It is October 25th, 2045, in San Francisco, California where Alejandra is an artificial intelligence engineer at Orange Train. Alejandra who is 37 identifies as a woman, is in a polyamorous marriage, and is a dual citizen of the United States and Uruguay. She immigrated to the US in 2030 after her family was forced to abandon their farm due to climate change.

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Alejandra was most productive in the final hours of the four-day work week. On Thursday afternoons the office was empty, and she could talk with the Orangenie, the AGI machine she had helped build. Orange Train (OT) – the company behind Orangenie – had entered uncharted territory in AI when it decided to build a commonsense AGI machine whose purpose was to do the heavy lifting of difficult decision making. “Where should I raise my family?” “Which meetings can I skip that will anger the fewest people?” “Who should I support for school board?” Climate change, disease, and the increasing complexity of everyday life, politics, and culture had made answering questions like these ever more difficult.

To build Orangenie, OT engineers had developed a new technique for harnessing BCI implants to map the brain’s neuronal pathways. These pathways combined with a better understanding of sub-atomic randomness informed Alejandra’s discovery of the new neural network on which Orangenie was built. The business model followed quickly: give the ultra-wealthy answers and explanations for the hardest decisions they have to make.

Despite loving the technical aspect of her work, Alejandra had become disillusioned. OT executives were militant about keeping Orangenie to themselves, their wealthy customers, and the American government – and strong American IP laws and North America Bloc export allowed them to do so. Alejandra believed that OT did not share Orangenie more broadly because the executives enjoyed the social capital that accompanied its exclusivity more than monetary gains. She hated this decision. Back in Uruguay, her family had to balance paying for her grandpa’s dementia treatment while also saving for retirement. She felt decisions her family had to make were more complex and had far greater consequences than those of the wealthy Americans who sought Orangenie’s help.

Leaving work for the weekend, Alejandra swung her car – or rather, the car swung itself – into the self-driving lane of the highway. She still drove because she liked being able to switch into human mode and feel the uncertainty and risk that comes with human judgement. As her car drove, Alejandra passed the Bay’s floating barge nuclear power plant. She was initially skeptical about nuclear, but the Department of Energy’s “Nuclear Near You!” campaign had shifted her – and 85% of the population’s – thinking.

Alejandra met Mills and Unity (her husband and wife) at their favorite bar – Spotless – for dinner. Spotless was the first restaurant in San Francisco to have a fully robotic kitchen and serving staff but was also the first to comply with legislation that relegated robotic workers to menial tasks. They had re-hired human workers for skilled and customer-facing roles. Like many restaurants, Spotless was entirely vegan. The European Union’s release of the Nicomachus AGI touched off a global moral revolution whose chief result was a surge of support for animal rights. Imbued with the values of the EU’s Charter of Fundamental Rights, Nicomachus swayed visitors in favor of actions that would reduce animal harm. Moreover, because Nicomachus effortlessly understood visitors’ motivations, values, and beliefs it could tailor responses to be more effective for each visitor.

After dinner, Alejandra put in her AR contact lenses and called her parents. “Calling” was still used colloquially even though it was more like experiencing. The AR overlay was so realistic that she truly felt as if she was sitting across from her parents on the couch. Her mom explained that Brazil would increase grain shipments to Uruguay in 2046, and that more young Uruguayans continued to migrate to Brazil and Chile. This economic migration was a major factor contributing to why her 65-year-old father still had to work, even when adults usually retire at 55.

Alejandra started her weekend with an all-in-one pill which depressed her genetic predisposition for Alzheimer’s and a mug of hydroponically grown coffee. Like most people with more free time than in the past, Alejandra found fulfillment through volunteering. She was the lead trainer for Care For All, a nonprofit which trained people who had lost their jobs to automation for new jobs in older adult care. As she arrived at the Corporation Power hospital the soles of her shoes shifted to be more structurally supportive for a standing posture.

Care For All was never short on participants because the newly unemployed were attracted to the high wages and job security that accompanied older adult care. As the North America Bloc’s population aged and fewer young people were born, society placed a growing reverence on older adults. Those eighty years and up were seen as the physical link to a simpler era and the holders of knowledge needed for societal improvement and rejuvenation.

One of the programs that Alejandra taught was the Health and Human Services (HHS) Memory Capture imitative. Memory Capture’s goal was to archive as much older adult knowledge as possible and store it in an easily accessible database. HHS hoped that younger generations would use the stored knowledge to learn different ways of thinking and apply new approaches to solving contemporary problems. Alejandra trained Care For All workers to properly facilitate conversations with older adults to capture this critical information.

Leaving the hospital, Alejandra thought about her grandpa who used to work six days a week just to make ends meet and considered how different her life was from his. She was grateful – the world in 2045 was much more holistic and balanced than when her grandpa was young. Her days were relaxed, fulfilling, and full of variety.

