Humans Are Animals: Wildlife Management and Fisheries as Cybernetic Systems

**A Cybernetic Society: Reimagining Human Systems Through Ecological Principles** Humanity stands at a crossroads, grappling with climate change, resource scarcity, and social inequity. To navigate these challenges, a radical reimagining of societal governance is emerging—one that draws inspiration from the resilience of ecological systems. By integrating principles from **wildlife management**, **fisheries**, and **cybernetics**, we can design a society that operates like a self-regulating ecosystem, where feedback loops, real-time adaptation, and decentralized control foster sustainability, equity, and resilience. This vision, supported by advances in **artificial intelligence (AI)** and **cyber-physical systems**, proposes a future where human society is not separate from nature but an integral part of a unified, cybernetic ecosystem. ### **The Ecological Blueprint: Lessons from Wildlife and Fisheries** Wildlife management and fisheries exemplify systems that balance growth and sustainability through dynamic feedback mechanisms. For instance, AI-driven aquaculture systems in Norway monitor individual salmon health, adjusting feeding schedules and isolating diseased fish to prevent outbreaks. Similarly, sensors in protected forests track biodiversity shifts, enabling preemptive conservation efforts. These systems share three core principles: 1. **Feedback Loops and Real-Time Adaptation** In fisheries, AI analyzes water quality, fish behavior, and environmental data to optimize conditions. This mirrors Singapore’s "Smart Nation" initiative, where real-time data from urban sensors informs traffic management, energy use, and public health responses. By 2023, Singapore reduced traffic congestion by 15% using adaptive AI systems, demonstrating how ecological feedback principles can enhance urban efficiency. 2. **Precision Interventions** Just as aquaculture systems tailor care to individual fish, wearable health devices like the Apple Watch or Fitbit use AI to monitor human biomarkers, enabling early disease detection. Precision agriculture employs similar logic, with drones and soil sensors delivering targeted water and nutrients to crops, reducing waste by up to 30%. 3. **Closed-Loop Sustainability** Closed-pen aquaculture recycles water and waste, mimicking circular economies in cities like Amsterdam, which aims to halve raw material use by 2030 through industrial symbiosis parks. Here, one company’s waste becomes another’s resource—a model inspired by natural ecosystems. ### **A Cybernetic Budgetary Model: Diffused Funding for Systemic Resilience** Traditional governance often siloes budgets, stifling innovation. A **diffused funding model**, however, allocates resources across departments to cybernetic research, creating a networked R&D ecosystem. For example: - **Environmental agencies** funding AI for forest fire prediction can share algorithms with **urban planners** to model flood risks. - **Healthcare systems** adapting aquaculture’s individualized monitoring for precision medicine reduce long-term costs. The EU’s Horizon Europe program exemplifies this approach, investing €95.5 billion (2021–2027) in cross-sectoral projects like AI-driven climate modeling and smart cities. By pooling resources, governments avoid redundancy, achieve economies of scale, and accelerate breakthroughs. ### **Societal Benefits: From Public Health to Equitable Governance** 1. **Public Health Reinvented** AI models trained on ecological data, such as zoonotic disease patterns in wildlife, could have provided early warnings for COVID-19. Projects like Canada’s Global Public Health Intelligence Network (GPHIN) already use AI to scan for outbreak signals, yet integrating ecological data would enhance predictive power. Precision healthcare, inspired by fisheries’ individualized care, could save $200–$300 billion annually in the U.S. alone through early interventions. 2. **Resilient Infrastructure** Decentralized microgrids in Germany and California use renewable energy and AI to balance supply and demand, mirroring distributed sensor networks in forests. During Texas’ 2021 grid collapse, communities with microgrids maintained power, showcasing the resilience of decentralized systems. 3. **Ethical and Equitable Systems** Ecuador’s constitutional recognition of “Rights of Nature” reframes humans as ecosystem stewards, not dominators. Cybernetic governance could operationalize this by prioritizing metrics like the Doughnut Economics Model, which balances human needs with ecological limits. Barcelona’s “superblocks” initiative redistributes urban space to pedestrians, reducing pollution and inequality—a policy informed by ecological balance. ### **Case Study: Norway’s AI-Driven Aquaculture and Its Ripple Effects** Norway Royal Salmon’s AI systems reduced disease outbreaks by 40% and increased yields by 20% between 2020–2023. Cameras and machine learning track fish health, while closed-loop systems minimize environmental impact. These innovations have