ARTIFICIAL INTELLIGENCE SELECTION AND CONFIGURATION

1 . A computer-implemented method for selection and configuration of an automated robotic process, the method comprising:

receiving a temporal biometric measurement of a worker performing a task;

receiving a spatial-temporal environmental input provided to the worker;

identifying a type of reasoning used when performing the task based, at least in part, on the temporal biometric measurement of the worker;

selecting a component of an Artificial Intelligence (AI) solution to replicate the type of reasoning; and

configuring the component of the AI solution based on the spatial-temporal environmental input,

wherein the temporal biometric measurement comprises a set of spatial-temporal imaging data of a brain of the worker;

wherein identifying the type of reasoning further comprises identifying a set of spatial-temporal neocortical activity patterns of the worker and identifying an active area of a neocortex of the worker; and

wherein the selecting the component of the AI solution is based, at least in part, on the identified active area of the neocortex.

2 . The method of claim 1 , wherein the identified active area of the neocortex comprises a O1 neocortex region, and the selected AI component is optimized for visual processing.

3 . The method of claim 2 , wherein the configuring the component of the AI solution further comprises identifying a visual input for the component based on the spatial-temporal environmental input.

4 . The method of claim 1 , wherein the identified active area of the neocortex comprises a C3 neocortex region, and the selected AI component is optimized for at least one of data storage or retrieval.

5 . The method of claim 1 , wherein the selected AI component comprises a block-chain based distributed ledger.

6 . The method of claim 1 , further comprising identifying whether a serial or a parallel processing AI component is optimal based, at least in part, on the identified set of spatial-temporal neocortical activity patterns.

7 . The method of claim 1 , wherein the configuring the selected component of the AI solution further comprises identifying an ordered set of inputs to the component of the AI solution.

8 . The method of claim 1 , wherein the configuring the selected component of the AI solution further comprises identifying efficiencies from combinations of the spatial-temporal environmental input.

9 . The method of claim 1 , wherein the configuring the selected component of the AI solution further comprises identifying undesirable portions of the spatial-temporal environmental input that do not contribute to a positive solution; and configuring an input to a portion of the AI solution to limit undesirable input to the AI solution.

10 . The method of claim 9 , wherein limiting undesirable input to the AI solution further comprises removing input noise.

11 . The method of claim 1 , wherein the spatial-temporal environmental comprises at least one of an auditory environment, a visual environment, an olfactory environment, or a device user interface.

12 . The method of claim 1 , further comprising:

receiving a second temporal biometric measurement of the worker performing the task;

wherein the second temporal biometric measurement comprises at least one of an image of the worker, a video feed of the worker, an audio feed from the worker, a movement of the worker, a heartbeat of the worker, a galvanic skin response of the worker, or eye movements of the worker.

13 . The method of claim 1 , comprising:

identifying a plurality of performed tasks from the biometric measurements; and

extracting a performance parameter from the biometric measurements;

wherein the configuring the selected component of the AI solution is based, at least in part, on the performance parameter.

14 . The method of claim 12 , wherein the second temporal biometric measurement is provided in a training set for the component of the AI solution.

15 . The method of claim 12 , further comprising:

receiving results data related to the task; and

correlating the second temporal biometric measurement with the received results data;

wherein the selecting the component of the AI solution is further based on, at least in part, at least one of the results data or the correlation.

16 . The method of claim 1 , further comprising:

identifying a plurality of time intervals between each task of a plurality of performed tasks; and

configuring the selected component of the AI solution based on at least one of the plurality of time intervals.