There is a huge ambiguity in its objectives artificialς νοημοσύνης (artificial intelligence or AI) and machine learning used today by large companies that desire the creation of an artificial intelligence that could perhaps match or even exceed the capabilities of the human mind.
As they develop, artificial intelligence or AI and machine learning will be able to take on even more complex tasks, but it could take half a century or more before any AI reaches human-level intelligence at satisfactory levels. We have only seen the sequel in Movies disaster, but what is certain is that super-intelligence seems to excite some, and terrify others. Meanwhile, new technology continues to fuel science fiction for decades (see Skynet).
Currently, today's AI (artificial intelligence) helps companies improve customer service or refine their decision-making by identifying trends in data που διαφορετικά θα ήταν αόρατες. Το AI βοηθάει με την αυτοματοποίηση συνηθισμένων εργασιών, ή ακόμα και στην creation εντελώς νέων υπηρεσιών.
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, we need to find ways to make sure that decision-making through AI is constantly being questioned. The challenge is the beginning of every science and every scientific discovery. So some researchers are looking at the use of too many factors, such as responsibility, explanation, accuracy, controllability and fairness. As you understand, because the concepts are abstract and not governed by specific laws, it takes too much work.
It is also important to look at the impact of artificial intelligence on its broadest meaning:
These technologies will have the potential to significantly change some jobs, create some and destroy others. The developers of this technology and its users should consider and recognize the potential positive and negative consequences. AI-powered autonomous vehicles can, for example, reduce pollution and do the taximore fun – but it will also throw many drivers out of the job market. So we should understand more broadly and more discussions about the upcoming changes will follow.
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.