Automated Corrections and Artificial Intelligence - dummies

Automated Corrections and Artificial Intelligence

By John Paul Mueller, Luca Massaron

Humans constantly correct everything. It isn’t a matter of everything being wrong. Rather, it’s a matter of making everything slightly better (or at least trying to make it better). Even when humans manage to achieve just the right level of rightness at a particular moment, a new experience brings that level of rightness into question because now the person has additional data by which to judge the whole question of what constitutes right in a particular situation. To fully mimic human intelligence, AI must also have this capability to constantly correct the results it provides, even when such results would provide a positive result. The following discussion is about the issue of correctness and how automated corrections sometimes fail.

Considering the kinds of corrections

When most people think about AI and correction, they think about the spell checker or grammar checker. A person makes a mistake (or at least the AI thinks so) and the AI corrects this mistake so that the typed document is as accurate as possible. Of course, humans make lots of mistakes, so having an AI to correct them is a good idea.

Corrections can take all sorts of forms and not necessarily mean that an error has occurred or will occur in the future. For example, a car could assist a driver by making constant lane position corrections. The driver might be well within the limits of safe driving, but the AI could provide these micro corrections to help ensure that the driver remains safe.

Taking the whole correction scenario further, the car in front of the car containing the AI makes a sudden stop because of a deer in the road. The driver of the current car hasn’t committed any sort of error. However, the AI can react faster than the driver can and acts to stop the car as quickly and as safely as possible to address the now-stopped car in front of it.

Seeing the benefits of automatic corrections

When an AI sees a need for a correction, it can either ask the human for permission to make the correction or make the change automatically. For example, when someone uses speech recognition to type a document and makes an error in grammar, the AI should ask permission before making a change because the human may have actually meant the word or the AI may have misunderstood what the human meant.

However, sometimes it’s critical that the AI provide a robust enough decision-making process to perform corrections automatically. For example, when considering the braking scenario from the previous section, the AI doesn’t have time to ask permission; it must apply the brake immediately or the human could die from the crash. Automatic corrections have a definite place when working with an AI, assuming that the need for a decision is critical and the AI is robust.

Understanding why automated corrections don’t work

An AI can’t actually understand anything. Without understanding, it no capability to compensate for the unforeseen circumstance. In this case, the unforeseen circumstance relates to an unscripted event, one in which the AI can’t accumulate additional data or rely on other mechanical means to solve. A human can solve the problem because a human understands the basis of the problem and usually enough of the surrounding events to define a pattern that can help form a solution. In addition, human innovation and creativity provides solutions where none are obvious through other means. Given that an AI currently lacks both innovation and creativity, the AI is at a disadvantage in solving specific problem domains.

To put this issue into perspective, consider the case of a spelling checker. A human types a perfectly legitimate word that doesn’t appear in the dictionary used by the AI for making corrections. The AI often substitutes a word that looks close to the specified word, but is still incorrect. Even after the human checks the document, retypes the correct word, and then adds it to the dictionary, the AI is still apt to make a mistake. For example, the AI could treat the abbreviation CPU differently from cpu because the former is in uppercase and the latter appears in lowercase. A human would see that the two abbreviations are the same and that, in the second case, the abbreviation is correct but may need to appear in uppercase instead.