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Anthropic recently rolled out its tool, making a free version of Claude with advanced technical capacities available to any K-12 U.S. educator who applies to the company using a school email address and asserts that CfT will be used for educational purposes. The tool has many features that will make it appealing to teachers. Among the most important is its link to which provides high-quality instructional materials aligned to academic standards across all 50 states. Claude for Teachers also draws on proven curricula like and .

Drawing on this source material, Claude can generate lessons and materials aligned to an educator’s state standards and curriculum. Given how much teacher time goes into that kind of planning, it’s easy to see why CfT is appealing.

We’re glad to see artificial intelligence’s potential being tapped to help teachers individualize instruction at a scale that wasn’t possible even a few years ago. We are also happy to see a major frontier lab with the resources and technical skills to do it. But public school systems don’t operate like the private companies and government agencies Anthropic is used to working with. Teachers face legal exposure around sharing student data that simply doesn’t exist in those sectors.

This creates a severe employment risk for educators. 

Anthropic’s own shows the problem: 鈥淎nalyze class data to plan instruction. Hand Claude a folder of data 鈥� roster, diagnostics, attendance, your own notes 鈥� and it builds a clear picture of where every student is, allowing teachers to better tailor instruction. You control what data is shared; nothing you share is used in model training.鈥�

While this pitch appeals directly to overburdened educators, encouraging them to hand over those kinds of data immediately puts them at risk, because it invites teachers to sidestep district policy and, potentially, state and federal law.

CfT’s privacy terms are stronger than those of ordinary consumer AI products: It does not train on teacher inputs or outputs, and it offers data encryption, deletion rights, audits and breach notification. Anthropic says its with teachers is 鈥渨ritten to comply with FERPA鈥� 鈥� federal student privacy law 鈥� but that’s a claim about how the contract is drafted, not a promise that any individual teacher’s use is lawful.聽

Here鈥檚 the problem: The marketing prompt to 鈥渉and Claude a folder of data鈥� (even with the added disclaimer to check district policies) directly conflicts with CfT鈥檚 terms of service in two ways. First, the terms require that the teacher have the authority to designate Anthropic as a 鈥渟chool official.鈥� But FERPA dictates that a vendor qualifies as a 鈥渟chool official鈥� only if the district designates it as such and if the vendor is under the district鈥檚 鈥渄irect control.鈥� An individual teacher can’t make that designation.聽

Second, the terms of service require teachers to indemnify Anthropic for claims arising from what they upload. These terms also cap Anthropic’s liability. In short, the educator, not Anthropic, is assuming the risk. 

While the marketing describes an appealing set of features, the terms lay out requirements that are legally impossible for a teacher to meet. If educators agree to these terms and upload data, they could potentially be fired for it. These risks are even greater when any information about students with disabilities (like an individualized education program) or medical conditions (like a Section 504 plan) is shared. 

Both authors have spent years working with school district bureaucracies, so we know firsthand how hard the purchasing process can be and how legal barriers around data privacy and security can slow the adoption of innovative technology. We both agree that the procurement and purchasing process needs reform to enable such adoption, but bypassing districts and going straight to individual teachers defies fundamental tenets of education policy and practice. 

We want tools like CfT to work and to be used. But there need to be changes in how Anthropic (and other large-scale AI providers gain access to data. The way to make this work is to build data access and governance rules that school systems themselves control. Currently, several initiatives are underway to make this a reality. For example, the , the and the are active state- and district-led initiatives working to develop sophisticated, standards-based AI data access systems within district control. They ensure that AI models can draw on state-specific standards and curriculum and local classroom data where allowed, without requiring individual educators to take on the risk of feeding sensitive student information into third-party tools without the authority to do so.聽

Building such technology systems and their governance is hard and time-consuming work that may go against the 鈥渕ove fast and break things鈥� ethos that many tech companies embody. But Anthropic and other AI labs should be collaborating with states and school districts to help build and even assist in funding such systems for the public benefit. They would be part of the solution to this knotty problem instead of fueling the growing AI backlash in public education.

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