Cordelia Fine: Why does gender diversity matter?

In October 2020, I attended the virtual keynote by Cordelia Fine at the EMBO/EMBL conference on Gender Roles and their Impact in Academia. Cordelia Fine is a Canadian-born British philosopher, psychologist and writer. She is a Full Professor of History and Philosophy of Science at The University of Melbourne, Australia. Fine has written three popular science books on the topics of social cognition, neuroscience, and the popular myths of sex differences.  Cordelia spoke to us about why gender diversity matters.

Having analysed media articles on gender diversity, Cordelia found that 72% of them mainly looked at the organisational benefits of gender diversity, with most just stating that injustice exists. Only rarely did the media give the case for gender diversity, for example that it reduced power imbalance or helped an organisation to represent the community it served better.

In Cordelia’s view, journalists should go beyond plainly stating that gender imbalance exists in academia, or present this imbalance by itself as an injustice but should go on to explain why this is unjust. The counter argument is that people are not interested in the unfairness itself, they just want to know the benefits of better gender equality. But is this actually true?

In reality, we know very little about what people think about workplace gender diversity and what worries them about it. Cordelia’s team aimed to find out more about attitudes and concerns. They aimed to:
1. Learn how attitudes are moderated by demographic and organisational factors, comparing horizontal vs vertical workplace gender diversity i.e. between sectors and within the hierarchy
2. Better understand and respond to concerns, resistance and backlash

The study included 241, gender balanced, mainly Caucasian workers of whom the majority were managers. Cordelia’s team showed them the statistics for their sector and asked about the reasons, benefits and downsides of efforts to achieve greater gender balance across industries, occupations and in leadership positions. Benefits might include representation, fairness and a reduction in bias or disadvantage. Downsides might include undermining meritocracy or PC / virtue signalling. Participants could also say that there were no benefits or downsides.

The responses showed that perceived organisational benefits included a more diverse workforce with different attributes, a range of business benefits, a better workplace, a wider talent pool and benefits to the consumer. Downsides reported included psychological interpersonal damage resulting from tokenism and damage due to resentment from others.

In summary, people seem to care more about justice than concrete organisational benefits. There are substantial minority concerns, for example regarding psychological damage. Women are generally more positive than men about workplace equality, but this is more about justice than organisational benefits. Some said they could see no benefits to the organisation. People are also more positive about vertical workplace gender diversity, within the heirarchy than horizontal, across different sectors. They are more likely to say there are no downsides to diversity within the hierarchy. A wider study with 1000 participants is now underway to explore these findings further.

One tentative implication of the initial study is that horizontal workplace gender diversity is a bit neglected. We should be chipping away at that because sex segregation by occupation is the single biggest contributor to the gender pay gap in the UK. For leaders promoting workplace gender equality, they should work to anticipate concerns and address them upfront.  However, don’t give up on the justice arguments!

Organisational benefits are important but inclusion then becomes based on women needing to add value to the organisation in order to justify the efforts being taken. If the evidence for the benefits becomes shaky, this impacts on the justification for increasing diversity. The argument should be about what the organisation can do for women and to deliver justice and fairness for all.

On the whole, employees do care about gender justice for both vertical and horizontal diversity so there are receptive grounds for these ideas. That leaves the question of how to address the concerns of those who stand to lose from better workplace gender equality. It is not acceptable to just give up on the idea if people are concerned about diversity vs merit. Merit does not just reside in individual attributes but also in what people of all genders bring to the organisation. Affirmative action measures can help to facilitate access to goods, positions and opportunities, such as fellowships for women. You can also balance direct versus indirect actions, direct actions including those specifically targeted at women. An indirect action would be targeted in a way that benefits women more, for example for people who have taken time out of the workplace. Indirect actions often encounter less resistance. Try to get the naysayers involved by sponsoring someone – when not being forced, they are then part of the positive change. There is no simple answer to this issue but building up resentment is not good for anyone.

Gender Summit 17: Open science, diversity and AI

One of the key themes for the Gender Summit in Amsterdam in October 2019 covered fostering diversity in open science and AI to better connect science to society.

Greta Byrum from the Digital Equity Laboratory in the US described the state of play as she sees it. “This data almost feels radioactive,” she warned. The rush to market for automated digital systems based on AI is leading to built-in bias in areas such as facial recognition, policing and health care. “In the US, there is little protection for highly sensitive data,” she said. “You should be very happy that GDPR exists in Europe!”

