Who we are
We believe that humans and AI can empower each other by defining mutually beneficial goals. We develop models and methods that can help machines to learn from humans by taking into account human cognitive biases and preferences. We aim to create algorithms that can optimize machine learning models according to human feedback, in order to improve the performance of the overall system.
What we do?
Our group conducts studies to investigate how the use of artificial intelligence can enhance the performance of human activities and promote well-being. We seek to use artificial intelligence from different modalities such as audio, images, text, and telemetry data to understand human behavior from natural interactions. We collect and analyze data in the workplace for identifying trends and patterns that help machines to recommend better strategies to achieve our goals. This can assist humans in the decision-making process to make judgments that are more accurately based on data.
We perform experiments in real-world settings to identify the feasibility of current technologies in the wild. We explore the limitations of technology and define mitigation strategies to create accountable solutions. These tools are evaluated by users whose feedback feed the systems for continious improvement. The main goal of our research is understand how smart tools can help people to reach new opportunities and improve their lives.
Use Inspired AI
- Our technology is designed to provide solutions to common challenges in multiple contexts.
- We identify scenarios in which decision making can be assisted by AI technologies.
- Our approach provides the perspectives of the different stakeholders in a process.
Human-Centric Approach
- We involve humans in all the workflow steps of designing a smart solution.
- Our approach uses participatory design to include the opinion of multiple actors.
- We use Human-Centered AI design principles to define solutions that aligns to our interests.