Quantum Computing and Machine Learning for Efficiency of Maritime Container Port Operations; Addressing the Harms of the Inflated Expectations of Quantum Technologies

Author:
St John, Maxwell, School of Engineering and Applied Science, University of Virginia
Advisors:
Lambert, James, EN-Eng Sys and Environment, University of Virginia
Baritaud, Catherine, EN-Engineering and Society, University of Virginia
Abstract:

Quantum computing is an emerging technology with the potential to solve problems previously deemed impossible. The technical topic explores emerging technologies, including quantum computing, that can improve maritime container port operations. The emerging technologies researched can increase the efficiency of port operations and counteract the significant delays and backlog ports are currently experiencing. The STS topic identifies the causes and impacts of the inflated expectations of quantum computing. As these expectations continue to grow, they risk concealing the potential harms of quantum computing. The technical and STS research topics are tightly coupled, as the STS topic studies the societal view and impact on an emerging technology researched in the technical topic.
The technical topic explores emerging technologies that could potentially improve port efficiency. Since the start of the pandemic, port operations have been overwhelmed by factors such as increased consumer demand, a trucking shortage, and staffing shortages due to COVID. Emerging computing methods, such as quantum computing and neural networks, have the potential to help mitigate the issues created by the pandemic by increasing throughput while also decreasing energy usage and emissions. Additionally, using a set of neural networks reverse-engineered from the pseudocode of an advanced Google algorithm, the technical topic attempted to optimize the organization of containers in a container stack. Improved organization of a container stack allows for the desired containers to be removed with minimal reshuffling while simultaneously improving the efficiency of other operations connected to the container stack.
While the technical team did not have the computing power to run a full simulation, which would require millions of training steps, a model was trained on 1500 training steps to reorganize a container stack for optimal retrieval. The smaller simulation provided a proof of concept, as the efficiency of the re-stacking improved as the number of training steps grew. Next steps include running the full simulation to further evaluate its applicability to the improvement of port operations.
The STS research topic identified the causes behind the inflated expectations of quantum computing and addressed the consequences of this overhype. This excitement risks overshadowing significant issues that could arise with the development of quantum computing. The topic began by explaining the trajectory of the excitement behind an emerging technology over time, followed by an analysis of the causes and effects of the excitement towards quantum technologies. The research topic heavily relied on the experience and thoughts of individuals and groups working with quantum technologies.
The biggest factors driving the over-excitement of quantum technologies are the misunderstanding of the technology and the attempts of developers and investors of the technology to generate publicity. The over-excitement can mask the potential issues that could arise as quantum technologies continue to expand, such as privacy violations and the exclusion of stakeholders in its development. Actor Network Theory, created by Callon and Law in 1988, is used to analyze the inclusion and exclusion of different stakeholders from the development of quantum computing. To mitigate the risks of quantum technologies, previously overlooked stakeholders need to be included in its development.
Emergent computing methods can help remedy the current backlog at ports worldwide. More generally, emergent computing methods will impact countless different groups and industries, but pose some significant risks to society. It is essential these computing methods are developed in a manner in which as many stakeholders as possible are involved to mitigate its risks.

Degree:
BS (Bachelor of Science)
Keywords:
Quantum Computing, Neural Networks, Machine Learning, Maritime Container Ports, Actor Network Theory
Notes:

School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: James Lambert
STS Advisor: Catherine Baritaud
Technical Team Members: Ibrahim Hamdy, Sidney Jennings, Tiago Magalhães, James Roberts

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2022/05/07