Tag: politics

Before We Decide What Matters: Minneapolis, ICE, and the Work of Attention

If you’re like me, you are tired of being told what matters. Every day arrives already crowded with urgency from cable news to social media to our email inboxes. There is always something demanding a response, a position, a statement, a judgment. The crises are real and here at home, as we’re seeing in Minneapolis, but also here in Spartanburg. Ecological collapse, technological acceleration, political fracture, spiritual exhaustion. And yet the constant pressure to decide, to weigh in with friends or on social media, to declare allegiance or outrage over Trump’s latest missive, even which news outlets to consume… often leaves us less capable of genuine care rather than more. Moral life begins to feel like triage, and eventually like performance.

I have been wondering whether this exhaustion has less to do with a lack of ethics and more to do with how quickly we rush toward them.

Before we decide what matters, something quieter has already taken place. The world has appeared to us in a certain way. Something has shown up as worthy of concern, or not. Something has addressed us, or passed unnoticed. That prior moment, the way the world first comes into view, is rarely examined. Social media algorithms are designed to outrage us before we have even a moment to process an event. And yet this initial moment of appearance may be the most decisive moral act we ever perform.

Attention is not neutral. It is formative.

We often speak about ethics as if it begins with principles, values, or rules. But those only function once something has already been perceived as meaningful. I cannot care about what I do not notice. I cannot respond to what never appears. Long before moral reasoning begins, there is a posture of perception, a way of being present to what is other than myself.

This is where empathy has become important to me again, not as a sentiment or virtue, but as a mode of knowing. Empathy, understood phenomenologically, is not agreement or emotional fusion. It is not a projection of myself into another, nor a collapse of difference. For Edith Stein, empathy names the experience in which another’s interiority becomes present to me as other, irreducible, and real. It is a way of perceiving foreign consciousness without possessing it.

Crucially, empathy in this sense is not something that follows understanding. It is what makes understanding possible in the first place.

Seen this way, empathy is not primarily ethical. It is ontological. It concerns how beings appear to one another, how the world is allowed to disclose itself, how alterity is either received or flattened. Stein is careful here. Empathy does not erase distance. It preserves it. The other is never absorbed into my own experience, but neither is the other sealed off from me. Relation becomes possible without domination.

For example, this matters deeply for how we think about ecology. Much contemporary environmental discourse quickly shifts toward solutions, metrics, and outcomes, from AI data center debates at city council meetings to creation care initiatives once a group decides to engage locally. These are necessary, but they often skip the slower work of learning how to see. Ecology becomes a problem to manage rather than a field of relationships in which we already participate. The natural world is framed as a resource, a threat, or a victim, rarely as a presence capable of addressing us.

Stein herself did not write ecological theory, but her account of empathy offers a discipline of attention that easily extends beyond the human. If empathy is the experience of encountering another as a center of meaning, not of my own making, then it trains us to resist reducing the world to what it can be used for or controlled. It teaches restraint before response. Attention changes this.

To attend to a tree across seasons, to notice how it sheds, scars, and persists, is not to solve anything. It is to be apprenticed into a different tempo of significance. Ecological time resists panic not by denying urgency, but by deepening responsibility. It trains us to remain with what unfolds slowly, unevenly, and often without spectacle.

This kind of attention does not produce immediate answers. It produces orientation.

I have come to think that much of our moral confusion stems from a failure of perception rather than a failure of values. We argue about what ought to be done while remaining inattentive to what is actually present. We leap toward ethical frameworks while bypassing the more difficult task Stein insists upon by allowing the other to show itself as it is, before we decide what it means or what is owed.

Attention is costly (and incredibly valuable, as social media algorithms have taught us over the last decade, as I noted in my 2015 post). It requires patience, vulnerability, and restraint. It asks us to linger rather than react, to receive rather than master. In a culture shaped by speed and extraction with news cycles lasting just a couple of days, this can feel almost irresponsible. And yet without it, our ethics float free of the world they claim to serve.

To attend is already to take responsibility.

Not because attention guarantees correct action, but because it establishes the conditions under which action can be something other than projection or control. When we learn to notice, to listen, to allow meaning to emerge rather than be imposed, we begin to recover a moral life that is responsive rather than reactive.

Perhaps the most urgent task before us is not deciding what matters next, but recovering the capacity to perceive what has been asking something of us all along.

