Watch 5 AI models try to resolve variations of the trolley problem

Anthropic's interpretability team discusses how AI models' thinking mimics biology

Just as humans engage in complex behaviors to survive and reproduce, teams of experts in neuroscience, virology, mathematics, and other disciplines argue that large language models develop complex mechanisms to achieve their goals. These mechanisms can be manipulated to assess how they modify outputs—much like stimulating individual neurons—to uncover how LLMs "think."

Listen to an Anthropic staff philosopher discuss the importance of teaching ethics to AI.

Will AI kill us all? A debate

As AI becomes a bigger part of our lives, what does that mean for the future of humanity? The podcast Entanglements hosts a pessimistic former OpenAI employee and an optimistic Princeton professor to discuss whether AI brings dystopia or a brighter future.

Experiments involving AI agents operating in virtual societies for 15 days produced diverse outcomes, ranging from every agent dying to the creation of a functioning democracy, depending on the AI model used.

Neural implants blur the line between personal intention and machine execution

A key ethical dilemma—the contemplation conundrum—explores whether implants might misinterpret mere imagination as intent to act. Neuroscientists have found no brain signal that clearly marks when someone decides to act, making intent hard to detect in neurotechnological systems.

Anthropic's Frontier Red Team assesses the dangers of its AI tools through 'evals'—safety tests that probe models to disclose sensitive information.

Scientists increasingly can't predict what AI will do

Most AI systems are so-called "black box" models, where we only see inputs and outputs while the inner workings remain obscure. This piece, written prior to the launch of ChatGPT, cautions developers to know why and how a system produces its results, and not to sacrifice explainability for accuracy.

Test your ability to identify AI-generated images

This interactive project from MIT challenges users to distinguish between AI-generated images and real ones.

Is using VR as a tool to enhance empathy ethical?

This research paper explores whether virtual reality should be used as a tool for improving our moral character — and, if not, what ethical alternatives could be.

Some experts suggest there is an approximately 10% chance that AI agents will cause human extinction if they become superintelligent, go rogue, and hijack critical computer systems.

A vending machine run with Anthropic's AI went out of business after it was convinced to give away items for free and sell a video game console.

When you complete a CAPTCHA on a website to prove you are human, you may be unknowingly training algorithms for self-driving cars, whose systems require training data to help identify crosswalks, bicycles, and other outdoor objects.

Emergency room evaluations may be improved with AI algorithms

Emergency room care teams must make fast and crucial decisions. They must determine if patients need to be admitted or discharged and when to order more tests or not. Researchers have been exploring how often patients died in the week after they were sent home and evaluating how this and other aspects of emergency care decision-making could be improved with AI algorithms to assist decision-makers.

Just as large language models are trained on text to enable generative AI systems to mimic natural language, automated AI robotic systems are trained in virtual environments to help them 'learn' about the properties of reality.

Research suggests using AI for schoolwork may harm critical thinking skills

An MIT study finds lower brain engagement in students who used ChatGPT, resulting in consistent underperformance in neural, linguistic and behavioral levels. AI users struggled to recall their own essays, while the brain-only group showed the highest neural connectivity and satisfaction.

AI models incorporate a randomness parameter when generating responses to prompts

AI models use this parameter to prevent repeated outputs by sometimes choosing less likely next words during sequential generation. However, this randomness—alongside insufficient data and training—may cause hallucinations of incorrect results.

The promise and peril of AI in agriculture

Robots. Drones. Artificial Intelligence. All three are touted as potential saviors for farmers, and are already being deployed on large farms, where they assist with such tasks as managing crops, milking cows, and helping farmers make decisions about their land. But agricultural AI could have disastrous, unintended consequences.

Artificial intelligence may further enhance smart city data analysis

Identifying patterns within systems in the Internet of Things may enable AI tools to make informed decisions regarding transportation, safety, and sustainability without human intervention. However, such tools will also need to successfully address concerns about privacy, digital equity, and algorithmic bias.

