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Much of the debate about election integrity on social media focuses on harmful claims: what misinformation is spreading, where it’s appearing, how far it travelled, and whether platforms are doing enough to stop it. This approach understandably focuses attention on the content itself and the potential impact on democratic processes.

But the same misleading claim can behave very differently depending on where it appears. A recommendation-driven video feed distributes information differently from a social graph-based network, a private messaging service, or a livestreaming platform. Each gives its users different tools for creating, amplifying, contextualizing, monetizing, and responding to political information.

Election integrity is not only a content policy problem; it’s also a product design problem. Before asking what election-related content a platform should prohibit, election integrity teams should examine the architecture of the product itself. This includes how information moves, how users interact, where authority and credibility lie, and which affordances can be exploited.

A framework for understanding platform affordances

When assessing election integrity risks, it’s important to distinguish between a platform affordance and the harm that may result from its use. An affordance is a capability, opportunity, or constraint created by product design. Five dimensions are particularly relevant to election integrity: distribution, or how information reaches users; content; the formats a product enables; interaction, how users respond to and reshape content; identity, how credibility and accountability are established; and monetization, how attention can become financial support.

These features aren’t harmful by themselves. They shape the incentives, opportunities, and pathways through which harms can emerge. The same affordance can support legitimate political participation in one context while creating an avenue for manipulation in another. Election integrity teams should ask not just what content their policies prohibit, but how political information is created, distributed, and acted upon through the product. Those affordances don’t operate independently. Different combinations produce different platform architectures, concentrating risk, authority, and opportunities for intervention.Various platform architectures create different pathways for political information to spread and therefore require different approaches to election integrity. Three broad models illustrate how architecture redistributes election integrity risk, although many platforms combine elements of each. Recommendation systems can distribute content well beyond established follower networks, making the speed and scale of algorithmic amplification particularly important to detection and response. Social graph systems place greater weight on established accounts and relationships, making networks, influence, and trusted intermediaries more important. Open or federated systems distribute some governance functions across services or moderation layers, creating additional intervention points but also greater challenges for consistency and coordination.

None of these architectures is inherently more or less safe. They redistribute risk, authority, and responsibility. Election integrity programs need to be designed around the architecture they govern rather than assuming that interventions effective on one type of platform will transfer cleanly to another.

Affordances also interact with the political and institutional environments in which they sit. A recommendation system can help voters encounter accurate information about how to vote while also amplifying misleading procedural claims. Where election rules vary across jurisdictions, information that’s accurate in one place may be misleading in another. Local threats matter, too. Features that support participation or transparency may create different risks where candidates and election workers face elevated harassment or violence. Platform architecture shapes risk, but electoral rules, institutional trust, political norms, and local threats manifest it.

The 2024 US presidential election demonstrates how the same election integrity problem can be distributed through different platform architectures. On October 31, 2024, a video appearing to show a voting machine in Kentucky switching a vote from Donald Trump to Kamala Harris circulated on TikTok, where it reached 

. Election officials investigated and found no evidence of vote switching. The device printed a paper ballot that voters could review before casting their vote, and the voter ultimately submitted a ballot reflecting her intended selections after all. Officials described the episode as isolated and found no other reported problems with the county’s ballot marking devices.

As the video moved across platforms, different affordances shaped its reach and interpretation. On X, influential accounts supplied their own framing. Podcaster and pundit 

 reposted the clip and asked whether it showed a broken machine or election fraud, drawing millions of views. Versions also circulated on 

 in English and Spanish, including posts presenting the incident as evidence of broader election interference. By November 1, 2024, the allegation had reached Meta’s microblogging service, 

; with versions later appearing in Portuguese, Greek, German, Vietnamese, and French. The video remained the same, but recommendation systems, influential accounts, and social networks created distinct pathways through which users encountered and interpreted it.