She cited the example of period tracker apps that share data with third parties without explicitly asking for user permission, potentially sharing highly sensitive information about pregnancy status in a way that could intersect very badly with changes to legislation around abortion in the US.

“As datasets grow, biases can be reinforced rather than ironed out, depending on who decides on data quality,” she explained. For her, society could – and should – insist on and drive for industry standards, a code of ethics and better public awareness of what might be happening to their data.

Cecile Greboval from the Council of Europe had similar stories to tell of countries using flawed algorithms to decide on disability benefit rather than face-to-face interviews, relying on AI to filter admissions to university and image databases that return sexist images for simple search terms, such as female police officer. Women are severely under-represented in ICT, at only 13% of ICT-related graduates working in digital jobs in 2016 and numbers have actually been falling in recent years.

“We think that technology is neutral, like the law. But 80% is designed by white men who can project their own world view on to the data,” explained Greboval. “Gender stereotypes in childhood and education, together with sexism and harassment in the workplace have led to a dearth of women in IT. This means women are excluded from well paid, powerful jobs.”

Greboval called for safe conditions conducive to women at work and pointed towards the Council of Europe action against sexism: See it. Name it. Stop it.

Built-in bias

Algorithms can have bias built in from the ground up if particular groups are under or over represented in datasets. Sexism and stereotypes become transmitted to machines and are sometimes amplified, with historical inequalities hardwired into the data. Ozgur Simsek from the University of Bath described how Buolamwini & Gebru (PMLR, 2018) demonstrated that facial recognition systems perform better at detecting men than women and at detecting light-skinned than dark-skinned people.“The worst rates are for darker skinned women, by up to 35%. When guesswork will give you a 50% error rate, there’s not much learning going on there,” said Simsek wryly.

Caliskan, Bryson and Naraynan (Science, 2017) analysed 840 billion words – from tweets, the US Declaration of Independence, Reddit threads and many other sources. They found the same biases in text as shown by people taking the Harvard Implicit Association Tests. Unsurprisingly, machines learning from these datasets will tend to incorporate the same biases as humans.

To counteract these biases, Bath University puts learning ethics and transparency on the same footing as algorithms on their AI courses, combining computer science, AI, engineering, social science and policy making. “Students must cover all these areas to graduate,” said Simsek.

For Ghislaine Prins of Randstad, the route to improvements is to review datasets, establish diverse teams for creating algorithms, train leaders – and check, check, check again. “Then check the check!” said Prins.

Gender Summit 2019, Amsterdam: Identifying concrete measures for change

In Amsterdam last week, gender and inclusion professionals gathered for the 17^th Gender Summit. Ingrid van Engelshoven, Minister for Education Culture and Sport introduced the three themes for the event, which chimed with her ambitions for Dutch science policy: national frameworks to advance gender balance, diversity and inclusion; fostering diversity in open science and AI to connect science to society; actions towards a team-driven, innovative academic culture.

For van Engelshoven, there are two points to bear in mind to achieve gender equality. “We should judge research institutes by their gender equality and assume gender equality is the norm.” She cited the example of Emily Warren Roebling’s largely unsung contribution to the construction of the Brooklyn Bridge in New York after her engineer husband developed caisson disease. “Let’s not take 14 years to build bridges to equality,” she urged. “I am looking for very concrete measures we can take now, not in 10 years time.”

Mind the gap

Belle Derks of Utrecht University was the first speaker to rise to the challenge by identifying a number of ‘gender gaps’. “In Europe, the gender pay gap in academia is about 800 Euros. Age is a large factor in this as 50% of women drop out earlier in their careers. However, we actually see the widest gap at the highest pay grades.” Derks reported that there was no evidence that women negotiate less for their pay. “In fact, their more precarious employment often means that they negotiate more.”

Women at higher grades also report they spend more time teaching and have fewer resources in terms of staff, budget and equipment, leading to a ‘resources gap’. When men look ‘up’, they see people at the top like them. For others, the lack of role models can correspond to a ‘belongingness gap’.

Unconsciously, we expect women to be communal and men to be agentic and tend to dislike those who do not conform to these stereotypes. Simply trying to be more agentic is not as effective for women and taking a communal approach is not as valued. Women feel a lack of fit, which can lead to less engagement, work exhaustion, lack of agency and higher turnover. “The concrete solution here is to control for masculine definitions of excellence, focus on team science and value a diverse set of qualities in our reward systems,” explained Derk.

