New report: How we detect and counter malicious uses of Claude.
For example, we found Claude was used for a sophisticated political spambot campaign, running 100+ fake social media accounts across multiple platforms.
This particular influence operation used Claude to make tactical engagement decisions: commenting, liking, or sharing based on political goals.
We've been developing new methods to identify and stop this pattern of misuse, and others like it (including fraud and malware).
In this case, we banned all accounts that were linked to the influence operation, and used the case to upgrade our detection systems.
Our goal is to rapidly counter malicious activities without getting in the way of legitimate users.
New Anthropic research: How university students use Claude.
We ran a privacy-preserving analysis of a million education-related conversations with Claude to produce our first Education Report.
Students most commonly used Claude to create and improve educational content (39.3% of conversations) and to provide technical explanations or solutions (33.5%).
Which degrees have the most disproportionate use of Claude?
Perhaps not surprisingly, Computer Science leads the field, with 38.6% of Claude conversations related to the subject, which makes up only 5.4% of US degrees.
New Anthropic research: Do reasoning models accurately verbalize their reasoning?
Our new paper shows they don't.
This casts doubt on whether monitoring chains-of-thought (CoT) will be enough to reliably catch safety issues.
We slipped problem-solving hints to Claude 3.7 Sonnet and DeepSeek R1, then tested whether their Chains-of-Thought would mention using the hint (if the models actually used it).
We found Chains-of-Thought largely aren’t “faithful”: the rate of mentioning the hint (when they used it) was on average 25% for Claude 3.7 Sonnet and 39% for DeepSeek R1.
Last month we launched our Anthropic Economic Index, to help track the effect of AI on labor markets and the economy.
Today, we’re releasing the second research report from the Index, and sharing several more datasets based on anonymized Claude usage data.
The data for this second report are from after the release of Claude 3.7 Sonnet. For this new model, we find a small rise in the share of usage for coding, as well as educational, science, and healthcare applications.
We saw little change in the overall balance of “augmentation” versus “automation”, but some changes in the specific interaction modes within those categories.
For instance, there was a small increase in learning interactions, where users ask Claude for explanations.