Footnote: Edith Stein describes empathy not as inference, emotional contagion, or imaginative projection, but as a direct experiential act in which another’s consciousness is given as other while remaining irreducibly distinct from one’s own. Empathy, for Stein, is thus neither ethical evaluation nor moral sentiment, but a foundational mode of perception through which meaning first becomes accessible. See Edith Stein, On the Problem of Empathy, trans. Waltraut Stein (Washington, DC: ICS Publications, 1989), 10–12, 19–21.

Empathy Before Ethics (or Why We Should All Read More Edith Stein)

Empathy is one of those words that risks being worn thin by overuse and is too frequently misunderstood. It shows up everywhere now… in leadership manuals, in political rhetoric, in the well-meaning exhortations we give children and congregations. And yet, for all its familiarity, empathy remains deeply misunderstood. Too often it is reduced to a moral sentiment, a kind of emotional niceness, or worse, a strategy for persuasion. I want to suggest something quieter and more demanding… empathy as a way of perceiving.

“Empathy is the experience of foreign consciousness in general.”

Edith Stein, On the Problem of Empathy, trans. Waltraut Stein (ICS Publications), p. 11

I have come to think of empathy not primarily as an ethical achievement but as an ontological posture. It is not something we do after we have already decided what matters. It is the manner in which the world first comes to matter at all.

This conviction has been sharpened for me through sustained engagement with Edith Stein, whose phenomenology of empathy remains one of the most careful and restrained accounts we have. For Stein, empathy is neither emotional contagion, weakness, nor imaginative projection. It is the act through which another subject’s experience is given to me as theirs, not mine. Empathy discloses interiority without collapsing difference. It is, from the start, a mode of knowing that preserves distance.

“The empathized experience is not given to me originally, but non-originally.”

Stein, On the Problem of Empathy, p. 7

In my own work, empathy names the fragile, attentive space where another presence addresses us before we categorize it, manage it, or explain it away. This is as true of human encounters as of encounters with trees, landscapes, animals, or histories. Empathy is the discipline of allowing oneself to be interrupted.

That interruption is rarely dramatic. Most often, it happens slowly, almost imperceptibly. A pause before speaking. A hesitation before naming. A sense that what is before me exceeds my grasp. In that pause, empathy is born… not as fusion or projection, but as restraint.

One of the mistakes modern culture makes is assuming that empathy means feeling what another feels. That framing subtly centers the self. It asks how the other’s experience can be translated into my own emotional register. Stein is especially helpful here. She insists that empathy is a non-original experience… I do not live the other’s joy or suffering as my own, but I genuinely encounter it as real. This distinction matters. It protects the other from appropriation and the self from illusion.

“The subject of the empathized experience is not identical with the subject who empathizes.”

Stein, On the Problem of Empathy, p. 10

This has profound implications for how we relate to the more-than-human world. When I sit with a tree… especially the black walnut that has quietly shaped my days over the past year… empathy does not mean imagining what it would be like to be a tree. That is a category error. Instead, empathy means allowing the tree to show up as something other than a resource, a metaphor, or a background object. It means attending to its rhythms, its vulnerabilities, its way of occupying time.

Here, Stein’s work opens a door rather than closing one. If empathy is the basic way another’s interiority becomes perceptible without being reduced, then the question is not whether nonhuman beings “have” interiority in a human sense. The question is whether we have trained ourselves to attend to modes of presence that do not mirror our own. Empathy, in this sense, is ecological. It resists extraction. It slows us down. It teaches us how to dwell rather than dominate.

“Empathy gives us experience of other persons and of their experiences, but it does not make them our own.”

Stein, On the Problem of Empathy, p. 12

I have found that empathy is also inseparable from humility. It requires accepting that understanding is always partial, always provisional. Stein never treats empathy as exhaustive knowledge. It is an opening, not a possession. This is uncomfortable in a culture that prizes mastery and certainty. Empathy refuses shortcuts. It cannot be automated or optimized. It unfolds through presence, patience, and a willingness to remain with what does not resolve.

This is why empathy cannot be commanded. It cannot be forced through moral exhortation alone. It must be cultivated through practices of attention… through walking familiar paths slowly, through listening without rehearsing replies, through learning the names and habits of the places we inhabit. Empathy grows where curiosity is protected.

And perhaps this is the most important thing I have learned. Empathy is not a soft virtue. It is a demanding discipline. It asks us to remain open in a world that rewards closure. It asks us to stay porous when efficiency would prefer boundaries sealed tight. It asks us to receive before we judge.