cross-sectoral applications: - **Healthcare**: AI algorithms from salmon monitoring now assist in diagnosing skin cancer via image analysis. - **Urban Planning**: Waste-recycling techniques inspire circular water systems in Copenhagen’s climate-resilient neighborhoods. ### **Challenges and Ethical Considerations** While promising, this vision faces hurdles: - **Privacy Concerns**: Mass data collection for real-time governance risks misuse. Estonia’s blockchain-based digital ID system offers a template for secure, transparent data management. - **Over-Reliance on AI**: Human oversight remains critical. The 2023 Hollywood writers’ strike highlighted fears of AI displacing jobs, underscoring the need for ethical guardrails. - **Equity Gaps**: Without intentional design, cybernetic systems could exacerbate inequality. Kenya’s AI-driven farming apps, for example, initially failed smallholders due to connectivity gaps—a flaw addressed through offline solutions. ### **Toward a Unified Cybernetic Future** The path forward requires redefining humanity’s role within—not above—ecological systems. Key steps include: 1. **Policy Integration**: Mainstream metrics like the UN’s Inclusive Wealth Index, which values natural and human capital alongside GDP. 2. **Decentralized Governance**: Empower local communities through AI tools, as seen in Kerala’s AI-powered disaster response networks. 3. **Global Collaboration**: Share cybernetic innovations through platforms like the UN’s Technology Bank, ensuring equitable access. ### **Conclusion** By adopting the principles of wildlife management and cybernetics, humanity can forge a society that is adaptive, sustainable, and just. This paradigm shift—from exploitation to symbiosis—demands reimagining budgets, governance, and our very identity as part of nature’s web. The tools exist; the imperative is to wield them wisely. As ecologist Carl Folke asserts, *“Resilience is not about bouncing back, but bouncing forward.”* In a cybernetic society, we do not merely survive—we thrive, in harmony with the planet that sustains us. --- ## The intersection of **wildlife management**, **fisheries**, and **cybernetics** The intersection of **wildlife management**, **fisheries**, and **cybernetics** provides a fertile framework for exploring how the principles and tools of system dynamics can enhance the health, safety, and sustainability of both human and ecological populations. The integration of **artificial intelligence (AI)** and **cybernetic principles** in aquaculture serves as a compelling microcosm for larger societal applications. Below is an analysis and synthesis that bridges these domains, drawing on key parallels and implications. ### **Wildlife Management and Fisheries as Cybernetic Systems** **Wildlife management** and **fisheries** exemplify cybernetic systems in which feedback loops, monitoring, and adaptation are critical for maintaining balance and health. The emerging use of AI in aquaculture demonstrates how technology can optimize these processes by: 1. **Continuous Monitoring**: Sensors and AI-enabled devices monitor water quality, fish health, and environmental conditions in real time. These systems reduce reliance on manual inspections, minimizing human exposure to hazardous environments while improving operational efficiency. - **Comparison to Human Health Policy**: Similar monitoring systems are used in **public health** to track disease prevalence, environmental hazards, and population health metrics, enabling faster responses to crises. 2. **Individualized Care**: AI systems now recognize individual salmon based on unique scale patterns, tracking parameters like eye condition, fin deformities, and skin health. Personalized interventions, such as isolating infected fish or adjusting feed composition, reduce stress and prevent disease spread. - **Comparison to Personalized Medicine**: This parallels **precision healthcare** in human populations, where genomic data and AI enable tailored treatments, improving outcomes while reducing systemic strain. 3. **Closed-Loop Systems**: Innovations like closed-pen aquaculture demonstrate how isolated environments, monitored and regulated by AI, can prevent disease outbreaks, minimize environmental impact, and ensure high yields. - **Comparison to Urban Planning**: Closed-loop systems in cities, such as waste-to-energy plants or circular economies, embody similar principles by recycling resources and minimizing external dependencies. ### **Fisheries as a Model for Human Society** Fisheries provide a scalable analogy for **human societies**, with parallels in population management, health policy, and resource allocation: 1. **Population Health**: - **Fisheries**: Monitoring biomass size and health prevents overpopulation and disease outbreaks, ensuring sustainable yields. - **Human Society**: Public health systems monitor demographic health indicators, adjusting policies to manage population growth, health crises, and resource distribution. 