If we don’t do something about it now, AI might widen the gender gap – thenationalnews.com

Report on Artificial Intelligence and its Implications for Sustainable Development Goal 5: Gender Equality

Introduction

Artificial Intelligence (AI) presents a dual potential for global development, capable of either accelerating progress towards the Sustainable Development Goals (SDGs) or reinforcing existing inequalities. This report analyzes the opportunities and risks AI poses, with a significant emphasis on SDG 5 (Gender Equality), examining its impact on women’s leadership, economic participation, and representation in technology.

AI’s Potential to Advance Gender Equality (SDG 5) and Reduce Inequalities (SDG 10)

Enhancing Fair Recruitment and Leadership Selection

AI offers tangible opportunities to create more equitable workplaces, directly contributing to SDG 5. Properly designed AI-driven tools can mitigate systemic biases in recruitment and promotion processes.

• AI screening tools can evaluate candidates based on qualifications and potential, bypassing unconscious human biases that have historically limited women’s advancement into leadership roles.
• Studies indicate that well-designed AI recruitment systems have successfully increased the hiring of female managers and reduced gender discrimination in leadership selection, thereby promoting SDG 5’s target for equal opportunities in leadership.

Empowering Women Through Technology and Education (SDG 4)

Beyond recruitment, AI can serve as a catalyst for women’s professional development and empowerment.

• Personalized learning platforms provide flexible opportunities for skill development, supporting lifelong learning as outlined in SDG 4 (Quality Education).
• Virtual mentorship programs and global networking opportunities can connect women with valuable professional resources.
• Data-driven insights from AI platforms can illuminate workplace inequities, providing evidence to drive policy changes and advance advocacy for gender equality.

Risks and Challenges to Achieving Sustainable Development Goals

Algorithmic Bias and the Reinforcement of Inequalities (SDG 5, SDG 10)

A primary risk associated with AI is its potential to perpetuate and amplify historical biases, undermining progress on SDG 5 and SDG 10 (Reduced Inequalities).

• AI systems trained on historical data reflecting decades of gender inequality can learn and replicate discriminatory patterns, presenting them as objective outcomes.
• The pervasive, though false, narrative that technology is a masculine domain shapes corporate culture and educational pathways, creating barriers for women in the AI field.

Underrepresentation of Women in AI: A Barrier to Inclusive Innovation (SDG 5, SDG 9)

The significant underrepresentation of women in the AI industry is a critical challenge to achieving gender equality and fostering inclusive innovation (SDG 9). Current statistics illustrate a stark gender gap:

• Global Talent: Women comprise only 22% of AI professionals worldwide.
• Leadership: Women hold less than 14% of senior executive roles in AI.
• Research and Academia: Women account for only 18% of authors at leading AI conferences and 16% of tenure-track faculty researching AI.

This lack of diversity in AI development leads to inevitable blind spots, where gender biases are overlooked and solutions that could benefit women are not considered.

The Education and Usage Gap (SDG 4, SDG 5)

Disparities in education and technology adoption further widen the gender gap, impacting SDG 4 and SDG 5.

1. Education Pipeline: The percentage of male graduates in information and communication technologies is 400% higher than that of female graduates, perpetuating a cycle of underrepresentation.
2. Adoption Gap: Women constitute only 42% of ChatGPT’s average monthly users and 27% of its smartphone app downloads. Research indicates women’s adoption of AI tools is approximately 25% lower than men’s.

Economic Vulnerability and Automation (SDG 8)

The advancement of AI poses a threat to SDG 8 (Decent Work and Economic Growth), particularly for women. Research indicates that women are overrepresented in roles most susceptible to AI-driven automation and displacement. This vulnerability can breed anxiety and discourage engagement with AI-driven opportunities, further widening the gender gap in the future workforce.

Strategic Recommendations for Inclusive AI Development

To ensure AI supports gender equity rather than calcifying existing inequalities, deliberate action is required to align its development and deployment with the Sustainable Development Goals.

Fostering Participation and Leadership

• Implement policies and programs to ensure women participate not just as users but as creators, decision-makers, and leaders in the AI sector.
• Actively recruit and support women in technical fields through targeted educational programs, scholarships, and mentorship initiatives, addressing the pipeline issues related to SDG 4.
• Promote and amplify the visibility of women already shaping the AI landscape to provide role models and foster a sense of belonging for the next generation of female innovators.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article primarily addresses issues related to gender inequality within the rapidly growing field of Artificial Intelligence. Based on the content, the following Sustainable Development Goals (SDGs) are relevant:

• SDG 5: Gender Equality

  This is the central theme of the article. It extensively discusses the underrepresentation of women in the AI industry, from talent and research to senior management and consumer adoption. The article explores how AI can either perpetuate existing gender biases or, if developed inclusively, serve as a tool to empower women and promote equality in leadership and the workplace.

