Smart MIDI Controller for Novice Music Producers; Analysis of General Motor Electric Vehicle 1 Utilizing Actor-Network Theory

My technical project and STS paper are primarily related through the concept that they both create a sociotechnical system. The two papers differ in focus: my technical project centered on the design and impact of an innovative model of a Smart MIDI Controller, while my STS project presented a detailed analysis of the failure of General Motors’ first mass-produced electric vehicle (EV), the EV1. However, both projects involve new models that differ from current market offerings. More importantly, they both explore the intertwined relationships between human and non-human actors. To gain insights into how to prevent instability in new sociotechnical networks, my STS research examines in detail the factors that led to the collapse of the EV1 network.

Our Smart MIDI Controller aims to address the steep learning curve associated with current MIDI controller models. First, the Smart MIDI Controller includes a chord mode in which each pad corresponds to a chord rather than a single note. Composing music often requires understanding certain chord progressions to create melodic compositions, but the rules can be confusing for novice composers. With our chord mode, novice users with limited music theory background no longer need to memorize note-to-chord relationships to compose music effectively. In addition, unlike conventional models that feature only a keyboard or drum pads, our controller integrates an interactive screen. This allows each pad to display its corresponding note or chord, effectively eliminating the hurdle of learning the correlation between pad location and its associated sound. The controller also features a strum mode, enabling users without a guitar background to simulate strumming effects using the MIDI machine.

In my STS research paper, I conducted a comprehensive evaluation of the EV1 case to identify the various factors that contributed to the collapse of its network. I applied Actor-Network Theory (ANT) to analyze the case. I focused particularly on the translation process and how unsuccessful interessement and enrolment contributed to network instability. I argued that limitations in battery technology and charging infrastructure failed to generate sufficient consumer interest and drew criticism from reviewers. Despite GM's engineering team introducing multiple cutting-edge features and launching successful advertising campaigns, the EV1 network experienced poor market performance and ultimately collapsed.

Working on both projects simultaneously allowed me to apply the theoretical concepts I learned in STS to my technical project. I recognized the importance of ensuring stability within a technological system and used ANT analysis to guide design considerations for the Smart MIDI Controller. As an engineer, I plan to continue applying this approach to future projects. As a network builder, I will ensure that I consider all human and non-human actors and develop strategies to effectively integrate them into the system. I will also proactively address any discordance among actors to prevent conflict and foster network stability. In conclusion, these two projects not only helped me grow in terms of technical skills but also allowed me to become a more well-rounded engineer who is capable of designing products that are more likely to succeed.

School of Engineering and Applied Science
Bachelor of Science in Computer Engineering
Technical Advisor: Adam Barnes
STS Advisor: Benjamin Joseph Laugelli
Technical Team Members: Haizhou Yu, Wanghaotian Zhang, Tong Zhou, Jinhong Zhao