Answers.Body: <p>Consciousness is in general an extremely hard and vague problem as its existence is universally claimed yet there's currently no successful explanation mechanism for its subjective  integrated experiential nature. In the early years of AI, famous researcher Newell et al developed a cognitive architecture called <a href="https://en.wikipedia.org/wiki/Soar_%28cognitive_architecture%29" rel="nofollow noreferrer">Soar</a> which was designed to mimic human problem-solving and decision-making, and operated via production rules chunking, goal hierarchies, and search algorithms to simulate intelligent behavior of general problem solving (GPS). Yet no one believed it has consciousness. For connectionist models such as LLMs, they don't even have meta-cognitive functions compared to symbolic models since there's no explicit (symbolic) internal model of any external knowledge they can reason about directly, they can only simulate such higher-order reasoning (e.g., &quot;Explain how you arrived at your answer&quot;).</p>
  <p>According to a popular yet controversial theory of consciousness called Integrated Information Theory (IIT), consciousness doesn't only belong to biological neural systems such as human brains. So long as the information processed in any physical system is integrated enough surpassing some threshold, such system is said to possess consciousness, and the more degree of integration <span class="math-container">$\Phi$</span> measuring how much more the system is as a whole than the sum of its parts, the more conscious the system is.</p>
  <p>Therefore under IIT's view, consciousness is not about whether your bot is computing something useful like humans or not, and your highly modularized bot even with self-learning capability within each module has little to no integration across modules, just like a common computer. Each module’s behavior can be explained independently, reducing the integration (connection) across the whole system. Surprisingly, under the same view, to have a higher <span class="math-container">$\Phi$</span> you'd rather assemble a large singly-connected network of logic gates expressible for many different states without any isolated components, like the singly-communicating state-space of an ergodic process.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-12-26T07:31:23.880Z
Answers.LastActivityDate: 2024-12-26T07:31:23.880Z
Answers.UserDisplayName: cinch
Body: <p>Mimicking all human biological systems, like the bone system, excretion system, blood system, food system (e.g., using solar panels), and sensory system (camera as eye, speaker as mouth, ear as microphone).</p>
  <p>The basic living creature is energy from a food source, so consider that I create a robot with a solar panel where it detects the light intensity where it finds the optimal value (highest intensity), and they are aware that its current battery/energy level is so that it needs a solar panel, just like we are hungry and find the optimal value to find food.</p>
  <p>They are hardcoded; I mean, yes, the hardcoded part is mimicking a biological subsystem. but not the actual model of the subsystem where it implemented, like the digesting system (about food), algorithm (which is not hard programmed) to find the light source where it uses an optimizer (actually finding light intensity is very similar to gradient descent since it has magnitude and direction for every update over time) and from support from another subsystem like sensory (e.g., camera).</p>
