Generating artificial intelligence subjects and media stimuli to simulate and predict human responses

1 . A computer-implemented method for simulating responses to media stimuli in order to compare effectiveness of different versions of the media, comprising:

at an input device, receiving a study configuration object comprising a first set of parameters defining a demographic distribution for artificial intelligence (AI) subjects to be run on at least one hardware processor to simulate human subjects and a second set of parameters defining a plurality of experimental conditions;

at the at least one hardware processor, programmatically translating the study configuration object into a prompt grammar;

at the at least one hardware processor, generating a plurality of AI subjects by executing the prompt grammar on at least one large language model, wherein each AI subject is instantiated with specific characteristics based on the demographic distribution;

at a storage device, storing data defining the plurality of AI subjects;

at the at least one hardware processor, assigning each generated AI subject to either a control group or a treatment group defined by the experimental conditions;

at the at least one hardware processor, generating stimuli corresponding to the assigned experimental condition for each AI subject, the stimuli representing at least one version of the media;

at the at least one hardware processor, constructing a final prompt for each AI subject comprising the specific characteristics, the generated stimuli, and a response schema defining a required structured output format;

at the at least one hardware processor, presenting the final prompt to each AI subject, to expose each AI subject to a version of the media;

at the at least one hardware processor, recording responses from the AI subjects

at the at least one hardware processor, automatically comparing effectiveness of the different versions of the media;

at an output device, outputting a statistical analysis report based on the recorded responses and the comparison; and

at the storage device, storing the recorded responses.

2 . The method of claim 1 , wherein the stimuli comprises at least one selected from the group consisting of:

text;

a question;

at least one image; and

video content.

3 . The method of claim 1 , wherein:

each final prompt has a type;

each AI subject is implemented as a large language model instance; and

each large language model instance is adapted to automatically detect the type of each prompt.

4 . The method of claim 1 , wherein:

comparing the effectiveness of the different versions of the media comprises, at the at least one hardware processor, running a statistical analysis of the recorded responses of the generated AI subjects to the stimuli; and

the statistical analysis report is based on the statistical analysis.

5 . The method of claim 4 , wherein running the statistical analysis comprises automatically determining which of a plurality of techniques to use for the statistical analysis.

6 . The method of claim 4 , further comprising automatically generating additional stimulus for further research, based on the results of the statistical analysis.

7 . The method of claim 1 , wherein comparing the effectiveness of the different versions comprises computing composite scores from the recorded structured responses using construct mappings, and performing statistical testing on the composite scores across the control group and the treatment group.

8 . A non-transitory computer-readable medium for simulating responses to media stimuli in order to compare effectiveness of different versions of the media, comprising instructions stored thereon, that when performed by at least one hardware processor, perform the steps of:

causing an input device to receive a study configuration object comprising a first set of parameters defining a demographic distribution for artificial intelligence (AI) subjects to be run on at least one hardware processor to simulate human subjects and a second set of parameters defining a plurality of experimental conditions;

programmatically translating the study configuration object into a prompt grammar;

generating a plurality of AI subjects by executing the prompt grammar on at least one large language model, wherein each AI subject is instantiated with specific characteristics based on the demographic distribution;

causing a storage device to store data defining the plurality of AI subjects;

assigning each generated AI subject to either a control group or a treatment group defined by the experimental conditions;

generating stimuli corresponding to the assigned experimental condition for each AI subject, the stimuli representing at least one version of the media;

constructing a final prompt for each AI subject comprising the specific characteristics, the generated stimuli, and a response schema defining a required structured output format;

presenting the final prompt to each AI subject, to expose each AI subject to a version of the media;

recording responses from the AI subjects;

automatically comparing effectiveness of the different versions of the media;

causing an output device to output a statistical analysis report based on the recorded responses and the comparison; and

causing the storage device to store the recorded responses.

9 . The non-transitory computer-readable medium of claim 8 , wherein the stimuli comprises at least one selected from the group consisting of:

text;

a question;

at least one image; and

video content.

10 . The non-transitory computer-readable medium of claim 8 , wherein:

each final prompt has a type;

each AI subject is implemented as a large language model instance; and

each large language model instance is adapted to automatically detect the type of each prompt.

11 . The non-transitory computer-readable medium of claim 8 , wherein:

comparing the effectiveness of the different versions of the media comprises, at the at least one hardware processor, running a statistical analysis of the recorded responses of the generated AI subjects to the stimuli; and

the statistical analysis report is based on the statistical analysis.

12 . The non-transitory computer-readable medium of claim 11 , wherein running the statistical analysis comprises automatically determining which of a plurality of techniques to use for the statistical analysis.

13 . The non-transitory computer-readable medium of claim 11 , further comprising instructions stored thereon, that when performed by the hardware processor, perform the step of automatically generating additional stimulus for further research, based on the results of the statistical analysis.

14 . The non-transitory computer-readable medium of claim 8 , wherein comparing the effectiveness of the different versions comprises computing composite scores from the recorded structured responses using construct mappings, and performing statistical testing on the composite scores across the control group and the treatment group.

15 . A system for simulating responses to media stimuli in order to compare effectiveness of different versions of the media, comprising:

an input device, configured to receive a study configuration object comprising a first set of parameters defining a demographic distribution for artificial intelligence (AI) subjects to be run on at least one hardware processor to simulate human subjects and a second set of parameters defining a plurality of experimental conditions;

at least one hardware processor, each communicatively coupled to the input device, configured to;

programmatically translate the study configuration object into a prompt grammar; and

generate a plurality of AI subjects by executing the prompt grammar on at least one large language model, wherein each AI subject is instantiated with specific characteristics based on the demographic distribution;

a storage device, communicatively coupled to the at least one hardware processor, configured to store data defining the plurality of AI subjects; and

an output device, communicatively coupled to the at least one hardware processor;

wherein:

the at least one hardware processor is further configured to:

assign each generated AI subject to either a control group or a treatment group defined by the experimental conditions;

generate stimuli corresponding to the assigned experimental condition for each AI subject, the stimuli representing at least one version of the media;

construct a final prompt for each AI subject comprising the specific characteristics, the generated stimuli, and a response schema defining a required structured output format;

present the final prompt to each AI subject, to expose each AI subject to a version of the media;

record responses from the AI subjects; and

automatically compare effectiveness of the different versions of the media;

the an output device is configured to output a statistical analysis report based on the recorded responses and the comparison; and

the storage device is further configured to store the recorded responses.

16 . The system of claim 15 , wherein the stimuli comprises at least one selected from the group consisting of:

text;

a question;

at least one image; and

video content.

17 . The system of claim 15 , wherein:

each final prompt has a type;

each AI subject is implemented as a large language model instance; and

each large language model instance is adapted to automatically detect the type of each prompt.

18 . The system of claim 15 , wherein:

comparing the effectiveness of the different versions of the media comprises running a statistical analysis of the recorded responses of the generated AI subjects to the stimuli; and

the statistical analysis report is based on the statistical analysis.

19 . The system of claim 18 , wherein running the statistical analysis comprises automatically determining which of a plurality of techniques to use for the statistical analysis.

20 . The system of claim 18 , wherein the hardware processor is further configured to automatically generate additional stimulus for further research, based on the results of the statistical analysis.

21 . The system of claim 15 , wherein comparing the effectiveness of the different versions comprises computing composite scores from the recorded structured responses using construct mappings, and performing statistical testing on the composite scores across the control group and the treatment group.