Hi. I’m JR.

I work at the intersection of emerging technology and environmental governance, focusing on challenges that most people haven't recognized yet. My background spans cognitive neuroscience, environmental planning, and federal agency implementation, giving me an unusual perspective on how systems actually work (and fail) in practice.

What drives my work is seeing problems before they become crises. Right now, artificial intelligence systems are being deployed to make environmental decisions without any coherent framework for handling conflicts between immediate human needs and long-term ecological health. This isn't just a technical problem - it's a fundamental question about how we build democratic, responsive environmental governance in an era of rapid technological and environmental change.

My approach combines practical implementation experience with systems thinking that spans technology, policy, and community engagement. I've tested these ideas in real federal agencies, so I understand both what's theoretically possible and what actually works in institutional contexts. I know why elegant solutions often fail in bureaucratic settings, and how to design approaches that bridge the gap between innovation and implementation.

I'm particularly focused on this moment of opportunity: as federal environmental policies shift, state and local actors have unprecedented space to innovate. Meanwhile, AI capabilities are reaching a point where new approaches to environmental assessment, public participation, and adaptive management are actually feasible. I work to help organizations navigate this intersection of technological possibility and institutional change.

My goal is to help build environmental governance systems that are more responsive to communities, more protective of ecological health, and more capable of adapting to our rapidly changing world.

Problems that I’m Focused On

AI Systems Making Environmental Decisions Without Environmental Ethics

Artificial intelligence is increasingly used to guide resource allocation, environmental permits, and ecosystem management decisions. Yet these systems operate without any framework for representing non-human interests or long-term ecological health. As AI becomes ubiquitous in environmental governance, we're embedding anthropocentric assumptions into the technological infrastructure that will shape environmental outcomes for decades.

Public Participation Trapped in Outdated Categories

Environmental agencies analyze public comments using rigid, predetermined coding schemes that can't adapt to evolving community concerns. These static frameworks systematically miss emerging issues around environmental justice, climate adaptation, and cumulative impacts. Meanwhile, generative AI could identify what communities are actually saying rather than forcing their concerns into administrative convenience categories.

Adaptive Management Constrained by Inflexible Information Systems

Our environmental challenges are changing rapidly—climate impacts, shifting demographics, evolving community priorities—but our management approaches assume static conditions. We need information systems and governance frameworks that can adapt in real-time to changing environmental and social conditions while maintaining democratic accountability.

Extraction Outpacing Restoration

We lack systematic approaches to ensure that environmental restoration matches the pace and scale of resource extraction and environmental damage. Without better frameworks for matching restoration tactics to extraction impacts, we're systematically falling behind in environmental recovery efforts.

AI Transforming Education Without Pedagogical Foundation

Artificial intelligence is being integrated into educational systems without adequate understanding of how these tools affect learning, critical thinking, and knowledge development. As AI becomes ubiquitous in classrooms, we risk fundamentally altering how young people learn to think without intentional design for educational outcomes.

AI Literacy Gap in Young Learners

The next generation will live in an AI-saturated world, yet most educational systems provide little to no AI literacy education. Young people need to understand not just how to use AI tools, but how these systems work, their limitations, and their societal implications—especially around environmental and democratic decision-making.

Geoengineering and Environmental Restoration Tradeoffs

As climate impacts accelerate, geoengineering technologies are being proposed as solutions, but we lack frameworks for evaluating these interventions against natural restoration approaches. The policy choices we make about technological versus ecological solutions will shape environmental outcomes for generations.

Innovation Opportunities in Policy Transition

Federal environmental policy shifts are creating space for state, local, and non-governmental actors to innovate. These organizations need practical tools and frameworks to implement more responsive environmental governance approaches, but they often lack awareness of emerging alternatives to traditional assessment and management methods.

Policy Intersections Across Technology and Environment

Most policy development happens in silos, but the challenges I work on—AI ethics, environmental governance, education technology, democratic participation—are deeply interconnected. We need policy frameworks that can address these intersections rather than treating them as separate domains.

Democratic Deficit in Environmental Decision-Making

Traditional public participation processes often fail to meaningfully incorporate community input into environmental decisions. We need approaches that are genuinely responsive to public concerns while maintaining scientific rigor and legal compliance—especially as environmental decisions increasingly affect community health and environmental justice.

Professional Experience