Language for Hybrid Intelligent Teams

The field of Hybrid Intelligence (HI) is like a vast land with many tribes that speak different languages. Our goal is to develop a lingua franca to unify the peoples of the HI land.We expect our language to facilitate documentation and communication of research results and thus collaboration among various HI fields by making use of design...

Team design patterns for moral decisions in hybrid intelligent systems: A case study of bias mitigation

Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is key. The use of Team Design Patterns (TDPs) can advance this goal by describing successful and reusable...

Meaningful human control over opaque machines

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...

A Human-Machine Approach to Preserve Privacy in Image Analysis Crowdsourcing Tasks

Modern web information systems use machine learning models to provide personalized user services and experiences. However, machine learning models require annotated data for training, and creating annotated data is done through crowdsourcing tasks. The content used in annotation crowdsourcing tasks like medical records and images might contain...