Social media takes a lot of heat for spreading disinformation, but Francesca Tripodi thinks we should look more closely at another fixture of our browsers: search engines. On this episode of "Civic Genius" we learn more about how the same forces that shape our social media diets also drive the information we find when we search online, and how we can boost our own media literacy.
Many assume misinformation requires special effects or technical sophistication. In reality, much of it requires only timing, intent, and a caption.
Recently, videos circulated online that appeared to show Los Angeles engulfed in chaos: Marines clashing with protesters, cars ablaze, pallets of bricks staged for violence. The implication was clear, the city had been overtaken by insurrectionists.
The reality was far more contained. Much of the footage was either old, unrelated, or entirely misrepresented. A photo from a Malaysian construction site became “evidence” of a Soros-backed plot. Even a years-old video of burning police cars resurfaced with a new, false label.
This is the oldest trick in the misinformation playbook, and we see it in almost every big breaking news cycle. Use what’s real to distort what’s true. Today, it’s happening faster, fooling more people, and making verification more critical than ever. In our newsroom, we call it the context gap: the space between what a video depicts and what a viewer is led to believe. It’s widening and with it, public trust is eroding.
Many assume misinformation requires special effects or technical sophistication. In reality, much of it requires only timing, intent, and a caption.
Take the example of footage of President Zelensky signing artillery shells. The video was genuine, filmed at a U.S. factory during a 2024 visit. It later resurfaced with captions falsely claiming the shells were destined for Israel. No editing was necessary. The clip looked real, because it was. The framing alone changed the meaning.
This is what makes miscontextualized video so effective. It exploits our instinct to trust what we can see. Viewers may never question the footage, let alone realize they’ve been misled. In some cases, the false framing is intentional, what we call disinformation. In others, the content is shared by people who believe it to be true, that’s misinformation. Whether the deception is deliberate or accidental, the impact is the same: a public less certain of what to trust.
The real danger is not just deception, it’s assumption. When authentic content is misused without warning, it reinforces false narratives while bypassing skepticism entirely. The result isn’t just confusion. It’s confidence in the wrong conclusion.
This kind of manipulation shapes perception in ways that are hard to reverse. Even when corrections are issued later, the original framing often sticks, driving division, fueling misinformation cycles, and distorting how people understand events around the world.
Countering that kind of influence requires more than detection software or fact-checking. It requires a shift in mindset: a habit of slowing down, asking questions, and interrogating the frame, not just the footage. In journalism, we call that constructive skepticism, and right now, we need more of it, beyond the newsroom.
Journalists are trained to question, verify, and triangulate. Verification is not simply a task, it is a mindset. In our newsroom, this means identifying the original upload, analyzing metadata, and confirming time and place through visual context.
Central to that process is skepticism, not as cynicism, but as discipline. Journalistic skepticism means refusing to take visual evidence at face value. It means asking who benefits, what might be missing just outside the frame, and whether a clip has appeared before under a different guise. It’s not about doubting everything. It’s about demanding enough proof to support trust. These practices may be out of reach for most people. Yet the principles behind them are not.
Skepticism, when grounded in evidence, is one of journalism’s most valuable tools. Applied more widely, it can help the public navigate the flood of video and imagery without falling into conspiracy or confusion.
Anyone can adopt a more careful, skeptical approach by asking a few basic questions: Does this look like what it claims to be? Is the source credible or recognizable? Have I seen this before in a different context? These simple checks do not require technical expertise. A moment of hesitation, scaled across a viewing public, could have changed how the wildfire or Zelensky clips were received and shared.
We do not need every viewer to become a verification expert. What we need is a shift in mindset: toward curiosity, caution, and context.
Journalists must continue to treat visual content as seriously as any other source, verifying not just whether something is real, but when and where it was captured, who posted it, and whether it is being presented truthfully.
However, the responsibility does not end there.
Platforms also have a role to play. When old or previously viral footage resurfaces during breaking news, platforms should add the necessary context proactively, not just rely on users to act as de facto fact-checkers. Many major platforms already have content detection systems in place to catch copyright infringements.
