We need to stop worrying and trust our robot researchers

The work of Francis Crick and James Watson gives us a vision of what's to come.

It’s now 60 years since the publication of the structure of DNA. As we celebrate the past, the work of Francis Crick and James Watson also gives us a vision of what’s to come. Their paper was not subjected to peer review, today’s gold standard for the validation of scientific research. Instead, it was discussed briefly over a lunch at the Athenaeum Club. In an editorial celebrating the anniversary, the journal Nature, which originally published the research, points out that this is “unthinkable now”.

However, peer review has always been somewhat patchy and it is becoming ever more difficult. This is the age of “big data”, in which scientists make their claims based on analysis of enormous amounts of information, often carried out by custom-written software. The peer review process, done on an unpaid, voluntary basis in researchers’ spare time, doesn’t have the capacity to go through all the data-analysis techniques. Reviewers have to rely on their intuition.

There are many instances of this leading science up the garden path but recently we were treated to a spectacular example in economics. In 2010, Harvard professors published what quickly became one of the most cited papers of the year. Simply put, it said that if your gross public debt is more than 90 per cent of your national income, you are going to struggle to achieve any economic growth.

Dozens of newspapers quoted the research, the Republican Party built its budget proposal on it and no small number of national leaders used it to justify their preferred policies. Which makes it all the more depressing that it has been unmasked as completely wrong.

The problem lay in poor data-handling. The researchers left out certain data points, gave questionable weight to parts of the data set and – most shocking of all – made a mistake in the programming of their Excel spreadsheet.

The Harvard paper was not peer-reviewed before publication. It was only when the researchers shared software and raw data with peers sceptical of the research that the errors came to light.

The era of big data in science will stand or fall on such openness and collaboration. It used to be that collaboration arose from the need to create data. Crick and Watson collaborated with Maurice Wilkins to gather the data they needed – from Rosalind Franklin’s desk drawer, without her knowledge or permission. That was what gave them their pivotal insight. However, as Mark R Abbott of Oregon State University puts it, “We are no longer data-limited but insight-limited.”

Gaining insights from the data flood will require a different kind of science from Crick’s and Watson’s and it may turn out to be one to which computers and laboratorybased robots are better suited than human beings. In another 60 years, we may well be looking back at an era when silicon scientists made the most significant discoveries.

A robot working in a lab at Aberystwyth University made the first useful computergenerated scientific contribution in 2009, in the field of yeast genomics. It came up with a hypothesis, performed experiments and reached a conclusion, then had its work published in the journal Science. Since then, computers have made further inroads. So far, most (not all) have been checked by human beings but that won’t be possible for long. Eventually, we’ll be taking their insights on trust and intuition stretched almost to breaking point – just as we did with Crick and Watson.

President Obama inspects a robot built in Virginia. Photograph: Getty Images.

Michael Brooks holds a PhD in quantum physics. He writes a weekly science column for the New Statesman, and his most recent book is At the Edge of Uncertainty: 11 Discoveries Taking Science by Surprise.

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“The very beautiful, very troubled JANE”: quoting scripts to highlight film industry sexism

A producer is tweeting the introductions for female characters in the scripts he reads, verbatim. It’s not pretty.

Producer Ross Putman was growing tired of clichéd, sexist descriptions of women in film scripts. “The more that I read, the more I started to recognise some pretty awful constants,” he told Jezebel. “Women are first and foremost described as ‘beautiful’, ‘attractive’, or – my personal blow-my-brains-out-favorite, ‘stunning’. I went back and combed through past scripts too, and the patterns were pretty disconcerting.”

After finding himself “posting to Facebook far too often”, Putman decided to start a Twitter page cataloguing every introduction of a female character he found distasteful. The account, @FemScriptIntros, amassed 40,000 followers in days, prompting a kaleidoscope of heated reactions: stunned, angered, not-surprised-but-disappointed.

Reading like bad erotica, the introductions range from hackneyed to surreal, but can be broadly divided into two camps: Jane is either obviously beautiful, or beautiful, but not, like, in an obvious way. “The suggestion is that women are only valuable if they’re ‘beautiful’,” Putman added.

“Changing the names to JANE for me, while maintaining that focus on systemic issues, also – at least, I think – demonstrates how female characters are often thought about in the same, simplistic and often degrading way. [...] Jane has no control over her role in this world – which is far too often to be solely an object of desire, motivating the male characters that actually have agency in the script.”

So, meet Jane, in all her (limited) forms.

Jane: the clear stunner


Jane: gorgeous, but doesn’t know it


Jane: pretty, yet over 25?!


Jane: beautiful, but troubled

Anna Leszkiewicz is a pop culture writer at the New Statesman.