- A paper from NASA addresses the misconceptions about reporting UFOs.
- NASA is searching for both ancient and modern signs of life.
- Civilian UAP reports are currently made without a standardized structure, resulting in sparse and incomplete data.
A paper from NASA addresses the misconceptions about reporting UFOs (Underwater Asteroid Projects) and the necessity for a more thorough method of data gathering.
The research emphasizes how it is difficult to get data on these occurrences since those who report UFO sightings are frequently written off as crazy or crank. However, NASA’s participation in UAP will be crucial in decreasing the stigma attached to UAP reporting, which currently almost likely contributes to data retention.
NASA UFOs and Abnormal Phenomena
NASA is searching for both ancient and modern signs of life, and last year, a private team was hired to study UAPs. The well-known “GoFast” video, which US Navy aviators shot from the USS Theodore Roosevelt in 2014–2015, was refuted by the study, which claimed it wasn’t moving particularly quickly at all.
The research makes the case that AI and machine learning can be used to find uncommon occurrences—possibly even UAP—in large datasets. The whole endeavor should not, however, rely solely on computers. Understanding UAP also requires a crucial component: public engagement.
The paper recommends using open-source smartphone apps and other contemporary crowdsourcing strategies to support the search. As part of its approach, NASA should examine the potential of creating or acquiring such a crowdsourcing system.
Civilian UAP reports are currently made without a standardized structure, resulting in sparse and incomplete data that lacks curation or validation procedures.
The US commercial remote-sensing sector, which provides imagery with sub- to several-meter spatial resolution and is well-matched to the typical spatial sizes of known UAPs, is also hinted at by NASA as having a potential role.
The paper also makes the case that NASA’s resources can be extremely useful in figuring out whether particular environmental conditions are connected to certain observed UAP behaviors or occurrences.
