方式        线下

地点        李兆基人文学苑2号楼B112

简介        

Whilst the empirical evidence concerning the effects of automation on overall unemployment and employment patterns remains mixed, artificial intelligence-driven automation poses the risk of precipitating technological unemployment or significant downward pressures on net wages and welfare for individuals who remain employed. Within the subset of individuals experiencing these changes, those who consequently experience economic hardships, social alienation, psychological distress, and other detrimental states of well-being due to such processes, is termed Adversely Automation-impacted Workers (AAIWs). These adverse impacts cannot be attributed to any single morally blameworthy actor, nor are the results of any particular wrongdoing. None amongst the workers, employers opting to automate, and innovators facilitating automation should be held morally responsible for the unemployment of some workers, and the negative effects on welfare of other workers. Instead, such conditions should be treated as instances of structural injustices, as described and set forth by Iris Marion Young. Non-blame-centric responsibilities for these structural injustices are thus accrued on the part of actors who reproduce the background conditions of injustices. Such responsibilities should be identified and discharged through a model that is sensitive to the roles through which individuals interact with structural injustices.