As the adoption of language models advances, so does the need to better represent individual users to the model. Are there aspects of an individual's belief system that a language model can utilize for improved alignment? Following prior research, we investigate this question in the domain of opinion prediction by developing PrimeX, a dataset of public opinion survey data from 858 US residents with two additional sources of belief information: written explanations from the respondents for why they hold specific opinions, and the Primal World Belief survey for assessing respondent worldview. We provide an extensive initial analysis of our data and show the value of belief explanations and worldview for personalizing language models. Our results demonstrate how the additional belief information in PrimeX can benefit both the NLP and psychological research communities, opening up avenues for further study.

What does this have to do with AI? AI development is concentrated in the aging countries, and thus it will follow the path set by the realities, needs, and incentives in those places. Aging countries are seeing the ratio of working-age people to retirees collapse, making it more difficult to sustain pension schemes and contain health-care costs. Countries looking to maintain their retirees' living standards and their overall economic dynamism will seek ways to expand their effective labor force, be that with humans or with artificial agents. Limited (and likely highly unpopular) gains could come from increasing the retirement age. More sizable gains could come from immigration.

Hanging on the wall of Anthropic's offices in San Francisco in early May, a stone's throw from the conference room where CEO Dario Amodei would shortly sit for an interview with TIME, was a framed meme. Its single panel showed a giant robot ransacking a burning city. Underneath, the image's tongue-in-cheek title: Deep learning is hitting a wall. That's a refrain you often hear from AI skeptics, who claim that rapid progress in artificial intelligence will soon taper off. Another points to the devastated city: "wall."

Many tech experts have warned that AI is on a path of destruction, but a new survey of top researchers has quantified the chances of it causing human extinction. A team of international scientists asked 2,778 AI experts about the future of the systems, with five percent reporting the tech will lead to collapse. But, a far more frightening estimation came from one in 10 researchers who said there's a shocking 25 percent chance that AI will destroy the human race. The experts cited three possible causes: AI allowing threatening groups to make powerful tools, like engineered viruses, 'authoritarian rulers using AI to control their populations and AI systems worsening economic inequality by disproportionately benefiting certain individuals.' Artificial intelligence regulation control is the only answer to protecting humans, and if AI isn't regulated, researchers estimated that there is a 10 percent chance that machines will outperform humans in all tasks by 2027, - but it would increase to a 50 percent chance by 2047.

Artificial intelligence and automation have been transforming the job market for years, and as technology advances, many experts predict that this trend will only continue to accelerate, potentially leading to significant job losses in a wide range of industries. In this article, we'll explore how AI is changing the job landscape, what it means for workers, and what steps can be taken to prepare for the future of work. The impact of AI on the labor market is complex and multifaceted. On the one hand, AI has the potential to create new job opportunities by enabling businesses to automate repetitive tasks and focus on higher-level work. For example, AI can help businesses optimize their operations, improve customer service, and develop more effective marketing strategies.

Artificial intelligence is already making decisions in the areas of business, healthcare and manufacturing. However, AI algorithms can generally get help from people who apply checks and make the final call. Pop culture has long portrayed our general distrust of AI. In a 2004 science fiction movie I robotDetective Del Spooner (played by Will Smith) suspects a robot after being rescued by a robot from a car accident, but a 12-year-old girl drowned.he I was a logical choice.

Artificial intelligence is already making decisions in the fields of business, health care and manufacturing. But AI algorithms generally still get help from people applying checks and making the final call. What would happen if AI systems had to make independent decisions, and ones that could mean life or death for humans? Pop culture has long portrayed our general distrust of AI. In the 2004 sci-fi movie I, Robot, detective Del Spooner (played by Will Smith) is suspicious of robots after being rescued by one from a car crash, while a 12-year-old girl was left to drown.

Recent concern about harms of information technologies motivate consideration of regulatory action to forestall or constrain certain developments in the field of artificial intelligence (AI). However, definitional ambiguity hampers the possibility of conversation about this urgent topic of public concern. Legal and regulatory interventions require agreed-upon definitions, but consensus around a definition of AI has been elusive, especially in policy conversations. With an eye towards practical working definitions and a broader understanding of positions on these issues, we survey experts and review published policy documents to examine researcher and policy-maker conceptions of AI. We find that while AI researchers favor definitions of AI that emphasize technical functionality, policy-makers instead use definitions that compare systems to human thinking and behavior. We point out that definitions adhering closely to the functionality of AI systems are more inclusive of technologies in use today, whereas definitions that emphasize human-like capabilities are most applicable to hypothetical future technologies. As a result of this gap, ethical and regulatory efforts may overemphasize concern about future technologies at the expense of pressing issues with existing deployed technologies.

I was challenged by the editors here at Work: Reimagined to imagine what a corporation might look like in 2050. My immediate response was to think'that's a long ways off.' But on the other hand, it does take an incredibly long time to make foundational changes in society, except when major disruptions occur, as with the rise of the Internet over the past few decades, or the Black Death, when over 100 million people died, leading to the shifts in power that ultimately sparked the Renaissance. So I am resorting to a futurist sleight-of-hand to get to an answer in several steps. I can't just scramble to the roof of the house to see out over the horizon: First, I have to build a ladder to climb up to the roof.

AI is slowly seeping into our lives in profound ways. The way we think about AI is coloured by popular culture and science fiction. Many feel that if they could make that science fiction real then we wouldn't have to worry about messy kinds of stuff in society. My concern is not about the singularity that experts like Ray Kurzweil have talked about in his book Singularity Is Near nor Hollywood movies like Transcendence, which paint a dystopian view of a future transformed by AI. The human brain is a remarkable piece of engineering and fears that AI might take over human brain is not imminent.