Dark Metrics: Illuminating the Negative Impact of Digital Health Design

Key Insights

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  Traditional product metrics, like the Google HEART framework, often miss broader impacts on users, focusing narrowly on product success rather than holistic well-being.

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  Dark Metrics is a framework designed to measure negative unintended effects in digital health across four dimensions: disempowerment, exclusion, addiction, and distraction.

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  Disempowerment occurs when technology removes users’ autonomy, such as opaque black-box AI systems that undermine clinician or patient decision-making.

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  Exclusion can be subtle, as algorithms that proxy biased variables like healthcare cost can reproduce racial disparities without explicit intent.

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  Racial equity in design can be assessed using heuristics or rubrics co-created by diverse teams, as demonstrated by Raven’s IBM colleagues Dre Barbara, Sherees Cooper, and Morgan Foreman.

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  Addiction to technology is an overused concept in consumer health, but distinguishing healthy from excessive use requires linking engagement data to well-being measures.

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  Distraction from core tasks is common in clinical environments when new tech disrupts workflows, evidenced by studies with ER staff and clinical trial recruitment tools.

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  Ethics frameworks like the Institute for the Future’s Ethical OS help anticipate risks like surveillance, bias, and data control, which inform Dark Metrics design principles.

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  Engaging diverse stakeholders and including co-creation early in research helps uncover biases and unintended consequences before launch.

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  Addressing negative impacts requires transparency with clients and a strong ethical posture, even when business priorities may conflict with user protection.

Notable Quotes