Undergraduate Interdisciplinary Minor in AI

PHIL 1145. Technology and Human Values. (4 Hours) 

Studies philosophy of technology, as well as ethics and modern technology. Considers the relationship between technology and humanity, the social dimensions of technology, and ethical issues raised by emerging technologies. Discusses 

PHIL 1300. Knowledge in a Digital World. (4 Hours) 

Examines the impact that information technologies (such as the internet, search engines, blogs, wikis, and smartphones); information processing techniques (such as big data analysis, machine learning, crowdsourcing, and cryptography); and information policies (such as privacy norms and speech restrictions) have on what we know and how much we know, as individuals and as a society. The digital world can enhance our ability to acquire knowledge by providing us with fast and cheap access to huge amounts of information. However, it can also undermine our cognitive abilities and provide us with inaccurate or misleading information. Studies normative frameworks from epistemology and ethics (such as epistemic value theory, the extended mind hypothesis, and moral rights) to evaluate these technologies and policies. 

MKTG 4604. Creating Business Value with Data and AI Technologies. (4 Hours) 

Designed to prepare students for careers that demand an understanding of the intersection between the growing data-driven and technology-enabled possibilities and various ways in which they can be creatively leveraged for designing better digital products and markets. Rapidly emerging new digital ecosystems, platforms, products, and services have been fundamentally transforming business practices and market landscapes in almost every industry. Using real-life case studies and projects, students examine and apply fundamental economic principles and conceptual business frameworks that are essential for understanding how emerging data opportunities and new computing technologies can be used for value creation. Considers various approaches for establishing fair and appropriate rules, regulations, and policies to mitigate potential biases, ethical challenges, and discrimination arising due to the digital transformation. 

ORGB 3203. Behavioral Aspects of Digital Transformation. (4 Hours) 

Examines the relationship between digital technologies and human behavior through the lens of foundational organizational behavior frameworks. Covers issues related to the impact of digital technologies on behavior and the impact of human behavior on the development of these technologies and the process of digital transformation. Analyzes the behavioral implications of current developments in digitalization and digital transformation. Topics include algorithmic management, bias in training large language models, AI-driven influence, behavioral responses to disruptive change, and leadership of transformation. 

Pre-requisite(s): COOP 3945/COOP 3946/COOP 3947/COOP 3948, and ENGW 1102 or ENGW 1111. 

INMI 2710. Social Impact Consulting and Artificial Intelligence 

Engages student teams in actively crafting innovative solutions to critical social challenges. Students work directly with mission-driven entities to provide analyses, recommendations, strategies, and assessments critical to growth, viability, and impact. Emphasizes the equitable, responsible, and effective application of artificial intelligence tools and other frontier technologies to enhance problem-solving approaches and drive data-informed decision making. Offers students an opportunity to gain a richer perspective on catalyzing social impact; develop skills in communication across social, cultural, and disciplinary boundaries; and apply sound leadership and decision-making principles within diverse environments. Provides hands-on support to entrepreneurs, initiatives, and organizations in local communities and beyond. 

BUSN 3501. Impact of AI on Business. (4 Hours) 

Examines the impact of artificial intelligence on the core pillars of business—finance, sales, marketing, operations, engineering, and entrepreneurship. Offers students an opportunity to obtain a holistic understanding of how AI is reshaping these critical business domains and fostering the next wave of innovation. Discusses new business models, changes in go-to-market strategies for businesses, and the impact of AI-driven predictive analytics on finance. Explores new business possibilities enabled by AI and new approaches for using AI to complete traditional business activities. 

Prerequisite(s): FINA 2201 with a minimum grade of D- or INNO 2301 (may be taken concurrently) with a minimum grade of D- or MKTG 2201 with a minimum grade of D-

FINA 4390. Machine Learning in Finance. (4 Hours) 

Offers students an opportunity to prepare for rapid changes in the financial services world due to technological innovations and to understand how ML and AI tools are relevant in the financial services industry; to learn the basics of these tools, including machine learning; and to analyze the ethical considerations in the use of these tools in financial services. Seeks to train students to develop data analytics solutions using machine learning and deep learning models, allowing them to answer analytical questions that are encountered in the finance space. Working knowledge of Microsoft Excel or other spreadsheet programs is strongly recommended. 

