Artificial Intelligence
Dr Micheal Harre has been thinking alot about how our workplaces will involve incorporating artificial intelligence. His use of the technology in exploring the emergence of economic bubbles is already heavily reliant on AI to provide detailed analysis.
Dr. Michael Harré an artificial intelligence enthusiast and lecturer in Complex Systems at the University of Sydney, believes living and working with AI will force the world to reassess basic assumptions about our sense of self.
"What will it be like to regularly confront an AI, or a robot with an AI in it, that behaves like a human?"
"What will it be like to regularly confront an AI, or a robot with an AI in it, that behaves like a human?" Harré asks. "The fact that we will be interacting with the appearance of consciousness in things that are clearly not biological will be enough for us to at least unconsciously revise what we think consciousness is."Today, AI systems and people have very different decision-making processes. Humans rely strongly on intuition, while AIs calculate all possible options and deduce the most likely answer. All this data-crunching comes at a cost: the vast computational power that's needed limits the number of tasks AI can do.
According to Harré, AI is a very different discipline from robotics. Artificial intelligence is a field of computer science that mimics the natural learning process of the human brain by creating what are called artificial neural networks. A popular technique used today is reinforcement learning. In such systems, each correct answer reinforces the AI's neural pathways, so it actually learns from experience. The software isn't specifically coded – rather the program evolves its own algorithms and uses feedback to refine the results.
This form of machine learning is very good at dealing with big data, and makes them invaluable for services such as fraud detection and security surveillance. Working with these huge inputs of information makes AI a power-hungry beast that devours huge computational resources.
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AI has been moving into various industries since the 1990s – from finance to communications, heavy industry and even toys – constantly evolving and becoming more sophisticated. Over the last two years alone, there has been dramatic evolution of artificial intelligence. Energy-efficient computers and microchips based on the neural structure of the brain are driving the surge in AI advancement. Digital assistants such as Apple's Siri and Amazon's Alexa, movie recommendation services and online customer support are all examples of artificial intelligence in services that we increasingly take for granted.Harré is part of a new wave of researchers exploring the relationship between human thinking, artificial intelligence and economics. He believes that understanding human cognition will drive AI advancement – and vice versa. "The stronger the connection we can draw between economics, psychology and neuroscience – three very different fields studying humans at very different scales – the better our understanding will be in all three areas."
"We are not well equipped, cognitively speaking, to deal with the complexity of the systems that have come to dominate our world: financial and economic systems, climatic systems and even our social interactions and how information is spread," states Harré. "Everything depends on everything else, often leading to the impression that chaos and disorder dominate, and that trying to understand such systems is a lost cause. But if we scratch the surface, there are often some basic underlying principles. Understanding these is the biggest challenge we face today, and this is what my work aims to do."
"I look at the mathematics reflected in complex systems. This can give us a better understanding of how relatively small variations in human behaviour can lead to quite significant and sometimes sudden system-level consequences - such as the behaviours of individual buyers and sellers leading to a financial market crash."
To that end, Harré and his colleagues are developing simple AIs called agent-based models that simulate the Australian housing market and identify if it is at risk of collapse. Millions of households are modelled by these AIs, which interact with each other to buy and sell houses. The project will allow them to look at different suburbs, cities and regions across Australia to identify the factors that might lead to a system-wide collapse.
"We want to know what drives bubbles, whether those drivers are in the current Australian market, and how we deflate the problem of a potential crash by helping inform policy," Harré says.
For Harré, it's not just the computational power of AI that is useful, it's the potential of a future in which we will work with and interact daily with AI personalities – and he is excited about the diversity of viewpoints this implies. AI, by its nature, will have opinions.
"I think we're going to end up with a very dynamic workforce," he says. "The key thing for the future is going to be people who are more willing to be agile within the jobs they take."
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