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The Artificial Intelligence revolution

How much do we really know about AI? What are the positives? What are the risks? In this mini podcast we get to hear an interesting discussion about AI from Leonidas and Leo.

Leonidas: Good evening, ladies and gentlemen. We would like to welcome you to our audio show “Double experience”. I’m Leo, the host of the podcast for tonight and today we have with us a very special guest, an expert, as some say an upcoming genius at the field of AI. Mr. Leo, it’s an honor for having you tonight with us to discuss a burning issue that is in the news and concerns all of humanity, ethics of AI. But what AI stands for? AI stands for Artificial Intelligence. But what is artificial intelligence? Is the simulation of human intelligence processed by computer systems. AI technology can process large amounts of data in ways unlike humans. The goal of AI is to be able to do things such as recognize patterns, make decisions, and judge like humans. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. But do we really have achieved the AI?

 Leo: The simple answer is no, we don’t. A lot of people have in their minds examples of chat boxes or machine learning algorithms that are not AI.

Leonidas: Yes, but no single programming language is synonymous with AI. So how close are we on developing represent intelligence?

Leo: Actually, we are close, but at the same time we are not, because artificial intelligence in civilian level is not as much research as it can be in military, we don’t know in military research how far has it gone because it’s classified, of course. But when I say military, I mean it because the military has a lot of budgets and that’s, we know a lot of inventions that now civilians have come from military research.

Leonidas: As you already know, Mr. Leo, as part of its digital strategy, the EU wants to regulate artificial intelligence to ensure better conditions for the development and use of its innovative technology benefits such as better healthcare, safer, clean and transfer, more efficient manufacturing, cheaper and more sustainable energy. The European Commission proposed the first EU regulatory framework for AI. AI systems can be used in different applications, are analyzed and classified according to the visits they post the users. The different risk levels will mean more or less regulation. It will be the world’s first rule on AI. So, we’ve all seen the headlines about AI, both good and bad. Businesses of all sizes have found great benefits from utilizing AI and consumer across the globe using in their daily lives. Not the AI, just the AI that we have developed today. So, what are exactly the advantages and the disadvantages of AI? From my research I found some pros and some cons. AI eliminates human error and risks, has a 24/7 availability and it’s an unbiased decision-making machine. But it replaces and reduces human jobs and raises ethical problems and questions about the cheats.

Leo: AI is just like the nuclear power. It has its goods and bads. Goods are it can be used first of all, in civilian research for better understanding of topics that a simple human can’t understand very well, or it can be used for civil to make life easier. But just like nuclear energy, it has it’s bad. Just like nuclear energy has nuclear bombs, AI can be used against humanity. It can steal data from places and it can basically destroy anyone’s life very easily. It has access to a lot of data.

Leonidas: So, you say, that we can compare as a technological breakthrough, artificial intelligence with nuclear energy?

Leo: Of course, because both are basically revolution of its own, and each revolution has its own goods and bads. The artificial intelligence is the 4th revolution, as we know. The 4th revolution we can compare it to the second revolution which machines to cover the world and basically a lot of manual labor was out of the workplace. But, still, people found ways around to make jobs that, for example, maintenance of machines, research of machines or making of machines. So yeah, I think it’s just like nuclear energy.

Leonidas: Let’s hop on another topic. Generative AI. Enlighten us, please.

Leo: Generative AI it’s very simple. It takes information and with this information can generate more information, but get more information, not any information, can find personal info about anyone. It farms info from big data lakes, but what are basically big data lakes? Big data lakes are places where companies dump all your data. Not literally, but in their computer world. When you consent for a company to take your “cookies” or, like, information of what you search or what you do on their website, they most of the time dump it in one of these lakes, where any other company can try to search for it or, as specials say, mine for them and use them for their own purpose.

Leonidas: You are aware of the incident in England in 2021 for a university that used an algorithm to grade students?

Leo: Of course, it was a very nice example of bias.

Leonidas: Bias. May I interrupt you here? It’s a systematic distortion of statistical result due to a factor not allowed for its derivation. A method of sampling, measurement and analysis and etc.

Leo: Yes, that’s the little definition of what bias means in this example, about the England in 2021. In 2021, as everyone knows, covid became a thing. It was a huge pandemic that it was very not contagious. Yeah, that’s a little definition. But let’s go back to the example right now. In 2021, England, because of coronavirus, didn’t have examples for students to pass to the universities, so universities used an algorithm to grade the students. But the algorithm basically gave an advantage to private school students and not public. Private students pass to universities, but public students not, because if you go to a private school, you got more points. So that was very biased. But after the crowd of people started complaining a lot, the algorithm was passed out like, not exactly, it was stalled, and now they’re working on it again to restore it to not have bias. But after that, professors related the exams by themselves.

Leonidas: OK, let me ask you a final question, Mr. Leo, and I want you to answer me just with a yes or no. Do you think that artificial intelligence threatens to violate our privacy?

Leo: Yes.

Leonidas:  Thank you very much for your presence, your views and opinions illuminated us. We will be very happy to have you in our show again.

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