Liberty IT interview with Michael Blumenstein (Artificial Intelligence)

Video: Link to video on the Liberty ITCG YouTube channel:

John Dimitropoulos
Michael, you’re a technologist, you’re an educator of course, but you’re a technologist and I know, I know because I know you have a passion for artificial intelligence. You’ve studied it and you continue to study it, you continue to learn, you continue to teach, that’s a great passion of yours and you have many. I’m going to draw an analogy here, thousands of years ago or even hundreds of thousands of years ago when fire was a humankind first came across fire, they thought, oh my god we’re going to burn the whole planet, the planet’s going to end. Well human kind learned how to build that for good and look at all the benefits we got out of fire. Now fast forward to probably about a few decades ago when digitization was becoming more prominent and of course computer science helped with that, computers helped with that, personal computers, corporates, everyone thought all the jobs are going to disappear. They’re all going to miraculously go and computers are going to replace people. They’re going to replace them in the branches, they’re going to replace them because an ATM has been invented, some of the inventions and endless other innovations. Well, my experience has been, yes some jobs did disappear but many, many more were created, Different jobs. So now we come across AI and I’d like you to talk to me a little bit about the past because people think AI was invented last week, it’s not the case. Exaggerating! It’s been around for a long time. The present, and of course the future of AI.

Michael Blumenstein
But I would like to touch on the past a little bit, you know, and I’d like to just, that’s a really good point you raise. All the things you mentioned there around the analogy are really important for people to think about today. But to understand that, you do need to have a look at where AI came from in the past. So the current version of AI, and I’m not going to try and give a lecture here, but I will say that people need to know the context.

The current version that people see of AI, because AI means so many things to different people. But the current version is what we call connectionist AI. That’s AI that basically was based on the very granular version of the human brain, basically the neurons in our brain. And do you know when that actually was discovered, the first artificial neuron, which is the basis of everything we’re talking about today? 1943. 1943. So, I think that’s a good point. If you put that into context, an AI has had lots of evolutions and a lot of people have tried to do symbolic AI, which is very much based on logic and other things.

But really what we’ve seen that has triumphed in 2023 has been, we know what’s on the market at the moment and we know what people are trying to sell and so forth. But it all started in 1943 with the first ever artificial neuron that was invented by McCulloch and Pitts.

These were famous scientists of the day. The first ever innovation that really, there’s been many innovations, but the one that really sits as the predecessor to what we’re seeing now was a type of algorithm called back propagation. And that was the first ever algorithm. And the reason I’m mentioning this is because one of the current fathers of AI that speaks out a lot right now in this present day is a gentleman called Jeffrey Hinton. He actually had a part to play in actually discovering back propagation in 1986. And then he and other people in the AI sector created the next wave, which was deep learning. I’m not sure if people remember that term, but it was 2015.

And then guess what? In 2022, we’ve got chat GBT, generative AI and large language models or LLMs. Do you notice something about those dates? 1943, 86, 2015, 2022. What’s happening? The cycle of innovation is getting shorter. And so that may give you some clues of what’s going to happen in the future, which I’ll talk about in a second. But we’ve always had to see AI in context. The world didn’t come to an end at any of those innovation peaks. Right. What actually happened was we were brought closer to what we’re experiencing today, which is using AI for successful applications in business, in medical diagnosis, in sustainability and climate change analysis.

The technology we have today, that’s the super strength of the culmination of big data, coming in with the whole data analytics piece, be able to use and store lots of data, so cloud, and then the algorithm of evolution, which has created what we see today, which to some people is magic. Some people use chat GPD and say, well, this is magic. This thing can take over the world. Oh my God. And so we’ve got to look at it in context. It’s just another form of evolution on our journey of actually discovery in terms of AI innovation for the benefit of humanity.

I think we have to be clear on that. So I want to give some examples. One of the reasons I was attracted to come to UTS was I’ve been doing, AI research myself since 1996, you know, that’s showing my age a little bit, but you know, decades, you know, I came to UTS because at the time it was highly ranked in artificial intelligence computer science. This currently right now we’re number one in computer science in terms of ranking in one of the rankings, another rank in the US global rankings, we’re number three in the world in AI, number one in Australia.

Now why is that? Well to your point earlier, it’s about people. We’ve got these amazing, you know, people doing research cutting edge in AI. I wanted to join that. That’s where I came. But some of the innovations that have come out, and I want to use some UTS ones because I think it’s pertinent because all of them, believe it or not, were with industry. So the technology that my team and I developed for spotting sharks on the beach, shark spotter, which is an AI technology deployed on drones to actually keep our beaches safe and people safe from predators in the ocean.

That’s an AI application that’s been a benefit both to the environment because it’s trying to mitigate shark nets, but it’s also trying to support people going for a swim in a safe environment, so beach safety.

We’ve done work in keeping the safety of airports through working with a company called Drone Shield where we developed technology called Drone Opti -D, the first ever type of AI technology to actually look at how do you protect areas like airports or other sensitive places from drones that may infiltrate. So it’s public safety away from this new technology called unmanned aerial vehicles. So that was another innovation. But we’ve worked with governments. We’ve developed technology for predicting pipe failures to save Sydney water billions of dollars, again, through AI. We’ve actually partnered with major insurance companies to actually an underwriting AI assistant so that you can actually use AI to support people making claims quicker and also saving money for the organization.

So, that’s now been purchased by Zurich. So the reason I mention all this is all of those things have a benefit for people and for the future of humanity and all those applications also have real benefit to business in somewhere or another. So, in one case we partnered with SMEs or startups, in another case we partnered with multinational global companies. All of it has had a benefit here either in Australia or overseas but it’s for people.

So, I think the present is looking great. Everything we do, even potentially the recordings we’re having today can use AI to make our recording better. So a lot of this you We’ve got to look at AI and say, you know, this is something that is supporting, you know, humanity. It’s supporting the jobs of the future. As you said before, whether it’s, you know, the invention of the car to replace the horse or fire to replace no cooking, you know, or no heating in people’s caves or houses from the past, you know, the AI technology is going to create new jobs.

It’s going to create the jobs of the future. So I’d like to just say for the future is that we’re looking at a very, very positive future. I mean, the all the negativity around, you know, what AI might do and the potential for existential threats has to be looked at on the basis of where, you know, what are the benefits that are outweighing it?

I mean, we are seeing places all over the world, including Australia talking about regulation. And I have no qualms with that. I think as a technology innovator, someone that wants to see the best technology again to the hands of people that are, that need to use it, whether it’s for study, for business, for humanity, we probably also need to say, look, if you, you’ve got to balance the regulation, you’ve got to have it in such a way that doesn’t stifle innovation. So, so that’s something we need to look at carefully in Australia, because the future for AI in Australia is bright. It could be our best export. You know, we don’t need large trucks. We don’t need ships to carry merchandise over.

We can deploy novel technology that’s create digital technology, AI technology is created in Australia. We can actually, you know, export it to the world if we played our cards right. So I think, you know, the future is bright. Future is bright for, you know, saving lives through medical breakthroughs, through saving our environment through climate breakthroughs, through saving businesses by enabling better productivity and of course, benefiting the economy by creating more jobs and better jobs. So, I’m very excited about the future and AI and technology are part of that future for me.

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