The 2026 US election cycle also shows how new content production affordances can complicate election integrity. In Texas, Republican Senate candidate Ken Paxton released an 

 depicting Democratic opponent James Talarico reading and writing in a fictional “King James (Talarico) Bible.” The ad used an AI-created likeness of Talarico in a montage combining authentic remarks with missing context and words he had not used. A small disclaimer identified some video content as AI-generated, but the format demonstrates how campaigns can use generative tools to depict opponents saying or doing things that never occurred. The challenge is not only whether synthetic content is disclosed. Realistic looking content can also make authentic political speech harder to distinguish from fabricated media.

Separately, researchers linked an AI-generated disinformation video targeting Talarico to the 

 influence operation. The original X post attracted little attention until larger verified accounts amplified it 12 hours later. It then received more than 850,000 views. X removed the original, but copies continue to circulate online. Together, these cases illustrate two uses of the same content affordance – domestic political advertising and foreign influence — and demonstrate why election integrity programs must consider both how political content is manufactured and how distribution systems give it reach.

These examples reveal a tension in election integrity work: responses must be tailored to individual platforms, even as threats move between them. Different services can play complementary roles in amplification, coordination, fundraising, private communication, or the circulation of synthetic media. Content may originate in one environment, gain credibility through influential accounts in another, and then be translated, remixed, or moved into less visible spaces. The relevant reference point is often the broader information ecosystem rather than a single platform.

Cross-platform coordination doesn’t require uniform enforcement. Platforms can build shared awareness of emerging narratives, synthetic media, coordinated tactics, or threats while applying different interventions based on their architecture and policies. One service may focus on recommendation or distribution, another on influential accounts or network behavior, and another on provenance or labeling. Shared situational awareness can exist with platform specific thresholds and enforcement choices.

What election integrity programs can do differently

Election integrity programs should respond to these differences in platform architecture in three ways.

First, start with the product, not the policy. Before deciding what content to prohibit or how to enforce against it, trust and safety teams should map how political information moves through the platform. This includes how users discover content, interact with one another, establish credibility, and move between online communities. Policies should respond to the environment the product creates rather than assume the rules that have been developed elsewhere will necessarily transfer cleanly.

Second, build platform-specific threat models. Recommendation, social graph, and open or federated systems create different opportunities for amplification, interaction, coordination, and intervention. Effective election integrity planning should identify which affordances are most susceptible to misuse, how those vulnerabilities interact with the political context, and where the platform has meaningful opportunities to intervene.

Third, treat enforcement as one part of a larger system. Election integrity requires coordination across policy, product, detection, engineering, operations, communications, public policy, and external partnerships. Because election-related activity can move between services, platforms should, where appropriate, share information about emerging threats and tactics with other platforms, election authorities, researchers, and civil society. That coordination should improve collective awareness of the threat environment without assuming that every platform should respond in the same way.

The same principles should guide policymakers and researchers evaluating platform preparedness. The central question shouldn’t simply be, “What misinformation might appear here?” It should be: “What does this product make it unusually easy to do, and unusually difficult to prevent?”

After India’s Chief Justice flippantly referred to the nation’s unemployed youth as “cockroaches” in May 2026, it was not forgotten. The backlash led to the formation of the satirical 

 (CJP). It started as an Instagram page, posting reels and memes to raise awareness about government corruption and advocating for education reform. In demanding the resignation of India’s education minister over a paper leak, 

, and on July 25, the minister resigned. But CJP’s success in mobilizing Indians to speak up and organize is driven by its strong online presence. Their Instagram page 

 followers and counting—more than that of any individual political party in India. In the story of CJP’s rise, as 

 writes, Meta’s Instagram was not merely a digital record of the movement, “it was one of the principal engines of it.”

