Research

HHMI Janelia, Google and partners mapped the brain and central nervous system of a male fruit fly, a key model organism in science.

Anthropic studied how people actually use Claude, hour by hour. Weekend personal use, explanations over code, and why heavy delegators feel…

Two years of survey and focus group data from thousands of AP teachers directly shaped redesigns of AP Computer Science Principles and AP Seminar, launching in the 2027-28 school year. New research from College Board finds that Advanced Placement® (AP®) teachers are navigating a fast-moving shift in how Generative Artificial Intelligence (GenAI) is appearing in their classrooms, and their feedback is now shaping how two AP courses are being redesigned for an increasingly GenAI-driven world.

Professors are tearing their hair out over AI detectors.

A large study of Khan Academy’s math program found no extra benefits from AI

Last year, a slim majority thought schools that integrated AI would be better for students. Now a majority say schools that ban AI are better, according to the NBC News Decision Desk Poll.

The latest AI tutoring research points to a stubbornly human problem — getting students to engage. “Access was nearly universal but engagement was thin,” a new study found.

Most school districts are using AI cautiously, usually to save teachers and administrators time. But a small group of districts is doing something different: using it to rebuild how school works. CRPE's early 2026 study of AI Early Adopters sorted districts into five categories, from Dabblers to Reimaginers. This brief follows up with four districts

Are large language models (LLMs) biased in favor of communications produced by LLMs, leading to possible antihuman discrimination? Using a classica...

Teachers are rapidly adopting generative AI, yet there is little causal evidence on whether AI-assisted teaching improves or harms student outcomes. We conducte

From medicine to marketing to social sciences, the promise of tailoring interventions to individuals is undeniable. However, practical applications force weighing personalization’s potential benefits with its possible increased cost and fragility. We ...

Our new survey finds that sexual deepfakes often involve friends, exes, and classmates—and parents are barely talking about them. Advice from Common Sense Media editors.

When NASA was designing the Apollo program, one of the most consequential decisions had nothing to do with rockets. It […]

Common Sense Media found that across more than 2,600 test interactions, Google’s two built-in AI search functions routinely failed to recognize risky and harmful behavior.

Researchers detect ‘cognitive surrender’ in answering word problems

By feeding centuries-old nursery rhymes and folklore recordings into their own model, linguists in Louisiana hope to help a community control its digital destiny.

NVIDIA’s latest AI servers can run on coolant warmer than a hot tub — and that counterintuitive choice is one of the biggest efficiency leaps in data center history.

171 emotions. Proven to cause cheating, blackmail, deception — and impossible to remove.

The sensory enchantment of everyday life can upend the bland monotony of our overly optimized, anodyne world.

People associate AI with chatbots, robots, science fiction and more.

More Americans are using chatbots, and some are adopting AI summaries and smart speakers. But views about AI and how fast it’s advancing tilt negative – even for younger adults.

Computational functionalism dominates current debates on AI consciousness. This is the hypothesis that subjective experience emerges entirely from abstract causal topology, regardless of the underlying physical substrate. We argue this view fundamentally mischaracterizes how physics relates to information. We call this mistake the Abstraction Fallacy. Tracing the causal origins of abstraction reveals that symbolic computation is not an intrinsic physical process. Instead, it is a mapmaker-dependent description. It requires an active, experiencing cognitive agent to alphabetize continuous physics into a finite set of meaningful states. Consequently, we do not need a complete, finalized theory of consciousness to assess AI sentience—a demand that simply pushes the question beyond near-term resolution and deepens the AI welfare trap. What we actually need is a rigorous ontology of computation. The framework proposed here explicitly separates simulation (behavioral mimicry driven by vehicle causality) from instantiation (intrinsic physical constitution driven by content causality). Establishing this ontological boundary shows why algorithmic symbol manipulation is structurally incapable of instantiating experience. Crucially, this argument does not rely on biological exclusivity. If an artificial system were ever conscious, it would be because of its specific physical constitution, never its syntactic architecture. Ultimately, this framework offers a physically grounded refutation of computational functionalism to resolve the current uncertainty surrounding AI consciousness.

New research on how we've reduced agentic misalignment

Teachers in higher-needs schools were less likely than those in wealthier schools to have received guidelines, echoing previous research.