Recent court decisions have made one thing clear: design choices can create liability.
In late March, juries in New Mexico and California found Meta, and in California also Google/YouTube, liable in cases focused on child safety and the role of platform design in amplifying harm. Both companies say they will appeal.
For those of us who have spent years advocating for upstream, systems-focused intervention, including at Council on Tech and Social Cohesion, this is historic. It reinforces the core premise behind prosocial tech design: harms are not the result of ‘bad people’ posting ‘bad content’. They are shaped by the architecture of the digital platform—what it amplifies, nudges and rewards.
This logic sits at the heart of the Council on Tech and Social Cohesion’s Blueprint on Prosocial Tech Design Governance: platforms are not neutral intermediaries. Their design systems—recommender systems, monetization models, metrics, UX—form an interconnected system that shapes behavior at scale.
But the verdicts do not settle the debate.
They shift it. If design is governable, then the real question is not whether—but how.
Which design choices should be governed, by what standards, and toward what outcomes? And how to ensure, as Mike Masnick cautions, that our efforts to ensure ‘design liability’ don’t slide into zones of reasonable editorial or product decision-making.
So what should we be paying attention to now?
First, recommender systems.
Not “algorithms” in the abstract, but the ranking, recommendation, and feed architectures that determine what is surfaced, repeated, and connected.
These systems are now widely recognized as high-impact infrastructure. Under the EU’s Digital Services Act, platforms are already required to offer non-profiling feed options, explain how recommendations work, and offer meaningful user controls.
We are seeing active experimentation by most of the major digital platforms. From TikTok’s topic sliders, to YouTube’s custom feed prompts, to Instagram’s evolving topic controls, to Bluesky’s marketplace of user-selectable feeds—there is a shift underway from passive consumption to partial user agency.
Second, monetization.
If recommender systems shape visibility, monetization systems shape what kinds of visibility become profitable.
Investigations like those by Maldita.es show how AI-generated content is produced not primarily for ideology, but for revenue: to grow audiences, qualify for platform rewards, or sell reach. Similarly, BBC recently exposed polarizing AI-generated - and monetized - posts around the Iran - United States war.
As Victoire Rio of What to Fix has argued, monetization is a core driver of user behaviors. And yet, recent analysis of DSA risk assessments shows that platforms are still not meaningfully accounting for monetization-related risks—even where financial incentives directly reward harmful content and actors.
The Blueprint makes this explicit: engagement-based metrics misalign with the public interest. If harmful or polarizing content is more easily monetized, it will scale—regardless of moderation efforts downstream.
Design governance, in that sense, is also incentive governance.
Third, AI chatbots and attachment.
If the first design battle before the juries was about addiction, the next may be about attachment to AI systems - particularly chatbots. The sychophantic and anthropomorphic designs feel ‘helpful’, but they remove the friction through which people develop empathy, boundary-setting, and the ability to navigate disagreement.
The USC Neely Center for Ethical Leadership and Decision Making’s Social AI Design Code treats these as design constraints, not side effects—calling for limits on emotionally expressive systems, especially for minors, and for AI to reinforce human relationships rather than replace them.
The Center for Humane Technology points to this risk directly: design choices that prioritize seamless, always-positive interaction can erode the social capacities that underpin trust and cohesion.
Fourth, polarization as a metric.
One of the most important shifts underway is that we can now begin to measure these effects of different design choices.
Tools like the “polarization footprint,” developed by Build Up, offer a metric to measure how much affective polarization users experience across different platforms. More and more experiments point to how ranking and recommender choices can increase or decrease levels of affective polarization (Picardi, 2025, and Stray, 2026)
This reframes polarization, not as a content problem but as a design externality which can be both measured and governed—through audits, incentives, and regulatory frameworks like the DSA’s systemic risk assessments.
Finally, interoperability.
If users and creators cannot leave a digital platform without losing their networks, audiences, or history, then the efforts described above risk making dominant systems marginally safer while leaving their structural power intact.
The Blueprint points to interoperability, portability, and middleware as a critical piece of tackling the incentives of the business models. These measures enable users to move to differently designed platforms—with alternative norms, incentives, or governance models—without losing their social graph or accumulated presence. They also allow for third-party middleware to sit between users and platforms, offering independent curation, filtering, and ranking systems that can better reflect user values.
This is increasingly understood not just as a platform feature, but as a question of digital infrastructure. As the Project Liberty Institute and Global Solutions Initiative note in their Digital Infrastructure Solutions to Empower Citizens: A Toolkit for Policymakers, interoperability depends on shared standards, open protocols, and governance choices that allow systems to connect while preserving user control. Interoperability is not just about competition, but also about data agency—ensuring that users can carry their identity, relationships, and preferences across systems, and shape the environments they inhabit.
The significance of these US jury verdicts is not only proving the harm of the platform design, but opening the path for design itself to be treated as a legitimate site of governance.
The next phase of digital governance needs to focus on direction.
governing recommender systems as civic infrastructure
aligning monetization with public-interest outcomes
anticipating attachment-related risks in AI design
measuring and mitigating polarization as a systemic outcome
enabling interoperability so users are not locked into dominant systems
Design still matters—but what we choose to change next will shape what follows.
Lena Slachmuijlder is Senior Advisor for digital peacebuilding at Search for Common Ground, a Practitioner Fellow at the USC Neely Center, and Co-chair of the Council on Tech and Social Cohesion.
The court decisions establishing that design choices create liability shifts the whole conversation from 'should' to 'how' to govern algorithm-driven social media. The polarization footprint metric and the growing experimentation with user feed controls are good signs that alternatives to engagement-only optimization are becoming real rather than theoretical.
I've been coming at the same problem from the other end. My focus is on what sustained exposure to engagement-optimized environments does to the cognitive capacities users bring to the feed; shrinking attention, empathy, and the ability to tolerate ambiguity and change their minds.