Around midnight on April 16, 2025, after Chen Zimo learned that the Department of Homeland Security had threatened to revoke Harvard University's certification to enroll international students, he began communicating with a trusted source about possible legal scenarios. Chen, a Chinese citizen, still needed a number of courses before he could complete his degree in computer science at Harvard, and he felt panicked about the possibility of having his visa revoked. For him, the Harvard experience had been transformative. Chen--not his real name--had grown up in provincial China, where his family had modest resources and sent him to public schools. He could never have afforded Harvard without the university's generous financial support, and he had also received funding for summer language study.

The British-Canadian computer scientist dubbed the'Godfather of AI' has shortened the odds of artificial intelligence (AI) wiping out humans over the next 30 years, warning the technology could one day'take control'. Professor Geoffrey Hinton said we need to be'very careful' and'very thoughtful' about the development of AI which he says is'potentially very dangerous'. He had previously said there was a 10 per cent chance of the technology causing the extinction of the human race - but now predicts that figure to be '10 per cent to 20 per cent', because of the rapid pace at which AI is developing. Speaking on BBC Radio 4's Today programme, Professor Hinton said: 'You see, we've never had to deal with things more intelligent than ourselves before.' He continued: 'And how many examples do you know of a more intelligent thing being controlled by a less intelligent thing?

In this study, we introduce "CosmoAgent," an innovative artificial intelligence framework utilizing Large Language Models (LLMs) to simulate complex interactions between human and extraterrestrial civilizations, with a special emphasis on Stephen Hawking's cautionary advice about not sending radio signals haphazardly into the universe. The goal is to assess the feasibility of peaceful coexistence while considering potential risks that could threaten well-intentioned civilizations. Employing mathematical models and state transition matrices, our approach quantitatively evaluates the development trajectories of civilizations, offering insights into future decision-making at critical points of growth and saturation. Furthermore, the paper acknowledges the vast diversity in potential living conditions across the universe, which could foster unique cosmologies, ethical codes, and worldviews among various civilizations. Recognizing the Earth-centric bias inherent in current LLM designs, we propose the novel concept of using LLMs with diverse ethical paradigms and simulating interactions between entities with distinct moral principles. This innovative research provides a new way to understand complex inter-civilizational dynamics, expanding our perspective while pioneering novel strategies for conflict resolution, crucial for preventing interstellar conflicts. We have also released the code and datasets to enable further academic investigation into this interesting area of research.

This study examines the key factors that affect European reactions to artificial intelligence (AI) in the context of both full and flawed democracies in Europe. Analysing a dataset of 4,006 respondents, categorised into full democracies and flawed democracies based on the Democracy Index developed by the Economist Intelligence Unit (EIU), this research identifies crucial factors that shape European attitudes toward AI in these two types of democracies. The analysis reveals noteworthy findings. Firstly, it is observed that flawed democracies tend to exhibit higher levels of trust in government entities compared to their counterparts in full democracies. Additionally, individuals residing in flawed democracies demonstrate a more positive attitude toward AI when compared to respondents from full democracies. However, the study finds no significant difference in AI awareness between the two types of democracies, indicating a similar level of general knowledge about AI technologies among European citizens. Moreover, the study reveals that trust in AI measures, specifically "Trust AI Solution," does not significantly vary between full and flawed democracies. This suggests that despite the differences in democratic quality, both types of democracies have similar levels of confidence in AI solutions.

Sign up to receive our weekly newsletter of the best New Yorker podcasts. In November, OpenAI introduced ChatGPT, a large language model that can generate text that gives the impression of human intelligence, spontaneity, and surprise. Users of ChatGPT have described it as a revolutionary technology that will change every aspect of how we interact with text and with one another. American political life has already been profoundly altered by the Internet, and the effects of ChatGPT, Rothman says, could be even more profound.

