Technologies exist to improve people’s lives, create opportunities and break down barriers, and the possibilities don’t stop at smartphones and gadgets. Organizations across the world now are looking to systems such as blockchain and machine learning to close the gender gap.
In France, the government announced in March 2018 it will implement new measures to combat gender pay gaps in the workplace using new software. The software will be installed on company payroll systems to monitor and flag “unjustified” pay gaps between men and women, and companies that fail to comply face fines. Similar software tools are already in use in Switzerland and Luxembourg.
On the nonprofit side is UN Women, an offshoot of the United Nations dedicated to using innovation and technology to eliminate gender disparities and empower women and girls. In 2017, the organization led a hackathon at a festival in Oslo during which the innovators used blockchain – which offers decentralized, secure online database, records and money transfer systems – to solve the challenges faced by refugees and displaced persons.
Two of the winning apps directly addressed female empowerment:
- “VIPI Cash” used blockchain to ensure secure money transfer among women entrepreneurs to give them access to and control over their own money without needing male family members’ permission or assistance – a situation that is not uncommon in many parts of the world.
- Another app, “Diwala,” assigns tokens with which women can buy or sell services instead of requiring access to cash; it also helps them verify and endorse their skills. Its capabilities later were expanded to help refugees in disaster areas.
Even the movie industry is getting with the times. The Geena Davis Institute on Gender in Media, founded by the Oscar-winning actor Geena Davis in 2007, began collecting data on movies to determine whether there was an unconscious bias against women in film. The Institute teamed up with machine learning engineers to develop software that accurately measures how often we see and hear women on screen, in real time.
The engineers programmed the machines to “learn” from examples showing the correct answer, ensuring the technology improves its own understanding over time. The tool learned to detect different characters online, determine their gender, and calculate how often and for how long they spoke in relation to one another.
When the software analyzed the 100 highest-grossing live-action films in the United States, the numbers were disheartening – but education is the first step toward change. A survey following a presentation of the findings showed that 68 percent of filmmakers reconfigured two or more of their projects after hearing the numbers. Davis is confident we’ll start to see real change in the next five to 10 years.
We still have a long way to go before gender inequality is a thing of the past, but with technology’s assistance, we’re getting closer every day.