Gender Bias and Inclusivity of Gender

The following resources can help provide all stakeholders (i.e. teachers, school leaders, parents and students) with insights into the impact and harmful consequences of AI, such as inaccurate content and the promotion of gender stereotypes.

Humans are biased. Generative AI is even worse

By Leonardo Nicoletti and Dina Bass, Bloomberg Technology (9th June 2023)

This article introduces Stable Diffusion, a tool that generates images using artificial intelligence, but like many AI models it creates a distortion of reality by taking racial and gender disparities to extremes: (e.g. women are rarely doctors, lawyers or judges; men with dark skin commit crimes).

Tackling bias in artificial intelligence (and in humans)

By McKinsey Global Institute (6th June 2019)

This article explores the issue of bias across discipline areas (i.e. generally, rather than focusing on education), suggesting that AI can actually help reduce bias, but can also “bake in and scale bias”, with the underlying data often being the cause of the bias.

When AI Gets It Wrong: Addressing AI Hallucinations and Bias

By MIT Sloan Teaching & Learning Technologies (2024)

This resource explores: biased content, inaccurate content, why AI is flawed, and navigating AI’s pitfalls (e.g. critically evaluating AI outputs, diversifying resources).

 Decorative image of a man and woman using mobile devices

Organisation for Economic Co-operation and Development (OECD)

Of the many and varied publications produced by the OECD in the digital technologies field, occasionally, articles such as the following discuss the issue of equity and inclusion:

  • The working paper The potential impact of Artificial Intelligence on equity and inclusion in education (published 14th August 2024). Click to access the article.
  • Additional publications as they are produced can be found on the OECD website here.

This article provides a detailed insight into the different types of bias that exist, including gender bias. It also introduces the teacher to the six broad categories of algorithmic bias. In doing so, the teacher’s understanding of how the underlying algorithms that are integral to generative AI, is improved. The teacher is therefore better positioned to understand the complexity of bias within generative AI tools and develop useful strategies to counteract these biases.

eSafety Commissioner

The eSafety Commissioner is a crucial resource for all Australian schools, as it provides extensive and up-to-date advice/guidelines relating to digital technologies including AI and the safe use of digital technologies. As the eSafety Commissioner stays up to date with online trends and threats, it can offer insights that are relevant to schools worldwide. As our understanding of gender bias and inclusivity of gender improves, an increased number of useful resources in the form of articles and webinars will increase. Additionally, the eSafety Commissioner provides webinars and training for educators, with an increasing number of webinars and training dedicated to AI (e.g. Understanding AI companions: What educators need to know). These are updated regularly and can be accessed with a click.

Examples of articles and guides that are useful for schools/educators in relation to AI are as follows:

  • Generative AI – position statement, which provides background information on generative AI, opportunities and risks, emerging good practice, and advice for users.
  • DALL-E 3, an AI text-to-image generator developed by OpenAI. The eSafety Commissioner provides detailed insight into what DALL-E is, how it’s used, and how personal information can be protected.
  • Adobe Firefly, an AI tool text-to-image generator, which can generate new images or modify existing images.

Steering transformative technology towards benefitting life and away from extreme large-scale risks

FLI provides free access to articles, such as those that discuss the basics of AI, its regulation, and the potential threats of AI, as well as providing insight into the broader societal implications of biased AI, such as amplifying inequality or discrimination, including gender and cultural biases.

FLI aims to guide transformative technology towards benefiting society and away from the detrimental aspects posed by AI, which in the extreme could create an existential risk to society.

Teachers can use the resources provided by FLI to develop their knowledge of how bias occurs in AI systems, and thus develop their awareness of inclusivity of gender. With this knowledge, teachers would be able to incorporate AI in their classroom in ways which are more gender inclusive. Additionally, FLI provides case studies that teachers could use within their lesson and unit plans, to assist them in illustrating AI bias, such as unfair algorithmic hiring systems and biased facial recognition systems.