May 20, 2024
Gender Gap Siin

The Gender Gap Siin the AI Industry: Recognizing Women’s Contributions and Breaking the Glass Ceiling

The artificial intelligence (AI) industry is at a crucial point in its development, but it is on the verge of becoming another boys’ club. A recent article published by The New York Times shed light on the lack of recognition and representation of women in the history of AI. This revelation came shortly after the news of a fake auto-generated woman being featured as a speaker at a software conference. The omission of women from the narrative of science, technology, engineering, and mathematics (STEM) is not a new phenomenon and has been prevalent for centuries.

However, as AI continues to advance and make significant contributions to various industries, we have a choice to make. Will we continue to exclude women from these conversations, even though they are actively shaping the AI industry? This exclusion risks perpetuating the fallacy that computing itself is a man’s world, which is far from the truth. Before computers, the term “computer” was used to describe individuals who performed complex mathematical calculations, and many of these people were women.

Ada Lovelace, an English mathematician, is often regarded as the first computer programmer. Her work on the analytical engine in the mid-1800s showcased the potential of computers beyond mere math calculations. In the late 19th century, a group of around 80 women worked as computers at the Harvard Observatory, carrying out vital tasks of cataloguing and analyzing astronomical data. However, they were often exploited for their lower wages compared to men. With increased access to education, a generation of women trained in math emerged, providing cheaper labor for computation compared to their male counterparts.

During both World Wars, women played crucial roles as computers, calculating artillery trajectories and undertaking various wartime jobs in the absence of men. Even in the early days of the American space program in the 1960s, women computers made significant contributions to NASA’s projects. Katherine Johnson, one of these computers, was responsible for quality-checking the outputs of early IBM computers for an orbital mission in 1962.

Despite their pioneering work, few women in the field of computing were recognized or financially compensated for their contributions. Gender disparities persisted, with female computer specialists earning significantly less than their male counterparts. Women worked diligently behind the scenes while men received the recognition and awards. Computing and programming are the foundation of AI, and the groundwork laid by these women from the 1800s onwards cannot be overlooked. The manual work they conducted for over a century has now been replaced by machines capable of analyzing vast amounts of data in a fraction of the time.

Transitioning to advanced AI technology does not diminish women’s contributions to computing and AI. Numerous women today are leading the way in the AI industry, helping make AI safer, more accurate, inclusive, and reliable. Their groundbreaking work encompasses fields such as Google’s decision science, computer science, and leadership roles at organizations like OpenAI.

Despite their achievements, women in the AI industry face significant challenges in a heavily male-dominated field. Studies have shown that women make up only 12% of published researchers in leading AI conferences. The underrepresentation of women is not limited solely to AI but is part of a larger systemic problem that affects many people.

The consequences of a lack of gender diversity in AI can be detrimental. Gender bias and stereotypes have already infiltrated AI systems, as evidenced by the targeting algorithms used by platforms like Facebook. These algorithms perpetuate sexist stereotypes by directing job advertisements predominantly toward men or women based on societal assumptions. Additionally, computer vision systems have shown higher error rates in recognizing women, particularly those with darker skin tones.

Addressing the gender gap goes beyond improving AI training datasets. Women should also be included in the data-collection processes to ensure a more inclusive and fair representation. The recent New York Times article highlights how media and industry play a role in perpetuating a status quo that favors men. This bias hinders progress in closing the gender gap.

Despite efforts to encourage women to pursue STEM careers, retaining women in these fields remains a challenge. It is crucial to recognize and acknowledge women’s contributions to AI, as failing to do so reinforces the glass ceiling and makes it seem insurmountable. The AI industry must prioritize gender diversity and create an inclusive environment that values and supports the contributions of women. Only by doing so can we harness the full potential of AI and ensure its benefits are truly equitable for all.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it