The Data driven approach

John Shawe-Taylor and Nello Cristiani - Kernel Methods for Pattern Analysis:

Many of the most interesting problems in AI and computer science in general are extremely complex often making it difficult or even impossible to specify an explicitly programmed solution. As an example consider the problem of recognising genes in a DNA sequence. We do not know how to specify a program to pick out the subsequences of, say, human DNA that represent genes. Similarly we are not able directly to program a computer to recognise a face in a photo. Learning systems offer an alternative methodology for tackling these problems. By exploiting the knowledge extracted from a sample of data, they are often capable of adapting themselves to infer a solution to such tasks. We will call this alternative approach to software design the learning methodology. It is also referred to as the data driven or data based approach, in contrast to the theory driven approach that gives rise to precise specifications of the required algorithms.