Page 45 - AI for Good - Impact Report

AI for Good

Sustainable Development Goal 5: Gender

Equality

Achieve gender equality and empower all women and
girls

SDG 5 faces significant data availability challenges, making
it difficult to accurately assess its status. However, based
213
on the available data, only 1 target (5.6 Technology for
Women Empowerment) is on track. At the current pace,
it is projected to take 300 years to end child marriage and
286 years to close the gender gaps in legal protection. 214

AI and SDG 5 Impact
According to a study on the impact of AI on
The connection between AI and SDG 5 is not extensively documented in SDG 5, AI could act as an (positive) enabler
various AI use case repositories from the UN: 3 use cases out of 40 in AI for for 56% of the targets an act as an inhibitor
Good: Innovate for Impact, 215 and approximately 90 use cases out of 408 (negative) for 33% of the targets. (Nature
Communications, 2020)
in the UN Activities on AI. 216 However, there are a few AI use cases that can
contribute to the progress of SDG 5. For example, AI can facilitate the moni- Use case 1
toring of the goal at a country or company level, which is particularly relevant Creating a tool to explore natural language
given the limited availability of data on gender equality globally. 217 Addition- processing (NLP) software to identify biases
ally, AI can support the development of platforms or chatbots for women to and stereotypes.
quickly seek help in cases of violence or abuse. 218 AI could also drive the use
of connected devices in households, reducing the time required for chores.
For instance, automated robot cleaners can alleviate some of the burden of
household chores, 219 which disproportionately impact women.
While AI can advance certain targets of SDG 5, it is important to address the
associated risks for gender equity. For instance, many AI solution developers
are men, posing challenges for women to enter this field. 220 According to
the World Economic Forum, women make up only 22% of AI professionals
globally, only 14% of AI paper authors are women, only 18% of authors at link
the leading AI conferences are women and just 2% of venture capital was Use case 2
directed towards start-ups founded by women in 2019. 221 This underrepre-
sentation can result in solutions that do not account for women's needs and Developing of a tool to help measuring
limit work opportunities for women. Moreover, historical data used in many Gender Based Violence in Latin America.
AI solutions may contain inherent biases. 222 For example, common GenAI
tools have associated women's names with words such as "home", "family",
or "children", while men's names were linked with "business", "salary", or
"career". 223 In finance, AI use can lead to bias against women, limiting their
access to loans or credits. 224 Across various sectors, AI-driven bias may
restrict women's access to employment, financial services, health services,
insurance, and more. Additionally, AI-driven content on social media can
exacerbate gender-based roles, 225 leading to challenges with body-image
and instanes of toxic masculinity, thereby compromising women’s safety on
the internet. link
Use case 3
Key Considerations for Stakeholders Designing an AI-driven transit safety app for
Manila to Ensure Women’s Transport Safety
• Women-centricity: The development of AI solutions should be aligned
with UNESCO’s “Recommendation on the Ethics of Artificial Intelligence”
to ensure that human dignity is maintained. 226
• Diversity in development: Provide women and girls the appropriate
financial and emotional support to join STEM careers, and work or
connect them with NGOs that can provide the right technical skills and
ecosystem to push those aspirations forward. 227

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