“Anything that can be automated will be automated,” says Benjamin Pring. “Over the next 20-30 years, a lot of the work people do today is going to be automated away. At the same time, this isn’t going to develop quite as quickly as some of the proponents and evangelists think it is.” Excerpts:
“We think AI is the next productivity and price points that company’s need to reach. Ultimately, at the end of the day, AI is just the next-generation productivity tool and people need to learn how to leverage that in whatever work they do, and if they can do that, then it’s a good news story.
A lot of people are over-extrapolating what AI can do because they are, as we are all in a way, so accustomed to Hollywood science fiction version of what this is. The reality is this is just a very smart, machine learning, reinforcement-based technology. The technology can be trained, in a way, to understand what the signal is and what the noise is. That is why these over-extrapolations of huge job collapse are actually pretty inaccurate and scaremongering, because the way this is going to develop and evolve, even though it’s along exponential lines, isn’t going to take us into that dystopian terminator view that people have.
We think — and that’s the point of our book ‘What To Do When Machines Do Everything’ — that so many people are spending cycles worrying about the far-off future, worrying about the ethics, the socio-economic dynamics of this for 50 years down the track. The real issue they should be worrying about is what they should be doing in the next quarter to use these technologies to get to the next price point and productivity point threshold. If they don’t do that now, you are not going to be in business and won’t be a relevant voice in 50 years’ time because you simply won’t be around.
This is such a broad generic technology that can be deployed across every aspect of big business. Who’s responsible for this? We work with a lot of companies who are trying to figure that out at the moment. People have been talking about having a chief digital officer and a chief data science officer for a number of years. An argument gathering steam is if we should have a chief AI officer. In reality, it’s going to take a while to work its way out. The more pragmatic way this is going to play out is, if you are running a trading desk or an HR department or supply chain logistics procurement department, you need to be in the driving seat of figuring out what tools are available, tools materially relevant to you, and deploying them into your business process now, rather than worrying about some central figure that’s going to do that for you!”
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