Mathematics, word problems, common sense, and artificial intelligence
This addresses a critical bottleneck for AI applications in mathematics and human-readable content, though it is incremental as it reviews existing methods without introducing new solutions.
The paper examines the inability of current AI systems to reliably solve word problems requiring elementary knowledge and commonsense reasoning, reviewing three AI-based approaches and their limitations.
The paper discusses the capacities and limitations of current artificial intelligence (AI) technology to solve word problems that combine elementary knowledge with commonsense reasoning. No existing AI systems can solve these reliably. We review three approaches that have been developed, using AI natural language technology: outputting the answer directly, outputting a computer program that solves the problem, and outputting a formalized representation that can be input to an automated theorem verifier. We review some benchmarks that have been developed to evaluate these systems and some experimental studies. We discuss the limitations of the existing technology at solving these kinds of problems. We argue that it is not clear whether these kinds of limitations will be important in developing AI technology for pure mathematical research, but that they will be important in applications of mathematics, and may well be important in developing programs capable of reading and understanding mathematical content written by humans.