Neural Natter

In a 2023 paper titled “Toward the Aircraft of the Future: A Perspective from Consciousness”, Ezhilarasu et al delve into the integration of consciousness into aircraft design, aiming to revolutionise the aviation industry by creating what is termed the “Conscious Aircraft.” This blog summarises this innovative concept and describes how it seeks to incorporate advanced cognitive features into aircraft, enhancing their autonomy and operational efficiency. It however is not just a technical document; it is a visionary blueprint for the future of aviation. It challenges current paradigms and opens up new possibilities for the integration of advanced cognitive systems in aircraft. The concept of a Conscious Aircraft, as proposed in this study, could lead to significant advancements in how aircraft are designed, operated, and maintained.

What is consciousness?

Background

The term “consciousness” has been used in various contexts through the centuries, with its etymology tracing back to the Latin word “conscio,” meaning “knowing” or “aware.” Historically, to be conscious of something was to possess knowledge of it, either shared with someone else or oneself. The modern concept of consciousness, often attributed to John Locke’s 1690 definition, is described as “the perception of what passes in one’s own mind.” The paper outlines three principal meanings of consciousness that are widely adapted across different fields:

1. Consciousness as the waking state: This refers to the neurological context where consciousness is about the degree of wakefulness, ranging from being fully awake and alert to being in a coma. In this state, consciousness involves interacting with the external environment in an integrated way.

2. Consciousness as experience: This pertains to the subjective experience or the quality of consciousness, describing what it feels like to experience something. This is often considered from a personal or subjective point of view.

3. Consciousness as mind: Echoing the Latin “conscientia,” this refers to the awareness of one’s mental state.

These definitions highlight the complexity and multifaceted nature of consciousness, encompassing both internal processes and interactions with the external world. The major philosophies and debates surrounding natural consciousness are primarily centred around different views of dualism and monism, which are fundamental philosophical theories concerning the nature of consciousness.

1. Dualism: This philosophy posits that mind and body are two distinct phenomena. Within dualism, there are several subtypes:

   • Cartesian or Substance Dualism: Grounds consciousness in both materialistic physical substance and immaterialistic mental substance.
   • Property Dualism: Suggests that consciousness is grounded only in physical substance but includes both physical and mental properties. An example within this category is Epiphenomenalism, where mental properties (like fear) are seen as results of physical properties (such as an increase in adrenaline) but do not have causal power over physical events.

2. Monism: Contrasts with dualism by assuming there is only one realm of existence. Within monism, there are different perspectives:

   • Idealism: Believes that only the mind exists.
   • Solipsism (a subset of idealism): Holds that only one’s own mind is sure to exist.

These philosophical frameworks are crucial in understanding the various interpretations and theories about consciousness, including how it is defined, experienced, and interacts with the physical world. The debates often focus on whether consciousness can be explained through physical processes alone (as in some forms of monism) or if there is an immaterial aspect that eludes physical explanation (as in dualism). These discussions also delve into the “hard problem” of consciousness, which concerns the difficulty of explaining subjective experiences scientifically.

Innovation

Innovation is necessary in various fields, including aviation, as it drives the advancement of technologies and methodologies that enhance operational efficiency, safety, and sustainability. In the context of aviation, integrating advanced cognitive features into aircraft design, such as those inspired by natural phenomena and human consciousness, can lead to significant improvements in aircraft operation and maintenance. This includes the development of autonomous systems that can adapt to changes and handle complex scenarios with minimal human intervention. Moreover, innovation in areas like Artificial Intelligence (AI) and Integrated Vehicle Health Management (IVHM) systems helps in transitioning from human-centred processes to automated and autonomous processes, which are crucial for maintaining the reliability and availability of aircraft while reducing the risks and costs associated with unscheduled maintenance. Thus, innovation is not just beneficial but essential for staying competitive and meeting the evolving demands and challenges of the industry.

What is a conscious aircraft?

