AI, AI on the wall -- Who's the Fairest of them all?

"A world perfectly fair in some dimensions would be horribly unfair in others." "Fairness" in Artificial Intelligence (AI) applications -- both as a concept and a practice -- is the focus of many organisations as they deploy new technologies for greater effectiveness and efficiencies. That machines are faster at processing large amounts of information and the notion that they are'more objective' than humans, appear to make them an obvious choice for progressivity and seemingly impartial actors in'fairer' decision-making. Yet, algorithmic based decisions have not come without their share of controversies -- Australia's recent'robo-debt' government intervention which wrongly pursued thousands of welfare recipients; the UK's'A-Levels fiasco' of downgrading graduating grades based on historical data, its controversial visa application streaming tool; and concerns about Clearview AI's facial recognition software for policing are raising new questions on the role of these technologies in society. Risk assessments are part of the fabric of modern society, but what we are dealing with here is not just'scaling up' human capacity for decision-making without the unwanted human biases and errors -- we are also extolling the'virtues of objectivity' under the guise of'fairness' (which is inherently subjective!) and failing to recognise the many inter-relationships that are being unraveled through the use of these algorithms in our daily lives.