Startupology notes

[vit_r]

Please note: modern AI wave creates not Artificial Intelligence but Artificial Intuition.

This is quite obvious because
1) statistical algorithms must be extensively trained on vast amount of data,
2) the internal logic of statistical decisions is not only hidden but also not traceable,
3) the results of learning are completely useless in an altered context or for altered goals.

Comments

[juan_gandhi]

Да! Отлично; спасибо за правильное слово. Там никаких правил вывода нету.

[vit_r]

В принципе, слово уже зарезервировано под какой-то квазинаучный бред. Это, скорее, объяснение для тех, кто не считает себя экспертом в AI.

[rdia.livejournal.com]

А что вы хорошего плохого скажете про тн C4 modeling?

C4model.com

Я прослушал семинар этого мужика - смешанные ощущения.

[vit_r]

Какой смысл вваливаться в пост не по теме, если можно послать приватное сообщение или мейл?

Что я могу сказать про какой-то сайт, о котором ничего не знаю? Ничего не могу сказать.

Моделирование - это способ упростить подход к решению задач. Где-то это работает, где-то нет. Тот, кто разрабатывает методологию, должен об этом знать.

Ещё в восьмидесятых ДеМарко в своей книжке писал, что разные модели - это просто разные проекции одной и той же структуры или динамики. При одном и том же результате, проще использовать то, что удобнее.

Любой (пусть самый примитивный или самый странный) подход можно применять, если для данных условий и для данной задачи он работает. Если в данных условиях или для данной задачи подход не эффективен, лучше использовать другой.

[vit_r]

My Reddit post in r/artificial

Why do we call AI based on modern statistical methods "artificial intelligence" and not "artificial intuition"?

1. Statistical algorithms must be extensively trained on vast amount of data.

2. The internal logic of statistical decisions is not only hidden but also not traceable.

3. The results of learning are useless in an altered context or for altered goals.

4. ... etc.

This all corresponds to the definition of the word "intuition": "the ability to acquire knowledge without proof, evidence, or conscious reasoning, or without understanding how the knowledge was acquired" (Wikipedia).

[Update]

The question is only about the interface between the AI community and the "external world".

The previous AI generation was based on expert knowledge, logic and formal proofs. This corresponds to the common understanding about intelligence.

The current AI generation is based on other principles and the word "intelligence" produces a lot of misleading ideas and false hopes. Wrong over-optimistic promises have killed the previous AI hype.

[vit_r]

My answers in comments:

Intelligence is more about logic and knowledge,
intuition is more about feelings and experience,
conditioning starts with "C" and is not suitable for explaining to customers what artificial "I" is hidden in "AI".

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It seems we use different definitions for the same words. [in comparison with the site http://artificial-intuition.com]

A child starts to understand logical thinking when it asks the first time the question "Why?" and consequently most people use some kind of logic in their everyday life. I also doubt that it is correct to include instincts into the description of the human intuition.

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Here is a nice comparison that explains why the word "statistics" is not suitable for marketing purposes
https://brenocon.com/blog/2008/12/statistics-vs-machine-learning-fight/

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[2. The internal logic of statistical decisions is not only hidden but also not traceable.]

Of course there may be some exceptions and some top papers are quite sophisticated but most people that try to create real world AI applications use software as a black box and simply throw datasets into it.

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[Why wee need the explanation of AI decisions]

The main goal is not to beat a human in some games but to make AI that helps a human to make informed decisions.

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You do not consider one important point: when the case about a wrong patient treatment comes into a court lawyers defending the AI decisions under question will be forced to prove the correctness of this particular decisions for this particular patient. It does not help to say that the success quote is good and that the dead patients are some marginal errors in the statistics.

There are many other fundamental problems that cause IBM to apply previous generation AI methods and to struggle with strong opposition by attempts to sell Watson to doctors.

Financial applications based on statistical methods also could predict only usual trends but will be completely useless against black swans. And it is impossible to correct this without knowing and controlling the whole process of decision choosing from facts till the conclusions.

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This is also a fundamental ethical problem: Could we allow companies to create robots that are allowed to kill us and how we prevent this robots from killing us intentionally.

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Errors made by AI in drug prescriptions could not be covered by insurance because each insurance company would not pay money, if it could have a possibility to claim that the damage was caused not by independent conditions but by faults, misconduct or ill intentions of a company that has produced this AI system.

And nobody could defend such company against such claims in a court, if this company is not able to provide documented logs that describe how and why the AI had taken the wrong decision.documented logs that describe how and why the AI had taken the wrong decision.