8.2.2022
EN
Official Journal of the European Union
C 67/145 Thursday 10 June 2021
21.
Calls on all the relevant stakeholders to address discrimination in their hiring practices and to introduce quotas to promote the inclusion of women, especially women from diverse racial and ethnic backgrounds, women with disabilities and LGBTI+ people;
22.
Encourages the establishment of an inclusive dialogue with the relevant stakeholders, such as private companies, non-governmental organisations, professional orders and institutes, state institutions, regional and local authorities, policymakers and civil society representatives, in order to coordinate and tackle the missing links to promote women in STEM; stresses that in view of the paramount importance of fighting cultural and social stereotypes against women’s abilities and roles in the STEM sector, targeted measures should be adopted to promote gender equality such as gender mainstreaming legislation or policies such as financial incentives or other measures in order to increase girls’ participation in STEM education and careers; calls for incentives to be provided to companies that support female role models, mentoring programmes and career paths, and for the visibility of women to be increased; recognises the essential role played by certain CEOs and senior management people in closing the digital gender gap by developing corporate policies aimed at combating digital gender-related stereotypes, promoting role models, motivating women to explore STEM studies, stimulating the reskilling or upskilling of women, promoting mentoring schemes, and improving the image of ICT jobs; calls on the Commission and the Member States to further engage with all ICT, digital, telecoms, media, audiovisual and technological business partners to promote an inclusive and gender-balanced working culture and environment, including by introducing measures such as awareness campaigns to promote gender equality in the private STEM sectors and public-private partnerships to facilitate access to the STEM labour market for recently graduated students, with the promotion of apprenticeship schemes and internships for girls and young women to enhance their transition to the labour market, through such initiatives as mentorships and scholarships for disadvantaged girls, and with public-private partnerships between education systems, governments and companies that work in emerging technologies, such as 3D technologies, AI, nanotechnology, robotics and gene therapy, and to share information and good practices across the Member States to this end;
23.
Highlights the relationship between the gender gap and the pension gap; calls on the Member States, therefore, to tackle and reduce these and to take further steps to ensure that women can get adequate access to education, the chance to attain economic independence and career progression opportunities;
Digital sector
24.
Regrets the fact that the gender gap exists across all digital technology domains, but is especially concerned about the gender gap in innovative technologies, such as the AI and cybersecurity domains, where the average worldwide female presence stands at 12 % and 20 % respectively (22); proposes that more attention and support should be devoted to sparsely populated and particularly rural areas, where this situation is getting worse;
25.
Stresses that the quality of the data sets used is paramount for the performance of AI technologies, that AI must not reinforce gender inequalities and stereotypes by transforming bias and prejudices from the analogue to the digital sphere on the basis of algorithms, and that AI can contribute significantly to promoting gender equality, provided that an appropriate legal framework is developed and conscious and unconscious biases are eliminated; highlights that one of AI’s most critical weaknesses relates to certain types of bias such as gender, age, disability, religion, racial or ethnic origin, social background or sexual orientation as a result of a homogeneous workforce; notes that intersectional types of discrimination leave women marginalised from emerging technologies, such as women of colour owing to errors in facial recognition technology; emphasises the need for diverse teams of developers and engineers to work alongside key societal actors to prevent gender and cultural biases from being inadvertently included in AI algorithms, systems and applications; supports the creation of educational curricula and public-awareness activities concerning the societal, legal and ethical impact of AI; calls on the Commission and the Member States to take all possible measures to prevent such biases and to ensure the full protection of fundamental rights; stresses that human oversight infrastructure must be developed before AI technologies are rolled out in high-risk sectors, notably health, and must include gender equality experts;
(22)
Sax, L. J., Kanny, M. A., Jacobs, J. A. et al., ‘Understanding the Changing Dynamics of the Gender Gap in Undergraduate Engineering Majors: 1971-2011’, Research in Higher Education, Vol.
57, No 5, 2016; Shade, L. R., ‘Missing in action: Gender in Canada’s digital economy agenda’, Signs: Journal of Women in Culture and Society, Vol.
39, No 4, 2014, pp. 887-896.