Archive for February, 2024

Beyond the Code: Shaping the Future with AI-Integrated Curricula

The inspiration for this blog post was sparked by engaging discussions in the last couple of months as we advance our campus’ AI Community of Practice (COP) initiative. This week, I talked with Professor Matt Beane about the intricacies of working and learning alongside intelligent machines. I also spoke with another professor about the critical importance of embedded ethics within our curriculum. Finally, the questions I raise below are also inspired by conversations with other attendees and listening to the University of California AI Congress panelists, which is currently in progress. These interactions have led me to contemplate two questions at the forefront of our journey into the future of higher education: 

  • How can we equip our students to navigate a life enriched by artificial intelligence in their living, working, and learning environments? 
  • In this rapidly evolving landscape, how do we redefine the pedagogical frameworks of higher education to empower our students as discerning consumers and transformative agents of their futures?
  • How could a major or discipline that promotes competencies prepare our students to live, work, and learn alongside intelligent machines? 

I asked ChatGPT what major could look like. The prompts I use, which resulted in the response below, could be more sophisticated. Still, they will introduce a starting point to answer the questions above.

Technology and Human Society Major

The Technology and Human Society major is an innovative, interdisciplinary program designed to prepare students for the challenges and opportunities of integrating artificial intelligence, robotics, and digital technologies into our daily lives. This four-year curriculum bridges the gap between technology and the liberal arts, focusing on developing a broad set of skills, including technical proficiency, ethical reasoning, and a deep understanding of the societal impact of technological innovation.

Year 1 lays the foundational knowledge in computer science, artificial intelligence, psychology, and ethics, emphasizing the role of technology in society and the ethical considerations accompanying technological advancement.

Year 1: Foundations

Fall Semester

  • Introduction to Artificial Intelligence and Robotics
    • Objective: Introduce students to AI and robotics fundamentals, including history, key technologies, and applications.
    • Content: Overview of AI (machine learning, neural networks), robotics (types, uses in industry), and the societal impacts of these technologies.
    • Activities: Lectures, essential programming assignments, and group discussions on AI’s ethical implications.
  • Introduction to Computer Science
    • Objective: Provide a foundation in computer science principles and programming.
    • Content: Basics of programming (using languages like Python or Java), data structures, algorithms, and software development processes.
    • Activities: Coding exercises, project work to develop simple applications, quizzes.
  • Introduction to Psychology
    • Objective: Offer insights into human behavior, cognition, and how this knowledge applies to technology design and interaction.
    • Content: Cognitive processes, learning theories, motivation, emotion, perception, and human factors in design.
    • Activities: Case studies, experiments, and written assignments on psychology’s role in technology.
  • General Education Requirement (Mathematics)
    • Objective: Strengthen mathematical skills foundational to technical disciplines.
    • Content: Algebra, trigonometry, basic statistics, relevance of mathematical principles in technology and science.
    • Activities: Problem sets, exams, group projects applying mathematical concepts to real-world problems.

Spring Semester

  • Introduction to Ethics in Technology
    • Objective: Explore the ethical challenges in technology development and deployment.
    • Content: Privacy, security, data ethics, AI biases, and ethical frameworks.
    • Activities: Debates, ethical dilemma case studies, reflective essays.
  • Principles of Sociology
    • Objective: Understand the impact of technology on society and vice versa.
    • Content: Social structures, cultural norms, technology’s role in societal change, digital divide issues.
    • Activities: Research papers, group presentations, and discussions on technology’s societal impacts.
  • Calculus for Engineers
    • Objective: Equip students with calculus tools applicable to engineering and technology fields.
    • Content: Limits, differentiation, integration, applications of calculus in problem-solving.
    • Activities: Problem-solving sessions, quizzes, and application projects.
  • General Education Requirement (Writing)
    • Objective: Enhance written communication skills, which are crucial for all professional fields.
    • Content: Academic writing, research paper construction, argumentative essays, technical writing basics.
    • Activities: Writing assignments, peer reviews, workshops on research and citation.