In the aftermath of a protest on July 20, the party’s Instagram account was 

 in India. “Cockroach Janta Party’s Instagram account has been taken down by Narendra Modi,” CJP founder Abhijeet Dipke 

, sharing a screenshot that merely stated that Instagram restricted the page following a “legal request.” Other CJP members 

 that their posts about the protests had been restricted. These legal requests are de facto orders, and they go far beyond content posted by CJP members: between March and July 2026, the government issued nearly 

, up from just 2,300 between October 2024-25. But now, the orders Meta receives are reportedly being 

The Indian government has primarily relied on content takedown orders to stifle online dissent. These orders are often premised on alleged violations of law, in this case, India’s 

, which set the boundaries of permissible online speech in the country. Meta has long complied with such orders, in part because failing to do so risks its safe harbor protections, which shield it from legal liability for what its users post. Now, amendments to India’s IT rules that took effect in February mandate that platforms comply with takedown orders 

. These orders are now issued through a government system called the 

 which allows India’s law enforcement agencies to request the immediate removal of content from digital platforms. To comply with this new three hour rule, Meta has reportedly connected its systems directly to Sahyog so that removal requests are 

, without review by Meta employees. In other words, the platform that helped propel CJP’s rise is now thwarting its influence—and the process is largely automated.

Despite the government’s best efforts to curtail CJP’s online and offline influence, the movement has only strengthened since its inception. On October 10, the CJP led 

 in Delhi, this time demanding the resignation of the Chief Election Commissioner over controversial 

 lose their right to vote. The government, in response, cancelled trains, closed metro stations, 

, including journalists. But the crackdown extended to platforms too. A week before the protest, on October 3, 

, a messaging service that works via Bluetooth and does not require internet connectivity, was 

 from the Google Play Store and Apple App Store in India.

Delhi Police detained protesters and journalists

, India’s Ministry of Electronics and Information Technology 

 asking the company to review its recommendation algorithms to ensure it does not result in “disproportionate exposure of users to a single or limited set of narratives,” and that Meta must provide “information or assistance” to law enforcement “with immediate effect.” The next day, 

, showing a woman clinging to a pole as police officers attempted to detain her was restricted on Instagram in India. This is not an isolated instance. Numerous Indian citizens have reported seeing their accounts blocked or posts removed. By mid-October, the Software Freedom Law Center—a digital rights group based in India—had documented 

 taken down in connection with the protests on its 

When Meta follows government orders to restrict content in India, they rarely tell users why. In cases examined by 

, Meta’s notifications cited only a “legal request” or using an “automated system,” without saying who ordered the restriction or why, and offered no option to appeal. But now, it seems Meta is using automation to proactively restrict content in India, and this time, without explicit government takedown orders. In the first half of 2026, Meta restricted over 

 pieces of content. Notably, this content was restricted based on Indian law, not for violating Meta’s own standards, and the content remained available outside India.

5.4 million is a staggering number. For context, in the previous six months between July and December 2025, around 

were restricted. By Meta’s own admission, a “

” of these restrictions were proactive and responsive to their legal obligations in India. Some of these obligations are especially vague and concerning. Content categories like “threats to the sovereignty and integrity of India” and “promoting enmity between groups” are notoriously hard to define, and the fact that Meta uses automated tools to make these judgements, exacerbates and brings to bear the depth of online censorship in India.

Takedown notices are far from transparent, especially because blocking orders under Section 69A of the IT Act are, by law, kept 

. But takedowns leave a trace, and in theory, can be challenged in a court of law. Meta’s move to proactive and automated restrictions, however, makes even this difficult. There may be no government order behind a restriction at all, and users are often told only that an “automated system” flagged their content under the IT rules.

The pattern is clear: stifle dissent on the streets via law enforcement and a sophisticated surveillance apparatus, and bully platforms to remove unfavorable content via takedown orders. But Meta’s move to automate both the processing of these orders and now to proactively restrict content using automation means that Meta is no longer just complying with the Indian state’s censorship, it's streamlining it.

, the European Commission can enforce general-purpose AI obligations under the AI Act through its AI Office, demanding documentation (

 putting EU safety teams inside frontier labs.

While access is necessary, the Office is enforcing against definitions it has little power over and that are not easily comparable. Compliance, frontier safety, and what “frontier” even means are still partly defined and acted upon according to 

providers’ own criteria and internal know-how

. More importantly, this makes the Office blind to a crucial kind of evidence. AI safety is not only about reporting technical findings or methods. It involves taking positions about 

 for safety-relevant features. These decisions shape a model’s safety profile. Yet, providers are not held accountable for them, nor are they compelled to disclose them as decisions. Access is the first step to achieve that.

