This study provides a framework for utilizing artificial intelligence (AI) in the college mathematics classroom. First, it reviews current trends in mathematics education, as they relate to active learning.  Historically, much mathematics instruction has been done in the traditional mode of a non-interactive lecture given by a faculty member, a format where the learner behaves passively while the lecturer delivers information in recent years, more student-focused instructional methods have gained some popularity.  The review of the literature provided herein includes an examination of the use of various techniques in college mathematics instruction. We look at instructional techniques that can be used in addition to or instead of purely didactic lecture-based methods. In contrast to the prior format, the lesson examples provided toward the end of this study present approaches that shift the learning paradigm from a model where the teacher is in complete authority to a participatory model where learners and educators together decide how curriculum is delivered and how learning outcomes are assessed by identifying, examining, and selecting modes of delivery and assessment. Following this, we look at topics related to the use of AI in the mathematics classroom. Since the use of AI, especially in the classroom, is a relatively new development, the literature in this area is still in its early stages. Next, this study develops a theoretical framework offering educators the ability to structure lessons on a variety of mathematical topics with both AI and more traditional instructional methods. This study concludes with three sample lessons, with the latter presenting examples of the utilization of the framework at various levels of college mathematics: developmental, core, and upper-level math major courses. The lessons each include an objective, procedures (including both AI-based and non-AI based instructional methods), and a listing of the knowledge, skills, and values acquired in the lesson.

In recent years, Artificial Intelligence (AI) has made significant progress, influencing a variety of aspects of our daily existence. Advances in AI technology must be considered with ethical concerns. There are concerns about how autonomous and advanced AI systems may affect human rights, privacy, and society. This led to the creation of AI ethics, a new area that sets standards for responsible AI development and implementation. Descartes' dualism serves as a fundamental framework for resolving inquiries regarding AI consciousness, moral agency, machine consciousness, moral agency, and ethical responsibility in the context of Artificial Intelligence (AI) ethics. In this paper, the relationship between Cartesian dualism and contemporary AI ethics is investigated, with a focus on the ways in which Descartes' philosophical concepts inform current discussions regarding the ethical treatment of AI entities, the nature of machine consciousness, and the implications for human-machine interactions. The ethical implications of AI technology must be addressed in conjunction with these advancements. As AI systems become increasingly autonomous and sophisticated, there have been apprehensions about their potential impact on human rights, privacy, and society. This has resulted in the emergence of a new field, AI ethics, which aims to establish guidelines and principles for the responsible development and deployment of AI systems. In this paper, the applicability of Descartes' concepts to the field of contemporary AI ethics is investigated. Specifically, it examines the ways in which Cartesian Dualism influences our comprehension of AI consciousness, the ethical treatment of AI entities, and the moral obligations of AI developers and users.

Some important warnings about how we use technology in the philosophies of Plato, Martin Heidegger, Zhuangzi, and C. S. Lewis are relevant to the use of AI in education. Plato cautions us concerning what is lost when we let technology replace some of our own thinking processes. Far from making us more intelligent, the use of AI in writing falls into the mistakes Plato warns us against: We get lazy with learning and remembering, and we substitute a bundle of information for the wisdom and comprehension that constitute genuine knowledge. Heidegger advises against using technology to create more of a product and reducing the role of humanity to merely a part of the system of production. When writing with AI, we abandon our responsibility to shepherd our own work, and we become tools in the machinery of creating a written product, even letting the software guide us rather than the other way around. Zhuangzi teaches us not to follow the patterns set by social convention. Material written by AI is a distillation of conventional word-patterns. Lewis warns us that we abolish part of humanity when we use technology to get what we want without first learning to love what is good. Using AI to get our writing done means sacrificing the essential human love for finding and understanding the truth, instead allowing our own words to be conditioned by unknown authors of algorithms. In this article I explain these matters and close with some helpful suggestions for how we might use AI more constructively—assuming we are going to use it at all.