ThirdShifter 1. Autonomous Landing Systems: AI will be integrated into autopilot systems to do fully automated landings. These systems use sensors and algorithms to assess the aircraft's position, speed, and altitude, making real-time adjustments to ensure a safe landing.
It's do-able right now at major airports that have appropriate instrumentation. Even so, regulatory agencies are loathe to let planes take-off and land themselves.
- Sensor Fusion: AI will process data from multiple sensors, such as radar, lidars, and cameras to create a comprehensive understandings the whole environment.
In the list of sensors, you forgot to mention MCAS, which worked behind the pilot's back, and was difficult/impossible to over-ride.
- Weather Prediction and Analysis: AI algorithms will analyze weather data in real time. It will predicting changes in conditions that could affect landing like no human can do. It will be assessing wind patterns, visibility and precipitation which will accomplish better decision-making during the approach and landing phases than any human.
I repeat... MCAS
- Machine Learning for Pattern Recognition: AI will be trained on vast amounts of flight data to recognize patterns associated with successful landings in adverse conditions. Its already begun. This knowledge is going to be applied to improve landing techniques and strategies.
Already being applied in the hospital environment. Images from radiology are compared against a database of images of patients with/without cancer. If a patient's image has a high match rate against images of cancerous patients, the computer flags it... "Hey Doc, I think you need to take a closer look at this". The computer does not send the patient to the operating room by itself.
I do not believe that "pattern recognition" == "Artificial Intelligence". It can be a very useful tool, but it has its limitations.