Problem

Failure of methods to appropriate data

Other Names:
Absence of method to appropriate available data
Breakdown of reducibility in science
Replication crisis in science
Nature:

To function effectively in the modern world people need technologies to appropriate data. All of the past processes by which people handled data have become ineffective. The ever increasing amount and diversity of information available to any individual simply overwhelms simplistic methods of data retention. Past wisdom is seemingly irrelevant, decisions are confusing, learning is difficult, and capacity to operate is reduced.

Incidence:

A growing amount of scientific research involves using machine learning software to analyse data that has already been collected.  However, machine learning algorithms have been developed specifically to find interesting things in datasets and so when they search through huge amounts of data they will inevitably find a pattern.  The challenge is are these really true scientific discoveries? Are they reproducible?  Often these studies are not found out to be inaccurate until there's another real big dataset that someone applies these techniques. One analysis suggested that up to 85% of all biomedical research carried out in the world is wasted effort.

Strategies:
Collecting statistics
Problem Type:
E: Emanations of other problems
Date of last update
09.04.2019 – 12:01 CEST