input: from typing import List
  
  def average_absolute_deviation(numbers: List[float]) -> float:
      """ Given a list of floating-point numbers, compute the Mean Absolute Deviation
      centered around the mean of this list.
      Mean Absolute Deviation quantifies the average absolute differences 
      between every number and the dataset's mean:
      MAD = mean | x - mean_x |
      >>> average_absolute_deviation([1.0, 2.0, 3.0, 4.0])
      1.0
      """
output:     mean_x = sum(numbers) / len(numbers)
      mad = sum(abs(x - mean_x) for x in numbers) / len(numbers)
      return mad