Re:Simulated data: the great equalizer in the AI race?
by cbrun on Thursday December 19, 2019 @03:04PM
(#21838661)
Sounds like a pretty bad experience indeed - surprised that was their recommendation vs completely anonymizing the data. You didn't share if you went ahead with it and saw any results? If so, it sounds like they were not good. Either way, I don't think you can let one bad experience cast doubt on a whole field. There are plenty of example of medical research institutes using synthetic data in combination with real patient data to improve their neural nets. I'm no medical expert, but data augmentation or full simulation works when it's used in the right context. Having said that creating biased algorithms that generate biased data is certainly a reality as well.
Re:Simulated data: the great equalizer in the AI race?
by omarhaneef on Thursday December 19, 2019 @04:37PM
(#21839588)
we didn't go ahead with it because we kept having calls with the different people in the university, and they kept putting off the decision. This was years ago and as far as I know, maybe their process is still going on.
Re:Simulated data: the great equalizer in the AI race?
by Buttons840 on Thursday December 19, 2019 @04:28PM
(#21839525)
You could simulate your own data that disagrees with their simulated data and thus draw attention to the absurdity of the whole situation.
Re:Simulated data: the great equalizer in the AI race?
by omarhaneef on Thursday December 19, 2019 @04:37PM
(#21839591)
this made me chuckle out loud. Great idea. Should have done exactly that.
Now this was for the public good and we were going to fund the technology to display the data, and they would provide the data. This way people could assess how much various drugs could help them and what the outcomes were.
It was also thought that other researchers could find patterns in the data.
Suddenly the not-for-profit institute got cold feet because they would be "giving away" the data they had spent millions to acquire. Meanwhile we, a for-profit institute, were happy to fund our share as a public good.
They decided that, instead of giving away their data, they would give away simulated data. This, it was felt, would benefit the patients and researchers who might draw conclusions from the data.
Now these are phds at the top of their field. But, you know, its sort of obvious that all they would do is reproduce their biases and make it so that no one else could challenge those biases. I mean, for you data science types, this is 101.
Ever since that experience, I have a distrust of simulated data.