Leesakul, Natalie
(2024)
Robotics and the law: exploring the relationship between law and technology adoption challenges in the case of collaborative industrial embodied autonomous systems (Cobots).
PhD thesis, University of Nottingham.
Abstract
The introduction of emerging robotic technology in manufacturing poses different legal issues from their predecessor of industrial robotics and automation where the separation between humans and machines is clearly visible. This new generation of industrial robots would allow for a more lean process and maximisation of efficiency at work. With human-robot collaboration, the advantages are the combination of high levels of accuracy, strength, precision, speed, endurance, and repeatability from the robot and the flexibility, sensitivity, creativity, and cognitive skills from the human.
To paint a picture, this emerging collaborative industrial embodied autonomous system (hereinafter referred to as "Cobot") explored in this thesis is often being referred to as robotic ‘co-workers’ in a popular culture. This notion is particularly important, despite its potential illegitimate claim, it establishes a position where this technology might find itself in the future of industrial workplace being considered as another worker. Although manufacturing industry is no stranger to robotics, this emerging type of industrial robotics poses new challenges; identifying the relevant regulations is a challenge in itself.
This multidisciplinary thesis brings forward an integration of technology law, business management, and human-computer interaction (HCI) studies to explore Cobot adoption challenges and the role of law in addressing the challenges. This thesis approach to a socio-legal investigation of Cobot adoption is twofold: 1. Establishing the challenges through conducting exploratory research 2. Tackling legal challenges through conducting doctrinal research. It is vital for the exploratory research to be the first tier in order to explore concerns from different stakeholders. Thus, we interviewed 15 experts in relevant sectors to Cobot adoption and identified adoption challenges under 10 themes: adoption of new technology, trust, risk, safety, due diligence, regulatory, ethics and social challenges, data & privacy, design, and insurance. In the doctrinal research, we investigated different legal doctrines in addressing safety, liability, data and privacy challenges found in the empirical studies which we concluded that the current regulatory frameworks are sufficient in responding to such challenges.
The novelty of this thesis is the findings from the orchestrating of a study to identify the challenges of Cobot adoption from multi-stakeholders’ perspective and synthesize interdisciplinary material to present an elaborated landscape of Cobot adoption pain points. This thesis provides the breadth of the subject matter which has not been gathered before and the depth of specific regulatory responses to liability, safety, data protection and privacy challenges.
In this thesis, we made 5 contributions:
• Identified a gap in research and establish a new working term
of Cobot (Chapter 2).
• Identified 10 adoption challenges based on empirical studies
(Chapter 3).
• Created a framework for responsible Cobot adoption principles
from multi-stakeholder’s perspectives (Chapter 3).
• Presented a new perspective on Cobot regulations as a symbiotic relationship of safety, liability and data protection (Chapter 4).
• Provided recommendations and future research directions towards responsible Cobot adoption (Chapter 3, Chapter 4, Section 5.1.4 and Section 5.2).
Item Type: |
Thesis (University of Nottingham only)
(PhD)
|
Supervisors: |
Hyde, Richard Wilson, Max L. Urquhart, Lachlan McAuley, Derek |
Keywords: |
robot, law, adoption, responsible innovation, cobot, AI |
Subjects: |
K Law > K Law (General) Q Science > QA Mathematics > QA 75 Electronic computers. Computer science |
Faculties/Schools: |
UK Campuses > Faculty of Science > School of Computer Science |
Item ID: |
77392 |
Depositing User: |
Leesakul, Natalie
|
Date Deposited: |
23 Jul 2024 04:40 |
Last Modified: |
23 Jul 2024 04:40 |
URI: |
https://eprints.nottingham.ac.uk/id/eprint/77392 |
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