Research & Commentary

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Modular Legislative Components for Better Algorithmic Feeds

Model Text /

Modular Legislative Components for Better Algorithmic Feeds

Modular legislative components published by the Knight-Georgetown Institute support lawmakers developing legislation that encourages better algorithmic feeds.

The Technical Feasibility of Divesting Google Chrome

Report /

The Technical Feasibility of Divesting Google Chrome

A new report by the Knight-Georgetown Institute shows how the US government’s proposed Google Chrome divestiture is technically feasible. The in-depth engineering assessment shows how an independent Chrome browser can thrive outside of Google and compete with Chrome’s major rivals.

Eric Rescorla, Alissa Cooper

New EU Guidelines Set to Strengthen Digital Safety for Children in Europe

Commentary /

New EU Guidelines Set to Strengthen Digital Safety for Children in Europe

New draft guidelines by the European Commission aim to shape a better and safer online environment for minors. The Knight-Georgetown Institute submitted comments to the European Commission on its guidelines for protecting minors online under the Digital Services Act – underscoring the need for an evidence-based approach that focuses on strengthening risk reviews, refining default account settings, and improving algorithmic recommender system design.

Peter Chapman, Zander Arnao

Systemic Risk Assessment under the Digital Services Act

Commentary /

Systemic Risk Assessment under the Digital Services Act

The EU’s Digital Services Act risk assessments and audits create the possibility of increased platform transparency and accountability, but the first round falls far short of realizing that potential. The first assessments and audits largely fail to sufficiently consider the role of platform design in relation to risk and lack specificity about the data, metrics, and methods used to evaluate risk and mitigation effectiveness. External analysis of risks and mitigations are further undermined by an ongoing lack of access to data.

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