Europe wants users to verify their age to navigate the Internet. Google does not need it: you can estimate it with AI

In February Google advertisement They were going to start starting an experimental system based on AI and automatic learning (Machine Learning) for Estimate the age of users of its services. That technology, initially thought to avoid access to adult content on YouTube, will now serve much more, although for now it will be restricted to the United States. Automated restrictions. If Google detects that a user is under 18 in the US, it will apply the same restrictions that it applies when users are proactively identified as minors – for example, when creating Gmail accounts. Thus, it will enable reminders to go to sleep on YouTube, it will limit content recommendations and disable both personalized advertising and access to Adult applications in Play Store. What happens if AI is wrong. If Google’s system incorrectly estimates that a user is under 18, said user will be able to send a photo of his identity card (in the US, that of driving usually), of a credit card or even a selfie. First, that Google ends up having a photo of those documents It is quite disturbing. Second, the selfie option is especially surprising, because a priori might not be enough to verify that someone is not a minor. Remembering How-Ord.net. Microsoft a decade ago launched an AI experiment according to which a user could upload a photo of one or more people, and the service He tried to guess the age of those people. The tool quickly went viral, but it was also controversial because of its possible impact on privacy. A study Of 2022 he revealed that various systems of this type were quite precise when guessing age in young people, but not so much in older people. Companies specialized in this area as Yoti explain that The margin of error is already reducedand its system has an average 1.3 -year error in young people between 13 and 17 years old. How to estimate the google age. Google’s age estimation model will use the existing data of its users, including the websites they visit, what type of videos do they see on YouTube or how long their accounts have had. What about privacy. According to Google, this approach “does not imply the collection of additional data”, but of all that information that you already have thanks to the profiles that users use to access their services. They also ensure that they will not share that estimate with apps or websites. Goal already implemented A similar system on Instagram months ago. The age verification fever. The movements in this regard are increasingly striking. Before the excuse for companies and governments to spy on us and knew more about us was the terrorist threat. Now it is that minors They can access adult content. There is a unique fever for developing age verification systems everywhere, and we are seeing it especially in Europe … and the United Kingdom. The United Kingdom teaches us how the future can be. One of the first countries to move in this area is the United Kingdom, which these days these days has activated its regulation so that minors cannot access adult content. The age verification systems must be present in all types of platforms, something that has been especially controversial there and that has generated a surprising (or perhaps not so much) Collateral effect: British users They have begun to subscribe in mass to VPN services to avoid having to pass those age verification controls. The EU wants its own “pajporte”. The controversy introduction of the Digital portfolio beta In Spain —Popularly known as “Pajortport” – is one of the great steps that EU member countries are facing the future European digital identity. Among the options that will enable this mobile application will be to verify the age of the users, and in fact the Spanish initiative is serving as inspiration For a European system. Said system, yes, is not exempt from controversy. It remains to be seen if the Google system is really effective, and if it is, how its deployment progresses and what impact that has on the intentions of various countries to control the age of users. In Xataka | Allowing an app to “all photos” of our gallery looks like the most harmless action in the world. It is not at all

We have tried to use AI to verify if the images of the war between Iran and Israel were made with AI. It has been a disaster

False images circulate on social networks is no novelty, but in the era of AI It is increasingly difficult to detect them And they have even made Let’s distrust real photos. That photos taken with AI are viral when an important event is the new normality is; We saw it After the blackout And also with him Conflict between Israel and Iran. It is clear to us that AI is very good to generate false images, but what if we use it precisely for the contrary? Not so much. The photos in question. At the same time as a Half Iranian published The news that Iran had demolished an Israeli F-35, two images began to run like gunpowder on social networks, although We soon knew they were false. One of them, that of the star and surrounded by curious F35, is especially striking. To begin with, the proportions make no sense: the plane seems giant when actually measures 16 meters and people are larger than buildings. And that not to mention that the damage of the plane is minimal to have been shot down. These images were not the only ones generated by AI that circulated in the first days of the conflict. Several videos such as this one of a huge Iranian missile that it seems quite real until we see that the water brand has been left to see that it is made with the, or East of a tel aviv shattered. AI is terrible doing FACT-CHECK. Means dedicated to FACT-CHECKING as Damn already denied These and other images created with AI in the context of the conflict between Iran and Israel. However, there were users who tried to resort to AI tools to check the authenticity of the images and obtained quite confusing answers. Is What happened in X with Grok. An analysis of more than 130,000 posts revealed that Musk’s AI was not able to detect some false images or identify the sources from which they came. The community notes written by the users themselves were much more reliable. We have tried it. To check the AI ​​capacities, we have used the image of the disproportionate F-35 and have asked several AI tools. This is what they have answered: Chatgpt: The Openai tool begins “This image does not seem real” and then proceeds to make an analysis of the proportion of the plane, which correctly identifies as a F35, and states that the damage does not seem coherent. Perplexity: Like Chatgpt, he tells us that proportions, perspective, and airplane damage and other details suggest that the photo has been digitally manipulated. Gemini: It tells us that the image is real, but that it is not an attack in combat, but of a clash with birds that happened in Israel in 2017. When we answer that the sources show us, it happens several links to the news, but in none of them the image appears. After a while sending us confusing information, he ends up recognizing that he was wrong and apologizes for “the serious mistake.” Claude: It is the only one that states with forcefulness that the image is not real and gives us the exact context of what has happened “this is one of the many false images that have circulated as part of misinformation campaigns during the conflict between Israel and Iran.” The reliability, pending subject. In our test, Gemini has completely invented the answer, while Chatgpt and Perplexity succeed, although they do not get wet. Claude is the only one that gives us all the information and hits fully. Although language models have improved a lot in a short time, Many answers continue to be invented Despite having access to the Internet and searches. Undoubtedly, reliability is the pending subject of generative AI and where more improvement margin has. Images | 404 average In Xataka | Chatgpt guide: 22 functions and things you can do to squeeze this artificial intelligence to the maximum

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