1. An artificial intelligence expert learning system for screening comprising: a) a computer implemented screening item measuring instrument comprising a measuring instrument output device and a measuring instrument input device; b) a task performance database comprising task performance metric data for a set of N training persons wherein said N training persons all have a same task function characterized by said task performance metric; c) a computer implemented modeling engine comprising a modeling engine output device and a modeling engine input device; d) a computer implemented screening engine comprising a screening engine output device and a screening engine input device; and e) a permanent memory comprising computer executable instructions to physically cause: i) said measuring instrument to provide a characteristic profile comprising one or more screening items and one or more non-screening items to said set of N training persons through said measuring instrument output device; ii) said measuring instrument to read in responses to said items from said set of N training persons through said measuring instrument input device; iii) said modeling engine to: 1) read in said responses from said N training persons from said measuring instrument; and 2) read in said task performance metric data for said N training persons from said task performance database; iv) said modeling engine to fit a first path dependent model of said task performance metric data using responses to a first subset of said screening items, said first path dependent model comprising not more than M parameters where M is less than or equal to N/E wherein E has a value of 5 or greater; v) said modeling engine to fit a second path dependent model of said task performance metric using responses to a second subset of said screening items, said second path dependent model comprising not more than M parameters, and wherein said first subset of said screening items is different than said second subset of said screening items by at least one screening item; vi) said modeling engine to form a linear combination of said first and second path dependent models to form a combined model; vii) said screening engine to read in said combined model; viii) said screening engine to provide said characteristic profile to a candidate for said task function through said screening engine output device; ix) said screening engine to receive responses to the screening items in said characteristic profile from said candidate through said screening engine input device; x) said screening engine to execute said combined model using said candidate responses to produce an forecasted task performance metric for said candidate; and xi) said screening engine to reject said candidate for said task when said projected task performance metric is less than a minimum threshold task performance metric.