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Grow Innovate 12 min

AI is a major investment priority, impacting machine learning, chatbots and virtual personal assistants, staff upskilling and training, data analytics and business intelligence. 

Less than half of CIOs surveyed at ADAPT’s CIO Edge Conference in 2018 had started any AI specific projects. Nearly one third had begun pilot projects, but there was no organisation wide implementation.

At Digital Edge in May, we asked thought leaders what artificial intelligence means to them.

Simon Waller – Digital Champion, Author and Advisor

For me, AI is a new generation of technology that has followed, generation after generation technology before it. I think what we’re seeing in AI, the closest comparison we have is what happened in the Industrial Revolution. So prior to the Industrial Revolution, humans saw themselves as being people who make things, but makers. And then we created this technology that was better at making stuff than us. And as a result of that, we had to reinvent ourselves. So we no longer identify as human now with our ability to make that we actually identify with our ability to think. So AI is going to challenge that for us again, because we’re going to create machines. And we are creating machines, in some ways a better at thinking and processing information than we are.

Now, I think that that’s a huge challenge. Don’t underestimate the, we went through in terms of the Industrial Revolution, like we had a whole Luddite where people would go in and sabotage the machines, because of that loss of identity. You know, so we are going to face that again. But I do believe on the other side of that is something very beautiful, is that ultimately we define ourselves by what our technology is not and what our technology can’t do, and what it can’t give us. And what it can give us is things like love, compassion, creativity. These are things that are innately human skills, and my dream and my hope is that AI actually becomes a catalyst for humans to evolve into something more special, then we see ourselves as today.


Vincent Pierce – GM at Westpac NEXT

Look, I’ll put AI in the context of Industry 4.0, right, which, to me, really is all about ubiquitous connectivity, smart, everything always on. And when you think about what’s possible, in that Fourth Industrial Revolution, from a bank perspective, you start to think about how my customer wants the bank. I walk into a branch, I have a conversation with one of the branch staff, I decided on the way out, I want to start an application. So I pick up my mobile phone, I start an application, I get home, I log on to the Mac, I get on the website, I continue. Pick it up, right where I left off, I get stuck, I don’t understand an interest rate, I call the contact centre, they know exactly where I am, my identity is very easily confirmed. I don’t have to repeat myself. And the process just continues. It’s seamless, there’s limited friction. And those things are made possible by the technologies that underpin Industry 4.0, like AI.

So Westpac recently launched Red, which is our chat bot, and we’re currently teaching the chat bot and every conversation that chatbot has with a customer, the better it gets. But it just hits a database of interactions and responses and pulls all these different data sources, to respond to most inquiries that our customers have at a transaction and servicing level.

Dr. Ian Oppermann – Chief Data Scientist and CEO NSW Data Analytics Centre at NSW Government

So there is a fundamental premise that you can’t create information, it’s already in the data or it’s not. So the AI is just a different way of finding the information in the data. But the real problem comes when we let a decision be taken by the AI. So if it just produced the insights and said well, it re examine the data looked at it differently, and I found something else then I found something else. That’s one thing. If we then let the AI make, take an action, close the loop on doing something with that insight, without human intervention, then we start to get serious problems.

The simple example we all know about is the autonomous vehicle, literally the algorithm decides whether to turn the wheel this way or that way, very simple micro experiments, micro projects, leading to a micro change. But when we talk about in Australia, we had Robo debt where we had, of course, the system says “you owe…” a letter gets generated and sent out without the human intervention to say, Does this make sense or not? Is it worth? Is it worth the aggravation or the impact on the individual? Or what are the consequences of doing that? That’s where I think we still have a choice, we still have a choice about how much of that human current human decision making process will allow to be informed, assisted or even automated.


Kerrie Campbell – CIO at Flinders University

So to me, I love artificial intelligence, and RPA and robotics. And I think that’s the way the future. For an education sector, that’s really quite interesting that we’ve just had… I can’t remember the name of the company but they’ve put an AI on the learning the first year text for psychology, every first year set text for psychology of it, they’re putting it into an AI. So you can imagine educators are going to be nervous about that. But the other side of that is there’s a support, they have a 24/7 support for students. If they’re working in the middle of the night doing that they can actually just attack that robot and say, Hey, what about this, what about that? And it will give them the knowledge rather than just having that knowledge that’s just in one educator’s head. So that broadens things. So I think if they look at it as more of a glass, half full, half empty, then it can open up their world for them.


Toby Heaton – Armstrong – Head of Digital Technology at Dexus Property Group

If I think about ADAPT over the last three years and the Digital experience. I think the best part of me is being the thoughts it’s provoked around people. So how important people are in all of this transformation. From sessions last year, you ran about how to frame problems and solve problems through listening today the problems we have in running large scale it and how to transform. So I think as we move and we find things like AI machine learning, there’s more and more IoT, how we take people on that journey. I think that’s what fascinates me. We’re social animals.


