How Does Machine Advice Influence Design Choice? The Effect of Error on Design Decision Making

Nandy, Aditya; Goucher-Lambert, Kosa

doi:10.1007/978-3-031-20418-0_47

Cited by 1 publication

(1 citation statement)

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“…The effective design of these tools may be critical to successful deployment of data-driven design. Performance improvements expected by utilizing AI in design can only be achieved if the designers actually trust and are willing to work with the AI (Nandy and Goucher-Lambert, 2022). A possible action is to ensure that designers have adequate training in HCI, so that they can create/recognize design tools that will augment human design skill.…”

Section: User Perspectivesmentioning

confidence: 99%

Managing Data-Driven Design: A Survey of the Literature and Future Directions

2023

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Data-driven design is expected to change design processes and organizations in significant ways. What actions should design managers take to ensure the best possible outcomes in this new data-driven design environment? This paper employs an interdisciplinary literature survey to distill key impacts that data-driven design may have on designers, design teams, organizations and product users. Findings reveal that designers may need a broader set of skills to be successful. For data-driven design to be most effective, design managers will be challenged with many integration tasks, including the integration of AI-based tools into design teams, the closer integration of interdisciplinary teams, the integration of qualitative design thinking methods with new data-driven design paradigms, and the integration of data and algorithms into traditional human-centred design practice, in an effort to overcome cognitive limitations and augment human skill. This paper identifies gaps in the literature at the intersection of data-driven design and design management, design thinking, and systems thinking.

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Section: User Perspectivesmentioning

confidence: 99%