The fast-growing interest in AI from a technological and economic perspective has been quickly followed by an intense discussion of its societal impact on problems of fairness and accountability. Very recently, the sociological critique has been supplemented by a discourse on the effects that AI might have on politics. This discourse has so far primarily been conducted in popular science books and opinion pieces by writers such as Yuval Noah Harari. Elaborate journal articles with a foundation democratic theory or empirical analysis are still rated. However, their numbers are increasing, and the debate is set to accelerate further once the impact of AI technologies becomes more visible. 

In this article, we will look into AI's impact on democracy, considering AI and the democratic public sphere, the impact on the election campaign and the importance and accountability of automated decision-making systems in public services.  

The socio-technical background 

During the introduction of AI, expectations were high that machines would soon be able to think and act like humans. But the predicted progress never materialized, and a long AI winter followed. During this period, AI mostly disappeared from public discourse. But although not visible, progress was made, and many of the conceptual tools and algorithmic techniques on which our current expectations are based were developed. 

During this instance, digitalization made inroads into society, setting the foundation for AI to rise. Two decisive factors were the availability of enormous computing power and the ever-expanding data collection. From 2020 onwards, AI took off as the now-dominant machine-learning methods proved their worth in spectacular successes in fields such as speech and image recognition. In addition, the machine surpassed humans in playing board games. 

An inductive approach characterizes Deep Learning techniques that exist today. In the early days of AI developments, which often entailed complex deductive classification and reasoning, current approaches worked by large data sets, generating or adapting decision rules to allow for predefined criteria. 

Important developments 

Digital transformation has paved the way for the rise of social networks that, among other things, have intensified the personalization of news consumption and broken-down barriers between private and public conversations. Such developments are often thought to be responsible for echo-chamber or filter-bubble effects. Although empirical research on these has convincingly shown that the effects are grossly overestimated and that many non-technology-related reasons explain the democratic retreat, the spread of AI applications is often expected to revive the direct link between technological developments and democracy-endangering societal fragmentation. 

 The assumption is that AI will massively enhance possibilities for analyzing and steering public discourses or intensify the automated compartmentalizing of will formation. In a world of communicative abundance, automated content moderation is a necessity and commercial as well as political pressures further effectuate that digital tool are created to oversee and intervene in communication streams. The risk emerging in this development is twofold- on the one hand, malicious actors can use these new possibilities to manipulate citizens, and the other risk is the changing relationship between public and private corporations.  

Data-driven elections 

Elections are the single most important aspect of democracy. To fulfil its requirements, they must be conducted in specific ways where risk mostly lies in the voting process itself. In this area, AI might undermine political discourse by creating effective means for political actors to approach citizens deceptively. There are two AI-related developments cited as posing threats to the integrity of democratic elections 

• Possibility of directly manipulating political controversies 
• Expansion of online political micro-targeting 

AI and public services 

Proponents of automating society look at the outcomes of political systems. They expect legitimacy to be enhanced by automation because of the assumed objectivity of the processes and the improvement of the system's output. Therefore, problems arising from the logic of ML applications must be eradicated. Similarly, the difference between laws has to be rather explicit. Therefore, it can be contested and explained through interpretative reasoning and automated decision-making systems that create more frictionless processes by streamlining or personalizing choice architectures.  

To conclude, it is significant to understand that there is a range of challenges in that the widespread adaptation of AI-application in the realm of the public sphere, demo creating politics and public services might create for democracy. Although many of the risks highlighted so far are somewhat speculative and do not sufficiently consider countervailing forces and other balancing factors, we should be aware of the risks that even narrow AI poses concerning democratic politics. 

Source:

Heinrich Boll Stiftung

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