“It is only through empathy that we gain knowledge of the psychic life of others.”

Stein, On the Problem of Empathy, p. 14

If there is a future worth hoping for… ecologically, socially, spiritually… it will not be engineered solely through better systems or smarter technologies. It will be shaped by the recovery of this ancient, fragile capacity to be addressed by what is not ourselves.

Empathy does not solve the world’s problems. But without it, we cannot even perceive them rightly.

“Finite knowing is essentially fragmentary.”

Stein, Finite and Eternal Being, trans. Kurt Reinhardt (ICS Publications), p. 389

The Great Work Ahead of Us

Worth the time to read and process… The Great Work (to invoke Thomas Berry here) ahead of us is daunting. Still, we have the opportunity to create something where human and the more-than-human are encouraged not only to survive but to thrive (together), ultimately, if we only speak up… 

Is This Rock Bottom?:

So yes, the fights over SNAP, ACA subsidies, and shutdowns matter — but they’re symptoms, not causes. You don’t get 40 million people needing food aid and 100 million drowning in medical debt because of one bad president or one unlucky decade. You get there because the institutions that were supposed to protect the public spent decades serving somebody else.

Renewables Pass Coal’s Share in Global Electricity Generation

China is leading the way here in solar… It’s time for our leaders and economy here in the US to start waking up to reality. That won’t happen in the current scenario of our political landscape, obviously, but there needs to be intentional focusing on reducing consolidated power grid structures in favor of local (and flexible) sources of electricity and fuel (as well as our food supplies). 

Global Electricity Mid-Year Insights 2025 | Ember:

Solar and wind outpaced demand growth in the first half of 2025, as renewables overtook coal’s share in the global electricity mix…

Solar grew by a record 306 TWh (31%) in the first half of 2025. This increased solar’s share in the global electricity mix from 6.9% to 8.8%. China accounted for 55% of global solar generation growth, followed by the US (14%), the EU (12%), India (5.6%) and Brazil (3.2%), while the rest of the world contributed just 9%. Four countries generated over 25% of their electricity from solar, and at least 29 countries surpassed 10%, up from 22 countries in the same period last year and only 11 countries in H1-2021…

PDF Report availalbe here

Navigating Our Climate Crisis Without U.S. Leadership

Important piece here that gives voice to leaders from areas that aren’t usually covered by the mainstream press here in the USA when discussing climate issues and our ecological crisis in general… let those with ears to listen, hear…

Six World Leaders on Navigating Climate Change, Without the U.S. – The New York Times (Gift Article):

Debates around climate change often focus on the world’s largest economies and biggest emitters. But much of the hard work of figuring out how to adapt — both to a hotter planet and to a new geopolitical landscape — is happening in countries that have contributed relatively little to the problem yet are still navigating complex climate-related issues. Hoping to better understand how global warming and the changing world order are affecting some of these often-overlooked places, I spoke with six world leaders from different geographic regions. I heard some common themes: the ravages of extreme weather, the difficulties posed by the Trump administration’s retreat. But these conversations also illustrated the intensely varied predicaments facing world leaders right now.

Remembering

Merianna says what a whole lot of us (myself included) have been thinking and feeling and anxious about (particularly about our young ones after our summer travels to D.C. and NYC)…

“The World Turned Upside Down” – by Merianna Harrelson:

As we watched the barricades go up and the monuments close so that a parade route could be established, I wondered what our kids would remember about our trip to Washington, DC. I hope they will remember the stories of those who fought for the silenced and the oppressed. I hope they will remember the leaders who rose up and spoke against injustice and capitalizing on the labor of others. I hope they will remember the beauty of the art and the curiosity that led to innovation.

Convergent Intelligence: Merging Artificial Intelligence with Integral Ecology and “Whitehead Schedulers”

The promise of AI convergence, where machine learning interweaves with ubiquitous sensing, robotics, and synthetic biology, occupies a growing share of public imagination. In its dominant vision, convergence is driven by scale, efficiency, and profitability, amplifying extractive logics first entrenched in colonial plantations and later mechanized through fossil‑fuel modernity. Convergence, however, need not be destiny; it is a meeting of trajectories. This paper asks: What if AI converged not merely with other digital infrastructures but with integral ecological considerations that foreground reciprocity, limits, and participatory co‑creation? Building on process thought (Whitehead; Cobb), ecological theology (Berry), and critical assessments of AI’s planetary costs (Crawford; Haraway), I propose a framework of convergent intelligence that aligns learning systems with the metabolic rhythms and ethical demands of Earth’s biocultural commons.

