intelligence (AI) is the simulation of human intelligence processes by machines,
especially computer systems. Specific applications of AI include expert systems, natural language
processing (NLP), speech recognition and machine vision.
AI programming focuses on three cognitive skills: learning, reasoning and self-correction.Learning processes: This aspect of AI programming focuses on acquiring data and
creating rules for how to turn the data into actionable information. The rules, which are called
algorithms, provide computing devices with step-by-step instructions for how to complete a specific
task.
Reasoning processes. This aspect of AI programming focuses on choosing the right algorithm to reach
a desired outcome.Self-correction processes: This aspect of AI programming is designed to continually
fine-tune algorithms and ensure they provide the most accurate results possible.
Advantages and disadvantages of artificial intelligence
Artificial neural networks and deep learning artificial intelligence technologies are
quickly evolving, primarily because AI processes large amounts of data much faster and makes
predictions more accurately than humanly possible.While the huge volume of data being created on a daily basis would bury a human
researcher, AI applications that use machine learning can take that data and quickly turn it into
actionable information. As of this writing, the primary disadvantage of using AI is that it is
expensive to process the large amounts of data that AI programming requires.
Strong AI vs. weak AI
AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an
AI system that is designed and trained to complete a specific task. Industrial robots and virtual
personal assistants, such as Apple's Siri, use weak AI.Strong AI, also known as artificial general intelligence (AGI), describes programming
that can replicate the cognitive abilities of the human brain. When presented with an unfamiliar
task, a strong AI system can use fuzzy logic to apply knowledge from one domain to another and find
a solution autonomously. In theory, a strong AI program should be able to pass both a Turing test
and the Chinese room test.
Ethical use of artificial intelligence
While AI tools present a range of new functionality for businesses, the use of
artificial intelligence also raises ethical questions because, for better or worse, an AI system
will reinforce what it has already learned.
This can be problematic because machine learning algorithms, which underpin many of the most
advanced AI tools, are only as smart as the data they are given in training. Because a human being
selects what data is used to train an AI program, the potential for machine learning bias is
inherent and must be monitored closely.Anyone looking to use machine learning as part of real-world, in-production systems
needs to factor ethics into their AI training processes and strive to avoid bias. This is especially
true when using AI algorithms that are inherently unexplainable in deep learning and generative
adversarial network (GAN) applications
