TECH
You know we've reached peak interest in artificial intelligence (AI) when Oprah Winfrey hosts a television special about it. AI is truly everywhere. And we will all have a relationship with it—whether using it, building it, governing it or even befriending it.
But what exactly is AI? While most people won't need to know exactly how it works under the hood, we will all need to understand what it can do. In our conversations with global leaders across business, government and the arts, one thing stood out—you can't fake it anymore—AI fluency, that is.
AI isn't just about chatbots. To help understand what it is about, we've developed a framework which explains the broad range of capabilities it offers. We call this the "capabilities stack."
We see AI systems as having seven basic kinds of capability, each building on the ones below it in the stack. From least complex to most, these are: recognition, classification, prediction, recommendation, automation, generation and interaction.
Recognition...At its core, the kind of AI we are seeing in consumer products today identifies patterns. Unlike traditional coding, where developers explicitly program how a system works, AI "learns" these patterns from vast datasets, enabling it to perform tasks. This "learning" is essentially just advanced mathematics that turns patterns into complex probabilistic models—encoded in so-called artificial neural networks.
Once learned, patterns can be recognized—such as your face, when you open your phone, or when you clear customs at the airport.
Pattern recognition is all around us—whether it's license plate recognition when you park your car at the mall, or when the police scan your registration. It's used in manufacturing for quality control, to detect defective parts; in health care, to identify cancer in MRI scans; or to identify potholes by using buses equipped with cameras that monitor the roads in Sydney.
Classification...Once an AI system can recognize patterns, we can train it to detect subtle variations and categorize them. This is how your photo app neatly organizes albums by family members, or how apps identify and label different kinds of skin lesions. AI classification is also at work behind the scenes when phone companies and banks identify spam and fraud calls.
In New Zealand, non-profit organization Te Hiku developed an AI language model to classify thousands of hours of recordings to help revitalize Te Reo Māori, the local indigenous language.
Prediction...When AI is trained on past data, it can be used to predict future outcomes. For example, airlines use AI to predict the estimated arrival times of incoming flights and to assign gates on time so you don't end up waiting on the tarmac. Similarly, Google Flights uses AI to predict flight delays even before airlines announce them.
In Hong Kong, an AI prediction model saves taxpayer money by predicting when a project needs early intervention to prevent it overrunning its budget and completion date. And when you buy items on Amazon, the e-commerce giant uses AI to predict demand and optimize delivery routes, so you get your packages within hours, not just days.
Recommendation...Once we predict, we can make recommendations for what to do next. If you went to Taylor Swift's Eras tour concert at Sydney's Accor stadium, you were kept safe thanks to AI recommendations. A system funded by the New South Wales government used data from multiple sources to analyze the movement and mood of the 80,000 strong crowd, providing real-time recommendations to ensure everyone's safety.
AI-based recommendations are everywhere. Social media, streaming platforms, delivery services and shopping apps all use past behavior patterns to present you with their "for you" pages. Even pig farms use pig facial recognition and tracking to alert farmers to any issues and recommend particular interventions.
Automation...It's a small step from prediction and recommendation to full automation. In Germany, large wind turbines use AI to keep the lesser spotted eagle safe. An AI algorithm detects approaching birds and automatically slows down the turbines, allowing them to pass unharmed.
Closer to home, Melbourne Water uses AI to autonomously regulate its pump control system to reduce energy costs by around 20% per year. In Western Sydney, local buses on key routes are AI-enabled: if a bus is running late, the system predicts its arrival at the next intersection and automatically green-lights its journey.
No comments:
Post a Comment