In How Algorithm-Assisted Decisionmaking Is Influencing Environmental Law and Climate Adaptation, Ziaja provides a useful framework to analyze whether an algorithm-assisted decisionmaking (AADM) tool and its design process is procedurally equitable. Ziaja’s framework contains several different questions advocacy groups can use to analyze the AADM tools that are increasingly used for environmental resource governance, such as the INFORM and RESOLVE algorithms discussed in the article, which guide the allocation and distribution of water and energy resources. The questions within the framework can help stakeholders assess the legal and policy assumptions (“value-laden assumptions”) embedded in algorithmic decision tools and are a starting point for identifying potential biases and substantive equity issues within those systems and encouraging greater deliberation and coproduction of AADM tools between governmental agencies and advocacy groups. This Comment discusses some of the barriers advocacy organizations face when engaging in the development of algorithmic systems, how the framework can ease those barriers, and finally the need for the developers of algorithmic decision systems to complete impact or risk assessments to further enable informed discussion and coproduction of these tools.

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.

Agencies responsible for water and energy systems increasingly rely on algorithm-assisted decisionmaking to regulate these systems and shepherd them through climate adaptation. Legal scholars, attorneys, and environmental equity advocates should care about this fundamental change in governance for three reasons. First, climate adaptation depends on these tools. Second, algorithmic tools are not policy-neutral; rather they embed value-laden assumptions and biases. And third, the “rules” of this new forum impede equity and democratic participation, without deliberate countermeasures. This Article proposes an initial step in the development of such countermeasures: a framework for evaluating how algorithm-assisted decisionmaking, in environmental and energy regulation, influences law and what the consequences are for equity and participation.