This paper explores the development of a basic model of artificial consciousness and awareness, examining whether aspects of human consciousness can be replicated into machines. The author reviews existing literature on artificial consciousness, identifies gaps in current scholarship, and proposes a three-year research project using the waterfall software development model to create a functional artificial consciousness program implemented on a desktop PC avatar. The study addresses the core challenge facing researchers: determining whether machines can be designed to demonstrate genuine phenomenal experience and consciousness similar to human beings.
Artificial consciousness, sometimes referred to as machine consciousness, is a field of cognitive robotics and artificial intelligence that attempts to emulate human consciousness. In other words, the model of artificial consciousness is an aspect of human cognition and has become a controversial and elusive phenomenon within consciousness studies. Although the model of artificial consciousness is not an attempt to replace human consciousness entirely—because human consciousness is unique and built upon the interrelation of complex biological, social, cultural, and environmental conditions—some aspects of human consciousness could potentially be replicated in a machine.
The study develops research objectives to enhance understanding of the strategies needed to develop a basic model of consciousness and awareness, and to create a software model of artificial consciousness. Specifically, the research aims to accomplish two primary objectives:
First, to develop a basic model of consciousness and awareness. Second, to develop a software model of artificial consciousness involving a desktop PC avatar for practical implementation purposes. These objectives will guide the investigation into whether machines can be engineered to demonstrate genuine conscious experience.
One of the aims of artificial intelligence research is to design and implement a machine model that will demonstrate consciousness and thinking similar to that of human beings. However, scholars are still facing significant challenges in building machines that will demonstrate real phenomenal experience and genuine feeling. Consciousness, in its deepest sense, remains difficult to operationalize and replicate.
Sidharta (2012) argues that a classical problem facing scholars and practitioners is the strategy for designing artificial intelligence embedded with synthetic consciousness. The major challenge confronting professional designers is determining whether it is possible to design and develop a machine with artificial skin and embodied cognition—one that could stand as a true peer of the human race. Over the years, scholars have not provided a concrete solution to the strategy of integrating human consciousness into a machine in order to develop genuine artificial consciousness.
This study attempts to solve this problem by developing a program of artificial consciousness where its implementation will serve a practical purpose. The research will review previous literature to enhance understanding of artificial consciousness and identify gaps within the existing body of knowledge.
Several scholars have attempted to design and implement models of artificial consciousness (Buttazzo, 2001; Aleksander, 1992; Holland, 2003). The model of artificial consciousness has interested researchers for several decades; however, the concept was largely forgotten due to its limited practical application during certain periods. Within the last few decades, there has been a resurgence of scientific interest in artificial consciousness, with renewed attempts to model and implement conscious machines. Aleksander (1992) was one of the first serious researchers to explicitly mention the concept of artificial consciousness, and since that time, the field has gained considerable momentum and scholarly contributions.
Buttazzo and Manzotti (2008) define the field comprehensively: "Artificial consciousness or machine consciousness is an attempt by those who design and analyze informational machines to apply their methods to various ways of understanding consciousness and to examine the possible role of consciousness in informational machines" (p. 79). This definition underscores the interdisciplinary nature of the research.
Cardon (2006) identifies consciousness as a cultural concept and the main property of human beings. In essence, the model of consciousness can be transposed into an artificial brain where a computer could express consciousness and emotion. Buttazzo and Manzotti (2008) believe that the development of digital computers has enabled developers to produce machines that mimic human thinking and natural language, with artificial brain models assisting in developing adaptive behaviors for autonomous robots.
The development of human-machine interaction has overlapped several fields including control systems, data mining, speech recognition, and facial recognition. Despite rapid development of robotic technology, there remains a lack of artificial intelligence that delivers consciousness similar to biological agents. The model of artificial consciousness still struggles within its theoretical and methodological framework. Clowes and Seth (2008) identify methodological issues underlying artificial consciousness modeling. Despite their research contributions, their studies remain in a pre-paradigmatic stage, as common conceptual and accepted theoretical frameworks are still missing.
