Truth or consequences?
How to discern the differences between lies, truth, deep fakes and political dreams — all while being held captive by a delusional President and his projected fears
The impromptu memorial on Olney Street in Providence for Miya Brophy-Baermann, who was murdered in a drive-by shooting in 2021. A permanent city memorial square honoring the memory of Brophy-Baermann was installed on Thursday, July 23, 2026.
In the aftermath of the mass shooting at Brown University in December of 2025, safety has become a saleable political product.
But the “true” lesson of what actually solved the shooting was a homeless man who confronted the shooter, because the shooter was “out of place” in the neighborhood where the homeless person resided. An ironic twist.
It is easy to exploit our fears; it is much harder to build a sense of community through accurate storytelling. It requires patience; it asks for us to listen. It may require us to turn off our TVs and phones.
And, it requires us to ask questions: who was Miya Brophy-Baermann? How did she die? How was her case solved?
Editor’s Note: These are the facts, all true, as reported in news stories recently broadcast by WPRI.
Who, what, when and where: A city plaque creating a new memorial square honoring a local woman, Miya Brophy-Baermann, who was murdered in a drive-by shooting in August of 2021, was installed on Thursday, July 23, on what would have been Brophy-Baermann’s 29th birthday.
Why: The effort had been led by Providence City Councilor Sue AnderBois, now a candidate running for Lt. Governor. “Although her life was brief, Miya Brophy-Baermann made a meaningful impact on everyone around her, and her selflessness and genuine care for others will be forever remembered,” AnderBois wrote in the city council resolution that was enacted to create the new city memorial square at the corner of Olney and North Main streets.
“Every time I go visit her at the cemetery, I often look at the pole nearest to where she was actually shot,” her mother, Michelle, told reporters. “People put things on the pole to memorialize her, which I love, but those things get taken down. Having a permanent plaque or memorial for her, I know for many people it will just be a name,” she continued. “But for me, it will mean everything.”
The two men responsible for murdering Brophy-Baermann were arrested, prosecuted, and sentenced for their crime, under a task force led by the Attorney General Neronha’s office. A retrieved ghost gun was linked to the crime.
True, dat!
In matters of life and death, it is difficult to substitute fiction for facts. No amount of false statements or claims of“hoax” or “fraud” or “fake news” can distort the realty of what really happened, if we are willing to listen.
Still, we live in age of what author Shoshana Zuboff has aptly named “The Age of Surveillance Capitalism.”
Everyday we are subjected to the twists and turns of an endless stream of social media posts that attempt to distort our own experiences of life.
The news reports about the new city memorial square honoring the life of Miya Brophy Baermann provide us with the context about how to invest in truth-telling and in accurate narratives about our lives. Ian Knowles provides us with the story of why that has happened.
The post-industrial age that ended abruptly in the late 1980s has now been replaced by a cataclysmic shift into the “Information Age,” what Shoshana Zuboff has called “ The Age of Surveillance Capitalism.”
The primary sources of current information about the world have shifted away from newspapers, magazines, and books. Instead, today, most people get their information and develop their opinions based upon content from the internet that is accessed on their laptops or phones, and then conveyed by journalistic e-editions, podcasts, and social media platforms such as YouTube, Instagram, Snapchat, Reddit, Facebook, and X.
This shift gave us instant access to the world’s information flow that for a while was, usually, reliably true.
But technological advances have landed us in what the New York Times columnist Frank Bruni characterized as a “thoroughly polluted information ecosystem.”
It is clear that AI and its progeny, Generative AI, are the catalysts for a monumental upheaval of our world.
As Mo Gadat, former chief business officer of Google, said: "AI isn't coming — it's already here, changing everything.”
Multiple writers had predicted two trends in AI that could go off the charts this year – Deepfakes and Information Quality.
Deepfakes have joined the tech dystopian landscape that includes the negative aspects of social media, with its remarkable ability to generate and amplify antisocial behavior, porn, and the dark web.
Deepfakes (aka ‘synthetic media’ or ‘computer generated imagery’) are manipulated or fully synthetic media content, such as images, video, or audio, that portray something that does not exist in reality, creating fake events that have never occurred.
Nothing new under the sun.