The solution I propose is a public taxonomy that makes these choices visible without requiring providers to make them in a specific way. The possibility to contest these choices in fact depends on them being visible 

non-technical choices. Otherwise, these judgments give external actors nothing to push against, and no basis for attributing responsibility when something goes wrong.

How judgment calls pass as technical and necessary choices

, a voluntary instrument providers sign to create a presumption of compliance with Articles 

. It sets out important commitments, naming the steps of development where disclosure is owed. But it does not say what counts as relevant and how it is described and leaves that definition to providers.

A provider can meet requirements while disclosing little, or disclose a great deal because it chooses to, in which case the disclosure could align with safety purposes only contingently. Some sections of the Code do demand justification of, for instance, risk-tier acceptance criteria in the Safety and Security chapter. But they still leave space for discretion over what counts as an adequate justification and how much to justify. Other non-technical choices across models’ lifecycles remain untraced and unsystematized.

Three instances show what this means: one where a value choice reads as a method, one where a concept is contested and cannot be settled by better science, and one of corporate discretion.

The first instance can be found in OpenAI’s recent 

. Astra is trained to refuse dangerous requests. If, when evaluated for what it 

do, it refuses to pursue a user request, the refusal is 

 ambiguous about what this means. OpenAI 

, §10.1.1), treating the model as capable and simply not wanting to help whenever it declines. This is a choice about which error to prefer, whether over-attributing capability or missing it. It is defensible, and it is disclosed to some extent. Nothing in the system card differentiates this choice from a technical one,

The second example appears in the same card (

, §9), reporting that monitoring Astra’s reasoning became harder and less reliable. OpenAI deployed anyway, treating the model’s underlying alignment as the main safeguard and claiming they will not accept further loss of monitorability. More evaluators or better science will not automatically bridge this gap. Extra experts still grade against standards set by providers, and while better methods close the gap where a science is immature, no amount of methodological maturity alone settles what “harmful” or “good evaluation” mean.

The third case is about high-level corporate decisions. Anthropic 

did not give the UK AISI pre-release access

 committed the company to embedded third-party evaluators just a few days later. Either decision could have been made in good faith, commercial judgment, external pressures, or all combined. We might just be lucky that this happens to point in a safety-promoting direction. Good faith and other non-safety incentives ultimately end up doing work regulators ought to be doing.

These decisions may all be defensible. But a model’s safety profile is built out of dozens of such calls, and a generic instruction to disclose acceptability criteria reaches none of them. Regulators must outline 

they want justification to happen, even if they do not set the standard for what justification should look like.

Asking regulators to set fixed safety standards is overly optimistic and may be the 

 given how fast the technology moves. The next Code revision should instead make value-laden decisions disclosable and comparable across time and providers, through a regulator-owned taxonomy of the steps where non-technical judgment calls can happen across a model’s lifecycle. This would let the Office track patterns across providers (which positions cluster, which labs are consistent outliers and why), and challenge the choices behind them. Importantly, judgment that exists only as informal practice inside a handful of labs becomes a shared and readable record, so the Office stops depending on providers' word for where the relevant information sits.

First, providers locate their model within a public taxonomy they did not create.

The Office maintains a public taxonomy of the steps across a model’s lifecycle where value-laden choices are inevitable. This could follow the Code’s existing stages, from risk identification through post-market monitoring. A first version need not wait for providers: all three examples above come from public documents. Today the Code asks providers to justify conduct and criteria they set themselves, so that providers can define what decisions are worth disclosing, at what level, and for what purpose. Under the taxonomy, they would instead locate each decision, and the principles behind it, in a systematized and more fine-grained structure they did not establish. This reduces the Office’s dependence on providers. If we do not know what decisions they make at which step, we cannot enforce against them.

