Spotlight on gender, COVID-19 and the SDGs: Will the pandemic derail hard-won progress on gender equality?

A recent report from UN Women, the United Nations organisation dedicated to gender equality and the empowerment of women, examined the impact of the COVID-19 crisis on gender equality:

This paper presents the latest evidence on the gendered impact of the pandemic, highlights potential and emerging trends, and reflects on the long-term impact of the crisis on the achievement of the 2030 Agenda for Sustainable Development.

Read the full article here.

ACM WomENcourage 2020

The 7th ACM celebration of women in computing is going to be virtually hosted from 24th to 27th September by ADA university in Baku, Azerbaijan. The event is aimed at bringing together women in computing from a variety of disciplines and will have talks from distinguished speakers, a hackathon, career fair and poster session, as well as workshops and tutorials. The early deadline to register is the 14th August. To register or for more details on the different activities, check the event website here: https://womencourage.acm.org/2020/

Distinguished speakers for the event, with topics including “The Promise of Big Data Analytics” and “The Artificial Intelligence: from Algorithms to Ethics”

Queen Mary launch masters conversion programme in Data Science and AI and scholarships

The School of Electronic Engineering and Computer Science at Queen Mary is launching a new programme in Data Science and AI in September 2020. The MSc Data Science and AI is a conversion master’s designed for motivated students who have a good first degree in a subject other than Computer Science, who wish to develop the knowledge and skills to gain employment in the Data Science and Artificial Intelligence industry. 

Funding for the programme was awarded by the UK Office for Students (OfS) as part of an Institute of Coding (IoC) consortium bid to develop new postgraduate conversion courses in AI and data science. The OfS initiative was announced in June 2020, in response to the shortage of data science and AI specialists in the UK, a concern brought to light in the UK Government’s 2017 Digital Strategy.

An important aim for this programme of work is to increase the number of people from groups currently underrepresented in the AI and data science fields, and to encourage graduates from diverse backgrounds to consider a future in these occupations.

To support students from under-represented groups to access and participate in studies at postgraduate level, Queen Mary will offer 23 scholarships over three academic years, amounting to £10,000 each to eligible students.  

Find out more

Turning words into actions: Eliminating racism and racial inequality in higher education

quoting from universitiesuk.ac.uk:

This webinar will look at how institutions can effectively respond and take action to identify and implement change, and embed this across their university. We will hear lived experiences, as well as from university leadership and practitioners working to affect change in their institutions. The session will also help to inform ongoing work and new sector guidance being coordinated by Universities UK into tackling racial harassment at universities and addressing the BAME student degree awarding gap.

Top 50 Women in Engineering (UK): Sustainability awards

On INWED day, the Womens Engineering Society were delighted to announce the winners of the Top 50 Women in Engineering (UK): Sustainability awards!

Now in its fifth year, the 2020 WE50 celebrates women who have made a significant contribution within sustainability. Winning nominees were required to provide evidence of their successful support of UNESCO’s Sustainable Development Goals or the Net Zero Carbon Programme.

The #WE50 awards seek to recognise the wealth of female talent within engineering and related disciplines. The #WE50 theme changes each year to recognise women working in different fields and from varying routes into engineering

Here is the list of this year’s winners!

New DeepMind AI scholarships for women and BAME students at QMUL

The Institute of Coding at Queen Mary has strengthened its relationship with DeepMind through scholarship programme for women and BAME students. DeepMind is a leading British artificial intelligence (AI) company which has renewed its support for under-represented students pursuing postgraduate studies in AI at Queen Mary. The donation from DeepMind will be used to continue and expand the University’s DeepMind Scholarship programme, which launched in 2019. During the academic year 2020/2021, eight DeepMind Scholarships will be awarded to women and Black, Asian and Minority Ethnic (BAME) postgraduate students living in the UK who are currently under-represented in the field of AI. Find out more:

https://www.qmul.ac.uk/media/news/2020/se/queen-mary-strengthen-relationship-with-deepmind-through-scholarship-programme-for-women-and-bame-students-.html

Two awards from the Women’s Engineering Society (nominations by 13th July)


The Women’s Engineering Society is looking for nominations and self-nominations by 13th July for two awards. The Amy Johnson Inspiration Award is given to an individual who is not currently working as an engineer for furthering diversity within engineering and applied sciences. The Men as Allies Award is awarded to a man who has gone above the call of duty to support his female colleagues and address the gender imbalance within engineering and applied sciences. Both awards are accepting nominations until 13th July.

https://www.wes.org.uk/content/amy-johnson-inspiration-award

https://www.wes.org.uk/content/men-allies-award

Challenging power in data science

Data science has never been more important but there is a considerable issue. The Data Feminism book is a collaboratively crafted book led by Catherine D’Ignazio and Lauren F. Klein which seeks to investigate data science from a feminist perspective. Biased data sets and assumptions can lead to biased technology and there is a great possibility for harm. Assumptions, like a male/female binary can lead to incorrect and harmful classification systems. You can read more about the book here:
http://datafeminism.io/
and download it here:
https://mutabit.com/repos.fossil/datafem/uv/datafem.pdf