Ray Kroc of McDonald's fame was in his 50s when he started the business. The McDonald's fast-food chain happened to become successful company and top-brand within Ray's lifetime. He died in the 1980s. Before McDonald's he hadn't been known for anything truly glorious and exceptional as achievement.
Perhaps, besides amounting enourmous experience and insight about restaurants and sales. Something which took him decades in the hard way and is recognizable only afterwards.
And, any person can do so, not only special people. This is because people have free will and intelligence (i.e. are intelligent agents) and machines do not. Thus, it is mathematically provable that prejudice is always wrong.
How does it show this? And for what definition of "information"?
it is mathematically provable...
The first step of mathematics is to define your axioms and then your terms. IDT doesn't seem to do either.
http://marksmannet.com/RobertMarks/REPRINTS/2009_Conservatio...
A critique (FWIW):
http://scienceblogs.com/goodmath/2009/08/quick_critique_demb...
Dembski's paper shows that any search performing better than random sampling requires the addition of information. This is information in the Shannon sense, -log2(p), where p is the probability of sampling the target region in a search space normalized according to random sampling.
This cannot be done algorithmically for an arbitrary search landscape. According to IDT, however, the defining quality of intelligent agents is their ability to produce information. This can be measured and thus falsified or confirmed. I.e. do agents we normally identify as intelligent, such as humans, actually produce information?
Per question 2:
If the above does not define terms enough for you, let me know. Dembski does a very good job in defining ID mathematically. The following is a collection of his work, much of it freely available online.
Discount anyone at your own peril. These days, things are often not as they appear.