Two claims orient the argument. First, intelligence is not a private property of silicon or neurons but a distributed, relational capacity emerging across bodies, cultures, and landscapes.[1] Second, AI’s material underpinnings, including energy, minerals, water, and labor, are neither incidental nor external; they are constitutive, producing obligations that must be designed for rather than ignored.[2] [3] Convergent intelligence, therefore, seeks to redirect innovation toward life‑support enhancement, prioritizing ecological reciprocity over throughput alone.

2. Integral Ecology as Convergent Framework

Integral ecology synthesizes empirical ecology with phenomenological, spiritual, and cultural dimensions of human–Earth relations. It resists the bifurcation of facts and values, insisting that knowledge is always situated and that practices of attention from scientific, spiritual, and ceremonial shape the worlds we inhabit. Within this frame, data centers are not abstract clouds but eventful places: wetlands of silicon and copper drawing on watersheds and grids, entangled with regional economies and more‑than‑human communities.

Three premises ground the approach:

  • Relational Ontology: Entities exist as relations before they exist in relations; every ‘thing’ is a nexus of interdependence (Whitehead).
  • Processual Becoming: Systems are events in motion; stability is negotiated, not given. Designs should privilege adaptability over rigid optimization (Cobb).
  • Participatory Co‑Creation: Knowing arises through situated engagements; observers and instruments co‑constitute outcomes (Merleau‑Ponty).

Applied to AI, these premises unsettle the myth of disembodied computation and reframe design questions: How might model objectives include watershed health or biodiversity uplift? What governance forms grant communities, especially Indigenous nations, meaningful authority over data relations?[4] What would it mean to evaluate model success by its contribution to ecological resilience rather than click‑through rates?

2.1 Convergence Re‑grounded

Convergence typically refers to the merging of technical capabilities such as compute, storage, and connectivity. Integral ecology broadens this perspective: convergence also encompasses ethical and cosmological dimensions. AI intersects with climate adaptation, fire stewardship, agriculture, and public health. Designing for these intersections requires reciprocity practices such as consultation, consent, and benefit sharing that recognize historical harms and current asymmetries.[5]

2.2 Spiritual–Ethical Bearings

Ecological traditions, from Christian kenosis to Navajo hózhó, teach that self‑limitation can be generative. Convergent intelligence operationalizes restraint in technical terms: capping model size when marginal utility plateaus; preferring sparse or distilled architectures where possible; scheduling workloads to coincide with renewable energy availability; and dedicating capacity to ecological modeling before ad optimization.[6] [7] These are not mere efficiency tweaks; they are virtues encoded in infrastructure.

3. Planetary Footprint of AI Systems

A sober accounting of AI’s material footprint clarifies design constraints and opportunities. Energy use, emissions, minerals, labor, land use, and water withdrawals are not background variables; they are constitutive inputs that shape both social license and planetary viability.

3.1 Energy and Emissions

Training and serving large models require substantial electricity. Analyses indicate that data‑center demand is rising sharply, with sectoral loads sensitive to model scale, inference intensity, and location‑specific grid mixes.[8] [9] Lifecycle boundaries matter: embodied emissions from chip fabrication and facility build-out, along with end-of-life e-waste, can rival operational impacts. Shifting workloads to regions and times with high renewable penetration, and adopting carbon‑aware schedulers, produces measurable reductions in grid stress and emissions.[10]

3.2 Minerals and Labor

AI supply chains depend on copper, rare earths, cobalt, and high‑purity silicon, linking datacenters to mining frontiers. Extraction frequently externalizes harm onto communities in the Global South, while annotation and content‑moderation labor remain precarious and under‑recognized.[11] Convergent intelligence demands procurement policies and contracting models aligned with human rights due diligence, living wages, and traceability.

3.3 Biodiversity and Land‑Use Change

Large facilities transform landscapes with new transmission lines, substations, and cooling infrastructure, fragment habitats, and alter hydrology. Regional clustering, such as the U.S. ‘data‑center alleys’, aggregates impact on migratory species and pollinators.[12] Strategic siting, brownfield redevelopment, and ecological offsets designed with local partners can mitigate, but not erase, these pressures.

