Learning to See Through the Black Box: Develop X-Ray Vision Through Algorithmic Intuition

August 2023
ELR 10659
Mohit Chhabra

Environmental, natural resource, and energy planning will continue to rely on increasingly complex algorithms. Are these processes then also doomed to be inaccessible to key stakeholders? Hopefully not. There are multiple steps to ensuring process and participatory equity. There is ease of access to the process, access to necessary information, and then there is the matter of having the right information to be able to meaningfully impact outcomes of algorithm-assisted decisionmaking processes. In How Algorithm-Assisted Decisionmaking Is Influencing Environmental Law and Climate Adaptation, Ziaja proposes a useful framework for increasing participation and integrating process equity in algorithm-assisted decisionmaking. Guiding questions around uncertainty, transparency, and stakeholder collaboration provide a starting point to investigate and create accountability for climate models. The next step to facilitating meaningful participation in analytically complex processes requires stakeholders to develop algorithmic intuition. Model developers and process facilitators have the ability and the necessary information to bring stakeholders along. Stakeholders and decisionmakers can do their part by asking the right questions. This Comment proposes an additional set of questions for prospective participants, both technical and non-technical, to build familiarity, or intuition, of a given algorithm.

Mohit Chhabra is Technical Lead and Advisor, Natural Resources Defense Council.

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Learning to See Through the Black Box: Develop X-Ray Vision Through Algorithmic Intuition

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