Springer Publication:
Machine Intelligence and Digital Interaction Internation Conference

This research project examined how industrial designers perceive and negotiate trust when using Generative AI tools in early-stage concept development. Developed as part of my Master’s thesis and adapted for the 11th International Conference on Machine Intelligence and Digital Interaction (MIDI 2023), the study explores trust as a key component in human-AI collaboration within creative workflows and proposes strategies to foster trust in Generative AI among industrial designers.

Main Challenges

  • Investigating trust, a complex and subjective construct, through a design-specific lens.

  • Designing a study that combined qualitative and quantitative methods for meaningful insights.

  • Articulating findings in a way that bridges design practice and academic discourse.

Key Achievements

  • Presented at MIDI 2023 and published in Springer’s Lecture Notes in Computer Science.

  • Developed a trust-centered framework for evaluating AI tools in design contexts.

  • Contributed original, empirical research to the emerging dialogue on AI in creative industries.

Responsibilities

  • Designed and executed a mixed-methods study involving surveys and interviews with industrial designers.

  • Analyzed data to identify themes around control, authorship, and reliability in AI-supported design.

  • Authored a peer-reviewed paper accepted for publication by Springer.

  • Created diagrams and visuals to communicate research insights effectively.

  • Delivered a presentation at an international academic conference.

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