by Angela Guess
A recent article in The Conversation opines, “Data can’t be racist or sexist, but the way it is used can help reinforce discrimination. The internet means more data is collected about us than ever before and it is used to make automatic decisions that can hugely affect our lives, from our credit scores to our employment opportunities. If that data reflects unfair social biases against sensitive attributes, such as our race or gender, the conclusions drawn from that data might also be based on those biases. But this era of ‘big data’ doesn’t need to to entrench inequality in this way. If we build smarter algorithms to analyse our information and ensure we’re aware of how discrimination and injustice may be at work, we can actually use big data to counter our human prejudices.”
The article continues, “This kind of problem can arise when computer models are used to make predictions in areas such as insurance, financial loans and policing. If members of a certain racial group have historically been more likely to default on their loans, or been more likely to be convicted of a crime, then the model can deem these people more risky. That doesn’t necessarily mean that these people actually engage in more criminal behaviour or are worse at managing their money. They may just be disproportionately targeted by police and sub-prime mortgage salesmen. Data scientist Cathy O’Neil has written about her experience of developing models for homeless services in New York City. The models were used to predict how long homeless clients would be in the system and to match them with appropriate services. She argues that including race in the analysis would have been unethical.”
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