Inadequate participation by women in the creation of tools and research in AI is deeply problematic.
According to data, there are 12 % of women in research roles in AI, and about 20% of technical roles in machine learning companies are held by women.
Audrey Azoulay, Director General of UNESCO, has been quoted as saying, “There is an urgent need to rebalance the situation for women in AI to avoid biased analyzes and to build technologies that take into account the expectations and needs of all of humanity.”
The implications of gender inequality in AI:
- The lack of gender equality is problematic as it can amplify existing gender biases and create new ones.
- AI relies on the data. If the data fed consists of stereotypes, the systems created from that data will perpetuate and reinforce such stereotypes.
- Gaps due to inadequate data or representation of women can disadvantage women.