There is nothing new about the manipulation of images. The doctoring of photographs began in the mid-1800s.
An iconic portrait of Abraham Lincoln was actually a composite of Lincoln’s head and the body of John C. Calhoun (vice-
Computer-Generated Imagery (CGI) has been used extensively by Hollywood since the 1970s.
In 1988, Photoshop became easily available and widely used.
The 1989 cover of TV Guide spliced the head of Oprah Winfrey onto the body of Ann Margaret (without the permission of either woman).
In 2004, a faked photo of John Kerry and Jane Fonda together at a 1971 anti-war rally was used to discredit Kerry in his presidential campaign against President George W. Bush.
But the technology was crude and could be easily detected. The present technology is very sophisticated, difficult to detect, and continues to evolve.
Deepfakes are typically created using AI (Artificial Intelligence) and ML (Machine Learning).
Machine Learning occurs when an algorithm is given examples and learns to produce output that resembles the examples it learned from.
The leap in machine learning occurred in 2014 when Ian Goodfellow, a Ph.D. student at the University of Montreal, created the Generative Adversarial Network (GAN).
Basically, this new kind of machine learning called ‘deep’ learning involves two algorithms.
For example, one algorithm is trained to produce the best fake replicas possible of real images.
The other model is then trained to detect when an image is fake and when it’s not. The two models iterate back and forth, each getting better at their respective task.
This process eventually ends up with a model that produces images that humans often cannot tell whether it is fake or not.
The video Deepfakes started to spread widely in 2017 when a Reddit user named ‘deepfakes’ created and shared videos that inserted the likeness of a celebrity into sexually explicit videos.
And, at around the same time, breakthroughs in deep learning resulted in AI-powered voice cloning that can replicate a person’s voice from just short audio samples.
The audio and video synthesis has converged into Identity Modeling —unified systems that capture how a person looks, moves, sounds, and speaks across contexts.
Siwei Lyu, a University of Buffalo computer scientist, predicts that very soon deepfakes will be able to respond to people in real time: that they will move beyond ‘this resembles person X’ to ‘this behaves like person X over time.’
The 2022 public release of the synthetic media model Stable Diffusion by stability.ai moved deepfake image generation from specialist labs to the general public.
Today, billions of people have access to easily downloaded software for creating deepfakes.
Advertisers tout their products with come-ons such as, “Create high-quality videos from text prompts,” “How to create your own personal deepfake,” and “Create seamless, realistic face swaps in seconds with AI-powered precision.” One site will, for $10, “generate a deep swap video using AI in minutes.”
The viral infection.
And when deepfake creations go viral, they spread rapidly and exponentially across the internet, like a biological virus.
The initial sexual imaging use of deepfakes by the Reddit user ‘deepfake’ has become widespread and horrific due to the damage that can be done to individuals, especially children.
A 2026 George Mason University study of kids aged 13-17 asked about their consensual and non-consensual usage and interactions with sexualized AI images.
The study found that over half of the participants had created and had received at least one image.
The reported victimization levels were substantial – over one-third reported having a non-consensual image created, and a third had at least one image non-consensually shared.
Social media is complicit.
A just released report from the Institute for Strategic Dialogue revealed that dominant social networks such as YouTube and X have directly referred millions of users to sites that will ‘nudify’ a person.
There has been some national response in the form of deepfake legislation that addresses non-consensual intimate imagery.
As of this spring, 46 states have enacted laws that prohibit non-consensual creation or distribution of sexually explicit deepfakes.
Last year, Rhode Island updated the state’s ‘revenge porn’ law to include deepfakes that put a person’s likeness onto sexually explicit material.
However, the deepfake bills of the individual states generally target individuals, but do not target generative AI platforms, payment processors, and the hosting services that enable deepfake production and distribution.
And last spring, Congress passed the TAKE IT DOWN Act which criminalizes the distribution of any non-consensual sexual deepfakes, and now requires online platforms to remove those particular deepfakes.
The art of political deception.
In this crucial election year, our most immediate concern should be the ability of the deepfake technology to widely and rapidly disseminate politically-
And, not only has it started, it has surged. The Governance and Responsible AI Lab at Purdue has catalogued more than 1,000 incidents of social media posts of political deepfakes last year and into this year.
