Algorithmic memory and the right to be forgotten on the web

Abstract

The debate on the right to be forgotten on Google involves the relationship between human information processing and digital processing by algorithms. The specificity of digital memory is not so much its often discussed inability to forget. What distinguishes digital memory is, instead, its ability to process information without understanding. Algorithms only work with data (i.e. with differences) without remembering or forgetting. Merely calculating, algorithms manage to produce significant results not because they operate in an intelligent way, but because they ''parasitically'' exploit the intelligence, the memory, and the attribution of meaning by human actors. The specificity of algorithmic processing makes it possible to bypass the paradox of remembering to forget, which up to now blocked any human-based forgetting technique. If you decide to forget some memory, the most immediate effect is drawing attention to it, thereby activating remembering. Working differently from human intelligence, however, algorithms can implement, for the first time, the classical insight that it might be possible to reinforce forgetting not by erasing memories but by multiplying them. After discussing several projects on the web which implicitly adopt this approach, the article concludes by raising some deeper problems posed when algorithms use data and metadata to produce information that cannot be attributed to any human being.

Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing

“…Other camps of thought, notably those that have forever been skeptical of an all-too-schematic private/public-bifurcation, such as utilitarians and the virtue ethicists, might instead concentrate their assessment on the practical consequences of the employment of nudges based on personalized data. Thus, future research may follow-up on algorithmic memory and the right to be forgotten, which is also an important aspect to consider for algorithmic pricing (Esposito 2017).…”

“…Further practical issues may also arise in this regard. A programmer designing the algorithm, and the company selling it, might neither know the exact data the algorithm processes nor can they fully control the output (Esposito 2017). Additionally, an algorithm responsible for some form of misconduct cannot be questioned like a human person; likewise, from a technical point of view, secondgeneration algorithms that build on reinforcement learning, can individually develop their code such that their developers might not even be able to decipher how the algorithm arrived at a certain decision (Calvano et al 2019;Xia et al 2019).…”

Moonwalking together: Tracing Redditors’ digital memory work on Michael Jackson

“…Moreover, as data companies, social media themselves represent past posts to their users, which shapes how we view our past selves in relation to others (Prey and Smit, 2018). Such automatic processing and representation of our past leads Esposito (2017) to claim that 'algorithms remember memories that had never been thought by anyone' (p. 8). Digital memory may indeed be continually emergent, but it is increasingly shaped by the socio-technical parameters of platforms.…”

“Loading, please wait” – Temporality and (bodily) presence in mobile digital communication

“…page rankings in search engines or recommendation lists in webshops (cf. Esposito, 2017). Here, the particular logic of communication and its decoupling from the subjective level become notably evident.…”