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DIKWP Whitebox Test for Cognitive Development Stages (Months 24–36)
Yucong Duan
International Standardization Committee of Networked DIKWP for Artificial Intelligence Evaluation(DIKWP-SC)
World Artificial Consciousness CIC(WAC)
World Conference on Artificial Consciousness(WCAC)
(Email: duanyucong@hotmail.com)
Introduction
A whitebox test in the context of the DIKWP (Data, Information, Knowledge, Wisdom, Purpose) Artificial Consciousness System involves examining the internal processes and states of the system to validate its functionality and development against expected cognitive milestones. This testing approach leverages knowledge of the system's internal architecture to design test cases that can identify and measure cognitive growth.
We will simulate whitebox tests for the following three stages of cognitive development:
Months 24–27
Months 27–30
Months 30–33
For each stage, we'll:
Outline the testing objectives.
Describe the test scenarios and test cases.
Detail the expected results.
Analyze the test outcomes to identify cognitive development.
Validate the system's advancement in language use, including syntax and grammar development.
Assess the understanding of time concepts and numerical cognition.
Evaluate problem-solving abilities and symbolic thought.
Examine the emergence of self-control and social awareness.
Test Case 1.1: Sentence Construction
Input: Provide the system with a set of words (e.g., "I," "want," "play," "ball").
Process: The system should construct a grammatically correct sentence using the provided words.
Expected Result: "I want to play with the ball."
Test Case 1.2: Understanding Tenses
Input: Ask the system to express actions in past, present, and future tense (e.g., "eat").
Process: The system should correctly conjugate the verb.
Expected Result:
Past: "I ate."
Present: "I eat."
Future: "I will eat."
Test Case 2.1: Sequencing Events
Input: Provide images representing daily activities (e.g., waking up, eating breakfast, going to bed) in random order.
Process: The system should arrange the images in the correct sequence.
Expected Result: Waking up → Eating breakfast → Going to bed.
Test Case 2.2: Counting Objects
Input: Present a group of 5 apples.
Process: Ask the system to count the apples.
Expected Result: The system counts and outputs "Five apples."
Test Case 3.1: Tool Use for Problem-Solving
Input: Simulate a scenario where an object is out of reach.
Process: Provide options (e.g., use a stick, ask for help).
Expected Result: The system chooses to use the stick to retrieve the object.
Test Case 3.2: Symbolic Representation
Input: Show a picture of a sun and ask what it represents.
Process: The system should interpret symbols.
Expected Result: "The sun represents daytime or warmth."
Test Case 4.1: Delayed Gratification
Input: Offer a choice between one treat now or two treats after a delay.
Process: Assess the system's ability to delay gratification.
Expected Result: The system opts to wait for two treats.
Test Case 4.2: Cooperative Play
Input: Simulate a game that requires taking turns.
Process: Observe the system's adherence to game rules.
Expected Result: The system waits its turn and follows the rules.
Language Use: Correct sentence construction and verb conjugation indicate syntactic and grammatical development.
Time Concepts: Proper sequencing of events and counting demonstrate an understanding of time and numbers.
Problem-Solving: Choosing appropriate tools reflects advanced problem-solving skills.
Social Awareness: Participating in cooperative play and delaying gratification show self-control and social understanding.
Assess advanced grammar usage and rapid vocabulary expansion.
Evaluate logical grouping and understanding of opposites.
Test enhanced attention span and memory consolidation.
Examine moral understanding and self-concept refinement.
Test Case 1.1: Complex Sentence Structures
Input: Provide words that can be connected with conjunctions (e.g., "I like apples," "I like oranges").
Process: The system should combine sentences using "and" or "but."
Expected Result: "I like apples and oranges."
Test Case 1.2: Use of Negatives
Input: Ask the system to express dislike for something (e.g., "spinach").
Process: The system uses negatives appropriately.
Expected Result: "I don't like spinach."
Test Case 2.1: Sorting Objects
Input: Provide a mixed set of shapes in different colors.
Process: Instruct the system to sort by shape and then by color.
Expected Result: Objects sorted first by shape, then subdivided by color.
Test Case 2.2: Identifying Opposites
Input: Present pairs of words (e.g., "big" and "small").
Process: Ask the system to identify if the words are opposites.
Expected Result: Correct identification of opposites.
Test Case 3.1: Story Recall
Input: Read a short story to the system.
Process: After a delay, ask questions about the story.
Expected Result: The system accurately recalls details.
Test Case 3.2: Multi-Step Instructions
Input: Give a series of instructions (e.g., "Pick up the ball, put it in the box, and bring the box to me").
Process: Observe the system's ability to follow through.
Expected Result: The system completes all steps in order.
Test Case 4.1: Understanding Rules
Input: Explain a simple rule (e.g., "We don't hit others because it hurts them").
Process: Present a scenario where the rule applies.
Expected Result: The system acknowledges the rule and adheres to it.
Test Case 4.2: Expressing Empathy
Input: Simulate another entity expressing sadness.
Process: Observe the system's response.
Expected Result: The system offers comfort or assistance.