The public must also be equipped to pause, question, and seek clarity. Educators and institutions can help foster these habits of verification alongside broader digital access. One of the most overlooked tools in fighting misinformation is not software, but curriculum, training people to interpret the media landscape around them.
We live in an age when anyone can broadcast to the world, with algorithms built to capture and keep attention regardless of veracity or intent. The context gap is not narrowing. It is widening. Every swipe, share, and caption now plays a role in shaping how we see the world—and how others see it too. Slowing down to ask “why this, why now?” may be one of the most powerful tools we have.
James Law is the editor-in-chief at Storyful.
“Media and technology are essential to our democracy” is the first statement that appears on Free Press’ website, a suitable introduction to an organization dedicated to reshaping the media landscape. Founded in 2003, Free Press was established to empower people to have a voice in the powerful decisions that shape how media and technology operate in society. Over the years, the media industry has undergone dramatic shifts, with corporate consolidation swallowing up local TV stations, radio outlets, and newspapers. This has led to a decline in independent journalism, resulting in the loss of numerous jobs for reporters, editors, and producers across the country.
Due to the Telecommunications Act of 1996, a piece of legislation that allows anyone to enter the communications business, it was up to Free Press to closely monitor decisions shaping the media landscape when people’s right to connect and communicate is in danger.
Vanessa Maria Graber, a director of journalism and media education, leads the News Voices project, which connects local communities and the newsrooms that serve them through public engagement, advocacy campaigns, and collaborative projects.
Graber was able to work with Free Press on issues related to net neutrality, broadband access, and campaigns surrounding the Federal Communications Commission (FCC). Through the media justice movement, Free Press can focus on protecting free speech, press freedom, fighting hate and misinformation, and holding media and tech companies accountable. The media justice movement is based on the understanding of the intersectionalities between federal policy work and the influence of corporate media on journalism. It aims to challenge power structures and ensure the media reflects the needs of all communities.
With Graber, Free Press has worked on various projects, including Democracy Is.
They will be holding various series of briefings and training sessions for media professionals and communities to protect democracy. One of the most recent discussions focused on the recent elections and understanding how free and fair elections are supposed to work, as well as disinformation surrounding elections and its potential to undermine democracy.
Through educating the public and media professionals, Free Press emphasizes the crucial role media literacy plays in combating disinformation and gaining a better understanding of how technology affects our perception of content. Vulnerable communities are often the most targeted when it comes to disinformation. That’s why the educational work Free Press does can help people recognize what’s real and what’s not. One of their recent polls showed that Spanish speakers in the U.S. are even more likely to feel like they don’t have enough independent news sources to make informed decisions when it comes to voting.
It highlights why Free Press has been calling on social media platforms to take more action to prevent the spread of misinformation, particularly in languages such as Spanish.
They hold media institutions accountable by overseeing telecommunications in the United States and by collaborating with the FCC and FTC. They can monitor all policies and individuals who may potentially pose a risk to the public. Additionally, Free Press can shape regulations that are favorable to the public.
“ A very small number of people own the majority of media in this country and until that changes, we're still going to have a very unbalanced system where majority of people do not have power and access to equitable media, and that's why we have been for the last 20 years fighting for more access to media platforms and to create our media and for smaller groups of people who are not giant media corporations” Graber said.
Through research, advocacy, and activism, Free Press also hosts a media power collaborative that people can join to learn more about journalism policy and media justice issues.
One of their major wins was restoring funds to the New Jersey Civic Information Consortium, which Governor Murphy had proposed cutting to zero. With Free Press launching a campaign in New Jersey to advocate for the funds not to be cut and to be restored, they were able to secure their restoration for $2.5 million.
Graber is currently working on the future of a journalism team that is collaborating on a research project with a dozen newsrooms from across the country, which produce civic journalism, and is trying to understand how people are meeting the information needs of their communities. They will explore the types of innovations and engagement they have had or attempted to achieve.
