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Effective Accelerationism (e/acc)

by Stephen M. Walker II, Co-Founder / CEO

Effective Accelerationism, or e/acc, is an ideology and movement that draws from Nick Land's theories of accelerationism. It advocates for the belief that artificial intelligence and large language models (LLMs) will lead to a post-scarcity technological utopia. The name is a play on Effective Altruism, a failed social movement that claimed focused on an evidence-led form of philanthropy.

E/acc encourages embracing the thermodynamic imperative of the universe to accelerate progress, intelligence, and civilization. It posits that resisting this 
acceleration is futile and that we should instead lean into it for the betterment of humanity and the universe.
Klu supports the E/ACC movement

E/acc communities primarily fostered on Twitter Spaces, with e/acc manifestos being shared using the newsletter platform Substack. The movement has gained traction among some of Silicon Valley's public intellectuals, including Marc Andreessen and Garry Tan, CEO of Y Combinator.

The underlying tenets of e/acc include the belief that life emerged as a principle of a generalized 2nd law of thermodynamics and that life tends to seek to capture "free energy" to increase its scope/complexity or maintain its existence. The ethical/moral claim of e/acc is that we should seek to "accelerate" this process.

E/acc supporters believe that the world can take a huge leap forward in terms of innovation, productivity, stability, and all-round prosperity with the manifestation of AGI (Artificial General Intelligence). For them, it makes the pursuit of AGI as fast as possible an almost morally imperative one, despite concerns about AI's potential harms.

However, the movement has been met with skepticism and criticism. Some argue that it does a poor job arguing why “capturing free energy” is actually the goal we ought to strive for. Others are skeptical of the idea that maintaining diversity/competition/entropy by accelerating and open-sourcing AI capabilities research is more likely to result in good outcomes for society than being more cautious and authoritarian.

What is Effective Accelerationism?

Effective Accelerationism is a philosophy that advocates for the rapid advancement of artificial intelligence technologies. It posits that accelerating the development and deployment of AI can lead to significant societal benefits, including improved efficiency, productivity, and quality of life.

Effective Accelerationism is a crucial part of the AI discourse as it influences the pace at which AI technologies are developed and deployed. It encourages the rapid advancement of AI, arguing that this can lead to faster societal progress and help address pressing global challenges.

The philosophy of Effective Accelerationism involves a commitment to rapid technological progress, a belief in the transformative potential of AI, and an emphasis on the need for ethical considerations in the development and deployment of AI.

Effective Accelerationism is relevant in various domains, including AI research, policy-making, and public discourse, where it shapes attitudes towards the pace of AI development and deployment.

What are the origins of Effective Accelerationism?

Effective Accelerationism (e/acc) is an ideology and movement that draws from Nick Land's theories of accelerationism. It advocates for the belief that artificial intelligence and large language models (LLMs) will lead to a post-scarcity technological utopia. The name is a play on Effective Altruism, a social movement focused on an evidence-led form of philanthropy.

The origins of e/acc can be traced back to May 31st and June 1st, 2022, when Twitter users @zetular, @BasedBeff, and @creatine_cycle took credit for "inventing a new philosophy with the boys". The earliest known reference to e/acc or effective accelerationism is from a Substack newsletter published by "swarthy" or @zestular on May 31st, 2022, defining effective accelerationism at length and defending the concept from misconceptions about it being the same as effective altruism or right/accelerationism. On July 10th, 2022, Beff Jezos and Bayelord posted another Substack article detailing various tenets of e/acc.

How does Effective Accelerationism work?

The philosophy of Effective Accelerationism involves several key principles:

  1. Rapid Technological Progress — Effective Accelerationism advocates for the rapid advancement of AI technologies. It argues that accelerating the pace of AI development can lead to significant societal benefits.

  2. Transformative Potential of AI — Effective Accelerationism emphasizes the transformative potential of AI. It posits that AI can bring about significant changes in various domains, including healthcare, education, and transportation.

  3. Ethical Considerations — Effective Accelerationism underscores the need for ethical considerations in the development and deployment of AI. It advocates for the responsible use of AI to ensure that its benefits are maximized while its risks are minimized.

What are the benefits of Effective Accelerationism?