This first year sets a strong foundation across various disciplines, emphasizing the integration of technical skills with an understanding of ethical, psychological, and societal aspects. This holistic approach prepares students to navigate the complexities of technology’s role in society.

Year 2 expands on this foundation with courses in human-computer interaction, digital humanities, environmental science, and data science, encouraging students to explore the interdisciplinary nature of technology’s relationship with human culture and environmental sustainability.

Year 2: Interdisciplinary Exploration

Fall Semester

  • Human-Computer Interaction (HCI)
    • Objective: Explore the design, evaluation, and implementation of interactive computing systems for human use.
    • Content: Principles of HCI, user-centered design, usability testing, and the impact of HCI in developing compelling user interfaces.
    • Activities: Design projects, usability studies, and critiques of existing systems.
  • Environmental Science and Sustainable Technology
    • Objective: Investigate the role of technology in addressing environmental challenges and promoting sustainability.
    • Content: Fundamentals of environmental science, renewable energy technologies, sustainable design principles, and case studies on technological solutions to ecological problems.
    • Activities: Research papers on sustainable technologies group projects designing sustainable solutions.
  • Digital Humanities
    • Objective: Introduce students to the application of digital technologies in humanities research and scholarship.
    • Content: Digital tools and methods in humanities research, digital archiving, text analysis, and the impact of digital technology on cultural artifacts.
    • Activities: Digital project assignments, workshops on digital tools, analysis of digital humanities projects.
  • Elective (e.g., Foreign Language, Creative Arts)
    • Objective: Allow students to explore interests outside their major and enhance their soft skills or global competencies.
    • Content and Activities: Depending on the elective chosen, students might engage in language learning, artistic creation, or other creative pursuits, emphasizing the importance of diverse skills in a technologically driven world.

Spring Semester

  • Data Science Fundamentals
    • Objective: Offer an introduction to the core concepts of data science and its applications.
    • Content: Basic statistics, data analysis, machine learning algorithms, and data visualization techniques.
    • Activities: Data analysis projects using real-world datasets and hands-on exercises with data science tools.
  • Technology Policy and Governance
    • Objective: Examine the complex relationship between technology innovation, policy formulation, and governance mechanisms.
    • Content: Overview of technology law, privacy issues, intellectual property rights, and governance models for emerging technologies.
    • Activities: Policy analysis papers, guest lectures from technology law and policy experts.
  • Introduction to Robotics
    • Objective: Provide foundational knowledge on robotic systems’ design, operation, and application.
    • Content: Basics of robotics, including sensors, actuators, control systems, and robot programming.
    • Activities: Robotics lab exercises, programming assignments, and design of simple robotic systems.
  • Elective (e.g., Business Fundamentals, Philosophy)
    • Objective: Allow students to explore additional disciplines that complement their understanding of technology’s societal role.
    • Content and Activities: Depending on the elective chosen, students could study the basics of business management, ethical philosophy, or other areas that broaden their educational experience.

This year builds on the foundational knowledge acquired in Year 1, expanding students’ understanding of the interaction between technology and various facets of society and the environment. The curriculum is designed to foster an interdisciplinary approach, encouraging students to apply technology in solving complex societal problems while considering ethical, environmental, and policy implications.

Year 3 delves into advanced topics such as cyber-physical systems security, cognitive science, healthcare robotics, and the societal implications of technology, preparing students for the complex ethical and practical challenges they will face in the tech-driven world.

