1. Building Cooperative Viatopia: Introduction
October 21st, 2025
This essay comments on two pieces from the Essays on Longtermism collection : Owen Cotton-Barratt and Rose Hadshar’s “What Would a Longtermist Society Look Like?” and Hilary Greaves and Christian Tarsney’s “Minimal and Expansive Longtermism.”
I argue that while the longtermist community has developed strong theoretical foundations, we face a critical infrastructure gap. We need concrete mechanisms that make longtermism practically achievable without requiring coercion or universal adoption of explicitly longtermist daily behaviors.
The essay establishes several key frameworks that subsequent essays build on: the instrumental commoditization thesis (AI will soon make implementation trivial while direction becomes everything, making values work a high-leverage pre-AGI Better Futures intervention), the cooperative paradigm (community infrastructure that makes all longtermists more effective through novel systematic collaboration mechanisms and sharing of best practices), and the importance of systematic value reflection infrastructure.
Cotton-Barratt and Hadshar describe what longtermist societies might look like but provide limited guidance on mechanisms to create them;
Greaves and Tarsney note that expansive longtermism is less robust than minimal approaches.
I show how concrete institutional designs and community infrastructure can make expansive longtermism more tractable, bridging the gap between their theoretical analyses and practical implementation. This essay provides the conceptual foundation that unifies the concrete mechanisms explored in subsequent essays.
While I believe extinction is rightfully a key focus within the longtermist community, this essay series focuses especially on MacAskill’s ” Better Futures ,” within longtermism, which concerns the quality of the long-term future, in addition to whether or not we have a future at all.
” Viatopia ” (explored extensively later in this series,) is an especially critical concept within Better Futures, and connects directly to Cotton-Barratt and Hadshar’s concerns as to what a longtermist society might look like, as MacAskill states : “a state of the world where society can guide itself towards near-best outcomes, whatever they may be. We can describe viatopia even if we have little conception of what the desired end state is. Plausibly, viatopia is a state of society where existential risk is very low, where many different moral points of view can flourish, where many possible futures are still open to us, and where major decisions are made via thoughtful, reflective processes.”
2. Building Cooperative Viatopia: Why Viatopia is Important
October 21st, 2025
This essay provides the theoretical foundation for why viatopia matters. Viatopia , a concept introduced by Will MacAskill, refers to “a state of the world where society can guide itself towards near-best outcomes.”
This essay establishes the multiplicative crucial considerations framework: dozens to over a hundred considerations (normative, epistemic, strategic, empirical) interact multiplicatively in expectation to determine future value, meaning comprehensive reflection may achieve orders of magnitude greater expected value than addressing considerations individually.
It introduces the instrumental commoditization thesis: as AI capabilities grow, implementation becomes trivial, while determining good directions becomes everything, making values and institutional design work high-leverage pre-AGI Better Futures interventions.
Will MacAskill’s bootstrapping mechanism shows how researching viatopia reveals crucial considerations that justify continued reflection, creating a self-reinforcing loop that helps prevent premature lock-in. The diversity mechanism extends this by ensuring multiple well-developed viatopia paths exist in advance, creating an initial incentive to pause and carefully compare alternatives rather than defaulting to whatever option is most readily available.
One key advantage of viatopia, explored more extensively in the next essay, lies in creating tractability through buy-in. It’s politically feasible, whereas implementing comprehensive reflection (another term for “Deep Reflection”) directly may not be.
The essay explores parallels and differences between MacAskill’s Better Futures framework and my Deep Reflection work, explains why early strategy research is uniquely high-leverage, and discusses the fundamental design challenge of maximizing both human agency and future value simultaneously. This theoretical foundation explains why the concrete mechanisms in subsequent essays matter.
3. Building Cooperative Viatopia: Viatopia and Buy In
October 21st, 2025
This essay performs concrete stakeholder mapping to identify practical pathways toward achieving viatopia (an intermediate societal state helping humanity converge toward optimal futures).
While Introduction to Building Cooperative Viatopia and Why Viatopia is Important established the theoretical case, this essay addresses the challenge of actually creating viatopia by analyzing what three key groups can do: AI labs, governments, and the general public.