3.4 Water

High‑performance computing consumes significant water for evaporative cooling and electricity generation. Recent work highlights the hidden water footprint of AI training and inference, including temporal mismatches between compute demands and watershed stress.[13] Designing for water efficiency, including closed‑loop cooling, heat recovery to district systems, and workload shifting during drought, should be first‑order requirements.

4. Convergent Design Principles

Responding to these impacts requires more than incremental efficiency. Convergent intelligence is guided by three mutually reinforcing principles: participatory design, relational architectures, and regenerative metrics.

4.1 Participatory Design

Integral ecology insists on with‑ness: affected human and more‑than‑human communities must shape AI life‑cycles. Practical commitments include: (a) free, prior, and informed consent (FPIC) where Indigenous lands, waters, or data are implicated; (b) community benefits agreements around energy, water, and jobs; (c) participatory mapping of energy sources, watershed dependencies, and biodiversity corridors; and (d) data governance aligned with the CARE Principles for Indigenous Data Governance.[14]

4.2 Relational Architectures

Borrowing from mycorrhizal networks, relational architectures privilege decentralized, cooperative topologies over monolithic clouds. Edge‑AI and federated learning keep data local, reduce latency and bandwidth, and respect data sovereignty.[15] [16] Technically, this means increased use of on‑device models (TinyML), sparse and distilled networks, and periodic federated aggregation with privacy guarantees. Organizationally, it means capacity‑building with local stewards who operate and adapt the models in place.[17]

4.3 Regenerative Metrics

Key performance indicators must evolve from throughput to regeneration: net‑zero carbon (preferably net‑negative), watershed neutrality, circularity, and biodiversity uplift. Lifecycle assessment should be integrated into CI/CD pipelines, with automated gates triggered by thresholds on carbon intensity, water consumption, and material circularity. Crucially, targets should be co‑governed with communities and regulators and audited by third parties to avoid greenwash.

5. Case Explorations

5.1 Mycelial Neural Networks

Inspired by the efficiency of fungal hyphae, sparse and branching network topologies can reduce parameter counts and memory traffic while preserving accuracy. Recent bio‑inspired approaches report substantial reductions in multiply‑accumulate operations with minimal accuracy loss, suggesting a path toward ‘frugal models’ that demand less energy per inference.[18] Beyond metaphor, this aligns optimization objectives with the ecological virtue of sufficiency rather than maximalism.[19]

5.2 Edge‑AI for Community Fire Stewardship

In fire‑adapted landscapes, local cooperatives deploy low‑power vision and micro‑meteorological sensors running TinyML models to track humidity, wind, and fuel moisture in real time. Paired with citizen‑science apps and tribal burn calendars, these systems support safer prescribed fire and rapid anomaly detection while keeping sensitive data local to forest commons.[20] Federated updates allow regional learning without centralizing locations of cultural sites or endangered species.[21]

5.3 Process‑Relational Cloud Scheduling

A prototype ‘Whitehead Scheduler’ would treat compute jobs as occasions seeking harmony rather than dominance: workloads bid for energy indexed to real‑time renewable availability. At the same time, non‑urgent tasks enter latency pools during grid stress. Early experiments at Nordic colocation sites report reduced peak‑hour grid draw alongside improved utilization.[22] The aim is not simply to lower emissions but to re-pattern computing rhythms to match ecological cycles.

5.4 Data‑Commons for Biodiversity Sensing

Camera traps, acoustic recorders, and eDNA assays generate sensitive biodiversity data. Convergent intelligence supports federated learning across these nodes, minimizing centralized storage of precise locations for rare species while improving models for detection and phenology. Governance draws from commons stewardship (Ostrom) and Indigenous data sovereignty, ensuring that benefits accrue locally and that consent governs secondary uses.[23] [24]

6. Ethical and Spiritual Dimensions

When intelligence is understood as a shared world‑making capacity, AI’s moral horizon widens. Integral ecology draws on traditions that teach humility, generosity, and restraint as technological virtues. In practice, this means designing harms out of systems (e.g., discriminatory feedback loops), allocating compute to public goods (e.g., climate modeling) before ad targeting, and prioritizing repair over replacement in hardware life cycles.[25] [26] [27] Critical scholarship on power and classification reminds us that technical choices reinscribe social patterns unless intentionally redirected.[28] [29] [30]

7. Toward an Ecology of Intelligence

Convergent intelligence reframes AI not as destiny but as a participant in Earth’s creative advance. Adopting participatory, relational, and regenerative logics can redirect innovation toward:

  • Climate adaptation: community‑led forecasting integrating Indigenous fire knowledge and micro‑climate sensing.
  • Biodiversity sensing: federated learning across camera‑traps and acoustic arrays that avoids centralizing sensitive locations.[31] [32]
  • Circular manufacturing: predictive maintenance and modular design that extend hardware life and reduce e‑waste.

