Automation, digitalisation and artificial intelligence in the workplace: Implications for political behaviour

Taking a complex view of automation that acknowledges its link with economy and politics, Gallego and Kurer explore the ‘mechanisms’ that see ‘technology-related workplace risks’ pass over into ‘political behaviour and policy demands’. They identify that voters ‘may fail to fully comprehend the relative importance of different causes of structural economic change and misattribute blame to other factors’. This results in the proposal of, and support for, policies that do not match the problem at hand. Whilst the precise balance of material and status concerns is contested, economic insecurity associated with technological change has been identified as a potential cause of the populist upheavals of recent years. However, the direct material consequences that confront those for whom the threat is actually realised, and who therefore face unemployment and economic hardship, are in fact more likely to abstain from electoral politics altogether (see Kurer 2020).

Yet, it remains the case that there is no inevitable or predetermined relationship between economic change and voting patterns, the translation between which rests upon political rhetoric and voter perceptions. This is demonstrated in how those who lose out from automation do not always hold technological shifts responsible for the vulnerability it causes, blaming immigrants or globalisation instead. Likewise, those who benefit from technological shifts tend not to see the technology itself creating the conditions for their success so much as the apparent effects of meritocracy in action (Sandel 2020). This misperception can lead to calls for policies that do not address the source of the insecurity and loss. There is thus not a direct relationship between material shifts, economic interests and political behaviour, with studies uncovering no coherent connection between automation risk and demand for specific kinds of policy response.

Populist parties have prospered by offering apparently tangible explanations that connect economic, cultural and political phenomena, posing apparent solutions, whereas the actual effects of automation are in practice slow, sometimes imperceptible and thus difficult to politicise. This presents a problem: it is challenging for voters to correctly establish the contribution of technological change versus other causes of structural change and to discern which policies are more likely to be helpful, and political parties may find it difficult to mobilise around a complex discourse of how technology affects employment structurally. There is clearly more work to be done to understand the translation of automation and digitalisation into a political realignment and polarization whereby right and left take divergent paths to satisfy their new sectional electoral coalitions. Gallego and Kurer outline seven areas that require further research in this domain: research design; gender, race, and generations; winners of technological change; the role of political parties; perceptions and mechanisms; comparative work, and policy responses.