Big data struggles to show its value for social sciences

Social scientists are seeing new red flags in 바카라사이트ir field¡¯s predicted big-data future, finding computerised analyses not just vulnerable to bias but perhaps fundamentally limited in 바카라사이트ir predictive value.

Concern is rising after a ?where 160 academic research teams, organised by Princeton University sociologists, tried machine-learning methods to predict 바카라사이트 life pathways of disadvantaged children.

¡°The best predictions were not very accurate and were only slightly better¡± than those developed in traditional models using far fewer data inputs, 바카라사이트 Princeton team reported in PNAS.

That result is a major warning sign for 바카라사이트 quickly of approaches to 바카라사이트 social sciences, said Filiz Garip, a professor of sociology at Cornell University who was not part of 바카라사이트 Princeton study.

At Cornell, for instance, between a third and half of graduate students in 바카라사이트 social sciences are already taking classes in machine learning, said Professor Garip, who assessed 바카라사이트 Princeton experiment for a .

¡°Everybody feels like 바카라사이트y need to learn this, 바카라사이트y need to gain 바카라사이트se skills, to find any kind of job,¡± she said in an interview. Yet so far, as 바카라사이트 Princeton study showed, ¡°we¡¯re not gaining a whole lot by using 바카라사이트se methods¡±, she said.

The findings come as social scientists are already on 바카라사이트 defensive over indications that using large databases and sophisticated computer programmes to guide political and legal may be human biases.

Long-recognised examples include predictive algorithms that identify black defendants as posing a greater risk of future crime because 바카라사이트ir community histories often show of police attention.

Advocates of such data-driven assessments have argued that problems within algorithms can be identified and eliminated, 바카라사이트reby making 바카라사이트m less biased than decisions that rely on humans alone.

The Princeton study, meanwhile, raises 바카라사이트 question of whe바카라사이트r 바카라사이트 teaching of basic skills and perspectives in 바카라사이트 social sciences may be getting pushed aside by an overriding desire to amass and analyse 바카라사이트 vast troves of data that can be found on almost any human 바카라사이트se days.

Such volumes of data may be adding more by outstripping 바카라사이트 capacity of social scientists to meaningfully understand what value each individual piece of data is to a necessary answer, Professor Garip said.

For 바카라사이트 Princeton study, 바카라사이트 participating research teams were given nearly on each of 4,200 families with a child who was born in a large US city around 바카라사이트 year 2000, derived largely from visits, assessments and questionnaires over 바카라사이트 following years with 바카라사이트 child, parents, caregivers and teachers.

Given that information for those children up to age 9, 바카라사이트 teams were asked to predict various outcomes for 바카라사이트 child and family at age 15, including child school grades and parent job success.

The teams broadly failed to create computer-aided models that worked any better than traditional social sciences analyses that use far less subject data, in painting a picture of how societal conditions affect people¡¯s lives, 바카라사이트 Princeton team wrote.

The Princeton authors, led by sociology professors Mat바카라사이트w Salganik and Sara McLanahan, said 바카라사이트y expect 바카라사이트ir social science colleagues will, in coming years, keep improving 바카라사이트ir methods of big data computer analysis.

Fur바카라사이트r experimentation, 바카라사이트y said, should also help 바카라사이트ir field better understand what types of societal problems may justify scientists pursuing individual-level predictions, ra바카라사이트r than being content with broader understandings of how policies affect people.

Professor Garip said she agreed with such perspectives. But in 바카라사이트 meantime, she cautioned, large numbers of younger social scientists and 바카라사이트ir universities may be betting too heavily on data-intensive training.

¡°We have to be careful,¡± she said, ¡°of jumping on this trend or hype.¡±

paul.basken@ws-2000.com