Intelligence of everything
Artificial Intelligence (AI), when combined with the ‘internet of things’, has the potential to improve our understanding of the differentials between men’s and women’s economic empowerment, as well as their causes. These insights will enable society to deliver equitable solutions that are able to better meet the needs of women and girls across a variety of sectors, from healthcare and education, to infrastructure and financial institutions (e.g. innovative credit assessment technologies based on psychometric tests are improving access to finance for those who fall short of traditional collateral and documentation requirements). However, AI also brings new risks. For example, it could drive further automation, particularly in several female-dominated sectors, such as textiles. Equally, the rapid creation of data on women’s use of everything, from infrastructure to healthcare, brings with it consumer protection and privacy issues that have the potential to erode women’s independence.
- Opportunity
- high
Among other opportunities, AI has the potential to (1) improve our understanding of the differentials between the economic empowerment of men and women, as well as their causes, (2) reduce the burden of domestic housework on women, allowing them to take on paid work during the day, and (3) introduce mobility gains for women.
- Risk
- medium
Risk of AI worsening the gender gap (e.g. in terms of employment, access to resources, etc.).
Risk of consumer protection and privacy issues eroding women’s independence.
- Opportunity
- high
- Risk
- medium
Currently, women in the low and middle-income countries produce substantially less data than men. Women are 10 percent less likely than men to own a mobile phone and 23 percent less likely to use mobile internet. Mobile banking and big data analytics based on data from the internet of things can provide the information necessary to improve credit assessment technologies and increase financial inclusion for women. For example, companies such as Lenddo and EFL use a wide range of data in their credit scoring algorithms, from social media and smartphone records to psychometric tests.
To harness the potential for AI to increase financial inclusion, gender-smart investors could:
- Integrate AI into existing investees’ credit scoring methodology, where possible.
- Invest in innovative companies produce AI for institutions, working with investees to maximise utility and drive down costs to customers.
Sources: https://www.fico.com/blogs/where-and-why-efl-alternative-credit-scores-work https://www.cio.co.ke/mobile-phone-penetration-rises-despite-the-gender-gap-ownership-disparities/
- Opportunity
- medium
- Risk
- medium
There is a risk that AI could worsen the employment gender gap for two reasons. First, AI is likely to increase automation, and thereby eliminate jobs across a variety of manufacturing sectors, including female-dominated sectors such as textiles. As McKinsey states: “Tomorrow’s successful apparel companies will be those that take the lead to enhance the apparel value chain on two fronts: nearshoring and automation.” Second, AI relies on real-world data and so can inadvertently reinforce existing social biases. For example, Gartner (2016) predicts that by 2022, 85 percent of AI projects will deliver erroneous outcomes due to bias in data or algorithms. At the same time, AI has the potential to reduce the burden of domestic housework on women, allowing them to take on paid work during the day.
Gender-smart investors could improve women’s job retainment by supporting investees focused on skills development. This would provide employees in female-dominated sectors at high risk of automation with the skills required by future working environments.
Gender-smart investors could also invest in smart devices adapted to developing country environments to reduce the burden of domestic responsibilities on women and thus allow them to take on paid work.
- Opportunity
- high
- Risk
- medium
AI has the potential to adapt educational content according to student’s needs, delivering individualised remote learning (e.g. putting greater emphasis on certain topics, repeating things that students have not yet mastered). This could improve the quality of education received by women and girls, for example, by enabling them to catch up more easily (in the event of school dropouts) than classroom conditions in which teachers do not have time to reteach materials or spend a large amount of time assessing individual’s needs.
Gender-smart investors could support investees to incorporate the latest AI technology, encouraging its adaptation to national curriculums and ensuring it is differentiated to students’ needs in developing economies.
- Opportunity
- medium
- Risk
- low
“While it is clear that both men and women suffer in poverty, gender discrimination means that women have far fewer resources to cope.” AI and big data could help to identify access differentials and their causes, enabling a more equitable distribution of healthcare.
Gender-smart investors could support investees to incorporate the latest AI technology that is adapted to working in data-scarce environments.
Source: https://www.worktheworld.co.uk/blog/womens-health-developing-world
- Opportunity
- low
- Risk
- low
Currently, women in low and middle-income countries produce substantially less data than men. Women are 10 percent less likely than men to own a mobile phone and 23 percent less likely to use mobile internet. Similar to the dynamics highlighted in the Financial Institutions note, gender-smart investors’ investees within OGS may create significant amounts of data on women that can be used to create opportunities for inclusion.
- Opportunity
- medium
- Risk
- medium
Women make up 45-80 percent of the food-producing workforce in developing countries. AI and big data could help to improve productivity (e.g. automated drip irrigation systems) and risk mitigation (e.g. weather index-based insurance).
To harness the potential for AI to improve the productivity of smallholders, gender-smart investors could:
- Encourage investees to utilise and test AI technologies.
- Evaluate potential barriers that inhibit women’s access to AI-based products (e.g. weather-index insurance), working with and through investees and other stakeholders to tackle them.
- Work with universities, governments and investees to adapt AI technologies to the needs of smallholders, as well as data-scarce, low-resource agricultural environments.
- Opportunity
- high
- Risk
- low
Infrastructure is often designed without a gender perspective, which makes it harder for women to access it and use it to their benefit. It is critical to ensure women’s needs are considered in future developments. AI and big data could help to develop more female-friendly infrastructure, identifying widespread usage patterns, barriers to use and opportunities to increase women’s mobility.
To harness the potential for AI to create inclusive infrastructure, gender-smart investors could:
- Evaluate potential barriers that may inhibit women’s access to new infrastructure, working with and through investees and other stakeholders to tackle them.
- Help investees integrate AI into existing businesses and projects where possible.
- Invest in innovative companies producing AI for infrastructure projects, working with investees to maximise utility and drive down costs to customers.
Source: http://www.sddirect.org.uk/media/1332/icedinfrastructurefull-paper-20161130173941.pdf