Ines Almeida – Digital Transformation Advisor at ANZ

I talked about AI with trepidation and excitement. The trepidation is that we should I’ll be scared and worried about what’s coming in, from the point of view that businesses are going to get to know too much about us. And it’s not just about our vital signs, it’s our emotions, and what do we react to and how to influence us… Perhaps manipulation. So we need to be careful with that. But it’s also the power of having personalised services and products that are just right for me. I get super excited about that. That song that plays just in time on Spotify that I never listened before. But it’s perfect for that moment. I think that’s super exciting. Businesses are still struggling to get the right data, clean the data, remove biases, and from algorithms and data sets and all of that. But once we stabilise that, and we apply some empathy, and human centred design, to analytics and machine learning, we can benefit from the best of AI.

Paul Shetler – Partner at AccelerateHQ

It means very little. If I think about AI mean, the thing that I guess, you know, AI is really statistics essentially apply to very large data sets with lots of compute. So it’s not anything really new. When I think about AI, I think probably the most effective or most interesting use of AI and machine learning on large datasets. I think you can come up with some very interesting insights be very difficult to otherwise just because of the sheer volume of data that you’re actually analysing.

And the techniques that they’re using to do that with does a company called Quilt that does AI, for instance, based out of Singapore to do some amazing work. It’s essentially the equivalent of qualitative marketing reports that would normally take months to do and they can turn them out in an afternoon or in a couple of hours. And then they’re really amazing. And it’s all based on ingesting you know, Instagram feeds, Facebook feeds, Google searches, blogs, news and everything else. And then their secret sauce does it. That’s quite interesting to me. But typically when you start seeing AI sort of being used to describe automation… it’s marketing. It’s not something which is terribly interesting.


Sherif Mansour – Distinguished Product Manager at Atlassian

I have this love/hate relationship with artificial intelligence, to be honest. To me, Clippy back in the day Windows, Windows Clippy is like, hey, it looks like you’re trying to write a letter. That is a lie. Like that was a guy back in the 1990s. So I spoke to a guy Steven Sinofsky who lead product and Microsoft. He’s known as the man who made Clippy and I spoke to him a few months ago, and he was sharing the story about how Clippy was AI well, ahead of its time, like it was a little ahead of its time. And we joke and laugh about, “hey, looks like you’re trying to write a letter.” But I think the key difference that’s changed in the market between then and now is the quantity of data that organisations have. Therefore, you know, a silly paper clip that jumps up that looks like it’s from a little, it can be much more intelligent now than it ever has been before.

So I think it’s definitely something to be looked at. I think a lot of organisations struggle with, expect something revolutionary out of it from day one. And I think that’s probably where we are struggling and everyone else is struggling. And everyone sees the Googles, and the Microsoft’s and the Facebook’s doing amazing things with AI, and they’re trying to apply that to the workplace. But it all starts with baby steps. And so the way we like to think about it is, AI is basically better the more data you have or with all the different kinds of data you have. So unique advantage, every organisation has is the data. So they’ll say a question ask yourself is, what information do you have about your customers that you can use to solve unique problems? And they say unique because no one else has that information, it’s your products. And if you mix and match that with other information, other problems that you can solve with partners and that kind of stuff. So that’s the question to ask yourself, but how you go about an action that it’s often baby steps, you know, you may make a small capability of your organisation a little bit smarter, because you can recommend the best hotel room.

That’s AI, you know, you can break it down to like, just start with small smart capabilities, and work your way up. I think people try to jump straight to the “How do I get a voice activated solution that can mimic my voice?” It’s just hard. And so yeah, just start by asking yourself, what data do we have? And then what unique problems can we solve with it with that data? And if we have more data, does that problem become better? So at Atlassian we’re thinking about it, for example, a lot of software teams use Atlassian. So we have information about you know, how long people spending time on their sprints, how they’re doing the retrospectives, different industries. So we could say these kinds of industries typically take these kinds of times to complete a sprint. So trying to use that information to better aid our customers that way. And there were lots of baby steps but you find the sum of all the baby steps is hopefully something amazing.


Pontus Siren – Partner at Innosight

AI is obviously going to have a huge impact on all facets of human life and business endeavour. That’s clear. In some realms of business, it’s already had that impact. But the challenge with AI that it is that it goes together with data capture. So without data capture that is both massive and standardised, it’s very difficult to develop effective AI solutions.

Now in some situations, we have massive and standardised data, and AI is very good at that. What’s happening now is that the Internet of Things and the data capture piece is getting a lot better. So AI will expand its reach and impact into new industries and new applications. Inevitably, it’ll play a big role in business. And it is, it’s a huge opportunity. And of course, industries will change and all that, as many of your speakers have highlighted. But I think sometimes we focus too much on the analytics and we forget the critical component of the data capture, which goes hand in hand with artificial intelligence and will really revolutionise the solutions it can provide.

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