No need for employees when Watson can do it all. Unbeknownst to these people, they renamed it Watson Health due to the fact Watson is going to run the entire division itself. Amazing! The future of AI is finally here! Watson has spent the last few years learning all these peoples' jobs.
IBM Watson Health slashes workforce
21–30 of 79 posts
Re: IBM Watson Health slashes workforce
#22I'm an MD, and I dabble in programming and AI/DL. While I don't really care much about Watson in particular, the pervasiveness of the "enter healthcare = death" equation is worrisome to me. And it should worry you, too. There's a lot of potential for good applications of this type of tech in healthcare, but the barriers to actually getting it off the ground strangle it in the crib.
Many of those barriers have historical reasons for existing -- which do you think could be lowered without risking patient health (or yielding sufficient benefit to be worth some added risk)?
Probably. The following applies to the US: It seems to me that some of the biggest barriers involve getting access to enough data to make a good training set. Some of this is related to HIPAA and related privacy laws, which are in place for a good reason but are still a major barrier. The other big factor is the fragmentation of the data across different, non-interoperable, non-standard formats from different vendors who have intentionally made interoperability difficult. That part bothers me much more. Many patients have data spread across a dozen or more paper charts, lab systems, EMRs, pharmacy databases, etc. As with most data science tasks, the "data munging" is the hardest part.
I care about this mostly from the perspective of treating patients. Beyond training sets for AI, I need those records for the same reason: to make appropriate and informed treatment decisions.
From the outside looking in, it's the kind of situation that begs companies to over-promise on results to get enough money to even give it a shot.
Re: IBM Watson Health slashes workforce
#23No need for employees when Watson can do it all. Unbeknownst to these people, they renamed it Watson Health due to the fact Watson is going to run the entire division itself. Amazing! The future of AI is finally here! Watson has spent the last few years learning all these peoples' jobs.
[deleted]
Re: IBM Watson Health slashes workforce
#24No need for employees when Watson can do it all. Unbeknownst to these people, they renamed it Watson Health due to the fact Watson is going to run the entire division itself. Amazing! The future of AI is finally here! Watson has spent the last few years learning all these peoples' jobs.
This sort of sarcastic, content-free comment doesn't contribute much, and isn't a great fit for this community.
Re: IBM Watson Health slashes workforce
#25Earlier quoted context omitted.
Many of those barriers have historical reasons for existing -- which do you think could be lowered without risking patient health (or yielding sufficient benefit to be worth some added risk)?
Probably. The following applies to the US: It seems to me that some of the biggest barriers involve getting access to enough data to make a good training set. Some of this is related to HIPAA and related privacy laws, which are in place for a good reason but are still a major barrier. The other big factor is the fragmentation of the data across different, non-interoperable, non-standard formats from different vendors…
As a patient, I'd love to be able to archive/hold my own comprehensive copy of all of my health records.
Re: IBM Watson Health slashes workforce
#26I'm an MD, and I dabble in programming and AI/DL. While I don't really care much about Watson in particular, the pervasiveness of the "enter healthcare = death" equation is worrisome to me. And it should worry you, too. There's a lot of potential for good applications of this type of tech in healthcare, but the barriers to actually getting it off the ground strangle it in the crib.
The two massive barriers to entry are regulatory uncertainty and sales difficulties
Regulations: Up until recently, the regulatory landscape for medical software was extremely confusing. People were sitting on the sidelines waiting for FDA to figure out how to deal with machine learning, agile development, app stores, blah blah. Startups that wanted to jump in were staring at yearly 100K+ regulatory consultant bills. FDA is now actively de-regulating the bulk of medical software, and will create a regulatory kit which should better explain the regulations in an actionable way (instead of "create a design history file" without much explanation of wtf that means in practice). This should ease pains on that front
Sales: This is where the big pain is. Getting paid for shit in healthcare is just too damn hard unless your product is on the hospital operations side of things. Getting an FDA approval (assuming it's required) DOES NOT mean one of the thousands of insurers will decide to reimburse you for your product; many require multiple clinical trials for reimbursement purposes; and many will decide to stop covering your product for stupid reasons (ie some editorial in the "No One Reads This Journal of Nonsense" said it was unclear the product was effective). Good luck getting patients to pay for anything, as they expect all products to be covered by insurance. Good luck convincing doctors they should use your product, as they are already overwhelmed with data entry / shitty UIs and don't want to perform any additional clicks or workflow changes.
Re: IBM Watson Health slashes workforce
#27Earlier quoted context omitted.
Many of those barriers have historical reasons for existing -- which do you think could be lowered without risking patient health (or yielding sufficient benefit to be worth some added risk)?
Probably. The following applies to the US: It seems to me that some of the biggest barriers involve getting access to enough data to make a good training set. Some of this is related to HIPAA and related privacy laws, which are in place for a good reason but are still a major barrier. The other big factor is the fragmentation of the data across different, non-interoperable, non-standard formats from different vendors…
I am working on a medical dictation app and the lack of any interoperability between 1000s of EHRs is mind boggling to me. There is absolutely no standards and like you mentioned its completely deliberate. Working through these platforms over the years has made me less and less optimistic about having a better health care system in the future.
Re: IBM Watson Health slashes workforce
#28I'm an MD, and I dabble in programming and AI/DL. While I don't really care much about Watson in particular, the pervasiveness of the "enter healthcare = death" equation is worrisome to me. And it should worry you, too. There's a lot of potential for good applications of this type of tech in healthcare, but the barriers to actually getting it off the ground strangle it in the crib.
Many of those barriers have historical reasons for existing -- which do you think could be lowered without risking patient health (or yielding sufficient benefit to be worth some added risk)?
Airplane security has a historical reason for existing too, but that doesn't mean the benefits justified the costs, either now or in the past.
Re: IBM Watson Health slashes workforce
#29I'm an MD, and I dabble in programming and AI/DL. While I don't really care much about Watson in particular, the pervasiveness of the "enter healthcare = death" equation is worrisome to me. And it should worry you, too. There's a lot of potential for good applications of this type of tech in healthcare, but the barriers to actually getting it off the ground strangle it in the crib.
The two massive barriers to entry are regulatory uncertainty and sales difficulties Regulations: Up until recently, the regulatory landscape for medical software was extremely confusing. People were sitting on the sidelines waiting for FDA to figure out how to deal with machine learning, agile development, app stores, blah blah. Startups that wanted to jump in were staring at yearly 100K+ regulatory consultant bills.…
Glad to hear things are improving on the regulations front. Sales is going to be hard for a while, but I think that there are some markets where this is less of an issue, as it's more cash-based anyway. It makes me sad, though, that a lot of the population-based preventative stuff for which AI would be a great fit is unlikely to be a financially appealing investment.
Re: IBM Watson Health slashes workforce
#30Earlier quoted context omitted.
I think this has more to do with the fact that Watson sucks than anything else, although it may be a harbinger for other efforts to sprinkle magic machine-learning pixie dust on complex problems in the hope for a solution.
In this case, you are probably right. But it seems to happen over and over again suggesting that the barriers to innovation are higher than they should be.
Yeah, to be clear, Watson failing is good news. This is marketing people losing their minds because they didn't understand the products they were selling, and hospitals failing to do due diligence.
I've talked to literally dozens of people / companies / academics running at problems in healthcare using deep learning and large data sets, and the recurrent theme is cowboys who pretty consistently fail to follow basic practices of experimental rigor. ML is frankly an area where more rigorous and clear regulation is desperately needed, because the potential to cut corners / cheat is so easy and the challenges of vetting these systems are specialized enough that most organizations won't successfully be able to catch fairly basic experimental mistakes.