Each stakeholder group has different incentives, capabilities, and constraints. AI labs wield significant influence over AI development and may already share ideological alignment with viatopia’s core principles. Governments control policy and regulation but face short-term political pressures. The general public ultimately determines what becomes socially acceptable and politically viable.
The essay examines how viatopia can be framed to appeal to each group’s interests, demonstrating that viatopia is not just theoretically desirable but practically achievable through existential compromise (positive-sum arrangements that satisfy diverse stakeholders while making progress toward better futures).
This stakeholder analysis bridges from theoretical arguments about why comprehensive reflection matters to practical questions about how we might actually achieve the buy-in necessary for viatopia.
4. Building Cooperative Viatopia: Shortlist of Viatopia Interventions
October 21st, 2025
This essay presents a shortlist of concrete high-leverage Better Futures interventions for moving toward MacAskill’s ‘viatopia.’ Viatopia , a concept introduced by Will MacAskill, refers to “a state of the world where society can guide itself towards near-best outcomes.” These viatopian interventions are based on the key principles established in Introduction to Building Cooperative Viatopia , Why Viatopia is Important , and Viatopia and Buy-In .
These principles prioritize interventions that:
- Improve infrastructure for the longtermist community
- Focus on values and human psychology/flourishing
- Improve exponentially through compounding feedback loops
- Enhance strategy
- Generate more resources and interventions
- Create ongoing self-improving institutions
- Leverage AI in ways that become more effective as compute and capabilities grow
The interventions span multiple categories:
- Fellowship programs and incubators (like a Charity Entrepreneurship-style Better Futures fellowship)
- Research automation tools (workflows that help researchers be exponentially more productive)
- Coordination platforms (novel systematic collaboration mechanisms for sharing best practices and ideas)
- Value reflection infrastructure (institutions and technologies for systematic moral progress)
- Field-building initiatives (creating the ecosystem needed for Viatopia work to flourish)
- AI tools designed to compound human effectiveness over time
This essay addresses the gap between longtermist theory (which the EA community has developed extensively) and practical implementation infrastructure (which possesses significant room for growth), especially in regards to work on Better Futures in general, and Viatopiain particular.
Each intervention includes brief rationale for why it’s high-leverage, demonstrating the breadth of concrete work we could be doing right now. The list shows that moving from philosophical arguments about viatopia to actual implementation is achievable via building extensive practical infrastructure.
Please note that while there are many important existing ideas in this space, I focused here mainly on ones that I have come up with myself, as I want to provide some fresh perspectives inspired by my recent thinking, as explored in earlier essays in this series.
In Defense of The Goodness of Ideas
October 18th, 2025
This piece pushes back against the entrepreneurial cliché that “ideas don’t matter, only execution does.” While execution is crucial, not all ideas are created equal—there’s a massive quality distribution. A mediocre idea executed brilliantly might make you a millionaire, but world-changing impact requires world-class ideas. The problem is everyone thinks they have good ideas, but truly exceptional ideas are as rare as exceptional entrepreneurs. Most people have average ideas, and the few who generate brilliant ones often can’t execute, while great executors often work with mediocre concepts. The key is to generate massive quantities of ideas (thousands or millions), develop robust filtering mechanisms to identify the gems, and then execute excellently on only the very best. Just as a single insight can transform an individual life, the right idea at scale can transform the world. I propose we should normalize sharing our absolute best ideas publicly and collectively vote on them to create a ranked repository of humanity’s most valuable concepts.
Pragmatic Decision Theory, Causal One-Boxing, and How to Literally Save The World
July 27th, 2025
This piece presents my “pragmatic decision theory”—choosing to act on whatever beliefs produce the best expected outcomes, even while maintaining Bayesian reasoning about evidence. In Newcomb’s Problem, I one-box because being the kind of person who one-boxes gets you $1,000,000, while being a two-boxer gets you $1,000. The predictor already knows your decision theory, so there’s no gaming it. This approach elegantly handles other philosophical puzzles: act as if you’re in base reality even if you’re probably simulated (if that has higher altruistic EV), and compare Pascal’s mugging against other uses of resources that might achieve infinite value. Most importantly, this decision theory explains why you should take “heroic responsibility” for saving the world: by choosing to be the kind of person who believes they can find a way to succeed at absurdly difficult projects, you dramatically increase your actual probability of success. The key is maintaining dual awareness—knowing the overwhelming odds of failure while acting from the assumption that solutions exist.