This report will be published in the fall with the results of that research. In addition, the Free Press’ journalism team is working to pass legislation in states such as California, Illinois, Wisconsin, Massachusetts, and Pennsylvania to provide funding for local journalism projects, including those in New Jersey, through the Civic Information Bill.
Whether it’s privacy, surveillance, misinformation, or the future of local journalism, Free Press continues to fight for a media system that truly reflects and serves the people. Through activism, education, and policy work, they’re creating a space where everyone can have a voice in the media and in our democracy.
Nathaly Suquinagua is a bilingual multimedia journalist with a B.A. in Journalism and a minor in Dance from Temple University and a cohort member with the Fulcrum Fellowship.
The Fulcrum is committed to nurturing the next generation of journalists. To learn about the many NextGen initiatives we are leading, click HERE.
U.S. President Donald Trump talks to reporters from the Resolute Desk after signing an executive order to appoint the deputy administrator of the Federal Aviation Administration in the Oval Office at the White House on January 30, 2025 in Washington, DC.
Nvidia, now the largest corporation in the world, just received the green light from the Trump administration to resume sales of its H20 AI chips to China—marking a dramatic reversal from April’s export restrictions.
The H20 Chip and Its Limits
The H20 is a scaled-down version of Nvidia’s top-tier AI chips, specifically engineered to comply with U.S. export controls. It’s powerful enough to handle AI “inference” tasks but falls short of the benchmarks used to train cutting-edge models—making it legally exportable.
Policy Flip
In April, the administration clamped down, requiring special licenses for H20 exports over fears that even these reduced-performance chips might be leveraged for strategic military or surveillance purposes. Nvidia warned that the move could cost billions. Then came intensive lobbying efforts—including a high-profile dinner between Nvidia CEO Jensen Huang and President Trump at Mar-a-Lago. By July, the administration reversed course. Nvidia began filing applications to resume shipments with confidence that licenses would be granted.
Strategic Importance
China represents a substantial share of global demand for AI chips. This policy reversal carries enormous implications not only for Nvidia but for the broader question of technological rivalry and national security. As Huang put it, “Half the world’s AI researchers are in China”—making it clear that U.S. companies cannot afford to be absent from such a vital and dynamic market. The move could reshape the global AI supply chain and ease tensions in an intensifying semiconductor trade war.
The Reversal Rationale
At its core, this shift illustrates a tension between national security imperatives and economic priorities—and for now, economics appears to have won.
By July, the landscape shifted. Nvidia’s pledge to invest $500 billion in domestic AI infrastructure may have helped reframe the company as a strategic asset rather than a liability in the administration’s eyes.
A Delicate Balancing Act
This pivot reflects deeper fault lines in U.S. tech policy. On one side, national security hawks push for rigid restrictions to blunt China's AI momentum. On the other side, industry leaders warn that overregulation risks isolating American firms and ceding global influence. The chips didn’t change—but the political calculus did. The administration is betting that economic leverage and domestic investment can coexist with strategic caution. Skeptics, though, see only a temporary détente.
Rare Earths: The Hidden Chess Piece
Behind the scenes, China’s rare earth diplomacy may have helped tip the scales.
It’s difficult to prove direct causality, but the timing suggests a mutual de-escalation. Washington likely viewed China’s flexibility as an opening to stabilize supply chains and avoid driving Beijing toward self-sufficiency or alternative suppliers like Russia. Even Huang emphasized the importance of preserving U.S. influence in China’s AI ecosystem—an objective threatened by rising trade barriers.
Looking Ahead
While nothing is conclusive, it’s clear that rare earth policy is part of the larger chessboard—a subtle but significant backdrop to Nvidia’s reentry. What comes next—whether related to tariffs, TikTok, or the broader balance of power between the world’s two largest economies—is almost certain to reshape the global tech landscape.
Stay tuned.
David Nevins is co-publisher of The Fulcrum and co-founder and board chairman of the Bridge Alliance Education Fund.
