Orli
An interactive desk lamp that reflects AI’s behavior in response to our digital habits.
(Interaction Design, Physical computing, Physical Prototyping)
Collaborators: Sojung Pak and Joan Lee
Duration: 4 weeks
Skills: Figma, Fusion, Rhino, After Effects, Python, Laser Cutting, 3D Printing
Why and how has AI become essential in our lives?
As artificial intelligence increasingly permeates our daily environments, from our homes to our workplaces, it has become an integral part of our digital interactions. The concept of an interactive lamp serving as a self-probe emerged as a means to explore and illuminate AI's profound impact. This innovative approach aims to guide our understanding of how AI shapes our daily routines, ultimately enhancing our awareness of its pivotal role in our lives.
Prototyping interactions
Experimenting with different behaviors like pulsing, rotating and vibrating to understand user interactions for a holistic experience.
_gif.gif)
_gif.gif)
_gif.gif)
Designing the different phases for the personalized interaction
The customization phase asks users to determine their preferred level of AI interaction, adding a personal touch to the product and experience.
.png)
The active phase determines how the AI responds to the frequency and manner of user interactions.
The passive phase reflects on the user's AI interactions throughout the day, providing insights into their engagement patterns.
The reflective phase evaluates long-term AI interaction patterns, showing how usage has influenced user behavior and engagement over time.
Developing the technical system
The interactive desk lamp uses sensors and actuators with precise coding to dynamically respond to digital interactions. This setup reflects AI's influence on our habits through motion detection and programmable lighting, prompting user reflection.
How Orli enhances our workflow?
Mapping user interactions to uncover opportunities and create a holistic experience.
Future Consideration
Future considerations for the project include examining more complex aspects of AI behavior to enhance its responsiveness and adaptability. We plan to gather data from a larger user base to compare usage trends on a broader scale, providing deeper insights into user interactions. Additionally, we will create detailed personas based on this usage data to better understand and cater to different user needs and preferences, ensuring a more personalized and effective experience.