YouCongress - Expert and Citizen Preferences

Rather than treating AI and data-driven profits as a private windfall, governments should tax the use of data and the rents from highly profitable digital and AI firms, and return that money to people as a regular dividend. You are contributing your ...

Rather than doing something immediately, it would be better first to have academic research and examination, and then apply the scholarly findings to reality. It is an issue that, in the later legislative process, must win public consensus and fully ...

Going one step further from the performance bonus demands and strikes by vested-interest unions at major companies such as SK hynix and Samsung Electronics, the Blue House policy chief is now arguing for a 'corporate profit distribution system' that ...

The UN plays an indispensable role in building an inclusive and consensus-based governance framework with universal participation.

Yeah, I, so I tend to share Tom's pessimism about the likelihood of new international agreements in this space at all. But I will say I do think there's probably some space for thinking about interoperability and other related AI questions, legal int...

The 1,640 IT decision-makers Box surveyed for our 2026 State of AI in the Enterprise report reveal what’s actually happening: 58% expect their organization's total headcount to rise over the next three years. Of the most mature companies in terms of ...

We appear to be approaching the most significant reorganization of work in generations. This transition could create new opportunities, but it could also come with some costs.

This essay takes the approach that it is both wise and prudent to start devising policies that respond to potential scenarios in which AI does not end most human work but leads to unprecedented job dislocation and, left to its own, at least some long...

Singapore launched the AI Verify Foundation in 2023 to harness the collective contributions of the global open-source community to develop AI testing tools. As of May 2026, it has grown to more than 250 corporate members worldwide. Through this found...

I think the default prediction you should have for that is what the AI system learns to do is, “I’m going to take opportunities to reward hack, seek reward as much as possible that would allow me to get a high score after a week” or something like th...

No one knows—it’s an open problem, but I will review some ideas and research directions.

A more fundamental fix would be to train the models not to cheat in the first place – but given this kind of behaviour was reported in frontier models more than a year ago, robustly aligning it away may not be easy.

A coalition of aligned democracies, who pool research, talent, compute, and procurement power, would offer a credible alternative to the dominant market actors that increasingly define the global AI landscape.

The answer isn't convergence for its own sake. We can push too hard on one thing. But if you have one standard, you could risk a lowest common denominator outcome that can cost us the innovation system as well and might have a risk on the national in...

I cannot say with certainty that AI will never be conscious or that people will not come to trust the machines in our future more than they trust other humans.

The question of whether artificial intelligence is or can ever be conscious remains unclear.

Being open to the possibility that LLMs are conscious is the same as being open to the possibility that Microsoft Word is conscious.

While the federal government dismantles contracting standards and removes basic protections for Americans, Governor Gavin Newsom today issued an executive order to explore stronger AI standards for state procurement — ensuring that companies demonstr...

I think federal pre-emption is something that should be part of it.

It is time to put safeguards in place to protect Rhode Islanders of all ages from this rapidly expanding technology, both at home and in a clinical setting.

Age verification can be done well in a privacy-protective way, but it is not easy.

Competition, innovation, and speech options will be limited as a result of these moves.

I argue that contemporary deep learning systems often can and do achieve such understanding.

AI systems, by contrast, do not understand meaning. They detect statistical regularities in large datasets and generate outputs that approximate meaningful responses without comprehension. AI does not know what something is or why it matters; it pred...

The most realistic near-term path is a sovereign wealth fund seeded by taxes on AI-generated profits, managed broadly to track economic growth, and distributing returns as periodic cash dividends.

The answer to that fear is to make job loss less scary by building a new unemployment program.

AI-generated abundance coexists with demand deficiency because economic institutions are anchored to human cognitive scarcity.

AI could make goods and services cheaper than ever, raising hopes for a new age of abundance where scarcity plays a smaller role in human life.

It is often suggested that the advent of powerful AI will create abundance and that it can thereby contribute to securing social harmony. This paper draws on Hirsch’s study of different kinds of limits to growth to show that this is false.

A common fear in AI safety is that human value is fragile -- that is, optimizing too heavily for an imperfect proxy to human values will lead to a catastrophic outcome.

I don’t think it will be doom and gloom in the next five years. But we have to put our effort into understanding vulnerabilities and mitigating the risks. Otherwise it will be too late.

I show how the argument from power-seeking rests on a strong version of a claim known as the instrumental convergence thesis. I explore leading defenses of the instrumental convergence thesis and argue that none establishes the thesis in a strong eno...

This approach allows threats such as deepfakes and synthetic content to be controlled from the start through data governance, transparency, risk assessment and clear accountability for developers and those who deploy AI systems.

A handful of bills introduced this year seek to categorically ban “deepfakes.” In other words, these bills would make it unlawful to create or share AI-generated content depicting someone saying or doing something that the person did not in reality s...

Using decision trees as an interpretable proof-of-concept model class, the methodology yields explicit trustworthiness plateaus, readable level transitions, and two simple lifecycle diagnostics: boundary margins and profile drift.

We have a very natural instinct to say: we want as much interpretability as possible. One of the sci-fi worry cases is that agents start speaking in languages to each other that we don't understand. [...] I bet there are ways to define boundaries tha...

[...] principles requiring that AI be explicable are misguided. We should be deciding which decisions require explanations. Automation is still an option;