A new open-source tool named DraftMarks has been introduced to make the role of generative AI in student writing visible. Developed by researchers at the Georgia Institute of Technology and Stanford University, the software shifts the focus from detecting AI presence to illuminating the entire writing process. This innovation addresses a growing challenge in higher education where traditional tools like Turnitin or Grammarly fail to capture the nuances of collaboration between humans and artificial intelligence. Recent data indicates that 90% of college students now use AI in their coursework, with nearly half integrating it during the drafting phase. Consequently, educators need more than binary detection; they require insight into how students iterate, revise, and refine their work. DraftMarks functions as an augmented reading tool by layering visual cues directly onto digital documents. These visual markers, designed to mimic physical writing artifacts, distinguish between human-written and AI-generated content while highlighting the evolution of the text. For instance, eraser crumbs indicate heavily revised passages, while masking tape highlights sections initially generated by AI. Smudges signal changes to the strength of an argument rather than the content itself, and glue residue marks where AI-generated text was removed. Additionally, ghost text reveals instances where a writer prompted the AI but chose not to incorporate the output. By tracking draft history in real time, the tool classifies various edits and interactions, allowing these cues to appear instantly as work progresses. The design philosophy behind DraftMarks prioritizes educational reflection over mere surveillance. In an initial study involving twenty-one instructors, researchers identified the specific cues educators value when assessing learning, revision, and originality. This feedback informed the creation of a visual language that emulates familiar writing processes. The goal is to help both students and teachers see the effort involved and determine if learning objectives were met. Momin Siddiqui, a master's student at Georgia Tech and lead author of the project, stated that making the invisible parts of the process tangible forces writers to confront whether they are actively engaging with AI or passively accepting its output. The research team officially debuted DraftMarks at the Association for Computing Machinery's Conference on Human Factors in Computing Systems in Barcelona in April. To evaluate its effectiveness beyond the laboratory, the team conducted a follow-up study with seventy participants, including students, teachers, journalists, and general readers. Results showed that instructors focused on how ideas developed and where students exercised judgment, while general readers used the marks to assess trust and authorial intent. Unlike AI detectors that simply provide a percentage score, DraftMarks is intended to prompt deep reflection on how AI choices might subtly reshape a writer's tone and message. Researchers hope this tool will shift the broader conversation toward transparency in the age of generative AI. By providing a clearer window into how humans and AI write together, DraftMarks aims to help educators and students navigate the complexities of modern composition. It offers a method to understand the collaborative nature of writing, ensuring that the use of AI enhances learning rather than obscuring the intellectual work behind the final document. As AI continues to reshape writing practices, tools like DraftMarks may become essential for maintaining academic integrity and fostering intentional collaboration.