Second, the checking can and should be outsourced. Independent accredited bodies can be delegated to audit whether the provider’s reported placement is honest. This is a genuine measurement against a fixed public reference. Evaluators never decide which position is correct, only whether the evidence produced matches declared positions.

Third, the taxonomy records positions rather than grading them and bites on honesty

The taxonomy does not aggregate judgments into single statements that a model is safe, and providers can adopt different principles across steps while reporting honestly. Enforcement would at first bite on honest judgment rather than on verdict to encourage honesty. What can be adjudicated is whether the provider placed its model faithfully, and said where its judgment sat when more than one position was available.

Fourth, the framework and the placements stay contestable. Where a disclosed position and evidence come apart, providers can be investigated under the AI Act. The Office remains responsible for filling gaps in the taxonomy. Because the structure is common across frontier labs, positions also become comparable over time. Finally, making these choices legible and comparable allows regulators to assess where the frontier of AI 

lies and how much it really tracks the frontier of capabilities.

The Office does not need more substantial powers to enforce this. The next Code of Practice revision could define the map with the help of the Scientific Panel (

) on the basis of the Code’s demonstrated shortcomings. 

 covers documentation requests, which could be structured against this new taxonomy. Under 

, the Office evaluations could test placements against the taxonomy and misplacement or missing entry could count as incorrect or misleading information under 

Placements would be public; the evidence behind them, which may be commercially or security-sensitive, could go through the confidential channels the Office already provides. This sharpens enforcement, as outliers become visible. With time, the Office could further complement this with its own guidelines about general value-laden trade-offs, such as prioritizing privacy in some domains.

The taxonomy is ultimately a middle ground between standardizing frontier safety and industry self-regulation and could reduce the Office’s epistemic dependence on frontier labs. Even embedded evaluators, with access to everything, would still need to know which decisions to look at. The Office could target its own evaluations at unusual steps, structure documentation requests more precisely, and trace which judgment call mattered when something goes wrong. Without such a structure, nothing breaks the cycle. Providers hold control over what is safety-relevant and how it is described. Described as technical decisions, judgments draw no scrutiny, and without scrutiny, no one can describe them otherwise.

Audio of this conversation is available via your favorite podcast service.

On October 6, the Privacy Center at Georgetown Law School hosted an event titled 

Life After Data: The Conference on De-datafication

. The prompt for the event asked us to, "Imagine a future in which digital data is no longer the currency mediating all of our social, economic, and political systems, structures and practices. How might we get there from here?" One of the topics offered as a provocation concerned the internet itself and whether it might make sense now or at some point in the future to abandon it.

Now, there are many communities I travel in where the knee-jerk reaction would be to consider that suggestion a heresy. And yet there are many others where some flavor of the idea has been discussed before. There's a great deal of writing and thought that considers the idea of the personal choice to abandon the internet or some of the platforms that have come to define it. Logging off, digital minimalism, refusal to participate in social media. There are ideas about retreat to smaller or more private spaces from the small web and closed networks to group chats. There's nearly an entire internet's worth of content devoted to the idea of rebuilding the internet on protocols, federation, public digital infrastructure on community networks.

There are ideas on how to effect a political or an economic rupture that would return the internet to some prior state. These use terms like 

. And there are notions about alternative infrastructures from 

. There are many death and decay diagnoses from 

. These diagnoses seem particularly compelling given the increasingly believable or perhaps likely prospect that AI agents and other automata may overrun the internet and thus leave little room for people anyway. 

To get reader ideas on this subject, I put a call in the 

 for two-minute voice memos from readers, inviting riffs on the topic generally, or responses to one of these questions:

What would have to break, or be built, before people would be willing to leave today's internet behind?

Who would lead such an effort, and who might stand in its way?

What from today’s internet and the platforms that define it is worth saving, and what should be left behind?

What would a better, healthier, more sustainable and pro-democratic network look like, and how would we build it?

What you'll hear next is a selection of the responses we received.

All right, this is Rushkoff. What am I supposed to say? Hey, I'm 

 and I write books about media, technology and society. The prompt actually reminds me of a moment way back when, early, early, early internet when the internet wasn't even the net yet. It was this place where weird people from the counterculture went to have strange discussions.

