# US 2023/0055092 A1 · Methods and systems for controlling pernicious lies in digital media

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- Number: US 2023/0055092 A1
- Document ID: US20230055092A1
- Status: Published application
- Kind: A1
- Application number: 17/793,857
- Filed: 2020-02-07
- Published: 2023-02-23
- Earliest claimed: 2019-05-03
- Applicants: Antique Books, Inc.
- Inventors: Robert H. Thibadeau, SR.
- Web page: https://patentgrep.com/patent/US20230055092A1

## CPC

- G06F 21/64: Protecting data integrity, e.g. using checksums, certificates or signatures
- G06Q 30/018: Certifying business or products
- G06Q 10/10: Office automation; Time management
- G06Q 30/0185: {Product, service or business identity fraud}
- G06Q 50/18: Legal services
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

Methods and systems for controlling pernicious lies in digital media are provided. A system server provides enforced moderated dialogue on the suspected lies in the form of a new type of private court. The system provides a way to identify and document lies, and gathering court participants. The system also provides a way of adjudicating the suspected lies through specific questions. Finally, the system provides a way of publishing verdicts. The system provides a method of incorporating Artificial Intelligence modules that can replace the specified human activities. One major advantage is that the present methods and systems are backed by science and history that provides an optimum, if nevertheless still imperfect, solution to the problem. It also provides a solution that can be near real time on the first appearance of an instance of lying deceit.

## Claims

### Claim 1

A method for controlling pernicious lies in digital media, the method comprising:
identifying a suspected lie in digital media;
determining a consensual truth of the suspected lie; and
distributing the consensual truth of the suspected lie.

### Claim 2 (depends on 1)

The method of claim 1 wherein the suspected lie comprises one or more of the group comprising: lies, misinformation, and disinformation in digital media.

### Claim 3 (depends on 2)

The method of claim 2 wherein at least one of the steps comprises a parallel manual and automated method which enables improving automation while sustaining auditability.

### Claim 4 (depends on 3)

The method of claim 3 wherein the parallel manual and automated method further enables using a sequence of manual events to train the automation.

### Claim 5 (depends on 4)

The method of claim 4 further comprising structuring dialogue to perform at least one of the steps.

### Claim 6 (depends on 5)

The method of claim 5 wherein structuring the dialogue is performed manually, automated, or a combination of manually and automated.

### Claim 7 (depends on 6)

The method of claim 6 further comprising:
assuring anonymity of humans participating in any of the steps.

### Claim 8

A computation node for controlling pernicious lies in digital media, the computation node comprising:
processing circuitry configured to:
identify a suspected lie in digital media;
determine a consensual truth of the suspected lie; and
distribute the consensual truth of the suspected lie.

### Claim 9 (depends on 8)

The computation node of claim 8 wherein the suspected lie comprises one or more of the group comprising: lies, misinformation, and disinformation in digital media.

### Claim 10 (depends on 9)

The computation node of claim 9 wherein at least one of the steps comprises a parallel manual and automated method which enables improving automation while sustaining auditability.

### Claim 11 (depends on 10)

The computation node of claim 10 wherein the parallel manual and automated method further enables using a sequence of manual events to train the automation.

### Claim 12 (depends on 11)

The computation node of claim 11 further configured to structure dialogue to perform at least one of the steps.

### Claim 13 (depends on 12)

The computation node of claim 12 wherein being configured to structure the dialogue is performed manually, automated, or a combination of manually and automated.

### Claim 14 (depends on 13)

The computation node of claim 13 further configured to:
assure anonymity of humans participating in any of the steps.

### Claim 15 (depends on 7)

A computation node for controlling pernicious lies in digital media, the computation node comprising:
processing circuitry configured to perform any of the steps of claim 7; and
power supply circuitry configured to supply power to the computation node.