Answers to prompts

Q. AGI has existed for at least five years but the world is not dystopian and humans are still alive! Given the risks of very high-powered AI systems, how has your world ensured that AGI has at least so far remained safe and controlled?

A. In 2045 there are three AGI systems: Orangenie which is controlled by a private American corporation (Orange Train), Nicomachus which was developed by the EU, and Guangqi owned by the Chinese Communist Party.

To control Orangenie, Orange Train (OT) boxed it by building its server with a proprietary, localized power supply, and not allowing it access to the internet. OT’s goal was to control the questions asked of Orangenie so that (a) the response was specific to the questioner, (b) the response required human action, and (c) the response would not enlighten Orangenie to its own capability.

Nicomachus was built as an approval directed agent. When asked for advice, it tailors its response to align with the values laid out in the European Union’s Charter of Fundamental Rights. The Europeans believe that the values, beliefs, and norms enumerated in the Charter give Nicomachus sufficient knowledge to base responses upon and that those values, beliefs, and norms will stop Nicomachus from expensing advice or taking action that could cause harm to humankind.

Guangqi has the goal of helping the Communist Party create a Chinese Socialist Utopia aligned with the party leader’s values. This ambiguous goal places the AGI on a path of continual learning as rules, beliefs, and values change over time. It must always optimize China’s path from its current position to the pre-defined end goal. However, this approach is not foolproof as it can easily be aligned to objectively negative values.

Q. The dynamics of an AI-filled world may depend a lot on how AI capability is distributed. In your world, is there one AI system that is substantially more powerful than all others, or a few such systems, or are there many top-tier AI systems of comparable capability? Or something else?

A. In 2045, AI is a general-purpose technology that is necessary for the majority of technologies, goods, and services – yet it’s unevenly distributed. The highest quality AI (best performance, most efficient, largest impact) is found in the North America, European Union, and China Blocs. These three Blocs have the most capital to invest in quality data, compute power, and ambitious applications. By 2045, the forefront of AI in the developed world tackles problems such as tailoring cancer vaccines to individual patients and automating the carbon tracking and offset market. In the developing world, the forefront of AI is focused on applications relating to equitable access to basic resources like a quality education and food that provides enough critical vitamins and nutrients.

As migration becomes more difficult and some Blocs become more authoritarian, AI talent continues to congregate where there is capital, compute power, and academic support. Blocs with limited AI talent institute policies that limit brain drain, protect intellectual property, and incentivize domestic corporations. In those Blocs, however, programmers’ work is less likely to be operationalized. This has a two-fold effect of (a) creating an unregulated global black market for programmers and access to their code as well as (b) a related loss of unrealized high impact algorithms. Further complicating matters, in some areas like the European Union, China, and MERCOSUR Blocs, government controls the industry to monitor its development and increase the capacity for state control, making these more or less optimal AI environments for certain people.

Q. How has your world avoided major arms races and wars, regarding AI/AGI or otherwise?

A. In 2025, the United Nations General Assembly adopted the Principles for Safe Development of AGI (PSDAGI). Though few believed AGI was possible, enough nations and corporations thought being the first to develop it could lead to a decisive power asymmetry. The off chance was reason enough to become party to the PSDAGI and signal one’s support for AI regulation. Moreover, the PSDAGI was a platform for corporations, nations, and Blocs to seek international consensus on AI regulation. Signatories did not relinquish the ability to achieve AGI, but rather agreed that (a) AGI should not be used for violence, (b) that AGI should benefit humankind, and (c) that signatories bear responsibility for the actions of their AGI in accordance with international law.

More practically, the North America, European Union, and China Blocs have avoided an AGI arms race because of the lack of political competency in the United States to achieve national AGI capability. The European Union decided that AGI regulation was the best tool to ensure that AGI would not tip the geo-political power balance and instead would improve human flourishing. Finally, China was open with the fact that its AGI ambitions were purely social and economic, not militaristic. Thus, all major geo-political forces tacitly agreed not to compete for AGI dominance. In reality, the only two players competing for dominance were China and the American private sector, and luckily, they did not share common goals – thus avoiding an arms race mentality.

Q. In the US, EU, and China, how and where is national decision-making power held, and how has the advent of advanced AI changed that?

A. In China, the Communist Party remains the sole political force and after fully incorporating Hong Kong and Taiwan it has effectively squashed any possibility of political upheaval. The percent of the population employed by the government has grown and each province has greater autonomy from Beijing. However, provincial governors – hand-picked by the party leader – must use Guangqi AGI to build their five-year plan, increase the efficiency of work, and improve the material quality of life in their province.