And I got a call from, I'm pretty sure it was Citibank, asking if I was interested in taking a job, a zillion dollar job to help the bank go online. They wanted to do online banking. "Can you help us get Citibank online?" And I remember saying to the guy on the phone, "Are you fucking crazy? You're going to take a bank online? Do you know what the internet is? Do you know what we are on there? Nobody's themselves. We're like dogs and cats and other things and the internet's not safe for that. Every computer is so promiscuous. Every computer is saying the whole time, 'Hi, hi, I'm me, what do you have for me? Here's what I have for you.'" That you can't put a bank there. But they did. They put the banks there and then everything else followed, the whole straight world of money and security and all that stuff went online. And what I'm thinking now is they're all online, they're all there. The whole straight, horrible world we were escaping is online.

So let's us go offline and take back the real world from them. So that's my thing. Leave it. Just leave it be and do democracy, do the pro-democratic healthy world, just do that here.

. So what would have to break or build before people would be willing to leave behind today's internet? And really, I think that it's our egos. I think that so many of us have spent so much time in these places and have become VERY IMPORTANT PEOPLE and that has created ... It's done something to our brains. And I think that we have to kill that in order for us to leave this entire thing.

Who would lead that? I really think it's got to be the next generation. They have a completely different relationship with the internet, especially having grown up with it and having been on it since a very, very, very early age and don't have the same sort of connection to ego and sort of connection to self that a lot of us who didn't have that very early connection or a lot of folks who created these technologies simply because they had no connection with self and were very unpopular in middle school.

What would a better, healthier, more sustainable and pro-democratic network look like and how would we build it? Some of us tried to do this, so we know that it's possible to do something that is not what is currently there. And so what does it look like? It looks safer. It looks happier. It looks healthier. And how do we build it? Again, I don't know that we do. I think that it might be time to pass on the baton, take our lessons that we have learned and give them to folks who don't have those same egos, the same desires for clout that has developed in so many folks, especially in the tech policy space.

And so then what from today's internet and the platforms is worth saving? It's always the people. The people are the very, very best thing about society, about the internet. It is the humans. It is the laughter. It is the joy. It is the imagination. It is the ability and the alchemy of taking some of the most horrific things happening on this planet in the form of news and turning them into purely jokes and shits and giggles. And that's a humanity that I think is worth fighting for. So those are my thoughts. Thanks. Bye.

Hi, I'm Bridget Todd. I'm the host of iHeartRadio's award-winning tech podcast, 

Love at First Prompt: AI and the Future of Intimacy

Berkman Klein Center for Internet & Society

 affiliate. And when I think about abandoning the internet, my first thought is that I actually do not want to abandon it, but I do kind of want to abandon this version of it because so much of what makes the internet beautiful to me, I think is still worth saving. The ability to find your people, to find your folks, the ability to make something and share it with the world without asking for permission, and then actually have people find it and connect with it and love it. The ability to learn from somebody that you might not have met otherwise, to build communities that aren't limited by geography or other limitations.

So what I want to leave behind is the bargain that we've been told is necessary to have all of that, that in order to participate online, we have to be constantly tracked, manipulated, quantified, profiled, and ultimately turned into data for someone else to profit off of. That is what I want to leave behind. And now with AI, that bargain, it seems kind of even more extreme. Our conversations, our labor, our creative work, our relationships, even our most intimate and human and sensitive interactions can just become more raw material for systems that we don't control. So to me, the real question is what would make people realize that the internet that we have now is not inevitable? I would like an internet where everyone can participate fully and equally without being legible to a corporation at all times, where privacy doesn't feel like some kind of a luxury item that you have to earn by opting out of 20 different things, where being a person online does not automatically mean becoming a data point, a target or training material. So I want an internet that asks less of us in exchange for being there.

, senior resident fellow. I don't think that our conversation should focus on whether we need to leave the internet. I don't believe we need to leave the internet. The internet is, for me, the most human technology. There's something profoundly human with this idea of still being autonomous and act autonomously yet participate in something that is truly global.

