How AI could help docs spot mums who hit the sauce too much while creating their version 1.1 Machine-learning algorithms can help doctors diagnose children affected by fetal alcohol spectrum disorder, according to fresh research. Fetal alcohol spectrum disorder (FASD) describes a range of conditions that are caused when a woman consumes excessive amounts of booze during her pregnancy. Such benders can impact the …
Dude what? It appears you don't have kids or have forgotten some things. This is really sticky... extremely.
1st, is abortion legal in that state/country?
2nd, did the woman know she was pregnant?
3rd, is it related to religious practices?
4th, is a man be held accountable as well?
5th, can you prove it was the woman and not the man?
6th, why do woman who don't drink have children with the same identical symptoms?
7th, if she hasn't drank and it is naturally occuring, how would she prove innocence?
8th, if she had drank, would she fear prosecution and neglect to see a physician?
9th, would parents in general now be afraid of prosecution?
Then you still have other issues not related to the mother. For instance, should a government have that much control over all stages of a pregnancy? Who covers these costs? What about all the lawsuits from men suing women, or women suing men?
To me, this might look friendly, but this would be a money generating trap that also decreases an already decreasing level of trust between partners.
Ask yourself, who's paying for this research?
are associated with other socio-economic issues - or to use real language, its mostly poor and disadvantaged people that will be affected.
This may be because rich people have access to other vices, or just because there are more poor people...
Anyway, the people most at risk are also those with least access to these diagnostic tools, or for that matter, personnel to use them.
FASD seems to be the new excuse in regional juvenile court cases, so apparently lawyers are getting pretty good at diagnosing it.
Knowing you have a problem used to be the start of working towards a solution - now, its knowing your mum had a problem...
78.26%? What a ridiculous accuracy figure based on 'Data taken from 46 participants' from an initial set of 207 participants. It looks to me like the test only found 36 out of those 46 participants to be affected by FASD when professional opinions considered all of them to be affected. (36/46 = 0.7826 to 4 decimal places). This looks like blatant cherry-picking of the study subjects.
According to Wikipedia 'FASD is estimated to affect between 2% and 5% of people in the United States and Western Europe.' - and the wiki article cites CDC as a source for that figure.
Although the El Reg article does not suggest such a thing an automated test of each annual cohort of children born in the USA (about 4 million per year) with 2% prevalence and test accuracy of 78.26% would give the following results: 62,800 (1.57%) correctly diagnosed, 17,392 (0.43%) missed, 3,067,792 (76.69%) correctly given the all-clear and 852,207 (21.31%) incorrectly diagnosed. The harm done to 852,207 children by incorrectly labelling them as affected by FASD would be outrageous.
Obviously, not every child would be tested. Only those who show some sort of 'problem' behaviour would be tested; but having labelled some people as affected by FASD (along with the associated finger-wagging directed at their mothers) there must be an intention to intervene to change their behaviour (an alternative which could be to use the label to avoid wasting valuable intervention resources on affected people is even more disturbing). I expect that the interventions used in cases of FASD are similar to those used for other developmental disorders - so why not target the interventions on all those displaying the undesirable behaviour rather than focus on a possible cause of that behaviour?
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