Abstract
AI and in particular large data machine learning are transforming many areas of society including healthcare, education, and finance. At their best these offer the potential to improve society, for example, finding new pharmaceuticals. However, they may also reproduce or reinforce existing divisions and inequalities as well as creating new problems. This has been evident in high-profile news items such as the case of racial discrimination in facial recognition systems used in policing. However, some of the deepest problems in unequal access to technology are still to be fully felt.
Fortunately, AI can also be used positively to address issues of social injustice, for example human-rights organisations scanning public domain images for evidence of abuse, or software using adversarial techniques to reduce bias in training data. At best some companies and institutions are addressing these issues proactively, seeking ways to ensure they prevent or detect problems before they happen, for others this may be a rear-guard action to fix problems that have already emerged.
In this talk we will present a high-level landscape of the ways on which AI interacts with social justice and illustrate this through examples so that we can take positive action for a fairer world.
Keywords: artificial intelligence, social justice, bias, digital inclusion, digital economy, design, machine learning
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