Year 3: Advanced Topics and Applications

Fall Semester

  • Cyber-Physical Systems Security
    • Objective: Understand the security challenges and strategies of cyber-physical systems, which integrate physical processes with networked computing.
    • Content: Principles of cybersecurity, vulnerabilities of cyber-physical systems, security technologies, and case studies on securing infrastructure.
    • Activities: Simulations of cyber-attacks, design of security solutions, analysis of recent cybersecurity incidents.
  • Cognitive Science and Artificial Intelligence
    • Objective: Explore the intersection of cognitive science and AI, focusing on how AI models can replicate or augment human mental processes.
    • Content: Basics of cognitive science, neural networks, natural language processing, and cognitive robotics.
    • Activities: Projects developing simple AI models, discussions on AI and cognition, and critiques of AI’s role in understanding the human mind.
  • Robotics in Healthcare
    • Objective: Examine the application and implications of robotics in healthcare, including surgery, rehabilitation, and patient care.
    • Content: Types of healthcare robots, ethical considerations, patient safety, and robotics case studies in clinical settings.
    • Activities include evaluating robotic healthcare technologies, guest lectures from healthcare professionals, and designing proposals for new healthcare robotics applications.
  • Elective (e.g., Advanced Programming, Machine Learning)
    • Objective: Provide in-depth technical skills relevant to the student’s interests and career goals.
    • Content and Activities: Depending on the elective, students could engage in advanced software development projects, machine learning model building, or other specialized technical tasks.

Spring Semester

  • Technology and Society
    • Objective: Delve into the complex relationship between technology and societal development, focusing on historical and contemporary perspectives.
    • Content: Technology’s role in social change, digital culture, technology and inequality, and future predictions.
    • Activities: Research papers on technology’s societal impacts, seminars with technology thought leaders and collaborative group projects.
  • Ethical AI
    • Objective: Address the ethical dimensions of AI development and use, including bias, transparency, and accountability.
    • Content: Ethical frameworks for AI, case studies of AI ethics in practice, regulation and policy implications.
    • Activities: Ethical audits of AI systems, debates on AI ethics topics, and development of ethical guidelines for AI projects.
  • Project-Based Learning in AI and Robotics
    • Objective: Apply knowledge and skills in AI and robotics to a real-world or simulated project.
    • Content: Project management, teamwork, technical development, and project presentation.
    • Activities: Team projects from conception to demonstration, project reports, presentations to peers and faculty.
  • Elective (e.g., Innovation and Entrepreneurship, Advanced Data Science)
    • Objective: Expand students’ abilities to innovate and apply data science techniques in various contexts.
    • Content and Activities: Depending on the elective chosen, students could create a startup business plan, engage in advanced statistical analysis, or explore innovative technology solutions.

This third year is crucial for deepening students’ technical expertise and understanding of the broader implications of technology. It emphasizes applying theoretical knowledge to practical and ethical challenges, preparing students for advanced study, research, or professional careers in technology and society.

Year 4 culminates in a capstone project that integrates the knowledge and skills acquired throughout the program alongside courses in professional development and electives that allow for specialization in areas of personal interest.

Year 4: Specialization and Integration

Fall Semester

  • Capstone Project I
    • Objective: Begin a comprehensive project integrating knowledge and skills acquired throughout the major. The project should address a significant issue at the intersection of technology, society, and ethics.
    • Content: Project proposal development, literature review, project planning, and initial implementation.
    • Activities: Weekly project meetings, progress presentations, peer feedback sessions.
  • Seminar on Current Topics in Technology and Society
    • Objective: Engage with cutting-edge discussions on the impacts of technology on society, including emerging trends and challenges.
    • Content: Guest lectures, current articles and case studies, and student-led seminars on topics of interest.
    • Activities: Participate in discussions, present seminar topics, and write reflective essays.
  • Elective in Area of Specialization (e.g., Advanced Robotics, AI in Finance)
    • Objective: Deepen technical knowledge and skills in a specific area of interest related to technology and society.
    • Content and Activities: Depending on the elective, coursework could involve advanced technical training, project work, and industry or research applications.
  • Elective (General Education or Free Elective)
    • Objective: Offer a final opportunity to explore interests outside the major or to complement the major with additional skills or knowledge.
    • Content and Activities: Varied, depending on the student’s interests and the offerings available, such as arts, humanities, social sciences, or additional technical electives.

