There is a huge ambiguity in the goals of artificial intelligence (artificial intelligence or AI) and machine learning that are used today by large corporations that wish to create an artificial intelligence that could perhaps match or even exceed the capabilities of the human mind.
As they develop, artificial intelligence or AI and mechanical learning or machine learning will be able to undertake even more complex tasks, but it may take half a century or more before each AI reaches the human level of intelligence at satisfactory levels. We have only seen it in movies of destruction, but it is certain that over-intelligence seems to excite some, and terrorize others. Meanwhile, new technology has continued to fuel scientific imagination for decades (see Skynet).
Currently, artificial intelligence (AI) helps companies improve customer service or perfect their decision making by identifying trends in data that would otherwise be invisible. AI helps with automating common tasks, or even creating completely new services.
From the above it follows that every AI technology should consider several issues:
Artificial intelligence is a rapidly growing and interesting technology but it is not the answer to every problem. In particular, pay attention to the prefix "AI" in future product names because it does not necessarily mean that it is better than someone else who does not contain the prefix.
In addition, the lack of skilled staff who can make the most of their technology, along with massive inflated expectations, could create a loss of confidence.
But perhaps most dangerous is treating every AI like magic. An algorithm is only as good as the data or rules human programmers feed it. THE nature of algorithms that can learn and evolve without programmers will be slow to come, and again that doesn't mean their answers will be accepted without question.
Instead, ways should be found to make sure that the λήψη decision-making through AI will be constantly challenged. Questioning is the principle of every science and every scientific discoverys. Thus some researchers consider the use of too many factors, such as responsibility, explanation, accuracy, controllability, and fairness. As you can see because the concepts themselves are abstract and not governed by specific laws it takes a lot of work.
It is also important to look at the impact of artificial intelligence on its broadest meaning:
These technologies will be able to significantly alter certain jobs, create some and destroy others. Developers of this technology and its users should consider and identify the possible positive and negative consequences. AI-powered autonomous vehicles can, for example, reduce pollution and make travel more fun - but it will also throw away many drivers from the labor market. So we need to understand more widely and follow up on the upcoming changes.
As artificial intelligence and mechanical learning are not something we need to worry about. Our concern should focus on human intelligence and our ability to learn and predict the future.
