Can AI do AI Research?

AI research can be carried out entirely within digital spaces, making it ripe for automation. Recent efforts have demonstrated that AI systems are capable of carrying out the whole process of research from ideation to publishing. Startup Sakana.ai has created an 'AI Scientist' that independently chooses research topics, conducts experiments, and publishes complete papers showing its results. While the quality of this work is still only comparable to an early-stage researcher, things will only improve from here.

Judging Social Situations

AI chatbots, including Claude and Microsoft Copilot, can outperform humans in evaluating social situations. In an established 'Situational Judgment Test', these AI systems consistently selected more effective responses than human participants.

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Analyzing Scientific Literature

While language models are known to hallucinate information, this tendency can be reduced. PaperQA2, an LLM optimized to reliably provide factual information, was able to match or exceed human subject matter experts across a range of realistic literature review tasks. The summary articles it produced were found to be more accurate than those written by human authors.

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Writing Emotive Poetry

A study has shown that non-expert readers can no longer tell AI-authored poems from those written by acclaimed human poets. The AI poems were also rated higher in rhythm and beauty.

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Writing Post-surgical Operative Reports

Surgeons take painstaking notes of the actions they carry out during surgeries, collecting them into narrative form as an 'operative report'. A machine vision system was trained to watch surgery footage and produce such reports. It did so with higher accuracy (and much higher speed) than human authors.

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Developing New Algorithms

AIs can find innovative solutions to difficult coding problems when given an appropriate framing. For example, a dedicated system called AlphaDev was trained to play a game about creating sorting algorithms. The algorithms it discovered were novel and outperformed existing human-authored benchmarks.

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Who is Building AGI?

The following companies have explicitly stated they intend to develop AGI, either through public statements or in response to FLI’s 2024 AI Safety Index survey:

Anthropic

OpenAI

Google DeepMind

Meta

x.AI

Zhipu AI

Alibaba

DeepSeek

How can we avoid AGI?

There are policies we can implement to avoid some of the dangers of rapid power seeking through AI. They include:

Compute accounting
Standardized tracking and verification of AI computational power usage

Compute caps
Hard limits on computational power for AI systems, enforced through law and hardware

Enhanced liability
Strict legal responsibility for developers of highly autonomous, general, and capable AI

Tiered safety standards
Comprehensive safety requirements that scale with system capability and risk

TOMORROW’S AI

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Os Trabalhinhos

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Intended Use: Corporate/Finance

Technology Type: Robots/Machines

Runaway Type: Social Enfeeblement

Control Lever: Innovation/Public Sector Engagement

Primary Setting: Brazil

Automation and Unrest

Across the 2030s, automation reshapes the global economy. Millions are displaced in Vietnam’s textile mills, China’s factories, and beyond. Protests and strikes roil manufacturing hubs, while Brazil’s northeastern cities, battered by 18% unemployment, face economic collapse. Rather than fight the current, Brazil resolves to lean into designing AI tools for economic revitalization.

‘Universal Basic Labor’

A coalition of Brazil’s Ministry of Innovation and tech firm Cooperabótico pioneers a radical idea: Universal Basic Labor offered by artificially intelligent machines. Drawing inspiration from models like community land trusts and energy cooperatives, they decide to structure ownership collectively. Small, durable worker robots affectionately called Trabalhinhos are distributed through digital cooperatives, with each household owning a fractional share. These little workers handle basic, repetitive tasks in infrastructure upkeep, farming, and light manufacturing. Revenue from government contracts and private industry partnerships funds local services, providing the opportunity to trade labor hours for basic income.

Little Workers

Within two years, household incomes rise by 22% in participating cities. Public infrastructure thrives as Trabalhinhos maintain roads, parks, and sanitation at a fraction of the former cost. Farmers boost yields without exploitative labor. Perhaps most importantly, resident owners are encouraged to pursue AI-assisted retraining programs in their newfound free time. In Vietnam and Bangladesh, labor activists pressure corporations to adopt Brazil's ethical automation model.

Fairness and Oversight

To prevent monopolization, no individual can control more than 0.5% of a city’s total robotic labor pool. AI governance panels, composed of local representatives, oversee work distribution, much like traditional cooperative boards. Yet concerns emerge: some residents become overly reliant on robotic labor, outsourcing daily physical needs and growing sedentary. People become a minority among crowds of Trabalhinhos in some community spaces. In response, operational limits are introduced: Os Trabalhinhos are barred from tasks that promote physical and social engagement, such as communal gardening, local markets, and traditional crafts.

Can It Scale?

The Brazilian model spreads, but its future remains uncertain. Funding shortfalls threaten to erode its cooperative structure, prompting wealthier cities to explore privatized alternatives. While younger generations embrace their freedom from drudgery, elders lament the decline of traditional communal rhythms. In contrast to other countries, where labor automation has sparked unrest, Os Trabalhinhos have actually strengthened Brazil’s social fabric. These humble robots stand as proof that automation can serve human dignity, if humans – all humans – retain personal control.

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