Australia’s Human Rights Commissioner Warns AI Could Worsen Racism And Sexism
Australia’s human rights commissioner, Lorraine Finlay, is warning the risks of artificial intelligence and its impact on racism and sexism during a labor debate over how to respond to the rapidly developing technology.
According to reports, Finlay stated that in the pursuit of advancing productivity from AI, it’s not worth it when it comes at the expense of discrimination, which is why it’s important for the world to put together proper regulations.
Finlay made the comments after Labor senator Michelle Ananda-Rajah called for Australian data to be “freed” to tech companies to prevent AI from perpetuating overseas biases and gain a greater reflection on Australian life and culture.
Ananda-Rajah has stated her opposition to a dedicated AI act but also believes that content creators should be compensated for their work.
Next week the government is set to hold an economic summit where unions and industry figures will raise their concerns over copyright, privacy protections, and productivity gains from AI, reports state.
Media and art groups all over the world have expressed their concern over the “rampant theft” of intellectual property from big tech companies who use content to train their AI models. Finlay said that a lack of transparency in what data AI is being trained on makes it even harder to identify which biases it could be creating.
“Algorithmic bias means that bias and unfairness is built into the tools that we’re using, and so the decisions that result will reflect that bias,” she said.
“When you combine algorithmic bias with automation bias – which is where humans are more likely to rely on the decisions of machines and almost replace their own thinking – there’s a real risk that what we’re actually creating is discrimination and bias in a form where it’s so entrenched, we’re perhaps not even aware that it’s occurring.”
The Human Rights Commission has been advocating for an AI act since the technology first began advancing, specifically pushing for a Privacy Act and intensive testing for bias in AI tools.
Finlay said: “The government should urgently establish new legislative guardrails. Bias testing and causing, ensuring proper human oversight review, you [do] need those variety of different measures in place.”
An Australian study published in May found that there is growing evidence that there is bias in AI tools in Australia in areas such as medicine and job recruitment. The study found that job candidates interviewed by AI recruiters were at risk of being discriminated against if they spoke with an accent or were living with a disability, the Guardian reported.
“AI must be trained on as much data as possible from as wide a population as possible or it will amplify biases, potentially harming the very people it is meant to serve,” Ananda-Rajah said.
“We need to free our own data in order to train the models so that they better represent us. I’m keen to monetize content creators while freeing the data. I think we can present an alternative to the pillage and plunder overseas.”
Ananda-Rajah continued to say that the way in which we can overcome any bias or discrimination against certain patients would be “to train these models on as much diverse data from Australia as possible.”
Finlay added that any release of Australian data should be done in an unbiased way, but we first need proper regulations put in place.
“Having diverse and representative data is absolutely a good thing … but it’s only one part of the solution,” she said.
“We need to make sure that this technology is put in place in a way that’s fair to everybody and actually recognizes the work and the contributions that humans are making.”
AI expert and former data researcher at an AI company, Judith Bishop, said that “we have to be careful that a system that was initially developed in other contexts is actually applicable for the [Australian] population, that we’re not relying on US models which have been trained on US data.”
Julie Inman Grant, the eSafety commissioner, also expressed her concern over the lack of transparency around the data AI utilizes.
“The opacity of generative AI development and deployment is deeply problematic,” Inman Grant said.
“This raises important questions about the extent to which LLMs [large language models] could amplify, even accelerate, harmful biases – including narrow or harmful gender norms and racial prejudices.”
“With the development of these systems concentrated in the hands of a few companies, there’s a real risk that certain bodies of evidence, voices and perspectives could be overshadowed or sidelined in generative outputs.”
Eric Mastrota is a Contributing Editor at The National Digest based in New York. A graduate of SUNY New Paltz, he reports on world news, culture, and lifestyle. You can reach him at eric.mastrota@thenationaldigest.com.