Prerequisite(s): FINA 4335 with a minimum grade of D- or FINA 4380 with a minimum grade of D- 

INTB 3330. Digital Globalization. (4 Hours) 

Examines the opportunities and challenges that digitalization presents for international business. Explores digitalization processes at the societal, country, and company levels across various international contexts, including both developed and emerging markets. Investigates the cost and benefits of digitalization for governments, countries, and different types of companies such as analog firms, platform-based businesses, and family enterprises within the global landscape. 

Restriction: Junior or Senior standing 

MKTG 2720. Enabling Technologies for Consumer Engagement. (4 Hours) 

Introduces how organizations use the latest technologies for enhancing consumer engagement. Uses case studies and exercises to offer a broad overview of creative marketing applications across multiple industries and touchpoints. Examples may include augmented reality, virtual reality, mixed reality, internet of things, real-time interactivity, geolocation tools, wearables, dynamic content personalization, automation, social media, chatbots, voice assistants, and artificial intelligence. 

MKTG 4606. Digital, Analytics, Technology, and Automation Research Practicum. (4 Hours) 

Offers an advanced-level experiential learning opportunity for students who wish to gain exposure to solving problems facing businesses and other organizations using data analytics and digital technology applications. The 

practicum offers students an opportunity to learn through active participation in client-centric challenges in a DATA context. Faculty and organizations present a variety of such challenges, and students are guided through solving these challenges. Discusses how new technologies affect human behavior, examines how digital convergence impacts society and organizations, and studies how to apply state-of-the-art methods in machine learning to create value for businesses and organizations. Students practice communicating and enabling change within organizations. Focuses on building students' technical and managerial skills to develop capacities to situate a business problem in a wider research context. 

HLTH 5800. AI Across the Health Sciences. (4 Hours) 

Presents foundational information about artificial intelligence and its applications in healthcare, public health, pharmacology, and pharmaceutical sciences. Develops AI literacies for entry-level clinical practice, public health, and health-related careers. Provides an overview of the history of AI, most common types of AI approaches, and state-of-the-art of AI in health-related applications. Distinguishes realities from hype around AI's capabilities and limitations and reviews ethical and regulatory considerations. Offers students experiential opportunities to build a conceptual AI solution to a real-world problem in the health space. Technical background in AI/computer science not required. 

PHTH 5360. AI at the Intersection of Health and Society (3 Hours) 

Studies how artificial intelligence can be applied in the domain of health and the issues that arise as a result. Examines how AI tools could affect social determinants of health, which are conditions that influence health and well-being (e.g., poverty, education, work, place, as well as discrimination by gender and racial identities). Explores the principles of machine learning predictions, classification, causality, and fairness. Covers the techniques to mitigate such concerns, notably through human-centered AI, participatory design, and value-sensitive design. 

Restrictions: Graduate, Junior, Senior standing 

PHYS 4211. Artificial Intelligence in the Physical Sciences (4 Hours)

Introduces artificial intelligence (AI) and machine learning (ML) approaches that are powering data-driven scientific research. Gives students a broad overview of why and how ML is used in multiple science disciplines. Introduces the underlying principles of a diverse set of ML models and AI frameworks. Discusses how to combine domain knowledge with AI tools to advance research and solve challenging problems in multiple fields of physical science. 

CRWT 1801: Writing Creatively in the Age of AI. 

Engages students in the practice of creative writing with state-of-the-art writing tools, collaborative platforms, and frontier technologies such as artificial intelligence. Examines a wide range of works of literature, both those written with machines and those written about machines. Focuses on student writing in diverse genres and examines how machine-produced writing is reshaping understandings of creativity, authorship, and copyright.