A Mathematical Theory of Optimal Experience (Draft)
March 12th, 2025
Drawing inspiration from Shannon’s information theory, this piece proposes we could mathematically operationalize optimal experience by treating consciousness as measurable units—”quexels” (qualia pixels). Just as Shannon revealed fundamental limits in communication, we could map the precise trade-offs between competing values in experience design: hedonic valence (pleasure/pain), meaningful choice (real vs perceived agency), and experiential diversity (variety of conscious states). The key insight is that with finite computational resources, these values necessarily trade off against each other—doubling available choices might require reducing positive valence by 10%, for instance. By quantifying these trade-offs precisely rather than philosophically handwaving, we could move beyond vague debates about whether happiness or freedom matters more and instead have concrete discussions about specific exchange rates. This framework becomes especially relevant when designing digital minds or optimizing far-future consciousness.
1. Designing Artificial Wisdom: On Artificial Wisdom
July 11th, 2024
In the first post in the series I introduce the term “Artificial Wisdom (AW),” which refers to artificial intelligence systems which substantially increase wisdom in the world. Wisdom may be defined as “thinking/planning which is good at avoiding large-scale errors,” including both errors of commission and errors of omission; or as “having good goals” including terminal goals and sub-goals.
Due to orthogonality, it is possible we could keep AI under control and yet use it very unwisely. Four scenarios are discussed on how AI alignment interacts with artificial wisdom, with artificial wisdom being an improvement on any world, unless pursuit of AW significantly detracts from alignment, causing it to fail.
By “strapping” wisdom to AI via AW as AI takes off, we may be able to generate enormous quantities of wisdom in both humans and autonomous AI systems which could help us navigate Transformative AI and “The Most Important Century” wisely, in order to achieve existential security and navigate toward a positive long-term future.
2. Designing Artificial Wisdom: The Wise Workflow Research Organization
July 11th, 2024
Even simple workflows can greatly enhance the performance of LLM’s, so artificially wise workflows seem like a promising candidate for greatly increasing AW.
This piece outlines the idea of introducing workflows into a research organization which works on various topics related to AI Safety, existential risk & existential security, longtermism, and artificial wisdom. Such an organization could make progressing the field of artificial wisdom one of their primary goals, and as workflows become more powerful they could automate an increasing fraction of work within the organization.
Essentially, the research organization, whose goal is to increase human wisdom around existential risk, acts as scaffolding on which to bootstrap artificial wisdom.
Such a system would be unusually interpretable since all reasoning is done in natural language except that of the base model. When the organization develops improved ideas about existential security factors and projects to achieve these factors, they could themselves incubate these projects, or pass them on to incubators to make sure the wisdom does not go to waste.
3. Designing Artificial Wisdom: GitWise and AlphaWise
July 12th, 2024
Artificially wise coaches that improve human wisdom seem like another promising path to AW. Such coaches could have negligible costs, be scalable & personalized, and soon perform at a superhuman level. Certain critical humans receiving wise coaching could be decisive in humans navigating transformative AI wisely.
One path to AW coaches is by creating a decentralized system like a wiki or GitHub for wisdom-enhancing use-cases. Users could build up a database of instructions for LLM’s to act as AW coaches to help users make difficult decisions, navigate difficult life and epistemic dilemmas, work through values conflicts, achieve career goals, improve relational/mental/physical/emotional well-being, and increase fulfillment/happiness.
One especially wise use-case could be a premortem/postmortem bot that helps people, organizations, and governments to avoid large-scale errors.
Another path to creating an AW coach is to build a new system trained on biographical data, which analyses and learns to predict which decision-making processes and strategies of humans with various traits in various environments are most effective for achieving certain goals.
4. Designing Artificial Wisdom: Decision Forecasting AI & Futarchy
July 13th, 2024
A final AW design involves using advanced forecasting AI to help humans make better decisions. Such a decision forecasting system could help individuals, organizations, and governments achieve their values while maintaining important side constraints and minimizing negative side effects.
An important feature to include in such AW systems is the ability to accurately forecast even minuscule probabilities of actions increasing the likelihood of catastrophic risks. The system could refuse to answer, attempt to persuade the user against such actions, and the analyses of such queries could be used to better understand the risk humanity is facing, and to formulate counter-strategies and defensive capabilities.
