Privacy-guided disclosure of crowd-based scores computed based on measurements of affective response

• US 20160224803A1
• Filed: 01/29/2016
• Published: 08/04/2016
• Est. Priority Date: 01/29/2015
• Status: Active Grant

• Current Assignee: Affectomatics ltd.
• Original Assignee: Affectomatics ltd.
• Inventors: Frank, Ari M, Thieberger, Gil
• Granted Patent: US 10,572,679 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 21/6245 Protecting personal data, e.g. for financial or medical purposes

Abstract

Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to filter measurements of affective response collected using sensors that measure physiological signals and/or behavioral cues of users. A bias may be tendency, attitude, and/or inclination, which may influence the affective response a user has to an experience. Some embodiments described herein involve learning a model of biases of the user from measurements of affective response of the user and descriptions of events to which the measurements correspond. The model may be used to filter measurements of the user, which may be provided to other entities, if the model indicates that the measurements are likely to contain a certain level and/or type of bias (e.g., bias to certain factors). Such a filtration process can help make results generated based on the measurements more accurate and also may help protect the privacy of the user.

Claims

1. A system configured to disclose scores in a manner that reduces risk to privacy of users who contributed measurements of affective response used to compute the scores, comprising:

a memory storing computer executable modules; and

a processor configured to execute the computer executable modules;

the computer executable modules comprising;

a collection module configured to receive measurements of affective response of users who had experiences;

wherein each measurement of a user who had an experience is taken with a sensor coupled to the user;

a scoring module configured to compute scores;

wherein each score is for an experience, and is computed based on a subset of the measurements comprising measurements of at least five of the users who had the experience;

a privacy risk assessment module configured to make a determination indicative of an expected risk to privacy due to a disclosure of one or more of the scores; and

a privacy filter module configured to disclose the one or more of the scores in a manner that is based on the determination;

wherein responsive to the determination indicating that the risk does not reach a threshold, the one or more of the scores are disclosed in a first manner, and responsive to the determination indicating that the risk reaches the threshold, the one or more of the scores are disclosed in a second manner, which is less descriptive than the first manner.

2. The system of claim 1, wherein the determination is indicative of extent of improvement in an adversary bias model comprising bias values due to an update of the adversary bias model based on values of the one or more of the scores.

3. The system of claim 2, wherein the improvement corresponds to a reduction, due to the update, in a distance between the adversary bias model and a ground truth model comprising bias values of a user;

wherein the ground truth model is trained on data comprising measurements of affective response of the user and factors of events to which the measurements correspond.

4. The system of claim 1, wherein the determination of the expected risk due to the disclosure of the one or more of the scores is done utilizing a function that receives one or more values, each indicative of at least one of the following statistics:

a statistic of the measurements contributed for the computation of a score from among the one or more of the scores, a statistic regarding the value of a score from among the one or more of the scores, a statistic regarding extent of disclosure of data regarding at least one user from among the users who contributed measurements for the computation of a score from among the one or more of the scores.

5. The system of claim 1, wherein the determination is indicative of an average extent of a risk to privacy of the users who contributed measurements of affective response to the computation of at least some of the one or more of the scores.

6. The system of claim 1, wherein the determination is indicative of a maximal extent of a risk to privacy of a user from among the users who contributed measurements of affective response to the computation of at least some of the one or more of the scores.

7. The system of claim 1, wherein having an experience involves doing at least one of the following:

spending time at a certain location, consuming certain digital content, having a social interaction with a certain entity in the physical world, having a social interaction with a certain entity in a virtual world, viewing a certain live performance, performing a certain exercise, traveling a certain route, and consuming a certain product.

8. The system of claim 1, wherein the privacy filter is further configured to provide, when disclosing the one or more of the scores in the second manner, fewer values associated with the one or more of the scores, compared to the number of values associated with the one or more of the scores the privacy filter is configured to provide, when disclosing in the first manner.

9. The system of claim 1, wherein the privacy filter is further configured to provide, when disclosing the one or more of the scores in the second manner, less information describing the users who contributed measurements used to compute the one or more of the scores, compared to the information describing users who contributed measurements used to compute the one or more of the scores, which the privacy filter is configured to provide, when disclosing in the first manner.

