Human-Technology Interaction group (HTI)

Psychological research regarding people's interaction with technology, with a focus on interaction with systems and services using a data centered approach. Some focus areas are: 

  • The role of data and human-data interfaces in human decision making, including:
    • Understanding the relative strengths and weaknesses of human-and machine-based decision making, and how to harmonize human decisions with machine learning.
    • Understanding the potential and impact of ‘Quantified Self’ data on human self-awareness and self-improvement, including steps toward behavior change 
  • Human-centered and value-sensitive design of digital media, ICT and product interfaces including:
    • Evaluate and improve human-data interaction to allow intuitive and effective data usage, and to support and promote positive behavior change (e.g., e-coaching)
    • Explore novel forms of interaction, including virtual and augmented reality interfaces, IoT, etc. to support intuitive exploration and understanding of data and their real-world implications

Success stories

Every decision that humans make in situations of uncertainty or incomplete information (which is almost always) is subject to a number of natural and unavoidable biases. For example, we humans tend to cherry-pick data that is in line with our preconceived notions, and ignore data that is at variance with such notions.

Insights emerging from big data and machine learning have the potential to provide a new lens on reality that forces us to be more systematic about our decision making processes. However, despite the great promise of data science, new types of biases may be introduced through the nature of the data and algorithms, and machine learning may lack the transparency to be held accountable for its decisions.

We promote a hybrid approach that combines the best of both worlds –humans and machines –, based on a deep understanding of cognitive psychology, artificial intelligence, data science, as well as specific domain knowledge. This is the approach that informs research, applications, and teaching in the HTI group, in collaboration with other groups in DSC/e and JADS.

Project examples

  • Philips-TU/e Flagship on Data Science
    Data-Driven Value Propositions Systems supporting customers and coaches.
  • Philips-TU/e Flagship on Data Science, Continuous Personal Health
    Improving health for hypertensive patients. 
  • Mine Your Own Body
    Psychological effects of the Quantified Self.
  • Cocoon
    H2020 CHIST-ERA grant Emotion psychology Meets IoT cybersecurity.
  • Exploring the click-stream
    Understanding user traces in online settings.
  • NWO –MVI grant
    Mobile support systems for behavior change.
  • NWO –Research Talent grant
    Social recommender systems for energy conservation.
  • NWO –PRICE grant.
  • Using process tracing to improve household IoT users’ privacy decisions.
  • 4TU Center for Humans & Technology 
    Smart social systems and spaces for happy and healthy living.