Intelligent Assistive Technology Ethics for Aging Adults: Spiritual Impacts as a Necessary Consideration
Bibliographic record
Abstract
Potential spiritual impacts of Artificial Intelligence (AI) driven Assistive Technologies (AT) for older adults are absent in most ethics conversations. Intelligent Assistive Technology (IAT) is the term used to describe the spectrum of Assistive Technologies that use AI. In this theoretical essay, I begin by introducing examples of AT and IAT for older adults with age-related disabilities. I argue that spirituality is a marginalized value in ethics that must be considered if IAT ethics is to address the whole person. Some of the potential spiritual impacts of IATs will be suggested through engagement with three core spiritual needs. I ask how IAT might impact these three core spiritual needs. This is not meant to be an exhaustive study of the spiritual impacts of AT. Through the engagement of one approach to spiritual needs, this article proposes that IAT ethics issues intersect with the spiritual needs of aging adults and, therefore, that potential spiritual impacts ought to be addressed as part of IAT ethics for older adults.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".