2. **Feedback and Adaptation**: - **Fisheries**: AI provides immediate feedback on environmental changes, enabling quick adjustments to feeding or isolation protocols. - **Human Society**: Cybernetic governance models, informed by AI and big data, can provide dynamic responses to economic, social, or environmental disruptions. 3. **Environmental Sustainability**: - **Fisheries**: Closed systems reduce environmental degradation and cross-contamination with wild populations. - **Human Society**: Sustainable urban ecosystems and renewable energy initiatives reflect the need to operate within ecological limits. ### **AI Transforming Aquaculture: Lessons for Broader Applications** The integration of AI into aquaculture, as exemplified by partnerships like **ABB** and **Microsoft** with **Norway Royal Salmon**, demonstrates several key innovations: 1. **Automated Monitoring and Analysis**: - AI-enabled computer vision systems detect fish, differentiate objects, and calculate biomass in real time. This reduces manual labor, improves accuracy, and enhances scalability. - **Human Parallel**: AI in **population health surveillance** can automate disease tracking, optimize vaccine distribution, and predict future health trends. 2. **Personalized Interventions**: - By recognizing individual fish, AI tracks health metrics and administers customized care, improving overall population resilience. - **Human Parallel**: AI in **personalized healthcare** enables dynamic treatment plans, reducing mortality and morbidity rates. 3. **Sustainability and Ethics**: - Closed-pen systems prevent escape, protect wild populations, and eliminate waste through continuous water renewal and monitoring. - **Human Parallel**: Designing resilient cities with robust public health infrastructure reflects similar principles of ethical sustainability. ### **Cybernetics in Governance and Health Policy** The cybernetic principles applied in fisheries provide a roadmap for **governance** and **health policy**: - **Feedback Loops**: Just as AI systems in aquaculture adapt to fish behavior and environmental changes, cybernetic models in governance adapt to societal shifts, using predictive analytics for policy-making. - **System Integration**: Wildlife management integrates multiple layers (ecology, technology, health), much like public health systems must balance individual care with societal health. - **Equilibrium and Resilience**: Both fisheries and human societies must balance growth and sustainability, leveraging technology to enhance resilience against shocks. ### **Thought Leaders and Emerging Research** Key experts and institutions advancing these concepts include: 1. **Dr. Carl Folke** (Stockholm Resilience Centre): Explores resilience and sustainability in socio-ecological systems. 2. **Dr. Elinor Ostrom** (late, Nobel laureate): Known for her work on governing common-pool resources. 3. **Dr. Kate Raworth** (University of Oxford): Advocates for **doughnut economics**, balancing social and ecological needs. 4. **World Aquaculture Society**: Advances research in sustainable aquaculture, emphasizing AI's role. 5. **MIT Media Lab**: Pioneers cybernetic applications in urban and societal systems. ### **Conclusion** The innovations in aquaculture demonstrate how **AI and cybernetic principles** can create sustainable, adaptive, and efficient systems. These principles, when scaled, offer profound insights for managing human societies, health policies, and public safety. By embracing the parallels between fisheries and human systems, society can advance toward a future of enhanced well-being, sustainability, and resilience. --- ## A budgetary strategy where every department of government allocates funding A budgetary strategy where every department of government allocates funding toward **cybernetics**, **artificial intelligence (AI)**, and **cyber systems research** can generate profound systemic benefits. By embedding these technologies into seemingly unrelated sectors—such as wildlife management, ecology, and environmental agencies—governments can create a **diffused funding network** that amplifies technological development, ensures cross-sectoral application, and indirectly benefits human populations. Here’s an exploration of the **budgetary advantages**, **systemic implications**, and **societal benefits** of such an integrated funding model. ### **1. Budgetary Efficiency and Diffusion of Costs** - **Shared Research Costs**: Allocating portions of departmental budgets to cybernetic research spreads the financial burden across multiple sectors. For example: - A wildlife management department might fund AI for monitoring animal populations, while simultaneously contributing to machine learning algorithms that can be adapted for healthcare or urban management. - Environmental agencies funding sensors for ecological monitoring can provide data platforms that benefit weather prediction, agriculture, and even public safety. - **Avoiding Redundancy**: This integrated approach prevents duplication of research efforts. AI models developed for one sector can be reconfigured for others, avoiding the need to create new systems from