But I do think that we need to save and remind ourselves of what the internet actually was originally built for and try to resist anything that seeks to change its properties and its characters. And by that, I mean concentration that platforms have created. I mean the idea that they can measure our behaviors and define how we operate within the internet. Decentralization of course is not panacea and it shouldn't be viewed as that, but also the idea that currently we're operating within closed gardens and our internet experience is defined by privatized networks that offer efficiency but take away the agency that the internet originally gave to users is something that we need to go back to. Agency is the currency of the internet. It is also the thing that distinguishes the internet from AI. So we should not allow our agency to disappear simply because some big companies have decided that it is better for users to become just consumers and not contributors to the internet.

My name is Caddie Alford and I'm associate professor of rhetoric at 

 and saw Justin's talk, snagged a couple of the printouts and decided to pose these questions to my digital rhetoric class. There's about 22 students ranging in age from about 19 to 31, many advanced English majors, but also mass communication majors, psychology, criminal justice, film production, et cetera. Right from the get-go, some of these questions were questioned. The ideal seemed kind of unrealistic to many students and they were wary of the hint of utopia because they understand where those rhetorics and promises have taken us and how you can tell a history of the internet from looking at those promises. So they don't see a mass exodus as likely.

In terms of who would lead an effort to abandon the internet, again, they had issues with the question. We're not leaving and a lot of them see the material constraints in trying to leave. But it was interesting to see a lot of their responses assumed that whoever would lead this effort would be kind of random and would be kind of unforeseen, that they would kind of emerge and all of a sudden create a mobilizing toward some other space or some other paradigm. In the blueprint model, they were thinking about the next network being owned by some kind of independent unaffiliated group. They thought about fanbases and equally distributed shares as well as periodic crowdfunding, but they also just kind of assumed there would be silent donors involved.

In terms of what they never want to see from some other model of the internet, there was a laundry list. They don't want to see users' data stored. They don't want to see political funding. They hate parasociality being rewarded and incentivized as well as just artificial intelligence problems, surveillance. They hate popups, they hate subscription models, pay-to-play.

In terms of what's standing in the way, it just came down to billionaires for them and paid off politicians as well as shareholders. Then the tipping point as the last set of questions, what would have to break or be built? Students said they'll leave the internet once they really feel like it is completely AI-generated and it is completely Dead Internet Theory come to life. Someone mentioned when the all-in-one super app finally gets built, they also talked about how they feel like they can opt out of certain types of surveillance now, but if they feel like they can't in the future, that'll be kind of a deal breaker as well as they don't want to be asked for ID or verification in terms of age. They stay because they have a hard time keeping track and staying in touch with old friends, but also niche interests. I have a lot of students who are in hobbyist communities and in communities with small artists. So yeah, that's what 22 young folks are thinking about.

Thanks to Caddie Alford for sharing those thoughts from her students at Virginia Commonwealth University. Next we'll hear from Janet Vertesi, 

an associate professor of sociology at Princeton

So here's the thing, an alternative internet is already here. People are already working on this. There's communities like the Veilid organization that are literally building an alternative underlayer for the internet in opposition to TCP/IP. There are people who are building alternative tech, decentralized tools, federated tools, operating systems that don't have Google or Apple in them. We already have all of the technology we need. What we need is more attention on those alternatives and more financing for those alternatives and more support for those alternatives.

So in terms of what we need for people to move over, we need to shift the idea of what constitutes innovation. Currently, we've decided that innovation means that a bunch of people who used to make a lot of money on Wall Street who couldn't make that money anymore because the Ponzi scheme of Bernie Madoff shut down and they weren't allowed to trade credit default swaps, moved over to Silicon Valley and started betting like horses on young men with hoodies. And the whole thing that came out of that was this massive swirling "innovation economy" in which the creation of "value" was associated with some kind of pie in the sky idea of a technology that would eventually come and in the meanwhile grow and grow investment funds at the same time. That's not the same thing as building tools that are valuable for people or tools that create the internet that we want. But what they've done is run completely amok and created an information ecosystem and an innovation ecosystem that are completely distorted.