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As we look back on 1776 after this July 4th holiday, it's a good opportunity to skip forward and predict what our forebears will think of us. When our descendants assess our policies, ideas, and culture, what will they see? What errors, born of myopia, inertia, or misplaced priorities, will they lay at our feet regarding today's revolutionary technology—artificial intelligence? From their vantage point, with AI's potential and perils laid bare, their evaluation will likely determine that we got at least ten things wrong.
One glaring failure will be our delay in embracing obviously superior AI-driven technologies like autonomous vehicles (AVs). Despite the clear safety benefits—tens of thousands of lives saved annually, reduced congestion, enhanced accessibility—we allowed a patchwork of outdated regulations, public apprehension, and corporate squabbling to keep these life-saving machines largely off our roads. The future will see our hesitation as a moral and economic misstep, favoring human error over demonstrated algorithmic superiority.
They will also criticize our stubborn refusal to integrate AI-based policy forecasting into our legislative processes. While AI models could have analyzed the long-term societal and economic impacts of proposed laws, helping us anticipate unintended consequences and optimize for human flourishing, we largely relied on antiquated, human-limited methods. This neglect meant our policies often lagged behind technological change, undermining the very notion of effective, responsive governance.
Crucially, they will likely question our failure to establish new intellectual property frameworks even after it became evident that current copyright and patent laws disproportionately favored incumbents and no longer served their intended purpose in the age of AI. Contemporary delay reinforced monopolies, rather than fostering a vibrant, decentralized ecosystem of innovation that truly benefited independent creators and inventors.
The future will equally lament our oversight in adjusting our schools and workforce development programs. They will see our delay in instituting widespread AI literacy for the general public as a critical blunder. We did not take the requisite steps to equip citizens with the fundamental understanding to navigate an AI-saturated world—to ensure they had access to the latest tools, discern AI-generated misinformation, and grok the foundational technical aspects of AI so that they could contribute to AI policy conversations. This lapse compromised our collective pursuit of an informed, participatory democracy. Compounding this, our sluggishness in adjusting reskilling and upskilling programs meant we left vast segments of the workforce vulnerable to displacement, rather than proactively empowering them with the skills to thrive alongside AI.
Perhaps more fundamentally, they will indict our failure to see data sharing as a social good. In an era where data is the new oil (or even the new water!), we allowed its collection and control to remain highly fragmented and proprietary. We did not establish robust, ethical frameworks for data cooperatives or public data trusts that could have fueled innovation for the common good—in healthcare, urban planning, and scientific research.
From an innovation perspective, the future will see our lack of sufficient investment in basic AI research as a monumental strategic error. Our focus skewed heavily towards optimizing existing models, rather than dedicating resources to more elementary inquiries that could uncover the next generation of transformative AI systems. This shortsightedness potentially limited humanity's long-term scientific and technological trajectory. This misallocation of resources will be underscored by our prioritization of Artificial General Intelligence (AGI) over the development and deployment of robust, beneficial generic AI applications. The speculative pursuit of an arbitrary, unspecified goal often overshadowed the immense, tangible benefits that could have been realized through focused development of practical, specialized AI solutions for pressing societal problems.
Finally, our descendants will not forgive our inadequate investment in public digital infrastructure and universal access. As AI became a foundational layer for economic opportunity and civic life, we allowed a significant digital divide—now an algorithmic abyss—to persist, denying equitable access to the very tools needed to participate in the new economy. From places like New Braunfels, Texas, to rural Virginia, the future will look at our massive, energy-hungry data centers and transmission lines and ask why we also showed a lack of adequate support for the communities disrupted by the immense physical requirements of AI development. These energy-intensive facilities placed environmental and social burdens on local populations without integrating them into the AI ecosystem's benefits.
As things stand, the ledger of future complaints against us concerning AI will be long. But this prophecy need not be our destiny. By confronting these potential failures now, by prioritizing sustained innovation and adaptive governance, we can still pivot towards a future where AI serves humanity's highest aspirations. The time for foresight and courageous action is now, before the future passes its final judgment.
Kevin Frazier is an AI Innovation and Law Fellow at Texas Law and Author of the Appleseed AI substack.
