Ingredients of intelligence: From classic debates to an engineering roadmap

Area of Science:

• Artificial Intelligence
• Cognitive Science
• Machine Learning

Background:

• Growing enthusiasm for human-like artificial intelligence (AI) and machine learning.
• Commentary on a proposed set of key ingredients for AI development.
• Disagreements exist regarding the origin and structure of these AI ingredients.

Purpose of the Study:

• To address key disagreements in AI development, focusing on nature vs. nurture, theory coherence, and representation types.
• To propose ways to move beyond classic debates in artificial intelligence and cognitive science.
• To consider the completeness of current AI ingredients and discuss future additions.

Main Methods:

• Analysis of commentary on AI development ingredients.
• Discussion of three dimensions of disagreement: nature vs. nurture, coherent theories vs. theory fragments, and symbolic vs. sub-symbolic representations.
• Exploration of ethical questions related to AI research.

Main Results:

• Identified and addressed three core dimensions of disagreement in AI development.
• Emphasized moving beyond traditional AI and cognitive science debates.
• Acknowledged the importance of additional ingredients for long-term AI progress.

Conclusions:

• The study provides a framework for understanding and resolving key debates in human-like AI.
• It highlights the need for ongoing development and incorporation of new ideas in AI.
• Ethical considerations are crucial for the advancement of AI research programs.