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>>But of your job is to look at data and make descisions based on that data, you're gonna be the first to go. I posted the other day about machine learning and

>>But of your job is to look at data and make descisions based on that data, you're gonna be the first to go. I posted the other day about machine learning and radiology. It's the type of job that squarely fits your definition, although things move much more solely in medicine.

TallGuyShort 10y ago
It's also likely that human-in-the-loop will stay around, possibly indefinitely in medicine. A human-in-the-loop is a huge safety thing for medicine, but it defeats the whole point of HFT.
fossuser 10y ago
My dad is a neuroradiologist so I've seen a decent amount of the reading work (which is one component of the job - though a big one). I also thought it'd be well suited to ML, but I suspect the future is more suggestions and flagging things in scans rather than entirely replacing the doctor (I'd be surprised if this isn't happening already in some capacity). It seems risky to lose the human understanding and interpretation of the images. Human augmentation is probably better? Already people make assumptions because of not understanding constraints in how the underlying tech works (like how FMRI is monitoring changes in blood flow not neural activity directly).
- abstractbeliefs 10y ago
  The thing is, when you have 4 radiologists reading 100 scans each, if flagging and highlighting and generally improving performance of these personnel leads to two of them being able to process 200 scans each, the other two are out of a job. They have been, de facto, replaced by computers, even if the job role still exists. It's easier to see this if you break down the work not into images but into human-image-minutes. If there are 100 minutes of work, but you can assign the computer 50 of them which it can complete in seconds, the same number of human-image-minutes can be completed as before, but the computer has now taken them away from a human.
  - fauigerzigerk 10y ago
    Unless the productivity gain is spent on doing more imaging. I think this aspect is underapreciated in many debates about automation, especially in health care. There is an insatiable demand for diagnostics for early detection of diseases or monitoring progression.
- IndianAstronaut 10y ago
  >Human augmentation is probably better? Most of the automation work I do in financial services is a 90% automation. This leaves room for more analytical tasks where people can free up time to drive more business decisions and insights.

TallGuyShort 10y ago

It's also likely that human-in-the-loop will stay around, possibly indefinitely in medicine. A human-in-the-loop is a huge safety thing for medicine, but it defeats the whole point of HFT.

fossuser 10y ago

My dad is a neuroradiologist so I've seen a decent amount of the reading work (which is one component of the job - though a big one). I also thought it'd be well suited to ML, but I suspect the future is more suggestions and flagging things in scans rather than entirely replacing the doctor (I'd be surprised if this isn't happening already in some capacity). It seems risky to lose the human understanding and interpretation of the images. Human augmentation is probably better? Already people make assumptions because of not understanding constraints in how the underlying tech works (like how FMRI is monitoring changes in blood flow not neural activity directly).

abstractbeliefs 10y ago
The thing is, when you have 4 radiologists reading 100 scans each, if flagging and highlighting and generally improving performance of these personnel leads to two of them being able to process 200 scans each, the other two are out of a job. They have been, de facto, replaced by computers, even if the job role still exists. It's easier to see this if you break down the work not into images but into human-image-minutes. If there are 100 minutes of work, but you can assign the computer 50 of them which it can complete in seconds, the same number of human-image-minutes can be completed as before, but the computer has now taken them away from a human.
- fauigerzigerk 10y ago
  Unless the productivity gain is spent on doing more imaging. I think this aspect is underapreciated in many debates about automation, especially in health care. There is an insatiable demand for diagnostics for early detection of diseases or monitoring progression.
IndianAstronaut 10y ago
>Human augmentation is probably better? Most of the automation work I do in financial services is a 90% automation. This leaves room for more analytical tasks where people can free up time to drive more business decisions and insights.