Transparent Peer Review By Scholar9
Revolutionizing Robotic Process Automation (RPA) with Autonomous AI Agents: How GPT and AI Models are Shaping the Next Generation of Process Automation
Abstract
Robotic Process Automation (RPA) powered by Generative Artificial Intelligence (GAI) has emerged as a critical component of the digital ecosystem. The emergence of Chat GPT, a publicly available tool created by Open GAI, and its underlying technology, Generative Pretrained Transformer (GPT), are expected to significantly boost the growth of generative AI in the upcoming years. GAI-enabled RPA mimics human interactions with applications and enables direct access to systems via APIs. When compared to human execution, RPA offers greater benefits including scalability, perpetual lifetime, and 24x7 execution. Process automation is not a new technology, but due to significant advancements in GAI, which RPA utilises, it has emerged as its own solution category. An overall strategy for resolving the matter is to enhance transparency. The study suggests using technology to improve data accessibility and readability while using artificial intelligence. "Transparency technology XBRL (eXtensible Business Reporting Language)" is integrated with this goal in mind. Sunstein (2013) states that XBRL is a component of the regulatory choice architecture used by governments. XBRL has a taxonomy associated with it. The study creates a taxonomy for RPA in order to make the use of artificial intelligence more transparent to the public, while also incorporating ethical considerations. Selected as a business case is the rapidly expanding RPA sector. The paper focusses on improving GAI in a way that is consistent with human values. How may incentives be offered to prevent GAI systems from becoming potential items that raise ethical questions. The paper's key finding is that, while transparency technologies simultaneously offer ways to reduce such dangers, they also highlight moral concerns related to GAI-enabled RPA. This is a human-written paper, devoid of any AI-generated text.
Priyank Mohan Reviewer
11 Oct 2024 05:37 PM
Approved
Relevance and Originality
This article is highly relevant in the context of today's digital transformation, particularly as organizations increasingly adopt RPA solutions enhanced by GAI. The examination of how tools like Chat GPT and the underlying GPT technology contribute to the evolution of automation provides fresh insights into a rapidly developing field. The focus on transparency and ethical considerations surrounding the use of GAI in RPA is particularly original, addressing a crucial aspect of technology adoption that is often overlooked. By integrating a discussion on regulatory frameworks like XBRL, the article contributes significantly to the discourse on responsible AI practices.
Methodology
The article employs a conceptual approach, utilizing existing literature and frameworks to build a case for transparency in RPA powered by GAI. While the methodology is appropriate for theoretical exploration, it would benefit from more empirical evidence or case studies demonstrating the effectiveness of transparency measures in real-world RPA implementations. Detailing the criteria for selecting relevant literature and the rationale behind focusing on specific regulatory technologies would also strengthen the methodology section.
Validity & Reliability
The validity of the article is supported by references to established concepts, such as Sunstein’s work on regulatory architecture and the functionalities of GAI-enabled RPA. However, to enhance reliability, the article could include more specific data or statistics illustrating the growth and impact of GAI in the RPA sector. Incorporating diverse viewpoints from industry experts or case studies would further validate the findings and provide a more rounded perspective on the implications of GAI in automation.
Clarity and Structure
The article is generally well-structured, with clear sections that guide the reader through the discussion of GAI and RPA. However, some technical jargon may require simplification for broader accessibility. Subheadings that explicitly delineate sections, such as "Introduction to GAI and RPA," "Transparency Technologies," and "Ethical Considerations," would enhance clarity and help readers navigate the content more easily. A concise introduction summarizing the main objectives and findings could also improve reader engagement.
Result Analysis
The analysis of GAI's role in enhancing RPA highlights both the benefits and potential ethical concerns associated with the technology. The discussion around transparency and the need for a taxonomy for RPA is particularly insightful, as it emphasizes the importance of making AI applications understandable and accountable to the public. To deepen the analysis, the article could provide concrete examples of how transparency technologies like XBRL can be implemented in RPA systems. Additionally, exploring specific ethical challenges, such as bias in AI decision-making or accountability in automation, would enrich the conversation and provide actionable insights for stakeholders.
IJ Publication Publisher
done sir
Priyank Mohan Reviewer