Beyond the Clouds, Part 2: What Happens to the Files You Store in the Clouds When You Die?
Bibliographic record
Abstract
This paper considers what happens to users’ rights in relation to the digital files they have stored in the cloud when they die. It is based in part on a survey of the terms and conditions of popular consumer-facing cloud services. A minority of cloud terms of service explicitly exclude heirs inheriting rights to access files stored in the cloud. Most terms do not address the point directly, but instead exclude the assignment of users’ contractual rights and copyright licenses. As a result, these rights and licenses do not constitute things in action. We argue that such rights will therefore not form part of the user’s estate and so not be transmitted to his or her heirs when the user dies. Unlike for physical assets, heirs therefore lack a clear legal claim to recover a deceased’s digital files from the cloud, many of which may instead be lost or deleted. This paper considers the extent to which this outcome could be challenged under consumer protection law and whether the law should be amended so as to grant heirs rights of access to digital assets. The paper focuses on English law, while drawing on examples from Canada, the United States, Germany, France, and the Netherlands.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.023 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".