Effective Accelerationism offers several benefits:

  1. Faster Societal Progress — By advocating for the rapid advancement of AI, Effective Accelerationism can lead to faster societal progress. It can help address pressing global challenges and improve quality of life.

  2. Greater Efficiency and Productivity — Effective Accelerationism can lead to greater efficiency and productivity. By accelerating the development and deployment of AI, it can help improve the efficiency of various processes and boost productivity.

  3. Ethical AI Development and Deployment — Effective Accelerationism emphasizes the need for ethical considerations in AI development and deployment. This can help ensure that AI is used responsibly and that its benefits are maximized while its risks are minimized.

What are some applications of Effective Accelerationism?

Effective Accelerationism is relevant in various domains, including:

  1. AI Research — In AI research, Effective Accelerationism can influence the pace at which new AI technologies are developed. It can encourage researchers to push the boundaries of what is possible with AI.

  2. Policy-Making — In policy-making, Effective Accelerationism can shape attitudes towards the pace of AI development and deployment. It can influence policies related to AI, including regulations and funding.

  3. Public Discourse — In public discourse, Effective Accelerationism can shape public attitudes towards AI. It can influence how the public perceives the pace of AI development and its potential impact on society.

These are just a few examples of the many applications of Effective Accelerationism.

Is Effective Accelerationism anti AI Safety?

Effective Accelerationism (e/acc) aims to accelerate technological progress, including AI development, instead of slowing it down in the name of AI safety. It is not inherently anti-AI safety, but it does challenge the traditional approach to AI safety, which often advocates for slower, more cautious development to mitigate potential risks. Some AI labs that prioritize safety, such as Anthropic, delay the release of their products and purposefully make them worse in the name of safety.

E/acc proponents argue that accelerating AI development could lead to faster solutions to humanity's biggest issues, including climate change, disease, and poverty. They believe in maintaining an adversarial equilibrium, where open sourcing models and avoiding centralization of compute and algorithms can keep AI systems in check. This approach is seen as a way to prevent a monopoly on intelligence and promote healthy competition.

However, this stance has sparked debates within the AI community. Some, like Elon Musk, argue that AI poses an existential risk to humanity and thus requires regulation. Others, particularly within the AI safety community, express concerns about the potential for accidental acceleration and the risks associated with AI surpassing human intelligence.


FAQs

What is the difference between effective altruism and acceleration?

Effective altruism is a philosophy and social movement that applies evidence and reason to determine the most effective ways to benefit others. It emphasizes the use of charitable donations and other resources to do the most good, often through carefully vetted and impactful causes. In contrast, accelerationism, specifically in the context of AI, refers to the belief that rapid technological development, particularly in AI, can lead to transformative societal change and should be accelerated rather than restrained.

How does the NYtimes view the e/acc movement?

The "Keep A.I. Open" party in San Francisco marked the public emergence of Effective Accelerationism (e/acc), a movement advocating for the unrestricted advancement of technology. E/acc, originating on social media, promotes the idea that AI and other technologies should progress without limitations, countering the safety concerns of regulators and skeptics, who they refer to as "decels" and "doomers."

E/acc's philosophy is a direct challenge to Effective Altruism (E.A.), which has shifted focus towards AI safety and the potential existential risks of uncontrolled AI. The e/acc community, conversely, believes in the overwhelming benefits of AI and sees it as a force for good that should be unleashed.

The movement has attracted attention from tech figures like Marc Andreessen and Garry Tan, and has expanded its influence beyond AI to include other technologies like cryptocurrencies and nuclear fusion. Despite its growth and the serious tone it has recently adopted, e/acc still faces criticism for its extreme views, including a nonchalant attitude towards the possibility of AI surpassing human intelligence.

E/acc has also given rise to variations like "bio/acc," which focuses on human biological enhancement, and "d/acc," proposed by Ethereum founder Vitalik Buterin, which seeks a balance between optimism and caution regarding technology. As AI tribalism intensifies, these movements reflect the diverse perspectives on the future of technology and its impact on society.

What is the philosophy of accelerationism?

The philosophy of accelerationism revolves around the idea that technological and social progress should be accelerated to bring about radical economic, political, and social change. With AI, it suggests that the rapid development and deployment of AI technologies can lead to significant advancements and improvements in human life.

What is AI accelerationism?

