Comments on: Of open data and pregnant men

By: JP

JP — Tue, 17 Apr 2012 09:31:17 +0000

@species5618 I agree, when carbon-based units act as servants to silicon-based units, the outcomes are depressing. We have to keep ensuring that it does not happen; and when it happens, we have to keep ensuring that we change it. There are cases where it would appear carbon-based units have forgotten how to think. But that can be amended.

By: species5618

species5618 — Tue, 17 Apr 2012 09:21:54 +0000

Yet another excellent thought provoking post, which also made me smile, possible for the wrong reasons.
Although I have a slight different, satirical twist. There are a lot of issues with the carbon based processing units and the way they used the data, “computer says no” & “it must be right, the computer told me” spring to mind
Even simple data sets like stock control, seem to be more than the average carbon based unit can cope with. Many years ago I went to a wholesaler to buy a piece of hardware. Pointing at a shelf of items, I said “Can I have one of those please?” The member of staff tapped away at the keyboard and said, “we don’t have any in stock”……

By: Joachim Stroh

Joachim Stroh — Tue, 17 Apr 2012 01:29:12 +0000

@JP Yes, absolutely, sort of connected in a chain, I.e. Humans interpret, not go out and curate on their own (that was KM1.0)

By: JP

JP — Mon, 16 Apr 2012 22:54:07 +0000

@Steve, not sure about it. It seemed to be pretty bad. GIGO. No real incentives to get it right, poor and misleading classification choices, underskilled data entry, the lot.

By: JP

JP — Mon, 16 Apr 2012 22:52:48 +0000

Tim O’Reilly introduced me to Jeff Jonas maybe a couple of years ago, but I don’t really know him. Have read his stuff though.

By: JP

JP — Mon, 16 Apr 2012 22:51:58 +0000

@Daen @Joachim I think we have to keep focusing on machines filtering and humans curating, augmenting the mechanical activity with human passion and intellect. Otherwise there are going to be many and different instances of what Kevin Slavin talked about in terms of algorithms going bad.

By: Steve Ellwood

Steve Ellwood — Mon, 16 Apr 2012 15:36:38 +0000

Chris Roebuck, HES Programme Manager, HSCIC (not verified) *does* suggest the “pregnant men” isn’t as bad as painted…

“HES is rich in detail and potentially can be a powerful driver for decision-making, as Dr Brennan rightly points out. Her study demonstrates this in several ways. It is an interesting and correct assertion that thousands of male finished consultant episodes (FCEs) were recorded under the obstetrics, gynaecological and midwifery specialisms. At first glance this would appear out of the ordinary.
However when we analysed the date further, by age as well as gender; almost all male FCES related to new-born or very young babies: with 96 per cent relating to babies less than one week old.
We are very keen to support initiatives such as this and always willing to offer our assistance with correct interpretation of data.”

By: Ken

Ken — Mon, 16 Apr 2012 09:14:14 +0000

JP, spot on – as usual… Have I mentioned Jeff Jonas’s work to you before, or have you already come across him? He is a very interesting guy (and great company) I think you will find some of his thinking of considerable interest…
http://jeffjonas.typepad.com/about.html

By: Joachim Stroh

Joachim Stroh — Mon, 16 Apr 2012 01:51:04 +0000

Thank you for this dose of reality in increasingly data-driven internal systems of record and hierarchical decision trees. After all, the more data-driven it becomes, the less people are needed to be involved in the decision. So, it’s time to make our systems and processes more people-centric (aka let people look at the data and the context) instead of assigning the task to a few selected who can make sense of it. After all, those few will probably find nothing odd about pregant men.

By: Daen de Leon

Daen de Leon — Mon, 16 Apr 2012 00:13:43 +0000

It’s also a big worry in life science R&D. High-throughput screens (HTS) of hundreds of thousands of sample points show affinity for ligand L against target T, papers are published where controls aren’t fully implemented, or data is harvested selectively, and before you know it, you have a drug failing in Phase III. Seems far-fetched? Consider what’s happened with Sanofi’s iniparib last year. It seems likely that there were data artifacts (and wishful thinking) all the way from hit discovery through to Phase II trials which mislead Sanofi as to the actual effectiveness of iniparib, and led to a spurious gating decision when moving the drug to Phase III.