OBSERVABILITY Signal 624 2 feeds carried it
Historian Jill Lepore says Silicon Valley misreads science fiction and undermines democracy
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Historian Jill Lepore warns that private tech firms are assuming state functions, turning governance into algorithmic, corporate rule.
For engineers, this shift creates pressure to make algorithmic systems transparent and auditable, turning observability from a performance tool into a governance requirement. Without such visibility, the “rule by algorithms, corporations, machines” Lepore describes can operate without public consent or oversight.
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Lepore says tech companies are taking on governmental roles, leading to a form of tyranny driven by algorithms and corporate control.
She separates criticism of the corporate takeover from criticism of technology itself, emphasizing intent rather than the tech.
The trend is framed as a return to mystification, implying that lack of transparency and accountability is a core risk.
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Lepore’s upcoming book describes a growing pattern where private corporations replace democratic functions with algorithmic decision-making. She characterises this as a “return to tyranny and mystification” because the rule is exercised by machines and corporate logic rather than elected bodies. For engineers, the change means that software once built for private efficiency now sits at the core of public governance, raising new expectations for visibility and accountability.
Because the shift is driven by “well-intentioned” innovations aimed at efficiency and cheapness, the underlying code often lacks the audit trails required for democratic oversight. Engineers must therefore extend observability practices, logging, tracing, and metric collection, beyond performance to capture policy-relevant outcomes. This adds a layer of responsibility: systems must expose how decisions are made, not just whether they are fast or reliable.
Implementing this level of observability incurs tangible costs: additional instrumentation, data-retention policies, and compliance reviews that consume development time and resources. Teams will need to design dashboards and alerts that surface governance-critical signals, such as bias metrics or policy-violation events, which are not part of typical operational monitoring. The investment is justified only if the organization accepts the role of a de-facto public actor and is prepared to expose its internal logic to external scrutiny.
Observability can only mitigate the risk where the algorithms remain accessible and the corporate entity is willing to share internal data. When decisions are encapsulated in proprietary black-boxes or when consent is absent, as Lepore notes, “no one consented to that”, monitoring tools cannot reveal the underlying intent or correct undemocratic outcomes. In those contexts, engineering solutions reach their limits and broader political or legal interventions become necessary.
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