Common Sense and Artificial Intelligence: Logical? Yes. Efficient? No

February 23, 2021

People easily forget that machines are only as smart as humans make them. Continuing on that that, AI and machine learning are the height of humanity’s most advanced technology but they are still stupid computer programs. AI and machine learning lack basic reasoning and logic, so these concepts must be taught to them. The Business Reporter discusses how AI needs more common sense programmed into its algorithms in “Trial And Error: The Human Flaws In Machine Learning.”

Humans are prone to cognitive biases and we need to monitor them. The best way to monitor cognitive biases are through slow, logical energy-intensive processes that point out illogical inconsistencies. Humans have two thought processes that are called different things in the varying science disciplines. However they are labeled, the thought processes are a “fast one” and a “slow one” or the reactive and active minds. Modern technology centers on the reactive/fast one, lacking active/slow one thought processes.

“But where does this fit into AI and machine learning? Those who trust technology more than humans believe that the most efficient way of eliminating the flaws in our thinking is to rely on disinterested, even-handed algorithms to make predictions and decisions, rather than inconsistent, prejudiced humans. But are the algorithms we use in artificial intelligence (AI) today really up to scratch? Or do machines have their own fallibilities when it comes to preconceptions?”

Machine learning algorithms are fantastic tools for closed systems when they are fed terabytes of data to learn and form correlations. Machine learning algorithms then apply what they know to the closed system and learn more via trial and error. One closed system machine learning algorithm cannot be transferred to another, so machine reasoning is a new technology concept.

Machine reasoning AI could eliminate cognitive biases, but no one has successfully programmed it yet. It will take tons of data, transferability of closed systems to discover common correlations, and lots of trial and error before computers have a nanobyte of common sense.

Enabling common sense in AI adds time and cost. The goal is to generate revenue with a juicy margin. That’s common sense.

Whitney Grace, February 23, 2021


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