The science of logicLogic as defined by the Merriam-Webster online dictionary is:
"A science concerned with the principles and criteria of validity of inferences and arguments; the science of the formal principles of reasoning.
"The question then arises: how can software be programmed to draw conclusions based on human reasoning and rationality?
For starters, let's get a better understanding of the science behind logic.
Logic looks at preset equations and rules, and then compares the data in question to those rules to decide whether something is true/false, right/wrong, on/off, etc.
The following is a hypothetical example of a conditional statement used in logic:
-Rule: If someone sleeps in, they will probably be late for brunch.
-Problem: Joe overslept.
-Solution: Joe will probably be late for brunch.To derive the correct solution to this problem, we consider what is true and what is false and then we look at the so-called "truth tables," which are used in ordinary logic to determine the outcome.
-Rule: If someone sleeps in, they will probably be late for brunch.Â
-Problem: Joe overslept. Â
-Solution: Joe will probably be late for brunch. TRUEAlooking at the truth tables, we see that TRUE and/or TRUE yields TRUE. The complete truth tables, give examples of the basic equations used in logic and their conclusions.
These common mathematical tables are useful to remember or keep in mind when constructing algorithms (instructions) in computer programming.
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What does artificial intelligence use to make decisions?
Artificial intelligence (AI) is the branch of computer science that investigates and studies the ability to program software that uses logic to make decisions that mimic human logic, only faster and more accurate.
How does it do this?
AI derives logical conclusions based on a combination of three key factors, including:
-Recorded historical data is used as a basis to construct the rules and logical conclusions that fit the scenario.
-Fresh incoming data continually adds to the base to further support logic
-Real-time human interaction occurs when a decision is not clear.
These factors are the keys used in building and training the complex algorithms that perform problem-solving computations.
Does AI ever make poor logical decisions?
As with all software, a necessary recovery plan must be available in case of complete failure.
However, it should not be necessary to double-check the results, logic or accuracy of automation software once it is implemented, as it will not make programmatic errors of judgment.
Automation software, such as WorkFusion's Smart Process Automation (SPA), is smart enough to realize it needs help when it encounters something it doesn't understand.
In fact, the software is programmed with this in mind, to expect that scenarios will arise where decision-making ability is impeded, or when the choice is not 100% clear.
In such cases, intelligent automation software will ask for human help instead of going ahead and using less accurate logic that could potentially lead to a bad decision.
The future of artificial intelligence and machine learning
AI and ML are poised to automate modern society and take it to the next level.
As with any technology, there are pros and cons to consider.
AI and ML will always be only as good as the human logic and business rules built into it and the basic algorithms.
But because they can compute, learn and adapt as needs change and grow, it is easy to see how they can quickly become an integral part of any company seeking a competitive advantage in the marketplace.