  <p>Here’s a table that compares the subsystems in humans and potential analogies in robots:</p>
  <div class="s-table-container"><table class="s-table">
  <thead>
  <tr>
  <th><strong>Subsystem</strong></th>
  <th><strong>Human</strong></th>
  <th><strong>Robot Analogy</strong></th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td><strong>Skeletal System</strong></td>
  <td>Bones, cartilage, ligaments, joints</td>
  <td>Structural frame, chassis, joints, and hinges</td>
  </tr>
  <tr>
  <td><strong>Muscular System</strong></td>
  <td>Skeletal muscles, smooth muscles, tendons</td>
  <td>Motors, actuators, hydraulic systems</td>
  </tr>
  <tr>
  <td><strong>Circulatory System</strong></td>
  <td>Heart, blood, blood vessels</td>
  <td>Power distribution system, wires, batteries</td>
  </tr>
  <tr>
  <td><strong>Nervous System</strong></td>
  <td>Brain, spinal cord, peripheral nerves</td>
  <td>Central processing unit (CPU), microcontrollers, wiring</td>
  </tr>
  <tr>
  <td><strong>Respiratory System</strong></td>
  <td>Lungs, trachea, diaphragm</td>
  <td>Air intake systems for cooling or combustion (if applicable)</td>
  </tr>
  <tr>
  <td><strong>Digestive System</strong></td>
  <td>Stomach, intestines, liver, pancreas</td>
  <td>Energy harvesting system (e.g., solar panels, fuel cells, charging systems)</td>
  </tr>
  <tr>
  <td><strong>Excretory System</strong></td>
  <td>Kidneys, bladder, urethra</td>
  <td>Waste heat dissipation system, coolant systems</td>
  </tr>
  <tr>
  <td><strong>Endocrine System</strong></td>
  <td>Hormone-secreting glands (e.g., thyroid, adrenal)</td>
  <td>Control algorithms, sensors for state monitoring (e.g., thermal or energy status)</td>
  </tr>
  <tr>
  <td><strong>Immune System</strong></td>
  <td>White blood cells, lymphatic system</td>
  <td>Error detection algorithms, cybersecurity protocols, system repair routines</td>
  </tr>
  <tr>
  <td><strong>Integumentary System</strong></td>
  <td>Skin, hair, nails</td>
  <td>Outer shell, protective casing, insulation layers</td>
  </tr>
  <tr>
  <td><strong>Reproductive System</strong></td>
  <td>Ovaries, testes, uterus</td>
  <td>Cloning mechanisms, modular self-replication processes (in theoretical advanced robots)</td>
  </tr>
  <tr>
  <td><strong>Sensory System</strong></td>
  <td>Eyes, ears, skin, nose, tongue</td>
  <td>Cameras (vision), microphones (hearing), tactile sensors (touch), gas sensors (smell), chemical sensors (taste)</td>
  </tr>
  <tr>
  <td><strong>Lymphatic System</strong></td>
  <td>Lymph nodes, lymphatic vessels</td>
  <td>Filtration systems for contaminants, redundant systems for fault tolerance</td>
  </tr>
  <tr>
  <td><strong>Hematopoietic System</strong></td>
  <td>Bone marrow, blood production</td>
  <td>Resource allocation systems for generating or redistributing energy or spare parts</td>
  </tr>
  </tbody>
  </table></div>
  <p>This table provides an analogy for each subsystem, demonstrating how biological processes can be translated into robotic systems. These analogies would allow robots to simulate various functions of living organisms while being tailored to their non-organic nature.</p>
  <p>So, can I consider it as consciousness? Yes the hard coded part is manually one by one like initializing skeletal system at first, but a mechanism where they are holding their skeletal structure is performed by soft coded e.g. by gradient descent that supported by another subsystem like muscular system which fix the minor skeletal structure problem. So, skeletal system and muscular system are communicating each other.</p>
  