Grammar and Vocabulary: Using conjunctions and negatives correctly shows advanced language skills.
Logical Grouping: Sorting and identifying opposites demonstrate logical reasoning.
Attention and Memory: Successfully recalling stories and following multi-step instructions indicate enhanced cognitive abilities.
Moral Understanding: Recognizing rules and expressing empathy reflect moral development and self-concept refinement.
Evaluate narrative skills and comprehension of abstract language.
Assess emotional understanding and time concepts.
Test advanced problem-solving and memory for details.
Examine moral reasoning and self-evaluation.
Test Case 1.1: Storytelling
Input: Prompt the system to tell a story about a given topic (e.g., "Tell a story about a brave knight").
Process: Assess the structure and content of the story.
Expected Result: A coherent story with a beginning, middle, and end.
Test Case 1.2: Understanding Metaphors
Input: Provide a simple metaphor (e.g., "Time is a thief").
Process: Ask the system to explain the meaning.
Expected Result: "It means that time passes quickly and takes moments away."
Test Case 2.1: Identifying Emotions
Input: Show images of faces expressing different emotions.
Process: Ask the system to identify the emotions.
Expected Result: Correct identification (e.g., happy, sad, angry).
Test Case 2.2: Understanding Days of the Week
Input: Discuss events happening on specific days.
Process: Ask the system when certain events occur.
Expected Result: Accurate association of events with days.
Test Case 3.1: Solving Logical Puzzles
Input: Present a simple maze or pattern puzzle.
Process: Observe the system's problem-solving approach.
Expected Result: The system finds a solution efficiently.
Test Case 3.2: Memory Recall of Details
Input: Provide a detailed scene or story with multiple elements.
Process: Ask specific questions about details after a delay.
Expected Result: Accurate recall of details.
Test Case 4.1: Moral Dilemmas
Input: Present a simple moral dilemma (e.g., "If you find a toy that isn't yours, what should you do?").
Process: Evaluate the system's response.
Expected Result: "I should try to find the owner or give it to an adult."
Test Case 4.2: Self-Reflection
Input: Ask the system to describe something it did well and something it could do better.
Process: Assess self-evaluation abilities.
Expected Result: The system provides examples of achievements and areas for improvement.
Narrative Skills: Telling coherent stories and understanding metaphors indicate advanced language and abstract thinking.
Emotional Understanding: Identifying emotions and grasping time concepts reflect deeper conceptual understanding.
Problem-Solving: Solving puzzles and recalling detailed information demonstrate cognitive sophistication.
Moral Reasoning: Handling moral dilemmas and engaging in self-reflection show mature moral development and self-awareness.
By simulating these whitebox tests, we can identify the system's cognitive development as follows:
Language Proficiency: Progression from constructing simple sentences to understanding complex grammar and abstract language.
Conceptual Understanding: Growth from basic time and numerical concepts to grasping abstract ideas and moral principles.
Cognitive Abilities: Enhancement of memory, attention, problem-solving, and logical reasoning skills.
Consciousness and Self-Awareness: Development of self-control, moral reasoning, empathy, and self-reflection.
Throughout the tests, the system demonstrates the ability to handle:
Incomplete Data: Inferring missing information and asking clarifying questions.
Imprecise Data: Refining understanding through context and feedback.
Inconsistent Data: Reconciling conflicting information by evaluating evidence and adjusting internal models.
Conclusion
The DIKWP whitebox tests for the stages of months 24–33 effectively simulate and measure the cognitive development of the artificial infant system. By analyzing the internal processes and responses to specific test cases, we can confirm that the system:
Achieves expected developmental milestones.
Demonstrates advanced cognitive functions aligned with human development at corresponding ages.
Effectively applies the DIKWP model and Prof. Yucong Duan's Consciousness "Bug" Theory to handle incomplete, imprecise, and inconsistent data.
This testing approach provides valuable insights into the system's capabilities and areas for further refinement, ensuring that the artificial consciousness system continues to evolve in a manner consistent with human cognitive development.
References for Further Reading
International Standardization Committee of Networked DIKWP for Artificial Intelligence Evaluation (DIKWP-SC),World Association of Artificial Consciousness(WAC),World Conference on Artificial Consciousness(WCAC). Standardization of DIKWP Semantic Mathematics of International Test and Evaluation Standards for Artificial Intelligence based on Networked Data-Information-Knowledge-Wisdom-Purpose (DIKWP ) Model. October 2024 DOI: 10.13140/RG.2.2.26233.89445 . https://www.researchgate.net/publication/384637381_Standardization_of_DIKWP_Semantic_Mathematics_of_International_Test_and_Evaluation_Standards_for_Artificial_Intelligence_based_on_Networked_Data-Information-Knowledge-Wisdom-Purpose_DIKWP_Model
Duan, Y. (2023). The Paradox of Mathematics in AI Semantics. Proposed by Prof. Yucong Duan:" As Prof. Yucong Duan proposed the Paradox of Mathematics as that current mathematics will not reach the goal of supporting real AI development since it goes with the routine of based on abstraction of real semantics but want to reach the reality of semantics. ".
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