Barriers such as policy inertia, vendor lock‑in, financialization of compute, and geopolitical competition are designable, not inevitable. Policy levers include carbon and water-aware procurement; right-to-repair and extended producer responsibility; transparency requirements for model energy and water reporting; and community benefits agreements for new facilities.[33] [34] Research priorities include benchmarks for energy/water per quality‑adjusted token or inference, standardized lifecycle reporting, and socio‑technical audits that include affected communities.

8. Conclusion

Ecological crises and the exponential growth of AI converge on the same historical moment. Whether that convergence exacerbates overshoot or catalyzes regenerative futures depends on the paradigms guiding research and deployment. An integral ecological approach, grounded in relational ontology and participatory ethics, offers robust guidance. By embedding convergent intelligence within living Earth systems, technically, organizationally, and spiritually, we align technological creativity with the great work of transforming industrial civilization into a culture of reciprocity.

Notes

[1] James Bridle, Ways of Being: Animals, Plants, Machines: The Search for a Planetary Intelligence (New York: Farrar, Straus and Giroux, 2022).

[2] Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (New Haven, CT: Yale University Press, 2021).

[3] Emma Strubell, Ananya Ganesh, and Andrew McCallum, “Energy and Policy Considerations for Deep Learning in NLP,” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (2019), 3645–3650.

[4] Global Indigenous Data Alliance, “CARE Principles for Indigenous Data Governance,” 2019.

[5] Donna J. Haraway, Staying with the Trouble: Making Kin in the Chthulucene (Durham, NC: Duke University Press, 2016).

[6] Thomas Berry, The Great Work: Our Way into the Future (New York: Bell Tower, 1999).

[7] Emily M. Bender, Timnit Gebru, Angelina McMillan‑Major, and Margaret Mitchell, “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?,” in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (New York: ACM, 2021), 610–623.

[8] International Energy Agency, Electricity 2024: Analysis and Forecast to 2026 (Paris: IEA, 2024).

[9] Eric Masanet et al., “Recalibrating Global Data Center Energy‑Use Estimates,” Science 367, no. 6481 (2020): 984–986.

[10] David Patterson et al., “Carbon Emissions and Large Neural Network Training,” arXiv:2104.10350 (2021).

[11] Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (New Haven, CT: Yale University Press, 2021).

[12] P. Roy et al., “Land‑Use Change in U.S. Data‑Center Regions,” Journal of Environmental Management 332 (2023).

[13] Shaolei Ren et al., “Making AI Less Thirsty: Uncovering and Addressing the Secret Water Footprint of AI Models,” arXiv:2304.03271 (2023).

[14] Global Indigenous Data Alliance, “CARE Principles for Indigenous Data Governance,” 2019.

[15] Sebastian Rieke, Lu Hong Li, and Veljko Pejovic, “Federated Learning on the Edge: A Survey,” ACM Computing Surveys 54, no. 8 (2022).

[16] Peter Kairouz et al., “Advances and Open Problems in Federated Learning,” Foundations and Trends in Machine Learning 14, no. 1–2 (2021): 1–210.

[17] Pete Warden and Daniel Situnayake, TinyML (Sebastopol, CA: O’Reilly, 2020).

[18] Islam, T. Mycelium neural architecture search. Evol. Intel. 18, 89 (2025). https://doi.org/10.1007/s12065-025-01077-z

[19] Thomas Berry, The Great Work: Our Way into the Future (New York: Bell Tower, 1999).

[20] Pete Warden and Daniel Situnayake, TinyML (Sebastopol, CA: O’Reilly, 2020).

[21] Sebastian Rieke, Lu Hong Li, and Veljko Pejovic, “Federated Learning on the Edge: A Survey,” ACM Computing Surveys 54, no. 8 (2022).

[22] David Patterson et al., “Carbon Emissions and Large Neural Network Training,” arXiv:2104.10350 (2021).

[23] Global Indigenous Data Alliance, “CARE Principles for Indigenous Data Governance,” 2019.

[24] Elinor Ostrom, Governing the Commons (Cambridge: Cambridge University Press, 1990).

