Artificial General Intelligence is a slippery concept – if we show we can do something on a machine, then ipso facto it doesn’t require a human level of intelligence. So, for Proof of Concept, we had to find a reasonably bounded hard problem. Anti-Money Laundering probably fills the bill. A money launderer is a criminal who turns dirty money into clean by a variety of techniques – they can turn a large sum of money into a large number of small amounts that fly below the radar, then reassemble the money, possibly offshore to pay for importation of illegal drugs, or have a reputable company issue fake invoices, or move the money through a casino, so it becomes “winnings”. The money launderer is willing to lose 15% of the money in the process, so they can afford the best lawyers, or a large workforce of “smurfs” (seemingly innocent people, like pensioners).

A bank can implement systems to combat money-laundering, but the bank and its systems are slow and cumbersome, while the money launderer can “turn on a dime”. What is needed is a way of increasing the speed of response of a bank to a threat. One way to do that is to change from a programmed system to the use of English in determining and implementing the strategy used to fight money laundering – to change from a response time of six months at best to a response time measured in days.  The application illustrates how a machine can be used to counter the activities of a well-resourced adversary with human-level intelligence, a determination to succeed, and the ability to see weaknesses in the bank’s defences, substantiating a claim for AGI.

The first step is for the machine to read and “understand” the Act. This already has substantial benefits, as a human reader without much legal experience can see exactly what is meant  by every word and group of words, without getting lost in a forest of bullets and other punctuation. An important aspect is that the Act uses the word “reckless”, which is not a word a programmer would be happy with, as it introduces human frailties to what is otherwise just simple database transactions. This is a precursor to handling the psychology of a Money Launderer in a machine – anticipating their moves instead of chasing after them.