Conceptualising a Conscious Aircraft involves several key factors derived from the fields of philosophy, cognitive neuroscience, and artificial intelligence. The major outcomes from these theories suggest that a conscious experience in an aircraft would require:

1. Learning about the self, environment, and others: conscious experience that involves understanding oneself, the surroundings, and other entities within those surroundings. This includes grasping the cause and consequences of one’s actions in relation to the environment and other individuals or systems. In the context of a Conscious Aircraft, this would mean the aircraft’s ability to comprehend its own operational status, the conditions it operates in, and how it interacts with other aircraft and systems. This learning is crucial for the aircraft to make informed decisions and adapt its behaviour based on past experiences and current scenarios. .
2. A model of itself and its world (digital twin): a digital representation that mirrors the physical characteristics, processes, and dynamics of an aircraft. This model is continuously updated with real-time data from the aircraft’s sensors and systems, allowing it to simulate and predict future states and scenarios. This capability enables the aircraft to perform counterfactual simulations (what-if scenarios) and make informed decisions based on its past and present conditions. Essentially, the digital twin acts as a self-model that helps the aircraft understand and navigate its environment more effectively, enhancing its operational efficiency and safety.
3. Autonomy and self hood: the essential characteristics required for a system to have a conscious experience. Autonomy involves the system’s ability to operate independently without human intervention, making decisions and adapting to changes based on its own assessments and capabilities. Self hood relates to the system’s understanding of itself as a distinct entity, capable of self-reflection and possessing a self-model that informs its interactions with the environment and other systems. These concepts are crucial for the development of advanced autonomous systems, such as the Conscious Aircraft, which must be capable of self-management and understanding their own state and actions within the broader operational context.
4. Emotion as part of its learning process: the idea that for a system, such as the Conscious Aircraft, to have a truly conscious experience, it must not only learn from its interactions and observations but also incorporate emotional responses into this learning. This concept suggests that emotion enhances the learning process by adding a qualitative aspect to the experiences a system undergoes, making these experiences more meaningful and impactfull. This emotional component helps the system to prioritise and value different experiences, influencing how it reacts to similar situations in the future and thus shaping its behaviour in a more nuanced and adaptive manner. .

How?

History

The development of Artificial Intelligence (AI) has seen significant advancements over the years, starting from the creation of basic robots to the development of sophisticated AI systems capable of performing complex tasks. The timeline of major developments in AI includes the invention of the first industrial robot, Unimate, in the 1950s, which was later modified for industrial purposes to improve manufacturing efficiency. Following this, the development of general-purpose robots like Shakey in the 1960s allowed for interaction with the environment to a certain extent.

AI has also demonstrated capabilities in various domains, such as beating human champions in games like Chess and Jeopardy, and more recently, in the game of Go with the AlphaGo program. Machine Learning algorithms have autonomously steered stratospheric balloons and even written poems using advanced models like GPT-3.

However, despite these advancements, AI still lacks the social capabilities and emotions that are distinctively human, as evidenced by incidents like the shutdown of Microsoft’s chatbot, Tay, due to inappropriate responses learned from interactions on social media. This has led to initiatives to develop ethical frameworks for AI systems globally.

Moreover, projects like the Human Brain Project and the BRAIN Initiative are focusing on developing and simulating brain models to understand the mechanisms of a brain, pushing AI towards mimicking more generic human actions and consciousness. This ongoing development highlights the transition from Artificial Narrow Intelligence, which is focused on specific tasks, to Artificial General Intelligence, which aims to replicate human-like intelligence and consciousness.

Neuroscience

The brain’s contribution to consciousness is explored within the field of cognitive neuroscience, which studies the biological processes underlying cognition and examines how brain functions support mental activities. This field aims to address questions about the brain’s relationship with consciousness, its emergence, and the functioning of consciousness. The Radical Plasticity Thesis, for example, suggests that consciousness arises as a result of the brain’s continuous attempt at predicting the consequences of its actions both externally and internally. This involves the brain forming meta-representations that allow it to anticipate and be aware of the consequences of its actions, linking consciousness closely with the brain’s predictive capabilities and the quality of its representations.