[25] Emily M. Bender, Timnit Gebru, Angelina McMillan‑Major, and Margaret Mitchell, “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?,” in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (New York: ACM, 2021), 610–623.

[26] Ruha Benjamin, Race After Technology (Cambridge: Polity, 2019).

[27] Safiya Umoja Noble, Algorithms of Oppression (New York: NYU Press, 2018).

[28] Ruha Benjamin, Race After Technology (Cambridge: Polity, 2019).

[29] Safiya Umoja Noble, Algorithms of Oppression (New York: NYU Press, 2018).

[30] Shoshana Zuboff, The Age of Surveillance Capitalism (New York: PublicAffairs, 2019).

[31] Sebastian Rieke, Lu Hong Li, and Veljko Pejovic, “Federated Learning on the Edge: A Survey,” ACM Computing Surveys 54, no. 8 (2022).

[32] Elinor Ostrom, Governing the Commons (Cambridge: Cambridge University Press, 1990).

[33] International Energy Agency, Electricity 2024: Analysis and Forecast to 2026 (Paris: IEA, 2024).

[34] Shaolei Ren et al., “Making AI Less Thirsty: Uncovering and Addressing the Secret Water Footprint of AI Models,” arXiv:2304.03271 (2023).

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Warden, Pete, and Daniel Situnayake. TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. Sebastopol, CA: O’Reilly, 2020.

Whitehead, Alfred North. Process and Reality. New York: Free Press, 1978.

Zuboff, Shoshana. The Age of Surveillance Capitalism. New York: PublicAffairs, 2019.

Full PDF here:

Convergent_Intelligence_Harrelson_2025Download

Mullins in the Political Spotlight

Have to say, I did not have Newsom touring my beloved and small rural hometown of Mullins, SC on the BINGO card for 2025… but glad to see Mullins and the Pee Dee getting some attention from national candidates!

I wasn’t sold on Obama in 2007 until I heard his stump speech in Columbia that year and he rolled out the famous “YES WE CAN” call and response (along with “Fired up” at the same speech…. it was pretty electric and inspiring when he said we can do a better job teaching children how to read in Dillon County)…

Column: Newsom needs to stop kidding around. He’s running for president – Los Angeles Times…

California Gov. Gavin Newsom tours downtown Mullins, S.C., with Mayor Miko Pickett on July 8.

Integral Ecology, AI, and Wage Futures of the Carolinas

Long piece I just published on Carolina Ecology…

Integral Ecology, AI, and Wage Futures of the Carolinas:

The kind of future we want is one where the Carolinas are thriving, ecologically flourishing, socially just, economically inclusive, and spiritually fulfilling. No one will hand us this future ready-made. It will be crafted, decision by decision, action by action, by us, the people of this beautiful corner of Earth.

“Maybe we need more middle-brow in our culture mix today.”

Amen…

How I Learned About Great Literature from Comic Books:

Opinion leaders nowadays would scorn these graphic novels. They would justifiably point out the narrowness of canon enshrined in their garish pages (even though, as the recurring presence of Afro-French author Dumas indicates, there was more range here than you might assume).

They would deride the corny images, loaded with anachronisms and stereotypes. And they would probably mock the middle-class aspirations of parents who bought these ten-cent classics for their children. It’s all so embarrassingly middle-brow.

But maybe we need more middle-brow in our culture mix today.

Thinking Religion 168: Tribalism and Identity with Matthew Klippenstein

Listen Here!

Episode Summary

In this episode of “Thinking Religion,” Sam is joined by Matthew Klippenstein to discuss a wide range of topics, including cultural differences, the development of early Christianities, political dynamics in the USA and Canada, and the philosophical and historical context of monotheism.

Topics Discussed

  1. Cultural Differences and Regional Dialects:
    • Sam and Matthew explore regional cultural differences within the United States, particularly focusing on dialects and food traditions.
    • The significance of regional barbecue styles in South Carolina.
    • Comparison to regional differences in Japan, such as variations in soy sauce.
  2. Early Christianities and Monotheism:
    • Discussion on the origins and development of monotheism in ancient Israel and the influence of early Desert Fathers and Mothers.
    • The role of Josiah’s reforms and the discovery of Deuteronomy in shaping Jewish religious practices.
    • Influence of Platonic philosophy on early Christian thought and the transition from henotheism to monotheism.
  3. Political Dynamics in the USA and Canada:
    • Current political climate in the USA, including the pressures within the Democratic Party for President Biden to step down​ (Politico)​.
    • The complexities of the two-party system in the US and the potential for future changes.
    • Comparison with Canadian politics and the challenges of maintaining political coalitions over long periods.
  4. Philosophical and Sociological Reflections:
    • The concept of tribalism in modern politics and social media’s impact on political identities.
    • Dunbar’s number and its implications for social networks and community sizes.
    • Reflections on the interconnectedness of humanity and the natural world.

