Thoughts: time warp to 2019


How can we make AI that reasons?

The past decade or so has been touted as a high point for achievements in Artificial Intelligence (AI). For the first time, computers have demonstrated formidable ability in such areas as image recognition, speech recognition, gaming, and (most recently) autonomous driving / piloting. Researchers and companies that are heavily invested in these technologies, at least, are in no small way lauding these successes, and are giving us the pitch that the current state-of-the-art is nothing less than groundbreaking.

However, as anyone exposed to the industry knows, the current state-of-the-art is still plagued by fundamental shortcomings. In a nutshell, the current generation of AI is characterised by big data (i.e. a huge amount of sample data is needed in order to yield only moderately useful results), big hardware (i.e. a giant amount of clustered compute resources is needed, again in order to yield only moderately useful results), and flawed algorithms (i.e. algorithms that, at the end of the day, are based on statistical analysis and not much else – this includes the latest Convolutional Neural Networks). As such, the areas of success (impressive though they may be) are still dwarfed by the relative failures, in areas such as natural language conversation, criminal justice assessment, and art analysis / art production.

In my opinion, if we are to have any chance of reaching a higher plane of AI – one that demonstrates more human-like intelligence – then we must lessen our focus on statistics, mathematics, and neurobiology. Instead, we must turn our attention to philosophy, an area that has traditionally been neglected by AI research. Only philosophy (specifically, metaphysics and epistemology) contains the teachings that we so desperately need, regarding what "reasoning" means, what is the abstract machinery that makes reasoning possible, and what are the absolute limits of reasoning and knowledge.