HHS deploys AI robots to “inoculate” social media users against HPV vaccine “misinformation”

Researchers at the University of Pennsylvania (UPenn) have developed an artificial intelligence-powered weapon for the Department of Health and Human Services (HHS) that will allow the government to police the internet for “misinformation” about HPV (human papillomavirus), Wuhan coronavirus (COVID-19), and other “vaccines” on social media.

The team says its AI policing robot can be “swiftly and efficiently” adapted to address the spread of content online that negatively impacts Big Pharma’s vaccine sales pipeline. Using United States taxpayer dollars, UPenn researchers say they now have the technology at the ready to “inoculate” social media users against “misinformation” about childhood vaccines.

Through a Freedom of Information Act request, Children’s Health Defense (CHD) was able to procure grant documents showing that HHS is spending $4 million on an “Inoculate for HPV Vaccine” randomized controlled trial that began in April 2022 and will run through March 2027. The National Cancer Institute is also contributing cash to the project.

Headed by Melanie L. Kornides, an associate professor of nursing at UPenn, the AI robot development program aims to increase vaccine uptake across the U.S. population. It is also focused on developing “strategies to combat misinformation” in general.

Kornides and her cohort of digital health communication experts, software and program designers, social media analysts, and machine learning experts will run their social media “inoculation” experiment on the parents of 2,500 children between the ages of eight and 12. Data is being collected from platforms like YouTube, Twitter (now X), Facebook, and Instagram.

(Related: Did you know that HPV vaccines like Gardasil are triggering severe injuries and deaths in children?)

Using natural language processing to train AI in the weapon of censorship

Since most online talk about vaccines seems to take place on the above social media platforms, Kornides and her colleagues are using natural language processing to train their AI robot in how to identify “HPV misinformation,” also known as posts and comments that are critical or questioning of HPV vaccines.

Regardless of whether the information is true or false, Kornides and her team aim to remove all of it that could cause parents to not vaccinate their children. Study subjects will be exposed to three separate study arms with different types of messaging in order to deploy the “inoculation tool” to test whether or not it makes them “immune” to “misinformation.”

“A control group will get no particular messaging and two test groups will be exposed either to messaging designed to inoculate viewers against content critical of of HPV vaccines and content critical of anti-vaccine arguments,” CHD reports.

“The subjects will get ‘booster’ doses of messaging at three and six months after their first inoculation … If successful, the researchers wrote, this novel approach to combating health ‘misinformation’ can be used in ‘wide-scale social media campaigns’ addressing pandemics, childhood vaccination and other health issues.”

The researchers claim that their new AI robot is necessary because “misinformation” about HPV vaccines is one of the leading drivers behind so-called “vaccine hesitancy,” which they claim often comes from “anti-vaccine organizations.”

According to Mary Holland, co-author of “The HPV Vaccine on Trial: Seeking Justice for a Generation Betrayed,” what these UPenn researchers are trying to do is “a sign of weakness” within the public health industry.

“When you are censoring information, labeling it misinformation and smearing us, this is a sign that they’ve lost the science and are now in a verbal food fight,” Holland is quoted as saying. “It’s just a sign they are going to lose.”

More related news about the AI takeover of the internet and Big Pharma’s involvement in the heist can be found at Robots.news.

Sources for this article include:

ChildrensHealthDefense.org 1

ChildrensHealthDefense.org 2 ^[PDF]

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