Why This U̳F̳O̳ Report Is Calling For AI Data Assessment


The Unidentified Aerial Phenomena Taskforce sent a report on U̳F̳O̳s to Congress recently, which shows that there’s no evidence of a̳l̳i̳e̳n̳ life out there as far as we know. However, we’re seeing more reports of UAPs, or Unidentified Arial Phenomena, than ever before. This is posing a threat to international air spaces, and so many are starting to call for AI to track U̳F̳O̳ and UAP data in order to make sense of it. Here’s why.

Searching For E̳x̳t̳r̳a̳t̳e̳r̳r̳e̳s̳t̳r̳i̳a̳l̳ Intelligence 

For decades there have been several groups and task forces all over the globe, looking for signs of life out in space. There have been sightings of UAPs for hundreds of years, and yet we’re no closer to a decision on what kind of life is out there. According to U̳F̳O̳ blogger Tim Chiles, from Academic Brits, we may be looking at it the wrong way.

“Here on Earth, there are lots of different life forms, and they all communicate in different ways. As humans, we have a limited idea of what a̳l̳i̳e̳n̳ lifeforms would look like and communicate like, so we need to expand our scope to understand what’s out there.”

This could be why the recent report to Congress hasn’t been able to deliver any significant theories or evidence of a̳l̳i̳e̳n̳ life. With the reports coming in, they’re being filtered through the idea we have of what an a̳l̳i̳e̳n̳ looks like. Because of this, we could be missing vital clues.

Using AI To Process Data

Before getting into the use of AI and UAP data, it’s important to understand how it works. AI is something that used to be in the realm of science fiction, but now is something that you use every day. Whether you ask Siri to look something up for you or use Alexa to play music as you’re cooking dinner, it’s a highly useful tool.

One of the most common forms of AI is machine learning. That’s when the AI is fed a set of data and is then continuously fed data over time. The AI forms patterns out of the data, and that helps it create data sets that are useful to the user. For example, when you shop on Amazon, the site is feeding the data of what you look at and buy into an AI. That AI then gets an idea of what you like and compares it to what other people like. That’s how it recommends items to you that you may like when you next log on.

This is just one way that machine learning is used, and it’s spread all over many different industries and can offer a lot of benefits. Many UAP experts, they feel that machine learning could actually help in this regard.

AI And U̳F̳O̳ Data

As mentioned earlier, we have more data on UAPs and U̳F̳O̳s than ever before. As such, you would think that we would have more idea about the existence of a̳l̳i̳e̳n̳s than ever before. This data comes from human sightings, air traffic reports, scientific abnormalities in testing, and so on. The problem is we have no context in which to view these reports, and so we can’t see the patterns that could tell us something.

That’s where machine learning AI comes in. This can be used to take that data, sort through it, and show us results that we may not have seen ourselves as we didn’t have the context for it. This has a lot of benefits for those studying U̳F̳O̳s.

Firstly, there’s so much data out there, that it would take far too long for humans to go through and process. An AI can take that and get to work right away, processing and learning from it much faster than we ever could. The other huge benefit is that we’ll get those patterns and predictions, which not only help with understanding U̳F̳O̳s but also improve safety. With the AI’s predictions, we can prevent air traffic accidents and other issues that come about due to UAPs.

As you can see, there are some good reasons for AI to be used in the search for a̳l̳i̳e̳n̳ life. It could well be the next step in researching U̳F̳O̳s and life in the universe.

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