5.6. Key Concepts & References

Key Concepts

• Artificial Intelligence (AI): A system trained on large datasets to identify patterns, generate content, make predictions, or assist with decision-making. In higher education, AI supports teaching, research, and administrative work.
• Generative AI: A type of AI that creates new text, images, code, or sound in response to prompts. Examples include ChatGPT, Claude, and DALL·E.
• AI Literacy: The ability to understand, evaluate, and ethically use AI systems, including awareness of their capabilities, limitations, and implications for privacy, equity, and inclusion.
• AI Scraping: The automated collection of data from websites or digital platforms using artificial intelligence tools or algorithms. AI scraping can be used to gather text, images, or metadata for analysis or model training but raises ethical and legal concerns related to consent, privacy, and copyright. Responsible practice requires verifying permissions, following institutional or site policies, and ensuring data are collected and used ethically.
• Prompt Design (Prompt Engineering): The practice of crafting effective and ethical input queries to obtain relevant, accurate, and purposeful AI outputs.
• Bias: Systematic distortion in AI outputs that reflects inequities, stereotypes, or omissions in training data, leading to underrepresentation or misrepresentation of certain groups or perspectives.
• Transparency and Disclosure: Clearly describing how AI contributed to text, data, or analysis, and identifying where interpretation and authorship remain human.
• Reproducibility: Providing enough documentation of tools, versions, and parameters for others to replicate AI-supported processes and verify findings.
• Ethical Use: Applying AI responsibly—verifying accuracy, protecting privacy, respecting intellectual property, and disclosing its use when appropriate.
• Integration of AI into Work and Life: The practical use of AI tools across professional, educational, and personal contexts, emphasizing balance between efficiency and ethics.
• AI in Education: Application of AI in teaching, learning, and student support, including tutoring systems, automated feedback, accessibility tools, and personalized learning pathways.
• AI in Research: Use of AI to expand scholarly inquiry through literature summarization, hypothesis generation, data analysis, visualization, and trend detection, while acknowledging limits related to accuracy and bias.
• AI for Productivity: Leveraging AI to streamline everyday work tasks—such as scheduling, drafting communication, or project management—while maintaining human oversight and critical judgment.
• Applied Challenges: Short, role-based scenarios designed to help users practice applying AI tools in authentic professional contexts, such as creating quizzes, drafting professional emails, or summarizing research.
• Do / Due Framework: A reflective approach to AI literacy that combines doing tasks with AI and considering what is due in terms of ethics, verification, and professional responsibility.
• AI in Personal Life: The use of AI for individual organization, learning, and creativity—such as journaling, habit tracking, or translation—while maintaining awareness of privacy and data-sharing boundaries.

References

Liu, Y., Wu, S., Ruan, M., Chen, S., & Xie, X.-Y. (2025, May 13). Research: Gen AI makes people more productive-and less motivated. Harvard Business Review. https://hbr.org/2025/05/research-gen-ai-makes-people-more-productive-and-less-motivated

Stapleton, A. [DrAndyStapleton]. (2025, May 6). How smart academics use AI (without breaking the rules) [Video]. YouTube. https://youtu.be/no0Tt-Ip9AI

Wharton School. (2023, August 3). Practical AI for instructors and students part 4: AI for teachers [Video]. YouTube.

Google. (2024). Google AI Essentials. Grow with Google. https://grow.google/ai-essentials/

Harvard Business Review. (2023, June 26). Boost your productivity with generative AI. Harvard Business Review. https://hbr.org/2023/06/boost-your-productivity-with-generative-ai

Harvard Business Review. (2025, February 28). How is your team spending the time saved by gen AI? Harvard Business Review. https://hbr.org/2025/03/how-is-your-team-spending-the-time-saved-by-gen-ai

Microsoft. (2024, May 8). AI at work is here. Now comes the hard part. Microsoft WorkLab. https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part

Microsoft. (2025, April 22). 2025: The year the Frontier Firm is born. Microsoft WorkLab. https://www.microsoft.com/en-us/worklab/work-trend-index/2025-the-year-the-frontier-firm-is-born