10. The system of claim 1, wherein the privacy filter is further configured to provide, when disclosing in the second manner, fewer bits of information describing the one or more of the scores, compared to a number of bits of information describing the one or more of the scores the privacy filter is configured to provide, when disclosing in the first manner.

11. The system of claim 1, wherein when disclosing the one or more of the scores in the second manner, the privacy filter does not provide data describing a values of the one or more of the scores.

12. A method for disclosing scores in a manner that reduces risk to privacy of users who contributed measurements of affective response used to compute the scores, comprising:

receiving, by a system comprising a processor and memory, measurements of affective response of users who had experiences;

wherein each measurement of a user who had an experience is taken with a sensor coupled to the user;

computing scores, each score is for an experience, and is computed based on a subset of the measurements comprising measurements of at least five of the users who had the experience;

generating a determination indicative of an expected risk to privacy due to a disclosure of one or more of the scores; and

disclosing the one or more of the scores in a manner that is based on the determination;

wherein responsive to the determination indicating that the risk does not reach a threshold, the one or more of the scores are disclosed in a first manner, and responsive to the determination indicating that the risk reaches the threshold, the one or more of the scores are disclosed in a second manner, which is less descriptive than the first manner.

13. The method of claim 12, further comprising computing an extent of improvement in an adversary bias model comprising bias values due to an update of the adversary bias model based on values of the one or more of the scores;

wherein the determination is indicative of the extent of improvement.

14. The method of claim 13, further comprising determining a reduction, due to the update, in a distance between the adversary bias model and a ground truth model;

wherein the ground truth model is trained on data comprising measurements of affective response and factors of events to which the measurements correspond.

15. The method of claim 13, further comprising determining an extent of divergence between values of parameters of the adversary bias model before the update and values of the parameters after the update.

16. The method of claim 12, further comprising utilizing a function to make the determination;

wherein the function receives an input comprising one or more values, each indicative of at least one of the following statistics;

a statistic of the measurements contributed for the computation of a score from among the one or more of the scores, a statistic regarding the value of a score from among the one or more of the scores, a statistic regarding extent of disclosure of data regarding at least one user from among the users who contributed measurements for the computation of a score from among the one or more of the scores.

17. A non-transitory computer-readable medium having instructions stored thereon that, in response to execution by a system including a processor and memory, causes the system to perform operations comprising:

receiving measurements of affective response of users who had experiences;

wherein each measurement of a user who had an experience is taken with a sensor coupled to the user;

computing scores, each score is for an experience, and is computed based on a subset of the measurements comprising measurements of at least five of the users who had the experience;

generating a determination indicative of an expected risk to privacy due to a disclosure of one or more of the scores; and

disclosing the one or more of the scores in a manner that is based on the determination;

wherein responsive to the determination indicating that the risk does not reach a threshold, the one or more of the scores are disclosed in a first manner, and responsive to the determination indicating that the risk reaches the threshold, the one or more of the scores are disclosed in a second manner, which is less descriptive than the first manner.

18. The non-transitory computer-readable medium of claim 17, further comprising instructions defining the step of computing an extent of improvement in an adversary bias model comprising bias values due to an update of the adversary bias model based on values of the one or more of the scores;

wherein the determination is indicative of the extent of improvement.

19. The non-transitory computer-readable medium of claim 18, further comprising instructions defining the step of determining a reduction, due to the update, in a distance between the adversary bias model and a ground truth model;

wherein the ground truth model is trained on data comprising measurements of affective response and factors of events to which the measurements correspond.

20. The non-transitory computer-readable medium of claim 17, further comprising instructions defining the step of utilizing a function to make the determination;

wherein the function receives an input comprising one or more values, each indicative of at least one of the following statistics;

a statistic of the measurements contributed for the computation of a score from among the one or more of the scores, a statistic regarding the value of a score from among the one or more of the scores, a statistic regarding extent of disclosure of data regarding at least one user from among the users who contributed measurements for the computation of a score from among the one or more of the scores.