Tags: <artificial-consciousness>
Title: If subsystems are hardcoded to match with biological analogy, but the implementations are using optimizers, can I consider it as consciousness?
UserDisplayName: Muhammad Ikhwan Perwira
ThreadText: # If subsystems are hardcoded to match with biological analogy, but the implementations are using optimizers, can I consider it as consciousness?
  
  (Asked by: username_0 on 2024-12-25)
  
  Mimicking all human biological systems, like the bone system, excretion system, blood system, food system (e.g., using solar panels), and sensory system (camera as eye, speaker as mouth, ear as microphone).
  
  The basic living creature is energy from a food source, so consider that I create a robot with a solar panel where it detects the light intensity where it finds the optimal value (highest intensity), and they are aware that its current battery/energy level is so that it needs a solar panel, just like we are hungry and find the optimal value to find food.
  
  They are hardcoded; I mean, yes, the hardcoded part is mimicking a biological subsystem. but not the actual model of the subsystem where it implemented, like the digesting system (about food), algorithm (which is not hard programmed) to find the light source where it uses an optimizer (actually finding light intensity is very similar to gradient descent since it has magnitude and direction for every update over time) and from support from another subsystem like sensory (e.g., camera).
  
  Here’s a table that compares the subsystems in humans and potential analogies in robots:
  
  | **Subsystem** | **Human** | **Robot Analogy** |
  | --- | --- | --- |
  | **Skeletal System** | Bones, cartilage, ligaments, joints | Structural frame, chassis, joints, and hinges |
  | **Muscular System** | Skeletal muscles, smooth muscles, tendons | Motors, actuators, hydraulic systems |
  | **Circulatory System** | Heart, blood, blood vessels | Power distribution system, wires, batteries |
  | **Nervous System** | Brain, spinal cord, peripheral nerves | Central processing unit (CPU), microcontrollers, wiring |
  | **Respiratory System** | Lungs, trachea, diaphragm | Air intake systems for cooling or combustion (if applicable) |
  | **Digestive System** | Stomach, intestines, liver, pancreas | Energy harvesting system (e.g., solar panels, fuel cells, charging systems) |
  | **Excretory System** | Kidneys, bladder, urethra | Waste heat dissipation system, coolant systems |
  | **Endocrine System** | Hormone-secreting glands (e.g., thyroid, adrenal) | Control algorithms, sensors for state monitoring (e.g., thermal or energy status) |
  | **Immune System** | White blood cells, lymphatic system | Error detection algorithms, cybersecurity protocols, system repair routines |
  | **Integumentary System** | Skin, hair, nails | Outer shell, protective casing, insulation layers |
  | **Reproductive System** | Ovaries, testes, uterus | Cloning mechanisms, modular self-replication processes (in theoretical advanced robots) |
  | **Sensory System** | Eyes, ears, skin, nose, tongue | Cameras (vision), microphones (hearing), tactile sensors (touch), gas sensors (smell), chemical sensors (taste) |
  | **Lymphatic System** | Lymph nodes, lymphatic vessels | Filtration systems for contaminants, redundant systems for fault tolerance |
  | **Hematopoietic System** | Bone marrow, blood production | Resource allocation systems for generating or redistributing energy or spare parts |
  
  This table provides an analogy for each subsystem, demonstrating how biological processes can be translated into robotic systems. These analogies would allow robots to simulate various functions of living organisms while being tailored to their non-organic nature.
  
  So, can I consider it as consciousness? Yes the hard coded part is manually one by one like initializing skeletal system at first, but a mechanism where they are holding their skeletal structure is performed by soft coded e.g. by gradient descent that supported by another subsystem like muscular system which fix the minor skeletal structure problem. So, skeletal system and muscular system are communicating each other.
  
  **Tags:** artificial-consciousness
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-12-26. Score: 1 | Accepted answer
  
  Consciousness is in general an extremely hard and vague problem as its existence is universally claimed yet there's currently no successful explanation mechanism for its subjective integrated experiential nature. In the early years of AI, famous researcher Newell et al developed a cognitive architecture called [Soar](https://en.wikipedia.org/wiki/Soar_%28cognitive_architecture%29) which was designed to mimic human problem-solving and decision-making, and operated via production rules chunking, goal hierarchies, and search algorithms to simulate intelligent behavior of general problem solving (GPS). Yet no one believed it has consciousness. For connectionist models such as LLMs, they don't even have meta-cognitive functions compared to symbolic models since there's no explicit (symbolic) internal model of any external knowledge they can reason about directly, they can only simulate such higher-order reasoning (e.g., "Explain how you arrived at your answer").
  
  According to a popular yet controversial theory of consciousness called Integrated Information Theory (IIT), consciousness doesn't only belong to biological neural systems such as human brains. So long as the information processed in any physical system is integrated enough surpassing some threshold, such system is said to possess consciousness, and the more degree of integration $\Phi$ measuring how much more the system is as a whole than the sum of its parts, the more conscious the system is.
  
  Therefore under IIT's view, consciousness is not about whether your bot is computing something useful like humans or not, and your highly modularized bot even with self-learning capability within each module has little to no integration across modules, just like a common computer. Each module’s behavior can be explained independently, reducing the integration (connection) across the whole system. Surprisingly, under the same view, to have a higher $\Phi$ you'd rather assemble a large singly-connected network of logic gates expressible for many different states without any isolated components, like the singly-communicating state-space of an ergodic process.
  
  
  ---
  
  