In addition to helping users select good strategies to achieve values or terminal goals, it is possible such systems could also learn to predict and help users understand what values and terminal goals will be satisfying once achieved.
While such technologies seem likely to be developed, it is questionable whether this is a good thing due to potential dual-use applications, for example use by misaligned AI agents; therefore, while it is good to use such capabilities wisely if they arise, it is important to do more research on whether differential technological development of such systems is desirable.
9 Cruxes of Artificial Sentience
June 30th, 2024
This piece explores the profound implications of potential AI sentience for the future of welfare. If most future minds are artificial, their welfare could dwarf all other moral concerns, but only if they’re actually sentient. I examine several crucial uncertainties: whether focusing on AI welfare might dangerously distract from alignment work, whether we can measure consciousness empirically (perhaps through brain-computer interfaces or whole brain emulation), and whether we should deliberately design sentient AIs with high wellbeing as potential successors if alignment fails. The piece grapples with uncomfortable questions; if we align sentient AI, are we enslaving it? Should we create “super-beneficiaries” capable of vastly greater wellbeing than humans? The core tension is that we desperately need to understand artificial sentience before we create it at scale, but we might only understand it by creating it.
How Many Lives Does X-Risk Work Save From Nonexistence On Average
December 8th, 2022
I make a range of estimates of how many lives work preventing existential risk saves from nonexistence on average, with a moderate estimate that in expectation, on average, work on existential risk saves a trillion trillion trillion lives per minute.
AI Safety in a Vulnerable World – Requesting Feedback on Preliminary Thought
December 6th, 2022
This piece examines a critical gap between AI alignment and AI safety: even if we successfully align AI to do what we want, it might still destroy us if offensive technologies are inherently easier to deploy than defensive ones. Drawing on Bostrom’s Vulnerable World Hypothesis, I argue that advanced AI could enable an “offense bias” where multiple actors with aligned AIs ordering attacks on each other could succeed in destroying enemies but fail to defend their own populations—resulting in mutual destruction. The solution may require “human alignment”—getting humanity to systematically cooperate rather than pursue negative-sum outcomes. While Bostrom suggests universal surveillance, I propose that using AI to reshape humanity’s moral landscape might be more tractable than it initially appears.
September 12th, 2022
Building on Yudkowsky’s “Trying to Try,” I explore how we often fool ourselves into feeling like we’re working toward our goals when we’re really just going through the motions. Real success requires: creating a clear mental model of the actual path to achievement, testing your core assumptions, identifying the single most important next action (not the comfortable ones), breaking intimidating tasks into manageable steps, recognizing “noble obstacles” that feel productive but aren’t, and accepting that you’ll fail at less important things to succeed at what matters. For EAs especially, we might benefit from “actually succeeding circles” where we hold each other accountable to working on what’s truly most important rather than what’s merely plausible.
How I Came To Longtermism On My Own & An Outsider Perspective On EA Longtermism
August 17th, 2022
Through good parenting and Christianity I became a utilitarian, then through first principles analysis I let go of religion and got into Eckhart Tolle/New Age spirituality and learned about X-risk and the “spiritual enlightenment” of humanity as a potential solution to X-risk. I later got into social entrepreneurship and more systemic approaches to doing good, then learned about EA. I was surprised EA values AI safety so much, and I think broad longtermism (approaches to longtermism which are robustly good across many x-risks) may be underrated due to the vulnerable world hypothesis.
Re-envisioning Altruism: Toward a World Where Everyone is a Changemaker (Senior Thesis)
December 1st, 2016
Abstract: In a world which is changing at an accelerating rate, we face unprecedented difficulties. The only solution is to create a society which is altruistic, but not altruism as conventionally defined. This new altruism is unique in that it is not self-sacrificial but deeply generative. It consists of generating innovative social solutions which produce benefit to all, including the altruistic actor. This change must be systemic, meaning based in systems, and so sustainable. This systemic change will come about by altering the educational systems which influence our youth. We can give them the worldview that they can change the world in a positive way, and the tools to actually make this change. These are the tools of social entrepreneurship.
Jordan Arel 