AI experts argue that artificial intelligence could annihilate humanity in two primary ways: Humans weaponizing extremely powerful AI, or humans losing control of it.

People are experiencing AI 'brain fry' at work

Workers, particularly in marketing, are experiencing mental fatigue in the workplace due to expectations—often unspoken—that they should use AI to multitask beyond their comfort levels. Many feel they are underperforming if they don't embrace this technology. This situation differs from typical burnout. This podcast discussion suggests that this "brain fry" tends to intensify when employees are required to use more than three AI tools.

AI excels at assisting with structured tasks involving logistics and planning

Tools like ChatGPT, Gemini, and Perplexity can help organize chaotic calendars, troubleshoot bedtime routines, and assist with salary planning and moving. However, specific quotes, like insurance, and local cost comparisons can be flawed since AI draws from nonlocalized datasets.

The free will versus determinism debate: major thinkers weigh in

Do we have free will in our actions or are we totally determined? An all-star cast of contemporary thinkers share insights on the crucial debate.

AI tools can reinforce existing societal biases—especially racial ones—because they are trained on human-created data containing implicit and explicit biases.

How constitutional AI helps cultivate good human values in Anthropic's AI tools

By incorporating elements from documents such as the UN's Universal Declaration of Human Rights into a framework against which it can check its outputs, Anthropic hopes the approach will help Claude operate with good human values and behaviors beyond what human-driven training alone can provide.

The history of torturing robots

When machines fail, its easy to get mad and even give them a good kick. But as humanoid robots become more sophisticated, the degree to which people abuse them has shifted, depending on how much emotion the robot expresses. Studies revealed when robots were programmed to cry during distress, participants felt empathy. Learn more about the history of human abuse of robots here.

Explore a visually captivating, interactive animation that lets users click through anxiety-inducing scenarios, make choices, and see the repercussions.

While robots tend to become more appealing the more humanlike they appear, beyond a certain point, humans have exhibited uneasiness and fear—a phenomenon known as the uncanny valley.

View a timeline of AI deployments from 2017 to 2025

The development of transformer architecture and the release of GPTs across AI labs led to rapid changes in LLM scale and power. Companies like OpenAI, Google, Meta, Microsoft, and Anthropic have invested billions of dollars to develop reliable, versatile models.

How Anthropic's experimental corporate structure incentivizes safe AI development

As Anthropic is a public benefit corporation, its board is tasked with making sure that AI tools are developed to help people and society thrive. Members of its Long Term Benefit Trust hold no equity in the company, but make up a majority of the board and can act to maintain Anthropic's public benefit purpose.

Understanding how Claude Code and other AI coding agents function

Under human oversight, a supervising large language model interprets user tasks and delegates work to subordinate LLMs, which can generate code, fix bugs, and run tests, often most effectively for proofs of concept. Incremental backups and versioning are crucial when using such agents, which can lose details during their work as a result of compressing context history to work around memory limitations.

Decoding the hype around AI

2022 was the year AI broke onto the scene, with applications like ChatGPT amazing users with its ability to generate realistic-sounding answers. Technologist Arvind Narayanan presents a clear-eyed view of what the technologies can (and can't) do.

Through prompt injection attacks, bad actors provide deceptive prompts to generative AI systems in order to manipulate their outputs and acquire sensitive data.

Sam Altman acknowledges the fears around creativity, copyright, and misuse of AI

In 2022, OpenAI's CEO, Sam Altman, popularized the use of large language models with the release of ChatGPT. He has emphasized the importance of involving society in shaping AI’s safety frameworks before models begin to act independently online.

Predictive brain implants raise ethical concerns about patient autonomy after surgery

These devices can accurately forecast neurological events like seizures and suggest or even automatically deliver responses. Their constant monitoring and prescriptive functions may blur the line between patient choice and device influence.

