AI - Opportunities

Questions to Think About:

• How can AI improve people’s lives?

• What challenges or problems can AI help solve?

• What are some examples of AI helping governments, businesses, or communities?

• How might AI be used ethically and responsibly in these areas?

Real-World Opportunities for AI

1. Healthcare Innovation
Example: AI for personalised medicine and diagnostics
AI is used to analyse patient data, medical history, and environmental factors to create personalised treatment plans. This allows faster diagnosis and more accurate predictions of illness progression, reducing hospital visits and improving patient outcomes.

2. Safer Roads and Smarter Transport
Example: AI in self-driving cars and traffic optimisation
Machine learning models help autonomous vehicles detect obstacles, predict traffic patterns, and make decisions in real-time. AI can also reduce congestion by improving traffic light timing and route planning.

3. Reducing Social Harm
Example: Predictive analytics for child welfare or problem gambling
Government agencies can use AI to identify patterns in data related to family violence, abuse, or gambling addiction. This helps with earlier interventions and resource allocation, ultimately reducing harm.

4. Smarter Virtual Assistants
Example: AI in chatbots and voice assistants like Siri or Google Assistant
These systems use natural language processing (NLP) to understand and respond to human questions, automating tasks like booking appointments, answering FAQs, or translating languages.

5. Environmental Protection
Example: AI for predicting earthquakes or reducing energy usage
AI models can detect seismic patterns faster and with more accuracy than traditional systems. In energy management, AI helps optimise heating, cooling, and electricity use in buildings and cities.

Merit & Excellence-Level Thinking

To get Merit or Excellence, go beyond listing the use. Explain:

• What kind of data is used

• What AI techniques are involved (e.g., neural networks, NLP, image recognition)

• What the impact is (social, ethical, environmental, or economic)

• Whether there are any risks, limitations, or improvements possible

NZ Context Examples (From AI: Shaping a Future NZ, pp. 74–78):

• Reducing traffic congestion with smart sensors and real-time analytics

• Improving earthquake prediction and environmental monitoring

• Optimising hospital workforce schedules and reducing costs

• Helping resolve inequality using AI to identify key contributing factors

• Accelerating affordable housing construction with AI-driven project management