From Machine Learning, my interest flew to Data Mining. Well, most of Data Mining techniques use machine learning algorithms anyway. But, why Data Mining?
Data Mining = given a bunch of data, Data Mining (automatically or semi-automatically) could extract an interesting information/pattern out of it. For example:
Once there is a competition similar to example about Mr. T above. So, University of Melbourne launch a competition to predict the outcome of a grant application: http://www.kaggle.com/c/unimelb. This competition is launch because there are so many grant application right now received by the university (and its professors has to review it all). In order to lower the work-rate of its professors in reviewing grant application, the idea is to have a machine that could predict a success-rate for each application. Next, the university could take only grant application which has score 80% or above to be given to its professors for a final decision. This approach could reduce the number of application reviewed by its professors tremendously. Of course the algorithm that is used by the machine should be a good algorithm.
Story about the competition by University of Melbourne above is a perfect example on how machine could really help human task. Example about Mr. T above could also extended: not merely the machine which give the decision, but the result by the machine should also be monitored by a human behind.
More article about Data Mining, see its article in wikipedia for details.