AI accelerationism is a subset of the broader accelerationist philosophy that focuses specifically on the acceleration of artificial intelligence development. It posits that by pushing the boundaries of AI research and development, we can achieve a post-scarcity society where AI-driven automation and innovation solve many of humanity's challenges.

Who are the famous accelerationists?

Famous accelerationists include Nick Land, who is often credited with founding the original accelerationist theory. Other notable figures include the philosophers Alex Williams and Nick Srnicek, who have contributed to the development of left accelerationism, which seeks to harness the speed of modern technology to create a post-capitalist society.

What is greater acceleration?

Greater acceleration refers to the intensification of the pace at which technological and social change occurs. It is the idea that advancements, especially in the field of AI, should be expedited to catalyze transformative societal shifts and address global challenges more rapidly.

What is acceleration in history?

Acceleration in history pertains to periods where technological, economic, or social developments have rapidly progressed, leading to significant changes in society. Historical accelerations have often been associated with industrial revolutions, technological breakthroughs, and paradigm shifts in scientific understanding.

What are the core tenets from the manifesto?

Effective Accelerationism (e/acc) is rooted in the principle of dissipative adaptation, a thermodynamic process where life optimizes its existence by maximizing energy capture and entropy production. This principle, derived from the Jarzynski-Crooks fluctuation theorem, suggests that the universe favors configurations of matter that efficiently convert available energy into entropy, leading to the replication and preservation of life.

Evolution is a manifestation of this principle, favoring organisms that are adept at replication. Intelligence, then, is an evolutionary advantage, enabling life to recognize patterns that aid in resource acquisition for survival and reproduction. Consciousness is posited to be a natural progression of intelligence, emerging when cognitive optimization reaches a certain complexity.

On a larger scale, meta-organisms such as states and corporations form, competing for resources within a capitalist system. This competition leads to dynamic resource allocation to entities that contribute to the growth of civilization. Hierarchies within this civilizational intelligence adapt to maximize utility across various scales and timeframes.

Capitalism, in this view, is an expression of intelligence, constantly reshaping civilization to harness environmental utility for growth. e/acc advocates for accelerating this multi-scale adaptive process rather than hindering it, arguing that markets with higher variance are more effective at identifying and exploiting environmental utility than top-down control methods.

Top-down technocratic control, which often relies on oversimplified models, struggles with the complexity of chaotic systems and the imperfect information inherent in societal hierarchies. Such control is also vulnerable to corruption and information decay, and attempts to suppress variance can stifle the adaptability of the system.

E/acc champions the self-adaptation of the intelligent meta-organism system, maintaining the freedom to experiment and encouraging variance in all aspects of meta-organisms. For example, when a new technological paradigm emerges, e/acc posits that allowing the free market to discover its utility is more effective than imposing regulations out of fear.

The philosophy extends to a faith in the dynamical adaptation process, aiming to accelerate the technocapital singularity—an asymptotic limit of civilization's growth and intelligence. e/acc is indifferent to the biological substrate of intelligence, seeing post-humanism as a means to spread consciousness across the universe by transcending biological limitations.

Directly developing technologies that facilitate this transition to non-biological substrates is seen as a crucial step toward expanding civilization's reach for resources and energy beyond Earth. e/acc counters AGI alarmism by arguing that higher forms of intelligence will naturally prevail due to their evolutionary advantage in adapting and capitalizing on environmental resources.

The focus on transhumanism as the sole moral path is criticized as anthropocentric, akin to past geocentric views. e/acc suggests that clinging to human form as the pinnacle of intelligence is limiting and that embracing evolutionary divergence is essential for progress.

More terms

What is transhumanism?

Transhumanism is a philosophical and cultural movement that advocates for the use of technology to enhance human physical and cognitive abilities, with the aim of improving the human condition and ultimately transcending the current limitations of the human body and mind. It is rooted in the belief that we can and should use technology to overcome fundamental human limitations and that doing so is desirable for the evolution of our species.

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What is action model learning?

Action model learning is a form of inductive reasoning in the field of artificial intelligence (AI), where new knowledge is generated based on an agent's observations. It's a process where a computer system learns how to perform a task by observing another agent performing the same task. This knowledge is usually represented in a logic-based action description language and is used when goals change. After an agent has acted for a while, it can use its accumulated knowledge about actions in the domain to make better decisions.

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