The European Union has become a more ideologically cohesive political body after welcoming Ukraine, Norway, and Iceland and removing Poland and Hungary. Additionally, to address the increased decision-making power of the European Commission President, the Parliament introduced Polis Populari. Polis Populari is a Nicomachus AGI sub-model that gives individual Europeans a personalized voting slate and the ability to vote directly on legislation. If EU citizens reach a 75% majority opinion on legislation, their vote overrules the Commission and Parliament.

In the United States, national decision-making power still rests squarely with the president, yet Congress has become more emboldened to challenge presidential power. This is possible through NIST’s creation of a prediction algorithm to model the real time impact of laws, regulations, speeches, and decisions. The algorithm’s goal is to allow citizens to hold their representatives more accountable and give congresspeople and senators more foresight into their decisions. Practically, however, congress uses this tool to check the president’s power by knowing and broadcasting the consequences of every presidential decision.

Q. Is the global distribution of wealth (as measured say by national or international gini coefficients) more, or less, unequal than 2021’s, and by how much? How did it get that way?  (https://en.wikipedia.org/wiki/Gini_coefficient)

A. In 2045, the international Gini coefficient has fallen to 56 from its 2013 level of 63. This increasing equality is attributed to large GDP gains and increased economic power of the African Union, ASEAN, and MERCOSUR Blocs. These Bloc’s economic gains are the result of protectionism and internal Bloc trading. In addition, the economies of the United States, Europe, and developed Asian countries have steadily declined in terms of growth and output. That being said, the American, European, and developed Asian economies still have large advantages over the developing world in terms of established wealth and degree of economic development. Decreased global trade and increased economic isolation have continued to protect the economic gains made by countries who benefited from globalization from 1990 to 2020.

Despite this, quality of life and economic resilience has improved across the board. Many nations (73% of UN members to be exact) have started universal basic income (UBI) programs which have helped slash the number of people living in poverty worldwide to 150 million from 700 million in 2017. The current global poverty rate is 1.5%. As people came out of poverty, economic growth accelerated due to increased economic participation and the fact that less money was spent on addressing problems caused by poverty (i.e., paying for universal healthcare is cheaper than covering the costs associated with not having healthcare).

Q. What is a major problem that AI has solved in your world, and how did it do so?

A. In 2020 more than 240 million people contracted malaria and 627,000 died from the disease. Malaria is highly contagious and deadly, but through the use of insecticides, vaccines, and gene drive it is also preventable. With the help of AI, the world in 2045 has seen a 99.9% reduction in the number of malaria infections and a 100% reduction in deaths. Experts consider malaria a problem of the past. Insecticides are one of the most effective tools to combat malaria, but they are only effective until malaria-carrying mosquitoes become resistant to them. Machine learning has helped scientists better predict when current insecticides will become ineffective and what new chemical or biological structures and formulas will be newly effective. Moreover, AI-enhanced protein folding prediction has allowed the WHO to coordinate the public-private production of five new malaria vaccines including the most effective – a mRNA vaccine. The WHO coordinated a massive vaccination campaign, using AI to decide which groups would receive the vaccine first and how to tailor public health messaging to promote the vaccine. Finally, scientists used AI to create an effective plan for executing an anti-parasite effector gene drive amongst malaria-carrying mosquitos. The anti-parasite effector approach eliminates the malarial vector in female mosquitos but allows the effected mosquito population to persist. The anti-parasite effector approach kills two birds with one stone by reducing the amount of malaria in mosquitos while not dramatically disrupting mosquito populations and the natural ecosystem.

Q. What is a new social institution that has played an important role in the development of your world?

A. Founded in 2024 by workers in Jersey City and its sister city New Delhi, the Union For The Future’s (UFTF) mission is to improve laborer’s lives in the most effective and time efficient manner possible. The UFTF is unique because its members are decidedly in favor of AI and automation – but only when used in limited and specific settings. For example, the New Delhi chapter supports automating trash recycling and social media content reviewing because its members see those jobs as low skilled, unsatisfying, and unfit for human labor. On the other hand, the UFTF argues against automating jobs that it sees as skilled and rewarding like those in the service industry and manufacturing.

While it is a global organization, the UFTF maintains growth and influence because regional, national, and local chapters have different initiatives and abilities. All chapters, however, are united in their common guiding principles that (a) human labor is sacred (b) when used correctly AI will improve the laborer’s life (c) meaningful work leads to a meaningful life. In addition to its labor activism, the UFTF focuses on promoting friendship and human connection. The UFTF’s local nature has made it an important pillar in many communities hosting social events, seminars, and offering advice on how to live a moral and involved life. Finally, and especially in the developing world, the UFTF provides essential services that the government cannot, mainly community health clinics and job training services.