The first known example of deepfake use in our national political campaigns occurred in 2024, just before the New Hampshire presidential primary.
Steven Kramer, a Democratic political consultant for a person running against Biden, released a fake AI-generated robocall of Biden’s voice telling voters not to vote in the primary.
In the 2025 New York City mayoral race, Zohran Mamdani was depicted by the Andrew Cuomo campaign as eating rice with his hands, and went on to show a black man in a keffiyeh shoplifting, a man abusing a woman, a sex trafficker, and a drug dealer, all showing their support for Mamdani.
In the Republican primary this May, the Kentucky MAGA PAC released a deepfake video of the incumbent Congressman Thomas Massie holding hands with Alexandria Ocasio-Cortez and Ilhan Omar, two of the left-wing congresswomen who comprise ‘the Squad.’
And, at the end of last year, a post on X from CA Gov. Gavin Newsom depicted President Trump, Pet
Persuasive fakes.
Political deepfakes can be persuasive, even if people know they aren’t real.
According to Valerie Wirtschafter of the Brookings Institution, “None of this, if you think about it, makes much sense or bears up to scrutiny. But people aren’t necessarily looking for things that are real; they are looking for things that represent their beliefs.”
The deepfakes are “just another layer added on in terms of this process of reinforcing, rather than revisiting, what people believe is true,” she said.
Deepfakes play into our human tendencies such as confirmation bias where we tend to believe information that is consistent with our biases.
They play into our human characteristic that we believe things if we hear them often enough, and we are more likely to act on bad information if it hits the right emotions in us.
There has been a tepid national response in the form of legislation to address the concern of election manipulation through deceptive political content.
As of this spring, 31 states have enacted laws regulating the use of deepfakes in political messaging,
As of this spring, 46 states have enacted laws that prohibit non-consensual creation or distribution of sexually explicit deepfakes.
Last year, Rhode Island updated the state’s ‘revenge porn’ law to include deepfakes that put a person’s likeness onto sexually explicit material.
However, the deepfake bills of the individual states generally target individuals, but do not target generative AI platforms, payment processors, and the hosting services that enable deepfake production and distribution.
Last spring, the R.I. General Assembly passed a law that prohibits deepfake ‘synthetic media’ within 90 days of an election unless there is an accompanying disclosure of the use of AI.
However, there have already been numerous challenges to the legislation.
In Hawaii and California, federal courts struck down the laws as unconstitutional violations of the First Amendment.
Presently, there is no federal statute that addresses political deepfakes.
The NO FAKES Act, which allows individuals to sue over the unauthorized use of their voice or visual likeness, was unanimously passed by the Senate Judiciary Committee last month and is awaiting a vote by the full Senate.
And the Protect Elections from Deceptive AI Act, which would prohibit and allow civil action against deepfakes against federal candidates, is currently pending in committee.
But, many of the laws only apply to political campaigns, and not to social media users who may easily spread politically-oriented deepfakes.
There is also research that suggest that disclaimers are not effective in preventing voters from being persuaded by false ads.
The fact is, as with negative hit ads, political deep fakes are inexpensive, effective, and are becoming normalized.
In addition to the creation of fake information, deepfakes can also undermine reality by allowing liars to claim that real content truth is an AI-generated fake. This is known as the ‘liar’s dividend.’
For example, a 1987 recording of Ronald Reagan trashing tariffs was cited last year by Canada during trade negotiations with the U.S.
President Trump immediately terminated the negotiations, and dismissed the 38-year-old historical footage, saying, “They cheated on a commercial. Ronald Reagan loved tariffs and they said he didn’t. And I guess it was AI or something. They cheated badly.”
Deepfakes have been just one of the tools used to bombard us with disinformation about elections, the press, the ‘deep state,’ the economy, immigrants, the justice system, science, public health, other nations, etc., since the 2020 presidential campaign.
The upcoming midterm elections this fall are the frontline for a critical convergence of power, politics, and technology.
Our nation’s election system is a primary disinformation target. The election denialism about the 2020 presidential election from the loser never stopped.
