Gender and AI: Addressing bias in artificial intelligence
AI appears neutral, but it's made by humans, which means it internalizes all the same bias as we have - including gender bias.
AI is a mirror of ourselves.
Where can we find bias in AI?
According to Harvard Business Review, there have been many incidences of AI adopting gender bias from humans. Harvard Business Review cites an example of natural language processing (NLP) that is present in Amazon’s Alexa and Apple’s Siri.
Harvard Business Review also cites word-embeddings as a bias aspect of AI. Like a game of word-association, these systems can often associate 'man' with 'doctor' and 'woman' with 'nurse'. These don't reflect modern society, or at least how we want modern society to progress. These are outdated views.
How does gender bias occur?
Gender bias occurs during machine learning. An example is in the dataset. If there's not enough women contributing, then there will be holes in the AI's knowledge, and this is why bias errors happen. Machine learning is of course led by humans, which means their own bias will be incorporated within the AI system.
How can AI overcome gender bias?
The first step towards overcoming bias is making sure training samples are as diverse as possible - in terms of gender, but also ethnicity, age, sexuality and so on - and the people developing AI are also from different backgrounds.
Of course, like with all industries, the AI industry also needs to work towards equality, both in its approach and perspective.
AI companies need to attract more women in tech jobs, to diversify the pipeline and the workforce creating these new technologies.
Why is it important to overcome bias?
AI equality experts at the LivePerson conference revealed how bias in AI that impact society. If AI that is used to screen potential job candidates is encoded by data scientists with gender bias, our workplaces could be entirely male.
“Can you imagine if all the toddlers in the world were raised by 20-year-old men? That’s what our A.I. looks like today. It’s being built by a very homogenous group," said Frida Polli, Chief Executive Officer of Pymetrics at Fortune’s Most Powerful Women Next Generation Summit.
According to CNN Business, gender bias could also cause problems for facial recognition software that uses AI, such as security applications at concerts, airports, and sport arenas, a concern that also extends into gender binary. If AI sees gender as simply male and female, this doesn't align with modern perspectives of non-binary and transgender expression, causing potential harm for these communities.
“In this bleak depiction of our future, decades of fights for civil rights and equality have been unwritten in a few lines of code,” said EqualAI Executive Director Miriam Vogel.
Reshaping the future of a bias-free AI world
Bias may be an unavoidable fact of life, but let's not make it an unavoidable aspect of new technologies.
New technologies give us a chance to start afresh - starting with AI - but it's up to people, not the machines, to remove bias. According to the Financial Times, without the training human problem solvers to diversify AI, algorithms will always reflect our own biases.
So hopefully women, together with men, will play a large and critical role in shaping the future of a bias-free AI world.