Spring Semester

  • Capstone Project II
    • Objective: Complete and present the capstone project, demonstrating the integration of technical skills, ethical considerations, and societal impact.
    • Content: Final implementation, analysis, and evaluation of the project results.
    • Activities: Public project presentation, final report submission, peer and faculty feedback.
  • Professional Development in Technology
    • Objective: Prepare for career success in the technology sector, including job search strategies, professional networking, and life-long learning skills.
    • Content: Resume building, interview skills, professional ethics, continuing education opportunities.
    • Activities: Workshops, mock interviews, networking events, alum panels.
  • Elective in Area of Specialization (e.g., Ethical Hacking, Digital Marketing)
    • Objective: Continue to build expertise in a chosen specialization, preparing for specific career paths or advanced study.
    • Content and Activities: Advanced coursework and projects tailored to the specialization, potentially including certifications, competitions, or collaborations with industry partners.
  • Elective (General Education or Free Elective)
    • Objective: Complete the undergraduate experience with a course that broadens perspectives or enhances personal and professional skills.
    • Content and Activities: Options could include advanced study in a foreign language, leadership development, creative arts, or other areas of personal interest.

The final year is designed to culminate the interdisciplinary learning experience, with a significant focus on the capstone project that embodies the student’s understanding and application of technology in society. It also emphasizes professional development and specialization, preparing students to transition from academic study to career or further education. This curriculum equips graduates with a comprehensive skill set that is both technically proficient and ethically aware, ready to tackle the challenges of a rapidly evolving technological landscape.

Graduates of the Technology and Human Society major will be uniquely equipped to contribute to various fields, from technology development and policy to digital humanities and environmental sustainability. They will possess the critical thinking, ethical reasoning, and technical skills necessary to navigate and shape the future of our increasingly digital world.

AI’s role in higher education is inevitable; it’s already integrated into all aspects of the campus, from teaching and learning to research and administrative operations. What is not inevitable is the utility and effectiveness of AI in the future world where our students will live, learn, and work. Higher education must consider the following questions to prepare students to live, work, and learn effectively in AI.

  • How can we equip our students to navigate a life enriched by artificial intelligence in their living, working, and learning environments? 
  • In this rapidly evolving landscape, how do we redefine the pedagogical frameworks of higher education to empower our students as discerning consumers and transformative agents of their futures?
  • How could a major or discipline that promotes competencies prepare our students to live, work, and learn alongside intelligent machines? 

Charting the Future of AI in Higher Education: An Invitation to Collaborate on a Higher Education AI Capability Maturity Model

As we navigate the evolving landscape and adoption of artificial intelligence (AI) in higher education, it’s become increasingly clear that a guiding framework is needed to help chart these efforts.

Since the launch of ChatGPT in November 2022, I’ve been closely observing how higher education institutions adapt to and embrace AI technologies. My observations suggest the vast potential of AI to transform our campuses, but it has also highlighted the complexities of effectively and ethically integrating these technologies.

In co-leading the AI Community of Practice at our institution, I’m excited about various AI-related initiatives emerging across departments. These are driven by genuine enthusiasm and a desire to innovate, and the campus can further enhance through a coordinated institutional-level effort. In addition, it’s as essential to acknowledge and learn from other institutions’ AI efforts to accelerate our campus initiatives. These observations led me to create the Higher Education AI Capability Maturity Model specifically for higher education—an initial attempt to develop a comprehensive framework that can unify disparate AI efforts cohesively and strategically.

This model is a starting point, a compass to guide campus leaders and communities through the initial stages of AI integration in higher education. It aims to evaluate current AI initiatives, foster discussions about future goals, and provide a benchmark for measuring progress against other institutions. Importantly, this model is designed to evolve through collaboration and shared insights from the broader higher education community.

I recognize that this initial model is beginning a journey toward a more robust and comprehensive framework. I invite the higher education community to join me in this conversation. I’m actively seeking ideas, feedback, and input to refine and expand this model, making it truly reflective of the diverse needs and aspirations of higher education institutions everywhere.

This effort is not just about creating a tool for assessment or benchmarking; it’s about fostering a culture of collaboration and innovation in using AI on our campuses. Let’s collaborate on improving this model and how we can ensure that our approach to AI is strategic, inclusive, and aligned with the core values of higher education.

Draft Higher Education AI Capability Maturity Model

Please get in touch with me at if you’re interested in working together.

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