• SDG 4: Quality Education

  The article points to a “pipeline problem,” highlighting significant gender disparities in education related to technology. It mentions that the percentage of male graduates in information and communication technologies is substantially higher than female graduates, and that women are underrepresented among AI-related PhD recipients and new faculty hires. This connects directly to the goal of ensuring inclusive and equitable quality education and promoting lifelong learning opportunities for all.

• SDG 8: Decent Work and Economic Growth

  The discussion revolves around women’s participation in the workforce, particularly in the high-growth AI sector. It addresses barriers to women’s advancement to leadership positions, the potential for AI to create more equitable recruitment processes, and the threat of AI-driven job displacement, which may disproportionately affect women. These topics are directly linked to achieving full and productive employment and decent work for all.

• SDG 9: Industry, Innovation, and Infrastructure

  The article focuses on AI, a key component of modern technological innovation and industry. It argues that for this innovation to be sustainable and beneficial for society, it must be inclusive. The underrepresentation of women as “AI creators and decision-makers” is presented as a flaw in the innovation process itself, leading to biased systems and missed opportunities.

• SDG 10: Reduced Inequalities

  The core of the article is about inequality between genders within a specific industry. It warns that AI, if not managed carefully, can “perpetuate – and even amplify – those same biases” found in historical data, thereby reinforcing and deepening existing inequalities rather than reducing them. The call for women’s inclusion in the design and governance of AI is a direct effort to reduce this inequality of outcome and opportunity.

2. What specific targets under those SDGs can be identified based on the article’s content?

Several specific SDG targets can be identified from the issues discussed in the article:

1. Target 5.5: Ensure women’s full and effective participation and equal opportunities for leadership in all levels of decision-making in political, economic and public life.

   The article directly addresses this target by highlighting the low numbers of women in the AI industry, especially at senior levels (“women occupy less than 14 per cent of senior executive roles in AI”). It discusses how AI can be a tool to either hinder or promote women’s rise to leadership positions.

2. Target 5.b: Enhance the use of enabling technology, in particular information and communications technology, to promote the empowerment of women.

   The article explores the dual nature of AI as an “enabling technology.” It discusses the “usage gap” where women’s adoption of AI tools is lower than men’s, but also points out AI’s potential to “amplify women’s voices,” provide skill development, and create fairer recruitment processes, all of which contribute to the empowerment of women.

3. Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship.

   The need for women to acquire technical skills to participate as “AI creators and decision-makers” is a key point. The article calls for “educational programmes [to] actively recruit and support women in technical fields,” which aligns with this target of increasing relevant technical skills for employment.

4. Target 4.5: By 2030, eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situations.

   The article’s mention of the “pipeline problem,” where “the percentage of male graduates in information and communication technologies is 400 per cent higher than women graduates,” directly points to the gender disparities in education that this target aims to eliminate.

5. Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value.

   The discussion on using AI to bypass “unconscious bias” in recruitment and evaluate candidates “based purely on qualifications and potential” supports the goal of achieving decent work for all. The article’s concern about AI reinforcing barriers to women’s advancement relates directly to ensuring equal opportunities in employment.

6. Target 10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regard.

   The article warns that AI systems trained on biased historical data can “replicate discriminatory patterns.” The call to address these biases in AI development is an action aimed at ensuring equal opportunity and reducing inequalities of outcome, as specified in this target.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article provides several specific statistics that can serve as indicators to measure progress towards the identified targets.

• For Target 5.5 (Women in leadership): The article provides direct quantitative indicators.
  • Proportion of women in the AI workforce: “women comprise only 22 per cent of AI talent globally.”
  • Proportion of women in senior leadership roles in AI: “women occupy less than 14 per cent of senior executive roles in AI.”
  • Proportion of women in AI research and academia: “Women make up only 18 per cent of authors at leading AI conferences, and just 16 per cent of tenure-track faculty who research AI.”
• For Target 5.b (Women’s use of technology): The article mentions a “usage gap” with specific data points.
  • Proportion of female users of major AI platforms: “women made up only 42 per cent of ChatGPT’s 200 million average monthly users.”
  • Proportion of female users of AI mobile applications: “only 27 per cent of ChatGPT app downloads came from women.”
  • The overall gender gap in AI tool adoption: “women’s adoption of AI tools was 10 to 40 per cent smaller than men’s, with the best estimate showing a 25 per cent gap.”
• For Target 4.5 (Gender disparities in education): The article cites statistics that measure the educational pipeline.
  • Ratio of male to female graduates in ICT: “The World Economic Forum reports that the percentage of male graduates in information and communication technologies is 400 per cent higher than women graduates.”
  • Proportion of women receiving advanced degrees and faculty positions in AI: “women making up only 20 per cent of new faculty hires and 20 per cent of AI-related PhD recipients.”

4. Table of SDGs, Targets, and Indicators

Source: thenationalnews.com