It is critical to understand past science education reform to know what could be explored in the future (Cheng et al., 2010). The purpose of this position paper is to describe a historical timeline of science education. Using historical documents and current science education research, the authors create an evolutionary description of science education changes over time and how these shifts could influence how Artificial Intelligence is used in science education. Teachers should meaningfully implement the use of AI in ways that focuses on student-centered learning and restore the progress made by the K-12 Framework and NGSS, including generating ideas about problems that students can solve in an interest area, analyzing large sets of real-world data, generating grade appropriate science readings to develop background knowledge, and using AI to grade unique student work to replace multiple-choice response exams. AI and science education may best be described by a Chat GPT response… “It's important to note that while AI can enhance science education, it should not replace human teachers. Instead, it should be used as a tool to augment and support their expertise, fostering a blended learning environment that combines the benefits of technology with human guidance and mentorship”.