When we talk about the future of work - naturally there are going to be new roles. There may be less or different tasks, the latter more likely.
But what you can bank on is that the roles that were here 100 years ago are far more likely to be here in another 100 years than those roles that have been with us for just a few short years.
That's not to say none of the new ones will stand the test of time, but a far higher percentage of the old ones will.
The longer anything lasts - the longer it is likely to continue to last. This is one of the lessons we can draw from Antifragility and other work by Nassim Nicholas Taleb. He would say it is a lesson we can learn from the wisdom of our grandparents.
Will a teacher's job exist in 100 years time? 90% yes. Will a social media strategists? 90% no.
We are often dazzled by the new and make projections into the future on very shallow data. This fails. As AI is proving all over again.
To create value with AI the proposition needs to be reframed in terms of prediction. But unless the correct weighting of what has come before is built into the programming, researchers find they hit the problem they call 'catastrophic forgetting'. The solution is to build in virtual memories (eg Deep Mind's Differential Neural Computer).
For AI to succeed it has to factor for what you and I instinctively know - the longer something has lasted, the longer it will succeed.
That's not to say none of the new ones will stand the test of time, but a far higher percentage of the old ones will.
The longer anything lasts - the longer it is likely to continue to last. This is one of the lessons we can draw from Antifragility and other work by Nassim Nicholas Taleb. He would say it is a lesson we can learn from the wisdom of our grandparents.
Will a teacher's job exist in 100 years time? 90% yes. Will a social media strategists? 90% no.
We are often dazzled by the new and make projections into the future on very shallow data. This fails. As AI is proving all over again.
To create value with AI the proposition needs to be reframed in terms of prediction. But unless the correct weighting of what has come before is built into the programming, researchers find they hit the problem they call 'catastrophic forgetting'. The solution is to build in virtual memories (eg Deep Mind's Differential Neural Computer).
For AI to succeed it has to factor for what you and I instinctively know - the longer something has lasted, the longer it will succeed.
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