We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2,200 manually labeled and 1.8 million machine-labeled titles that were posted from 2014 to the present by nine representative media organizations across three media bias groups - Left, Central, and Right in an active learning manner. The fine-tuned transformer-based language model achieves an overall accuracy of 0.84 and an F1 score of 0.78 on an external validation set. Next, we conduct a computational analysis to quantify the extent and dynamics of partisanship in news titles. While some aspects are as expected, our study reveals new or nuanced differences between the three media groups. We find that overall the Right media tends to use proportionally more hyperpartisan titles. Roughly around the 2016 Presidential Election, the proportions of hyperpartisan titles increased in all media bias groups where the relative increase in the proportion of hyperpartisan titles of the Left media was the most. We identify three major topics including foreign issues, political systems, and societal issues that are suggestive of hyperpartisanship in news titles using logistic regression models and the Shapley values. Through an analysis of the topic distribution, we find that societal issues gradually receive more attention from all media groups. We further apply a lexicon-based language analysis tool to the titles of each topic and quantify the linguistic distance between any pairs of the three media groups. Three distinct patterns are discovered. The Left media is linguistically more different from Central and Right in terms of foreign issues. The linguistic distance between the three media groups becomes smaller over recent years. In addition, a seasonal pattern where linguistic difference is associated with elections is observed for societal issues.

What would the inputs be to a machine whose output is the destabilization of a robust democracy, or whose emanations could disrupt the political power of nations? In the recent essay "The Coming AI Hackers," Schneier (2021) proposed a future application of artificial intelligences to discover, manipulate, and exploit vulnerabilities of social, economic, and political systems at speeds far greater than humans' ability to recognize and respond to such threats. This work advances the concept by applying to it theory from machine learning, hypothesizing some possible "featurization" (input specification and transformation) frameworks for AI hacking. Focusing on the political domain, we develop graph and sequence data representations that would enable the application of a range of deep learning models to predict attributes and outcomes of political systems. We explore possible data models, datasets, predictive tasks, and actionable applications associated with each framework. We speculate about the likely practical impact and feasibility of such models, and conclude by discussing their ethical implications.

OneZero is partnering with the Big Technology Podcast from Alex Kantrowitz to bring readers exclusive access to interview transcripts with notable figures in and around the tech industry. This week, Kantrowitz sits down with Meredith Whittaker, an A.I. researcher who helped lead Google's employee walkout in 2018. This interview, which took place at World Summit A.I, has been edited for length and clarity. To subscribe to the podcast and hear the interview for yourself, you can check it out on Apple Podcasts, Spotify, and Overcast. When I interviewed Tristan Harris about The Social Dilemma earlier this month, my mentions filled with people saying, "You should speak to the people who were critical of the social web long before the film." One name stood out: Meredith Whittaker. An A.I. researcher and former Big Tech employee, Whittaker helped lead Google's walkout in 2018 amid a season of activism inside the company. On this edition of the Big Technology Podcast, we spoke not only about her views on the film, but also of the future of workplace activism inside tech companies in a moment where some are questioning if it belongs at all. Alex Kantrowitz: It seems like your perspective on The Social Dilemma is a little bit different from Tristan's.

One of the most important jobs of any national leader is to quit. National liberation heroes, from George Washington to Nelson Mandela, who stepped down without being forced to, ought to be venerated for that as much as for any good they accomplished while in office. Generally, rulers do not give up power unless they have to. In Africa, peaceful transfers of power are rare enough that a billionaire has set up a generous annual prize to reward leaders who step down voluntarily; many years it goes unclaimed. Around the world, cases like Bashar al-Assad, willing to watch his country crumble rather than give up power over it, or Robert Mugabe, forced out by his own military after 47 years, are more common.

Artificial intelligence will probably be the most important agent of change in the 21st century. It will transform our economy, our culture, our politics and even our own bodies and minds in ways most people can hardly imagine. If you hear a scenario about the world in 2050 and it sounds like science fiction, it is probably wrong; but if you hear a scenario about the world in 2050 and it does not sound like science fiction, it is certainly wrong. Technology is never deterministic: it can be used to create very different kinds of society. In the 20th century, trains, electricity and radio were used to fashion Nazi and communist dictatorships, but also to foster liberal democracies and free markets.