Aleksander (1992) points out that it is still premature to venture fully into the field of artificial consciousness. Chrisley (2008) reveals philosophical concepts of artificial consciousness; however, many issues remain unresolved, and the author may overestimate the separation between artificial intelligence and artificial consciousness. Buttazzo (2001) believes that application of artificial consciousness can deliver real success because there is a chance in developing a biological machine that can demonstrate conscious experience. However, the author remains pessimistic about a machine achieving a better, faster, or more articulated form of consciousness (p. 20).
On the other hand, Harnad and Scherzer (2007) challenge the possibility of developing artificial intelligence that can demonstrate artificial consciousness, arguing that there can be no implementation of machine consciousness inspired by biological consciousness. Chatterjee (2012) argues that machine cognition does not necessarily involve thinking; rather, it attempts to include thinking processes into a machine, transforming it into a thinking machine. In essence, artificial cognition does not concern itself with reality but rather with information to process. The underlying assumption of replicating human consciousness into a machine is to make it capable of delivering similar sentience and thought. However, Chatterjee (2012) remains pessimistic about the possibility of developing a software program that can bridge the gap between machine awareness and human sentience.
The review of literature has revealed the following significant gaps: First, virtually all scholars remain pessimistic about the possibilities of developing a program that will make a machine demonstrate artificial consciousness. Moreover, there is a scarcity of literature that has developed a software program for implementing artificial consciousness on a desktop PC avatar for practical purposes. This study attempts to bridge this gap by developing a basic model of consciousness and a system that prioritizes practical implementation. The research methodology provides the strategy the proposal will employ to achieve its research objectives.
The proposal will employ multiple methods to achieve the research objectives. The researcher will use the Waterfall Model to develop the software that will be implemented for artificial consciousness. The waterfall model is a sequential software design process used in development where the process flows steadily downward like a waterfall, completing the following phases:
Conception, Initiation, Analysis, Design, Construction, Testing and Debugging, Implementation/Production, and Maintenance.
The underlying assumption of the waterfall model is that a developer should advance to the next phase only after the preceding phase has been verified and reviewed. The rationale supporting the waterfall model is that time spent perfecting the preceding stage can help the developer achieve greater efficiency at later stages in the software development lifecycle. For example, a bug detected at an early stage requires less effort and expense than one discovered in later stages. McConnell (2006) points out that a designer can rectify challenges in software implementation far more easily at an early stage than fixing errors discovered later.
Moreover, the waterfall model assists designers in setting detailed procedures and controls in a software project, helping to regulate every process of software development. Supporters of the waterfall model emphasize its focus on documentation, including design and requirement documents. A program developed with effective documentation accumulates the knowledge of the designer. Unlike software development models that do not emphasize documented methodologies, knowledge will not be lost if team members leave the project before completion. With comprehensive working documentation, new team members can familiarize themselves with project development by reviewing the documents.
The benefits derived from the waterfall model make it the ideal choice for software development implementing artificial consciousness. The proposal will implement the following sequential processes:
Requirement Analysis and Gathering: The proposal will collect all requirements needed to develop the project. At this stage, data will be gathered about human consciousness to identify concepts that will be integrated into the artificial consciousness model. Data will be collected through comprehensive document analysis from the fields of philosophy, psychology, and neuroscience.
Design: The system will be designed to specify the hardware that will assist in software implementation. This stage will also provide specifications of the software architecture appropriate for implementation. The proposal will use a desktop personal computer for implementing the software modules. At this stage, code for software development will be created.
Construction: The proposal will provide detailed construction of the software, with the necessary concepts of artificial consciousness integrated into the program.
Testing and Debugging: The entire program will be tested to identify faults and remove bugs that could delay implementation. This stage will conduct comprehensive testing to ensure the program achieves the research objectives.
Implementation/Production: Once the program is functional, the project will be deployed for implementation. The software development outcome will assist the research in delivering its findings.
Maintenance: The research will need to update the program to ensure compatibility with latest machine specifications and technological advances.
"Three-year schedule and research ethics protocols"
You’re 92% through this paper. Sign up to read the remaining 1 section.
Sign Up Now — Instant Access Already a member? Log inAlways verify citation format against your institution’s current style guide requirements.