Stephen Wolfram on AI's rapid progress & the "Post-Knowledge Work" era

AI, as a concept, has been around since at least the 1950s, but it's only in the last year or so that the technology has been able to equal humans at many tasks -- and in many cases surpass humans. In this podcast, mathematician and computer scientist Stephen Wolfram provides an AI 101, explaining how we got here, how highly advanced chatbots like ChatGPT work, and what our world is in store for next.

Teaching a robot to laugh

Researchers have designed a shared-laughter AI system that responds to human laughter in order to build a sense of empathy into dialogue. Learn how they did it with this explainer.

As of 2025, artificial intelligence systems remain narrow and specialized

Efforts are ongoing to create artificial general intelligence, where machines outperform humans across a wide range of cognitive tasks, including those for which they have not been specifically trained. Current models utilize machine learning and neural networks to perform tasks for which they are programmed, leveraging provided training data.

In 2026, a pilot program introduced two AI-powered humanoid robots to a San Diego charter school to increase engagement and academic gains, though some criticized the $500k purchase.

Because they are built on content produced by humans, who possess biases, generative AI tools inherit prejudices and stereotypes from training data, which later appear in their outputs.

Using generative AI to create video introduces physics-compatibility challenges

Models involved in generating video from text must maintain spatial and temporal coherence while adhering to the laws of reality to produce smooth, logical motion. Ensuring this consistency creates long-term dependencies with high computational times.

How artificial intelligence, which detects patterns, can identify burnout

Researchers are training AI to detect stress-related symptoms, helping physicians and other medical workers recognize and reduce stress from overwork and potentially avoid burnout.

In 2019, Tesla's autopilot system misinterpreted emergency lights and crashed

A Tesla Model X collided with stopped emergency vehicles on a Texas highway when flashing lights created hazy images that the software could not interpret. The crash injured five people and hospitalized another person while highlighting the challenges of autonomous systems.

'Context rot' explains why AI conversations degrade the longer they run

Research shows that as a large language model's context window fills up, performance declines, and models begin over-indexing on content at the start and end of a conversation while losing track of what's in the middle. The practical fix is simpler than you'd think: start a fresh chat more often.

The rise of generative AI could exacerbate anxiety because people may turn to chatbots for constant reassurance.

AI is not good at understanding satire

Social media has become rife with misinformation. In response, some organizations have deployed AI-assisted programs trying to curb the spread of this inaccurate content. The problem is that misinformation and satire, rhetorically speaking, often use the same kind of language, something AI struggles to understand.

What does it mean for AI to "understand" something?

This Quanta article discusses how programmers are working to create a reliable test for the depth and extent of the knowledge of machines. What does AI know and how does it know it, if it knows anything at all? There's been progress, but it hasn't been easy. Even humans can still be fooled some of the time.

The potential promises and pitfalls of AI in medicine

Artificial intelligence (AI) is increasingly being integrated into healthcare, offering the potential to aid in diagnoses, answer patient queries, and streamline administrative processes. In a recent PBS interview, Dr. Isaac Kohane, editor-in-chief of the New England Journal of Medicine AI and chair of Harvard’s department of biomedical informatics, discusses the current state and future of AI in medicine.

AI hallucinations are inaccuracies or falsehoods in generated content

AI hallucinations are a by-product of the sequential creation of content based on patterns in text, which may not reflect the context or meaning behind a prompt. Back-end issues like biased datasets and overfitting of model data contribute to hallucinations.

Is life all about pleasure? Debating the Experience Machine

If you could plug into an Experience Machine that gave you total pleasure all the time, would you do it? Philosopher Robert Nozick thinks you wouldn't, using this as evidence against hedonism, the view that life is all about pleasure. Explore the nuances of the argument and counterarguments with this accessible article.

Artificial intelligence may improve organ donation systems—and even organ health

Mayo Clinic transplant experts suggest that artificial intelligence could potentially improve organ donation systems in several ways, including better identifying patients most at risk for organ rejection, enhancing donor-recipient matching, and helping to avoid organ transplant needs by identifying health issues earlier.