Conceptualisation

The proposed stages of conceptualising a Conscious Aircraft are detailed in three distinct phases, each building upon the capabilities and awareness of the aircraft:

1. Stage 1: Conscious Aircraft with System-Awareness

   • This initial stage represents the current advanced aircraft that are equipped with sophisticated health management systems. These systems are aligned with an SAE Level 4 of IVHM capability, focusing on monitoring the health of the aircraft at both component and vehicle levels. The systems provide health indicators and failure predictions to maintenance personnel for condition-based and predictive maintenance. An example of such an aircraft is the Lockheed Martin F35 Lightning Joint Strike Fighter, which features advanced Prognostics Health Management (PHM) systems capable of perceiving and processing sensor data.

2. Stage 2: Conscious Aircraft with Self-Awareness

   • In this stage, the aircraft not only monitors its systems but also has self-awareness capabilities. This means the aircraft can self-diagnose and self-repair in the presence of faults at the component or system levels. It can also provide prognosis of its life, contributing to predictive maintenance. The aircraft at this stage is capable of integrating multiple individual system health perspectives to develop a holistic view of its status and future actions. This stage emphasizes the integration of the aircraft’s systems to predict and manage its course and future actions effectively.

3. Stage 3: Conscious Aircraft with Fleet-Awareness

   • The final stage involves the aircraft having fleet-awareness, where it can learn from and interact with other aircraft in its fleet. This stage enables the aircraft to generate different future scenarios based on past experiences learned from other aircraft, facilitated by the digital twin of the fleet. The collective intelligence of the fleet can be evaluated, and the aircraft can autonomously recommend maintenance actions not just for itself but across the fleet. This stage aims to achieve autonomous prescriptive maintenance and optimise logistics, reducing the exposure of aircraft being repaired and enhancing the overall efficiency and safety of the fleet.

These stages outline a progressive development from system-awareness to self-awareness and ultimately fleet-awareness, each stage adding layers of autonomy and capability to the aircraft, moving towards a more connected, conscious, and autonomous future in aviation.

In conclusion

The transformative potential of conscious aircraft lies in their ability to significantly enhance the aviation industry by introducing higher levels of autonomy, connectivity, and awareness. Conscious aircraft, through their stages of system-awareness, self-awareness, and fleet-awareness, can lead to more efficient, safe, and sustainable operations. These aircraft would be capable of self-diagnosing and self-repairing, predicting maintenance needs, and optimising their performance and lifecycle management autonomously. This would reduce the reliance on human intervention for routine checks and troubleshooting, potentially decreasing the risk of human error and increasing operational efficiency.

Moreover, with fleet-awareness, conscious aircraft can learn from the experiences of other aircraft, leading to a collective intelligence that could revolutionise maintenance strategies and flight operations. This shared learning could enable predictive and prescriptive maintenance, reducing downtime and improving the reliability of the fleet. The ability of these aircraft to autonomously manage and coordinate their maintenance and operations could lead to significant cost savings and improvements in aircraft availability and service quality.

Additionally, the integration of conscious aircraft into the broader aviation ecosystem, including interaction with human operators, could enhance decision-making processes and ensure that safety, legal, and ethical standards are maintained in autonomous operations. This could help in building trust in autonomous systems and facilitate a smoother transition to increasingly autonomous aircraft operations.

Overall, the development of conscious aircraft could propel the aviation industry towards a more aware, autonomous, connected, and conscious future, aligning with the principles of the circular economy and enhancing the overall efficiency and sustainability of air travel.

The references and citations included in the paper provide a rich resource for further reading and understanding the depth of research that has informed this study. Notable references include works on the ethics of artificial intelligence, thermographic non-destructive testing, and integrated information theory, among others.

“Toward the Aircraft of the Future: A Perspective from Consciousness” is a seminal work that combines philosophical, cognitive, and technological perspectives. It proposes a new frontier in aircraft development, where consciousness is not just a human attribute but a fundamental aspect of advanced aviation technology. This paper is a must-read for anyone interested in the future of aviation and the potential applications of consciousness in technology.

Reference

Ezhilarasu, C.M., Angus, J. and Jennions, I.K., 2023. Toward the Aircraft of the Future: A Perspective from Consciousness. Journal of Artificial Intelligence and Consciousness [Online], 10(2), pp.249–290. Available from: https://doi.org/10.1142/S2705078523300013.