RSS responds to Diversity in STEM consultation with IMA and LMS

The RSS has teamed up with the Institute of Maths and its Applications (IMA) and the London Mathematical Society’s Women and Diversity Committee to respond to a ‘Diversity in STEM’ inquiry launched by the House of Commons Science and Technology Committee.

The inquiry seeks to establish the extent of underrepresentation amongst those working in STEM, and what the UK government, UKRI and industry can do to address it.

In a joint response, the three learned societies summarised the key challenges in increasing diversity in the fields of mathematics, statistics and data science. It describes the lack of gender diversity in these fields but acknowledges that because ‘there is no single cause, there is no silver bullet to fix it’.  

The response acknowledges the higher levels of harassment that women and LGBTQ+ people are likely to face in these fields and the affect this has on their career progression, as well as the underrepresentation of black statisticians, mathematicians and data scientists that can discourage others from joining.

There are consequences in wider society; the response points out the ‘serious problem’ of algorithmic bias that can occur when there is a lack of diversity in the people designing and developing algorithms. It also identifies the current lack of consistency in collecting data on protected characteristics, which hinder efforts to monitor inclusion and diversity.

The response makes six recommendations on what could be done to improve equality, diversity and inclusion within the fields of mathematics, statistics and data science, as follows:

  1. Ensure that education in mathematics and statistics represents and reflects the interests of a broad part of society and that all students are encouraged to study mathematics and statistics by: bringing back an AS-Level qualification in maths to encourage more students to take the subject past GCSE and widening participation in Core Mathematics.
  2. Ensure that STEM professions remain an attractive area for diverse individuals to go in to by identifying measures to tackle bullying and harassment.
  3. Develop new educational and training routes to increase participation in data science and AI fields by students from lower socioeconomic backgrounds in consultation with relevant industries.
  4. Develop meaningful regulatory frameworks to ensure that algorithms are not violating people’s rights under the equality act, GDPR, consumer protection law or anti-competition law.
  5. EPSRC/UKRI should introduce mid-career acceleration grants which are open to individuals who are no longer eligible for the New Investigator Award (NIA) scheme, and who have not recently applied for or held UKRI funding. 
  6. Work with professional societies to choose benchmark professions within STEM in which to track progress. For example, statisticians, data roles, engineering roles, accountancy roles, developer roles.
Read the response in full (PDF)
 
Load more