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The first thing to realize is that AI is not coming for you or me or any other, it's coming for a subset of us. The subset of skills which can be rented out to

The first thing to realize is that AI is not coming for you or me or any other, it's coming for a subset of us. The subset of skills which can be rented out to an employer. AI and ML are just two things that are comming for that subset. Digitalization is also if not a bigger then at least a huge factor. The entire ecosystem of companies and people who were involved in supporting the music industry were more or less wiped out over the last 20 years. Leaving a thin layer of really successful people and then a huge group of people who makes no money. And the more things can be digitalized the more they are subject to pattern analysis which means the subsets of your that make you valuable are also easier to replace. Ironically a cleaning lady is probably the last person to loos her job because it's really hard to replace, but that just means the supply will increase too. So sure humans are better at BI but that's based on the assumption that how we do BI is the only way to do BI. I am not so sure it is. We will see.

jaabe 8y ago
We’ve seen a couple of examples with BI and analytics, I think you can put them into two categories. Prediction and automation. Prediction simply isn’t good enough. It may work well for google and Facebook, but that’s because failure is relatively harmless in advertising. No one dies just because you see a commercial for something you just bought. The failure rate is simply too high for us in the public sector, maybe that’ll change, but probably not. I say that because we’re severely limiting the access to data these years over privacy concerns. You could probably do some interesting things with medical data, but to get there, you’ll need to look at medical data and that’s just not happening in the current political climate. Then there is the automation. IBM wanted to sell us Watson analytics on the premise that it could recognise patterns and build the BI models our dedicated team does. So we let them try, and none of the models they came up with was even remotely useful. I can see this changing, but when? And what will our analytics department look like by then? It’s hard to say.
- ThomPete 8y ago
  Yes but you also have to think about predictions a little more nuanced. You can make a prediction it might be true but it doesn't mean that you will be successful with it. I wouldn't be surprised is 90% of all BI predictions doesn't actually lead to more successful outcomes also in the public sector also in Denmark (I'm Danish too :) )

jaabe 8y ago

We’ve seen a couple of examples with BI and analytics, I think you can put them into two categories. Prediction and automation. Prediction simply isn’t good enough. It may work well for google and Facebook, but that’s because failure is relatively harmless in advertising. No one dies just because you see a commercial for something you just bought. The failure rate is simply too high for us in the public sector, maybe that’ll change, but probably not. I say that because we’re severely limiting the access to data these years over privacy concerns. You could probably do some interesting things with medical data, but to get there, you’ll need to look at medical data and that’s just not happening in the current political climate. Then there is the automation. IBM wanted to sell us Watson analytics on the premise that it could recognise patterns and build the BI models our dedicated team does. So we let them try, and none of the models they came up with was even remotely useful. I can see this changing, but when? And what will our analytics department look like by then? It’s hard to say.

ThomPete 8y ago
Yes but you also have to think about predictions a little more nuanced. You can make a prediction it might be true but it doesn't mean that you will be successful with it. I wouldn't be surprised is 90% of all BI predictions doesn't actually lead to more successful outcomes also in the public sector also in Denmark (I'm Danish too :) )