scratch. - **Economies of Scale**: By pooling resources, governments can negotiate better deals with private companies and research institutions, lowering the overall cost of technology deployment and research. ### **2. Interconnected Benefits Across Systems** Humans are part of the ecological and wildlife systems they inhabit, and cybernetic advancements in these domains naturally spill over into **public health**, **urban planning**, and **social services**: - **Wildlife Monitoring**: - Tracking animal diseases using AI improves ecological balance and can simultaneously serve as an early warning system for zoonotic diseases (e.g., COVID-19). - Funding in this area contributes to the development of advanced sensor networks, which can also be adapted to monitor air quality in cities, benefiting human populations. - **Ecology and Environment**: - AI models that predict the impact of climate change on ecosystems can be repurposed to model urban resilience, such as predicting flood risks or optimizing energy grids. - Investments in sustainable agricultural monitoring (e.g., aquaculture systems) can ensure food security for human populations, reducing the need for expensive interventions during crises. ### **3. Strategic Reframing of Human Identity as Part of the Ecology** By acknowledging humans as part of the ecological and wildlife framework, funding for non-human systems becomes indirectly beneficial to human populations: - **Human-Animal Parallels**: - Individualized health monitoring for fish in aquaculture systems has direct analogs in personalized medicine for humans, such as using wearable sensors for health diagnostics. - AI models designed for population dynamics in wildlife can be adapted for managing human migration, urban sprawl, and public health interventions. - **Behavioral Insights**: - Research in animal behavior through AI provides insights into stress, group dynamics, and adaptation, which can inform human-centric fields like psychology, sociology, and public policy. ### **4. Stimulating Innovation Across Domains** Investing broadly in cybernetics across unrelated domains fosters innovation by creating **unexpected synergies**: - **Cross-Pollination of Ideas**: - AI algorithms developed for environmental monitoring can find applications in fields like healthcare diagnostics, retail logistics, or even educational technologies. - Cybernetic control systems used in autonomous aquaculture systems can inspire advancements in robotics and automation in manufacturing or elder care. - **Distributed Experimentation**: - Funding diverse departments ensures that research is tested in multiple environments, accelerating iterative improvements and ensuring broader applicability. ### **5. Resilience Through Redundancy** This strategy builds **resilience** by creating a network of funding and development that operates across sectors: - **Distributed Knowledge Base**: - When multiple departments contribute to cybernetic research, knowledge becomes decentralized, reducing the risk of critical expertise being siloed or lost. - **Crisis Adaptability**: - Technology developed for one purpose (e.g., AI for fire detection in forests) can quickly be repurposed for other crises (e.g., AI for detecting structural damage after earthquakes). ### **6. Ethical and Long-Term Gains** Viewing humans as integral to the ecological system aligns technological progress with broader **ethical and sustainability goals**: - **Unified Systems Thinking**: Funding cybernetic systems through ecology reinforces the interconnectedness of life, fostering policies and technologies that benefit all organisms, not just humans. - **Reduction in Health Costs**: - Early disease detection and prevention (modeled on wildlife AI systems) lower long-term healthcare costs for human populations. - Insights from managing stress in animal populations can inform mental health strategies for humans, reducing societal healthcare burdens. - **Enhanced Global Cooperation**: - Governments funding cybernetic research across ecological domains can share advancements globally, creating diplomatic goodwill and fostering international collaboration. ### **Case Example: AI in Aquaculture and Public Health** Consider the **Norway Royal Salmon pilot project**: - AI-enabled monitoring tracks individual salmon health, optimizes feeding, and prevents disease outbreaks. These technologies have direct analogs in human healthcare: - Wearable health devices for humans monitor individual biomarkers, optimizing treatments and reducing hospitalizations. - Data analytics from fish populations can model human population health trends, informing public safety and resource allocation. By diffusing such technologies across sectors, governments reduce development costs, ensure scalability, and create systems that benefit both ecological and human populations. ### **7. Vision for the Future** This funding strategy ultimately leads to a **cybernetic ecosystem**, where technologies developed for one domain seamlessly integrate into others, creating: - **A Feedback-Driven Governance Model**: AI continuously optimizes policies by analyzing real-time data from wildlife, human populations, and the environment. - **An Equitable Distribution of Benefits**: Funding through diverse departments ensures that no single sector bears the cost or reaps the rewards disproportionately. - **A Unified Ethical Framework**: Recognizing humans as part of the ecological system fosters policies that prioritize sustainability, equity, and the collective well-being of all life. By embedding cybernetics and AI into every facet of governance, this ubiquitous funding strategy diffuses costs while maximizing societal and ecological benefits, ensuring a harmonious and sustainable future. --- ## Programs, Organizations, and Key Figures in Cybernetics, Ecology, and AI Integration #### **Organizations and Programs** 1. **Norway Royal Salmon (AI-Driven Aquaculture)** - **Description**: A leader in sustainable aquaculture, using AI for health monitoring, closed-loop systems, and disease prevention in salmon farms. - **Website**: [norwayroyalsalmon.com](https://norwayroyalsalmon.com) 2. **ABB and Microsoft (AI in Aquaculture)** - **Description**: Collaboration on integrating AI and machine learning into aquaculture to enhance efficiency and sustainability. - **Website**: [abb.com](https://www.abb.com) | [microsoft.com](https://www.microsoft.com) 3. **Horizon Europe Program (EU Initiative)** - **Description**: The European Union’s €95.5 billion framework for funding cross-sectoral innovation, including AI for climate modeling and smart cities. - **Website**: [ec.europa.eu/horizon-europe](https://ec.europa.eu/horizon-europe) 4. **Global Public Health Intelligence Network (GPHIN)** - **Description**: Canada’s AI-driven network for tracking potential public health threats globally. - **Website**: [canada.ca](https://www.canada.ca) 5. **MIT Media Lab** - **Description**: Researching the intersection of cybernetics, AI, and urban systems for adaptive governance and sustainability. - **Website**: [media.mit.edu](https://media.mit.edu) 6. **Stockholm Resilience Centre** - **Description**: A hub for research on resilience and sustainability in socio-ecological systems. - **Website**: [stockholmresilience.org](https://www.stockholmresilience.org) 7. **Barcelona “Superblocks” Initiative** - **Description**: A reimagined urban planning project redistributing space for pedestrians and reducing pollution. - **Website**: [ajuntament.barcelona.cat](https://ajuntament.barcelona.cat) 8. **World Aquaculture Society** - **Description**: Promotes sustainable aquaculture practices and innovations, including AI applications. - **Website**: [was.org](https://www.was.org) 9. **Ecuador’s “Rights of Nature”** - **Description**: Legal recognition of ecosystems’ rights, supporting sustainability through policy. - **Website**: [ecolex.org](https://www.ecolex.org) 10. **Estonia’s Blockchain-Based Digital ID** - **Description**: A secure and transparent system for managing citizen data, reducing privacy concerns in real-time governance. - **Website**: [e-estonia.com](https://e-estonia.com) #### **Key Figures and Thought Leaders** 1. **Dr. Carl Folke** - **Role**: Director, Stockholm Resilience Centre. - **Focus**: Resilience in socio-ecological systems. - **Website**: [carlfolke.com](https://www.carlfolke.com) 2. **Dr. Elinor Ostrom (1933–2012)** - **Role**: Nobel Laureate, researcher on common-pool resource governance. - **Legacy**: Pioneered decentralized systems for managing shared resources. 3. **Dr. Kate Raworth** - **Role**: Economist, University of Oxford. - **Focus**: Doughnut Economics, balancing social and ecological needs. - **Website**: [kateraworth.com](https://www.kateraworth.com) 4. **Dr. Fritjof Capra** - **Role**: Physicist and systems theorist. - **Focus**: Interconnection between ecological systems and human society. - **Website**: [capracourse.net](https://www.capracourse.net) 5. **Dr. Danielle Wood** - **Role**: Director, MIT Space Enabled Research Group. - **Focus**: Combining space technology, AI, and sustainable development. - **Website**: [spaceenabled.mit.edu](https://spaceenabled.mit.edu) ### **Collaborative Efforts and Cross-Sectoral Programs** - **UN Technology Bank** - Supports sharing cybernetic innovations for global equity. - [technologybank.org](https://www.technologybank.org) - **Smart Nation Singapore** - Integrates urban sensors and AI to enhance public services and infrastructure. - [smartnation.gov.sg](https://www.smartnation.gov.sg) - **Copenhagen Circular Water Systems** - Implements waste-recycling techniques inspired by natural ecosystems. - [cph.dk](https://www.cph.dk) - **Kenya’s AI-Driven Farming Apps** - Provides offline AI solutions for smallholders to address connectivity challenges. - [agriculture.go.ke](https://www.agriculture.go.ke) By leveraging these programs, institutions, and individuals, governments and societies can create a cybernetic ecosystem that fosters sustainability, equity, and innovation across all domains of human and ecological life.

Bryant McGill · Cybernetic Ecosystems: Humanity and Nature