The disinformation foundation for the upcoming mid-term elections is on-going and accelerating, with the false allegations of widespread election fraud and election ‘interference’ that attempt to justify the need for his SAVE America Act.
The speedy creation and dissemination of deepfake disinformation make it an optimal tool for a well-timed October surprise, leaving no time to debunk the deception.
It is easy to predict that unacceptable election res
Based on history, we can expect that, should Democrats regain control of the House or Senate, some kind of national ‘emergency’ will be declared to attempt to void the result.
The short-term implications about which party controls Congress for the next two years are serious enough.
But the long-term implications for the future of our democracy are profound.
The first sentence of a recent study on Deepfakes and Democracy published by the Digital Society Project is: “Observers fear that deepfakes will shake the very foundations of democracy.”
As Nora Nahae Kim wrote in the Science and Technology Law Review, “The greatest danger isn’t just the creation of fake content — it’s a world where no content can be trusted. As deepfakes erode our collective ability to believe what we see and hear, the very foundation of democracy — an informed electorate — will be at risk.”
The objective of disinformation for any despot-wanna-be who craves absolute power and authority, and who cannot tolerate any opposition, is to instill such doubt and confusion in the people so that they simply don’t know what to believe, what is true, or whether objective reality is even possible.
Fiction reflects this reality on the TV series The Undeclared War, in which the editor of a disinformation news site whose goal is deep societal disruption in the UK, states that: “Whether the news is faked isn’t the point. The point is to get people used to the idea that everything’s a lie, that there is no truth. And, once they accept that, well, the biggest liar wins.”
Yuval Harai, in his book Nexus, drills down: “In a well-functioning democracy, citizens trust the results of elections, the decisions of courts, the reports of media outlets, and the findings of scientific disciplines because citizens believe these institutions are committed to the truth. Once people…lose trust in all these institutions, democracy collapses…”
Erosion of public trust.
The erosion of trust in our democratic processes and institutions, and our trust in each other, is well underway.
According to a Pew Research Center report issued in March, the United States is the only place surveyed where more adults describe the morality and ethics of others living in the country as bad (53 percent) than as good (47 percent).
The report found that only one in three Americans believe “most people can be trusted.” And, only one in five say that the federal government can be trusted to do the right thing.
An article this spring in a Canadian national magazine, The Walrus, was titled “The War Against Information is Over – The Lies Won.”
Have the lies won?
We were once able to assume that the old methods of recording audio and visual media were an accurate record. Will we ever be able to make that assumption again?
How do we make rational voting decisions if we cannot confidently distinguish truth from fiction?
Will the fear of deepfakes during the elections be enough to undermine trust in one of our core democratic practices and prompt people to simply disengage?
Is there a real existential threat to our democracy?
What can we, as individual citizens and as a nation, do?
Hany Farid is a UCal Berkely professor and considered the dean of digital forensics, and he gave his opinions in an interview published in February in the Scientific American.
He asserted that passing legislation such as the pending NO FAKES Act is “completely ineffective.”
He said that the solution is to rebuild the rules of liability, and that rather than merely going after content, we have to go after the infrastructure that makes digital deception cheap and profitable.
He specifically cited: “The couple of dozen companies out there that are hosting it; the Apple and Google stores; the Visa, MasterCard and PayPal systems that are enabling people to monetize it.”
He continued: “You have to go upstream. When you’ve got 1,000 cockroaches, you’ve got to go find the nest and burn it to the ground.”
In addition, he advised that another good protective step is what Australia did – ban social media for children younger than 16.
And for us as individuals, he urged that everybody needs to stay aware: “Public awareness doesn’t solve the problem, but it minimizes the impact, and it makes it less efficient for the bad guy.”
If we do not stay aware of and on guard against disinformation in our local and national election campaigns, we will be at the place where Hany Farid placed us, in a dialogue with a student as reported by the New York Times.
“So, the creation of deepfakes is easy, cheap, fast and reliable,” the student said. “Detection is costly and difficult.”
“Yes,” Farid said.
“Is there a solution in the near future, or are we just screwed?”
Farid paused and took a breath. He still believes there were solutions.
But first, he wanted people to understand what they were up against. “We’re pretty screwed,” he said.
Ian Knowles is a frequent contributor to ConvergenceRI.
