In 2023, Artificial Intelligence has continued to advance rapidly. Deep learning remains central, driving applications in healthcare, finance, and autonomous vehicles. Ethical considerations and regulations have intensified.

Women have been making significant contributions to artificial intelligence (AI), but the field still faces gender disparities. Efforts to promote gender diversity and inclusion in AI have gained momentum through organizations and initiatives dedicated to supporting women in AI, mentorship programs, and conferences like the Women in AI (WAI) Summit.

Pioneering women in AI, such as Fei-Fei Li and Yoshua Bengio, have inspired future generations. However, addressing gender imbalances and fostering a more inclusive AI community remains a challenge. Encouraging more women to pursue AI careers, providing equal opportunities, and combating bias in AI algorithms are crucial steps in advancing the field with diversity and equity.

Australians' impressions of artificial intelligence (AI) have been revealed in a new Roy Morgan study, giving surprising insights into the nation's feelings towards this disruptive technology.

While a majority of Australians feel that AI causes more issues than it solves, there is an interesting contrast when looking at AI's function in recruiting. The data, obtained from over 1,500 respondents, reveals a gender difference in AI scepticism, with women constituting the majority of those who doubt its overall value. However, when it comes to using AI in recruiting, the story takes an unexpected turn.

Skepticism Surrounding AI in Australia

According to Roy Morgan's poll, 57% of Australians believe that AI causes more problems than it solves. It is worth noting that 67% of individuals who expressed such worries were women. Furthermore, the data revealed that older Australians and people from rural regions were more skeptical about AI. This skepticism is consistent with PwC's 2021 AI Predictions Survey, which classified Australia as one of the most conservative nations when it comes to AI technology adoption.

The origins of this skepticism may be traced back to the fast mainstream adoption of AI, particularly in the last year. While AI use has increased, especially in the generative AI sector, many essential components and considerations in the AI domain have yet to be completely incorporated or mandated. As a result, it's not unexpected that concerns and reservations continue.

A Closer Look at Bias in AI and Human Bias

Bias is one of the most important challenges in the AI environment. AI systems might acquire biases from the data on which they are taught, posing substantial issues, particularly in business. According to IBM's 2022 Global AI Adoption Index, 74% of organisations that use AI are not properly preventing inadvertent bias in their AI systems.

However, it is critical to recognise that human bias is prevalent in recruiting and the workplace. Bias can influence choices on equal pay, promotions, and employment. Women and people from marginalised groups have long been aware of these prejudices, which impact their impressions of AI.

A recent white paper, "Does Artificial Intelligence Help or Hurt Gender Diversity?" revealed some intriguing findings. It revealed that when AI was used in the recruiting process, women were 30% more likely to finish a job application than when human assessors were used. According to this result, women view AI to be less biassed than human assessors.

The white paper also indicated that when gender-associated names are included with job applications, human evaluators frequently evaluate women "substantially lower" than males. Surprisingly, introducing AI into the hiring process improved the presence of women among qualified candidates by 30%.

Confronting the Paradox

This perplexing position poses two key concerns. For starters, it emphasises the continuous battle for employment equality. Despite improvements in numerous fields, prejudices exist and have an impact on people's professional chances. Second, it emphasises the need of framing AI queries in the proper context. Australians, particularly women, are sceptical about AI in general, but they are more likely to trust AI in recruiting, where human prejudices have a concrete and negative influence.

Conclusion

Australia's relationship with artificial intelligence is complicated, with scepticism prevalent in general but confidence increasing when AI is used in recruiting. This paradox emphasises the importance of tackling prejudice in both AI systems and human decision-making in order to achieve more workplace equality. As artificial intelligence continues to affect different aspects of our life, it is critical to engage in nuanced dialogues and evaluate the context in which AI is used to properly understand its potential advantages and problems. Ultimately, developing transparency, accountability, and ethical AI practises will be critical in realising this disruptive technology's full potential.