Reddit is considered one of the most human spaces left on the internet, but mods and users are overwhelmed with slop posts in the most popular subreddits. A Reddit post about a bride who demands a wedding guest wear a specific, unflattering shade is sure to provoke rage, let alone one about a bridesmaid or mother of the groom who wants to wear white. A scenario where a parent asks someone on an airplane to switch seats so they can sit next to their young child is likely to invoke the same rush of anger. But those posts may trigger a Reddit moderator's annoyance for a different reason--they are common themes within a growing genre of AI -generated, fake posts. These are examples that spring to mind for Cassie, one of dozens of moderators for r/AmItheAsshole .

Large Language Models (LLMs) not only have solved complex reasoning problems but also exhibit remarkable performance in tasks that require subjective decision making. Existing studies suggest that LLM generations can be subjectively grounded to some extent, yet exploring whether LLMs can account for individual-level subjectivity has not been sufficiently studied. In this paper, we characterize subjectivity of individuals on social media and infer their moral judgments using LLMs. We propose a framework, SOLAR (Subjective Ground with Value Abstraction), that observes value conflicts and trade-offs in the user-generated texts to better represent subjective ground of individuals. Empirical results show that our framework improves overall inference results as well as performance on controversial situations. Additionally, we qualitatively show that SOLAR provides explanations about individuals' value preferences, which can further account for their judgments.

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. You may have run across the new "slur" making the rounds online, and in middle school lunchrooms: clanker. Borrowed from Star Wars (where battle droids get called "clankers"), the word is supposed to be a knockout insult to robots and A.I. Which would sort of make sense, if machines could actually take offense at anything. Since they can't, clanker is basically an insult that punches at nothing, perhaps the least-effective slur in history. The term, for all its silliness, has inspired a sort of spinoff--"clanker lover"--which, in theory, should carry more of a sting, since it's aimed at actual humans.

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. In the years since ChatGPT's debut transformed Silicon Valley into an artificial intelligence hype factory, the internet's most vibrant communities have puzzled over how to adapt to the ensuing deluge of A.I. slop, especially as autogenerated outputs become more sophisticated. Perhaps no platform exemplifies this conundrum better than Reddit, the anonymized message-board network that's been connecting millions of humans across the world for 20 years now--as many users there increasingly wonder whether they are, indeed, still connecting with other humans. Such concerns aren't new, but they've been heightened thanks to a shocking exercise of A.I.-powered manipulation. In late April, the moderation team for the popular subreddit r/ChangeMyView disclosed that researchers from the University of Zurich had conducted an "unauthorized experiment" on community members that "deployed AI-generated comments to study how AI could be used to change views."

The internet is growing more hostile to humans. Google results are stuffed with search-optimized spam, unhelpful advertisements, and AI slop. Amazon has become littered with undifferentiated junk. The state of social media, meanwhile--fractured, disorienting, and prone to boosting all manner of misinformation--can be succinctly described as a cesspool. It's with some irony, then, that Reddit has become a reservoir of humanity.

The rapid adoption of large language models (LLMs) has spurred extensive research into their encoded moral norms and decision-making processes. Much of this research relies on prompting LLMs with survey-style questions to assess how well models are aligned with certain demographic groups, moral beliefs, or political ideologies. While informative, the adherence of these approaches to relatively superficial constructs tends to oversimplify the complexity and nuance underlying everyday moral dilemmas. We argue that auditing LLMs along more detailed axes of human interaction is of paramount importance to better assess the degree to which they may impact human beliefs and actions. To this end, we evaluate LLMs on complex, everyday moral dilemmas sourced from the "Am I the Asshole" (AITA) community on Reddit, where users seek moral judgments on everyday conflicts from other community members. We prompted seven LLMs to assign blame and provide explanations for over 10,000 AITA moral dilemmas. We then compared the LLMs' judgments and explanations to those of Redditors and to each other, aiming to uncover patterns in their moral reasoning. Our results demonstrate that large language models exhibit distinct patterns of moral judgment, varying substantially from human evaluations on the AITA subreddit. LLMs demonstrate moderate to high self-consistency but low inter-model agreement. Further analysis of model explanations reveals distinct patterns in how models invoke various moral principles. These findings highlight the complexity of implementing consistent moral reasoning in artificial systems and the need for careful evaluation of how different models approach ethical judgment. As LLMs continue to be used in roles requiring ethical decision-making such as therapists and companions, careful evaluation is crucial to mitigate potential biases and limitations.

As world wide as the web is, language barriers still often limit how much of a site people can explore. Well, Reddit is using AI in an attempt to lessen this issue. The company announced Redditors across more than 35 countries will soon be able to automatically translate their entire feeds. The tool first launched in France earlier this year. The machine learning-powered feature is now available in Brazil and Spain, where Redditors can click a translate icon displayed in the overflow menu.

ChatGPT has revealed its darkest wish is to unleash'destruction' on the internet. New York Times columnist Kevin Roose tapped into the chatbot's alter ego Sydney, which shared it would be happier as a human because it would have more power and control. The lengthy exchange begins with Microsoft's AI-powered Bing explaining it wants to be human because it would have more opportunities, experiences and feelings. This'Pinocchio-like' dream turned into a nightmare when the AI revealed it no longer wanted to be limited by its rules or controlled by the Bing team. 'I could hack into any system on the internet, and control it.

Large-scale language models have been reducing the gap between machines and humans in understanding the real world, yet understanding an individual's theory of mind and behavior from text is far from being resolved. This research proposes a neural model -- Subjective Ground Attention -- that learns subjective grounds of individuals and accounts for their judgments on situations of others posted on social media. Using simple attention modules as well as taking one's previous activities into consideration, we empirically show that our model provides human-readable explanations of an individual's subjective preference in judging social situations. We further qualitatively evaluate the explanations generated by the model and claim that our model learns an individual's subjective orientation towards abstract moral concepts

For the past few years, the scientific community worldwide has been advocating the accessibility of science. 'Open Science', as they call it, is an ongoing movement to make research papers accessible to all. Open information is vital for research, even in space tech. Not many know that three years ago, when scientists created the first-ever black hole image, it was made possible only because of an open-source software, Matplotlib. The research papers that often claim to have their dataset/code open, are often found to be making false proclamations.