There is a tremendous ambiguity in the objectives of Artificial Intelligence (AI) and Mechanical Learning currently used by large companies who want to create an artificial intelligence that might perhaps match or exceed the abilities 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 the most dangerous thing is to treat each AI as magical. An algorithm is as good as the data or rules that people are giving it to programmers. The nature of the algorithms that can be learned and evolved without the developers will be slow to come again, this does not mean that their answers will be accepted without any doubt.
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 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.
Registration in iGuRu.gr via Email
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.