Navigating the AI Horizon: The impact on marketing and education
Associate Professor Jimmy Wong
Deputy Head – Master of Management Programme School of Business
Objectives
• Provide an overview of what AI entails, to demystify it, understand its value rather than to fear it.
• We shall look at AI from two lens:
– Abstract & strategic level (manager’s and senior executive’s lens)
– Operational level (tool lens)
Strategic level discussion of AI
What’s wrong with the definitions?
• “…programs, algorithms, systems and machines that demonstrate human intelligence” (Shankar 2018)
• “… manifested by machines that exhibit aspects of human intelligence” (Huang & Rust 2018)
• “… technology capable of… making decision… taking actions on behalf of humans” (Rouse 2023)
• AI should be defined according to its applications (Davenport et al., 2019)
• “…brand of computer science dealing with the simulation of intelligent behaviour in computers” (AI Discussion, ChatGPT, 2023; Merriam-Webster, n.d.)
Should we fear AI?
• Will it take away jobs (vs tasks)?
• Will it have privacy issues?
• How about potential misuse and ethical dilemmas?
• Will it start WWIII? Leonardo_Diffusion_XL_AI_terminator_with_nuclear_bomb_mushroom_0
- We are in the 6th Kondratieff Wave; marked by intelligent technologies - Technology, in the form of AI, will become the common transformation denominator.
The Four AI Intelligences (why?)
- To set expectations
- To know the required human investments
• Repetitive work
• Drivers, waiters, cashiers, etc…
• Need skills on data mgt
• Accountants, Financial Analysts, etc…
• Creative thinking
• Active problem solving
• Marketing managers, lawyers, etc…
Huang & Rust 2018
• Relationship building
• Thinking with feelings
• Psychiatrists, etc…
Domain for machines. Mostly data driven.
Domain for humans.
Applied to Marketing?
Descriptive Data
Diagnostic Data
Predictive Data
Prescriptive Data
Huang & Rust 2021
• Hardware
• Infrastructures
• Back-end developers Foundation Models Consumers, employees, these are users
AI Applications in business activities, these are the deployers
Source: Sam Altman, CEO, OpenAI (https://www.youtube.com/watch?v=0uQqMxXoNVs)
Classical mechanics
Quantum mechanics
Thermodynamics
Fluid dynamics
Nuclear physics
Astrophysics
Biophysics
Geophysics
Relativity
https://www.youtube.com/watch?v=Yq0QkCxoTHM
Other sub-fields of AI includes:
- Cognitive Computing
- Affective Computing
- Quantum Computing
- Robotics
- Autonomous Systems, etc…
• ChatGPT (OpenAI)
• Bing Chat (Microsoft)
• Gemini (Google)
• Llama 2 (Meta)
• Claude Pro (Anthropic)
What is Generative AI?
• She sells seashells on the ___________...
• Humpty dumpty ___________________...
Lye, C. Y. (2023),AD139 Generative AI in Tertiary Education : Effective Prompt Writing
Switch over to demo
• ChatGPT 4o GPTs vs. Claude Pro Projects comparison
• Show demo Volve & Etoros Ads created by AI; how to do these with Runway
• Show Synthesia vs. Heygen
• Show AdCreative.AI
State of AI in education: Impact on
the three pillars (1)
• What are the three pillars?
– AI for teaching (for teachers)
– AI for learning (for students)
– AI for assessment design
Bloom’s Taxonomy
State of AI in education: Impact on the three pillars (1)
• AI for teaching
• Teacher Assistance Tools: for lesson planning, sourcing educational content, and creating interactive presentations – Topic 5 sample video
• New Curriculum Design: developing and updating curriculums based on future needs – prompt engineering, critical thinking, research, etc.…
• Professional Development: AI training programs for teachers to stay updated with the latest educational technologies and methodologies.
New curriculum design:
Service Robot Masterclass for non-programmers
Master of Management
• Introduction to service robots
• Construction and hardware principles
• Basics of operations and applications
• Custom programming scripts
• Practical programming 1: hotel scenarios
• Practical programming 2: elderly care scenarios
• Practical programming 3: retail scenarios
State of AI in education: Impact on the three pillars (2)
• AI for learning
• Adaptive Learning Platforms: systems that adjust learning materials and pace according to individual student's abilities. (Show next slide & video)
• Enhanced Engagement: Use of AI-driven chatbots and virtual assistants for 24/7 student support, clarifying doubts and offering learning assistance. (Work in progress)
• Collaborative Learning: AI-enabled platforms that facilitate group projects and peer-to-peer learning, even in remote or hybrid learning environments. (Future?)
State of AI in education: Impact on the three pillars (3)
• AI for assessment & design
• Automated Grading: grade assignments and quizzes, provide immediate feedback. (Learning Management System being evaluated)
• Performance Analytics: track performance, identify strength & weaknesses. (Learning Management System being evaluated)
• RID framework* for assessment design – show sample assignments
– Recency: apply theoretical knowledge/skills to current scenarios
– Immediacy: respond to the assessment tasks in real time and space, viva voce
– Discovery: creation of new understanding and knowledge
– Show TMA Sample
* Wong, J & Lye, C. Y. (forthcoming), Assessment Redesign in the Era of Generative AI:
The Recency, Immediacy and Discovery (RID) Framework.
Ethical Considerations
• Bias, Reliability & Accountability – AI models need to be trained well to do this
• Authenticity – AI vs. Human content; what is creativity, what is knowledge?
• Safety & Privacy – Costs vs. benefits vs. risks
• Job displacement – Aim for task displacement and not job displacement
• Life-long learning – Implications from task displacement; how to motivate?
Future Landscape
• AI should focus on Mechanical and Analytical tasks (for now)
• Human reserves the rights to make decision (Intuitive and Empathetic)
• AI should be used for enhancing productivity and value creation (Blooms)
• Continuous and lifelong learning is vital
Source: Matt Wolfe YouTube Channel