Bias in a meritocracy

For Prof Simone Buitendijk of Imperial College London, universities need to recognise the pernicious effects of bias and accept that it exists. “It’s not about being nice to women and ethnic minorities, it’s about including all talent to tackle global challenges,” she insisted. “If you tell us bias is not true, how dare you!”

The pervasive nature of bias is at odds with scientific research as a meritocracy. For example, BAME students experience more mental health issues while studying, which can become a vicious circle, impacting their eventual results.

“Just like a canary in the coal mine, minorities suffer most from competitive, individualistic and vicious atmospheres,” she reminded us. “Generally, we are poor at measuring excellence. No one can achieve perfection, even the superstars.”

“We need to tackle the system, but not shame individuals – unless they are in denial!” she said. Buitendijk called for leaders to be strategic in their approach and not let equality and diversity become the topic they aim get to once everything else is fixed. “Don’t leave it to the lone diversity officer in their cubicle,” she urged to a rueful laugh from the audience. “If we blindly insist that research is a meritocracy, then people blame themselves for bias in the system.”

The success factors linked to sustainable change are outlined in LERU’s recent report: “Equality and diversity at universities: The power of a systemic approach.”

• Discover and include a wide range of students
• Realise the potential of all staff and students
• Enhance performance and well-being
• Create an attractive community for all
• Increase the quality of knowledge production
• Connect with societal challenges

“Leaders should understand the statistics, listen to individual stories and take a strategic response,” urged Buitendijk. Hopefully, everyone in the audience is here to do just that.

From corporate boards to women in tech: Day 2 of the Gender Summit 15

Day 2 of the Gender Summit in London brings a wide diversity of talks on the programme. Elena Doldor of Queen Mary University London spoke to us about efforts to get more women onto boards in the UK. After noting that lapel mikes are not always friendly to women’s outfits (prime example of single gendered thinking) she reminded us of the 2011 Davies Review in the UK. The Davies Review argued that UK listed companies in the FTSE 100 should be aiming for a minimum of 25% female board member representation by 2015. There is no legislation or fixed quotas for board members in the UK, but through voluntary efforts, female representation has grown from 12% to 28% in 5 years or so.

The new target is 33% female representation, but achieving this will be impossible without more women in the pipeline. “We can’t get lost in vague statements on how much we value diversity,” warns Doldor. “Companies can, and should, set themselves concrete targets to clarify their goals.” For example, UK bank RBS is aiming to employ 30% women in its top 5000 roles by 2020. “Metrics are very important and your rate of promotion should reflect your intake pool,” said Doldor. “If that’s not the case, ask yourself why? Career choices are not made in a vacuum! What is the culture of your organisation?” Doldor believes that the voluntary approach works without legislation, if you take a pragmatic stance and carefully define the processes that are going to drive change. “Leadership should be directly accountable for targets but you also need champions throughout the organisation. In academia, professors need to be good managers and powerful mentors, as well as outstanding researchers.” Ron Mobed of Elsevier agrees. “We need to show what good looks like. For me, there is concern about the behaviour of some young males, which is taking us backwards.”

The GEDII Project has focused on measuring representation and attrition for men and women across seven pillars of a Gender Diversity Index, shown below.

GEDII: Seven pillars of the Gender Diversity Index

They are working on a self assessment tool to calculate your own organisation’s Gender Diversity Index . When GEDII related gender balance to research performance, they found that women are cited at equal rates, but publish less, especially in less diverse teams. Linking policy down to individual team level is difficult, as policy tends to be set at an institutional level.

Nigel Birch of EPSRC introduced their study of women in ICT with Napier University.  Motivations for working in tech seem to split into 2 camps: those who are interested in the tech and people who are fascinated by what you can do with tech. Women tend to be more interested in the latter (although by no means exclusively). ICT has a reputation of being an ‘always on’, long hours culture and women have more competing responsibilities, for example from good citizenship activities. They are also less confident in their abilities, which can be a learned attitude based on years of negative input, coupled with a general sense of not fitting in and being treated differently. (Check out the Petrie multiplier for more on this phenomenon). The ‘softer’ skills in ICT are often valued less, and part-time and flexible working have a negative impact on career progression. Unfortunately, the study also found that bullying and harassment are definitely present in ICT, as in many fields.

All this is rather depressing news, but EPSRC does have a plan of action. This involves establishing a baseline to measure progress, and running a workshop with Government and academia. They plan to develop case studies, targeted at particular audiences and tackle discrimination, harassment and aggression alongside other UKRI partners. “Women need to have trust in the system to raise their concerns, and funders are a neutral party,” said Birch. Let’s hope that proves to be true.