Relevant Links

Contact Information

Listener Q&A

  • Have questions or comments about this episode? Leave them in the comments section or reach out to Sam and Matthew directly through their social media profiles.

Basecamp’s New Politics Policy

Basecamp (and Jason) has been a bellwether for how companies operate for almost 20 years now. Here’s an interesting memo for the company that I can only imagine more organizations will be implementing in the coming months / years…

With that, we wanted to put these directional changes on the public record. Historically we’ve tried to share as much as we can — for us, and for you — so this transmission continues the tradition.

1. No more societal and political discussions on our company Basecamp account. Today’s social and political waters are especially choppy. Sensitivities are at 11, and every discussion remotely related to politics, advocacy, or society at large quickly spins away from pleasant. You shouldn’t have to wonder if staying out of it means you’re complicit, or wading into it means you’re a target. These are difficult enough waters to navigate in life, but significantly more so at work. It’s become too much. It’s a major distraction. It saps our energy, and redirects our dialog towards dark places. It’s not healthy, it hasn’t served us well. And we’re done with it on our company Basecamp account where the work happens. People can take the conversations with willing co-workers to Signal, Whatsapp, or even a personal Basecamp account, but it can’t happen where the work happens anymore.

Source: Changes at Basecamp

“Reopen” Domain Surge

Propaganda and misinformation are easy to propagate on the web as one of my mentors, Wayne Porter, would frequently show me. Now is not the time to let our guard down.

That lookup returned approximately 150 domains; in addition to those named after the individual 50 states, some of the domains refer to large American cities or counties, and others to more general concepts, such as “reopeningchurch.com” or “reopenamericanbusiness.com.”

Source: Who’s Behind the “Reopen” Domain Surge? — Krebs on Security

YouTube and “Reinforcing” Psychologies

“The new A.I., known as Reinforce, was a kind of long-term addiction machine. It was designed to maximize users’ engagement over time by predicting which recommendations would expand their tastes and get them to watch not just one more video but many more.

Reinforce was a huge success. In a talk at an A.I. conference in February, Minmin Chen, a Google Brain researcher, said it was YouTube’s most successful launch in two years. Sitewide views increased by nearly 1 percent, she said — a gain that, at YouTube’s scale, could amount to millions more hours of daily watch time and millions more dollars in advertising revenue per year. She added that the new algorithm was already starting to alter users’ behavior.

“We can really lead the users toward a different state, versus recommending content that is familiar,” Ms. Chen said.”

via “The Making of a YouTube Radical” by Kevin Roose in the New York Times

“Invisible Wire Pullers”

Eerily familiar to the American left…

Prideful of their own higher learning and cultivation, the intellectual classes could not absorb the idea that, thanks to “invisible wire-pullers”—the self-interested groups and individuals who believed they could manipulate the charismatic maverick for their own gain—this uneducated “beer-hall agitator” had already amassed vast support. After all, Germany was a state where the law rested on a firm foundation, where a majority in parliament was opposed to Hitler, and where every citizen believed that “his liberty and equal rights were secured by the solemnly affirmed constitution.”

— Read on www.newyorker.com/books/page-turner/when-its-too-late-to-stop-fascism-according-to-stefan-zweig

Defending the Liberal Arts

Long overdue…

The new statement offers a counterargument to the notion that the liberal arts are impractical, and perhaps unnecessary. The disciplines, it argues, increase students’ curiosity, prepare them to be lifelong learners, and offer a foundation for academic freedom. As a result, the associations argue, the benefits of the liberal arts should be available to “all college students and not solely a privileged few.”

— Read on www.chronicle.com/article/2-Associations-Forcefully/243544

By eating less meat and more fruit and…

By eating less meat and more fruit and vegetables, the world could prevent several million deaths per year by 2050, cut planet-warming emissions substantially, and save billions of dollars annually in healthcare costs and climate damage, researchers said.

http://www.nbcnews.com/health/diet-fitness/vegan-eating-would-slash-cut-food-s-global-warming-emissions-n542886