WIP: Privacy and Data Awareness Education in the Artificial Intelligence Age

This work-in-progress innovative practice paper describes how integrating data privacy education into a computer science/technology or engineering curricula will prepare students to adopt a privacy by design (PbD) approach when designing, building, and maintaining data driven systems. Artificial Intelligence (AI) is at the forefront of technological advancements and is revolutionizing everyday lives through aspects such as smart healthcare, self-driving cars, voice activation, and automated decision making. With exponential AI market growth, the need to better train AI models to behave in ways that emulate or complement human behavior necessitates large data sets often containing personal health, biometric, location and other personally identifiable information (PII). The data used for training AI applications has great transformative potential to improve our lives, but it offers a significant privacy risk to individuals. Using data without consent is a violation of global data protection laws and could result in financial and/or criminal penalties. The need to educate students about privacy is clear, but the literature is vague in addressing how to integrate privacy education into engineering, technology, or computer science programs. Given the complex and ever-changing privacy requirements, this paper discusses a roadmap for how data privacy can be integrated into AI, computer science and engineering curricula to help students comply with laws and ethical challenges when developing AI applications.