December 13, 2024

PerplexityAI Summary:

The document discusses the evolution of information access and the potential impact of artificial intelligence (AI) on education, work, and society. It highlights several key points:

AI's Transformative Potential

The author envisions a future where AI agents serve as personal consultants, managing various tasks autonomously. This aligns with the concept of "situational awareness" explored by Leopold Aschenbrenner, which anticipates the development of AI researchers capable of self-improvement.

Changing Work Landscape

By late 2024, Google reported that 25% of new code was AI-generated, indicating a significant shift in the nature of work. This trend echoes the predictions of scholars like Erik Brynjolfsson and Andrew McAfee, who have written extensively about the impact of AI on employment and the economy.

Transparency and Democratization

The document advocates for radical transparency in AI development and deployment, suggesting that AI companies should share benefits with the public. This idea resonates with the work of Cathy O'Neil, who has emphasized the importance of algorithmic transparency and accountability.

Post-Labor Society

The author envisions a post-labor world where productivity is decoupled from identity, allowing individuals to explore multiple roles and responsibilities. This concept aligns with the ideas of philosophers like André Gorz, who have explored the potential for automation to liberate humans from traditional labor constraints.

Challenges and Concerns

The document acknowledges concerns about AI's impact on content creation and intellectual property. These issues have been extensively discussed by scholars such as Ryan Abbott, who has written about AI and patent law.

In conclusion, the document presents a vision of a future shaped by AI, emphasizing the need for transparency, equitable distribution of benefits, and a reimagining of work and identity in a post-labor society.

November 6, 2024

Remember when you were a child and got to the “Why?” stage of your life? That time for me, growing up in the Piney Woods of East Texas as a pre-internet 90s kid, my mother, being an overly anxious and exhausted (as well as rage prone) single parent, when the whys came, she’d throw her hands up and say, “Look it up in a dictionary!” Of course, I knew a dictionary was only a few sentences on a topic, hardly able to explain anything in detail. At school, self directed inquiry was hardly acknowledged, if but what little was offered by the school library. Most students today are lectured to in a classroom, then required to perform the same repetitive tasks, priming one for a work environment not too dissimilar, exchanging grades for market output. Such an education system, as well as work environment, was suitable for the 1950s, but now those methods and spaces increasingly leave much to be desired.

Today we take for granted supercomputers in our pockets, now able to consult a new wave of artificial agents. Models can outline a topic and make references to scientific documents when prompted, while accessing the web to book flights and hotel rooms. The next frontier models basing these agents are anticipated to be Nobel winning PhD level thinking tools. This means a personal consultant to manage a variety of agents on your behalf. For institutions, this means a fair portion of administrative tasks performed autonomously.

An essential high level goal among top AI firms is to create an AI researcher, a topic explored in Leopold Aschenbrenner’s essay series ‘Situational Awareness’. This AI researcher or swarm will be able to spend weeks or months crawling the web and reasoning on how to meet objectives for better AI—including the ability to modify its own source code—all of which could happen within three years based on statements from executives in notable AI firms. Approaching the end of 2024, Google confirmed around 25% of new code was AI generated. By the time administrative tasks of entire organizations are able to run autonomously, individuals themselves will have the ability to summon fleets of agents hosted by a variety of AI consultants.

Concerns from content creators like authors and artists over work being used to train models has caused some backlash, but if AI companies work to become more transparent, while sharing the benefits with the general public, subsidized by enterprise and governmental customers, all organizations can follow suit (merge or fade away) and make technical and institutional process transparent, enabling opportunities for impactful customer and citizen engagement. China’s rise as a car manufacturer, considered inadequate twenty years ago, today as it excels as the world’s factory, now exceeds luxury vehicle standards at a standard vehicle price. The next foreseeable controversy will be in AI generated technologies reverse engineered from so-called intellectual property, including the machine-making-machines known as factories, particularly highly specialized products like microchip manufacturing largely based in Taiwan.

With the continued decline in labor value, removal of jobs, compounded by unpayable debt and interest payments, topped off by inflation, this looming condition warrants a new model for the old empire to transition into, or more likely, collapse onto. This new model will likely blur the lines between business and government, as the ethos of the digital commons spreads to environmental and material commons, rationing scarce materials until made abundant or alternatives are found.  

Given few are interested in technical details, AI will likely be summoned to generate modifications based on user preferences (within guardrails), but it should be crucial for users, when prompted, to have the reasoning demonstrated, at any point in the process chain, of a certain conclusion or advocacy for a particular action. One objection to radical transparency is that information could be used to cause harm, yet if access to AI and the physical robotic ecologies soon to follow are evenly shared, freely, shielding the poor or most vulnerable from the neoliberal order (while rendering it obsolete over time), with safety protocols embedded within each agentic link, appropriately distributed common resource pools, as they develop, can provide an ever-rising base to minimize potential malice and nurture trust and good will.

A culture and framework of transparency will make for a better map of the terrain, from 2D to 3D, as needed, expanding our definition of a map to include blueprint or description layers, starting with municipal projects highlighting infrastructural function and maintenance details—like for water, energy, and transport—to the hardware schematics of objects populating the environment. Contracts for physical materials, for example, will be labeled and tracked online, determining source, scarcity, with an environmental impact profile to be examined and interrogated using disciplines like circular economy and industrial ecology. Workers can be politely scrutinized by citizens and freely observed globally to provide potential templates for other regions. This is a world where elected officials do little more than host events, while citizen preferences determine laws and actions, increasingly executed by robotic ecologies. We will transition from a population of workers to that of conductors.

A post-labor world will mean a place where productivity is no longer entangled with identity. We’ll be free to take on more identities and responsibilities to our fullest capacities. We will work to evolve ourselves in harmony with legacy ecologies: Mother Earth. A world that enables warm heartfelt connections and play is on the horizon. What does that world look like to you?      

NWC