So in terms of what we need in order to have an alternative internet, we already have what we need. We're already building those tools, people in the hacking community and the making community, people in the EU where technologies are already being shaped by regulatory frameworks like the 

 or the data privacy regulations in Europe, they're already building the tools for the internet that we need and the internet that we want. What needs to change is the way that we stimulate innovation, where we see innovation happening, where we put our support, particularly in small communities and open source communities and small businesses, in any kind of organization that's taking on the mega eight billion ton gorilla that is Big Tech. And once we can sort that out, then I think we'll have more of the internet that we want.

. If we imagine a future in which data is unlinked from profit, then we have to dismantle the entire business of buying and selling data. This means that things like targeted advertising would have to change, data brokers would have to be abolished, and the ability of the government to buy data that it can't legally collect would have to be curbed. The problem is that most of the social media that we have today depends on this kind of business. So we would need to be looking for other forms of social media or online communication technologies that weren't profit-driven. This means they might be run by communities. Every college used to have some kind of internal electronic bulletin board and those have mostly been replaced by Facebook, which has really meant a lot of loss of community overall. Can we imagine ones that were funded as public technologies, technologies that allowed for community engagement?

The problem is that in order for any online communication technology to work, for it to really create community and bring people together, it has to be heavily moderated to avoid harassment, hate, disinformation, and somebody has to pay for that. So I think that the current social platforms would stand in this way. I think this current infrastructures would stand in the way. There's been a sort of capture of a lot of online communication by telcos, ISPs, things like that. What I would like to see is something that is more user-centered, that is built from the ground up and that is not janky. We do have things like that now, but they tend to be small or they don't tend to be very fun to use. We need technologies that are really fun to use and bring value to people's lives, but are also beautifully designed and community-centered and emphasize bringing people together rather than tearing people apart.

Hello, Justin. This is Liz Orembo, lead for international and regional engagement at 

 and speaking from Nairobi. I still keep fantasizing about the idea of an 

. Maybe at that time, the political climate was not as high because we didn't realize what the internet had to offer politically and economically, but it did give us access to knowledge, markets, independent media, and a voice in democracy. And I think this openness is one thing that has to stay. But today with everything running on data and AI, openness has to go deeper. It has to be a new environment. I don't think that the current power distribution frameworks are enough to tackle what the information environment will look like even in the next five years. So during the campaigns for open internet, there was a lot of effort going into internet access and private sector government-built connectivity infrastructure to connect people, and we just need to build this data and AI infrastructure the same way so that everyone can keep innovating.

Now on top of this, I'm looking at algorithms as lenses through which people view the data sphere. People need to have a choice. People need to have a choice there in the market, but also need to also custom make theirs. I'll also say that with a caveat, because someone will choose one that has harms. But right now the platforms that we are using pick the lenses for us. Imagine picking your own, you install it like an app and you choose it on your social media, one, a lens for your personal life, a lens for your community, one for management of community resources, even at a national level, democratic decisions. And for public life, they have to be public interest algorithms, explainable, transparent, and accountable.

Of course, the choice only works if people understand what they're choosing. So AI literacy is our first line of defense. But being honest also, the harms that we are seeing growing online now, they are because of deeper societal problems, inequality, corruption, poverty, race to power and to accumulate resources and also authoritarianism. Those same forces will stand in the way along with the platforms and data brokers profiteering from today's internet model. So we need institutions built for this new information age.

Who leads? Philanthropies will have to start us on that one, funding AI literacy in communities and grassroots groups building their own AI, connecting to their own records, adapting small and open model languages for their community and testing whether it actually works for them. And I think this is an internet I'd be happy to move to.

 in Brussels. I think if there's one thing that I would draw attention to in transitioning from the current internet to the next one, it's for lack of a simpler term, what I would call 

. If you look at the web, if you look at the old documents like 

The Architecture of the World Wide Web, Volume One

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