Invisible Women: Data Bias in a World Designed for Men

After giving birth, Maria ended up on a new university contract for just under three hours a week – the only hours on offer. She can, and does, work extra hours to cover staff absences, but the extra hours are often at short notice. And here we run into the second major problem that disproportionately impacts on female workers: unpredictable, last-minute scheduling.

As we’ve seen, women still do the vast majority of the world’s unpaid care work and, particularly when it comes to childcare, this makes irregular hours extremely difficult. This is partly because, in another case of having the data but failing to use it, British childcare provision has not caught up with the reality of how women are working. We know that 75% of UK families on low to middle incomes now work outside standard hours, but most formal childcare is still only available between 8 a.m. and 6 p.m. It must be booked and paid for well in advance, which is difficult if you don’t know when you’re going to need it. This problem is particularly acute for single parents (90% of whom in the UK are women29) a group that has seen a 27% increase in temporary work.30 And given Britain has one of the highest childcare costs in Europe, it’s also an expensive one.31

The scheduling issue is being made worse by gender-insensitive algorithms. A growing number of companies use ‘just in time’ scheduling software, which use sales patterns and other data to predict how many workers will be needed at any one time. They also respond to real-time sales analyses, telling managers to send workers home when consumer demand is slow. ‘It’s like magic,’ the vice president for business development at Kronos, which supplies the software for a number of US chains, told the New York Times.32

It probably does feel like magic for the companies that use his software to boost profits by shifting the risks of doing business onto their workers. It probably also feels pretty great for the increasing number of managers who are compensated on the efficiency of their staffing. It feels less great, however, for the workers themselves, particularly those with caring responsibilities. Jannette Navarro, a barista at a Starbucks in San Diego, showed the New York Times her upcoming algorithm-produced schedule.33 It involved working until 11 p.m. on the Friday, reporting again at 4 a.m. on Saturday, and then starting again at 5 a.m. on Sunday. She rarely learned her schedule more than three days in advance, causing havoc for her childcare arrangements – and forcing her to put her associate degree in business on hold. It’s another example of how the introduction of Big Data into a world full of gender data gaps can magnify and accelerate already-existing discriminations: whether its designers didn’t know or didn’t care about the data on women’s unpaid caring responsibilities, the software has clearly been designed without reference to them.

A Starbucks spokesperson told the New York Times that Navarro’s experience ‘was an anomaly, and that the company provided at least a week’s notice of work hours, as well as stable schedules for employees who want them’. But when journalists spoke to current and former workers ‘at 17 Starbucks outlets around the country, only two said they received a week’s notice of their hours; some got as little as one day’. And although a few cities have introduced laws regulating the minimum advance notice of a shift an employer can give their workers,34 there is no nationwide regulation in America – nor is there in many other countries, including in the UK. It is not good enough. The work that (mainly) women do (mainly) unpaid, alongside their paid employment is not an optional extra. This is work that society needs to get done. And getting it done is entirely incompatible with just-in-time scheduling designed entirely without reference to it. Which leaves us with two options: either states provide free, publicly funded alternatives to women’s unpaid work, or they put an end to just-in-time scheduling.


A woman doesn’t need to be in precarious employment to have her rights violated. Women on irregular or precarious employment contracts have been found to be more at risk of sexual harassment35 (perhaps because they are less likely to take action against a colleague or employer who is harassing them36) but as the #MeToo movement washes over social media, it is becoming increasingly hard to escape the reality that it is a rare industry in which sexual harassment isn’t a problem.

As ever, there is a data gap. The TUC warns of a ‘paucity of up-to-date, quantitative data on sexual harassment in the workplace’, a problem that seems to exist worldwide, with official statistics extremely hard to come by. The UN estimates (estimates are all we have) that up to 50% of women in EU countries have been sexually harassed at work.37 The figure in China is thought to be as high as 80%.38 In Australia a study found that 60% of female nurses had been sexually harassed.39

The extent of the problem varies from industry to industry. Workplaces that are either male-dominated or have a male-dominated leadership are often the worst for sexual harassment.40 A 2016 study by the TUC found that 69% of women in manufacturing and 67% of women in hospitality and leisure ‘reported experiencing some form of sexual harassment’ compared to an average of 52%. A 2011 US study similarly found that the construction industry had the highest rates of sexual harassment, followed by transportation and utilities. One survey of senior level women working in Silicon Valley found that 90% of women had witnessed sexist behaviour; 87% had been on the receiving end of demeaning comments by male colleagues; and 60% had received unwanted sexual advances.41 Of that 60%, more than half had been propositioned more than once, and 65% had been propositioned by a superior. One in three women surveyed had felt afraid for her personal safety.

Some of the worst experiences of harassment come from women whose work brings them into close contact with the general public. In these instances, harassment all too often seems to spill over into violence.

‘He picked her up, threw her across the room, pounded her face and there was blood everywhere.’

‘This is when he grabbed me and hit me with the glass. I slumped to the ground and he was still pounding me. [. . .] I fought him all the way down the hall. He put my head through the wall. There was blood on the walls from my elbows, my face.’

If this doesn’t sound like just another day in the office for you, be grateful that you’re not a health worker. Research has found that nurses are subjected to ‘more acts of violence than police officers or prison guards’.42 In Ontario in 2014, the number of workplace injuries that required time off work from the healthcare sector ‘greatly outnumbered those in other sectors surveyed’. A recent US study similarly found that ‘healthcare workers required time off work due to violence four times more often than other types of injury’.43

Following the research he conducted with fellow occupational health researcher Margaret Brophy, Jim Brophy concluded that the Canadian health sector was ‘one of the most toxic work environments that we had ever seen’. For their 2017 paper on the violence faced by Canadian healthcare workers the Brophys held focus groups where ‘people would regularly say, “Every day I go into work and I’m confronted with this.”’ When the Brophys pulled them up on this claim – surely ‘every day’ was hyperbole, they meant often? ‘And they would correct us. “No, we mean every day. It’s become part of the job.”’ One worker recalled the time a patient ‘got [a] chair above his head’, noting that ‘the nursing station has been smashed two or three times’. Other patients used bed pans, dishes, even loose building materials as weapons against nurses.

Caroline Criado Perez's books