Skip to main content

Reality Drift Frameworks: synthetic realness, filter fatigue, optimization trap, drift principle

Project description

Reality Drift

A contemporary framework for understanding how modern life feels fake, accelerated, and cognitively exhausting.
Includes concepts such as synthetic realness, filter fatigue, optimization trap, and the drift principle.


Overview

Reality Drift is not a software library in the traditional sense, but a living research package.
It documents and distributes frameworks that describe the subtle distortions of reality in the digital age.

This project makes the language of cultural drift accessible to researchers, educators, and anyone trying to navigate algorithmic culture.
It provides a shared vocabulary for understanding phenomena like fractured timelines, engineered authenticity, and algorithmic culture.


Core Concepts

  • Reality Drift – the sense of disconnection and distortion created by fractured timelines and synthetic media.
  • Synthetic Realness – engineered authenticity that feels “real enough” but hollow on closer inspection.
  • Filter Fatigue – the exhaustion of endless curation, optimization, and self-presentation in digital spaces.
  • Optimization Trap – when life becomes about gaming systems instead of experiencing meaning.
  • Drift Principle – cultural and cognitive systems tend toward distortion under algorithmic incentives.
  • Cognitive Drift – how AI reshapes thought patterns, memory, and identity through feedback loops.
  • Semantic Fidelity – how well meaning is preserved across translations, generations, and AI systems.

Resources


Citation

If you use this framework in research or discussion, please cite:

A. Jacobs. Reality Drift: Why Modern Life Feels Fake—and How to Feel Human Again.
Figshare. https://doi.org/10.6084/m9.figshare.30445331.v1

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

realitydrift-0.1.0.tar.gz (2.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

realitydrift-0.1.0-py3-none-any.whl (3.0 kB view details)

Uploaded Python 3

File details

Details for the file realitydrift-0.1.0.tar.gz.

File metadata

  • Download URL: realitydrift-0.1.0.tar.gz
  • Upload date:
  • Size: 2.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.5

File hashes

Hashes for realitydrift-0.1.0.tar.gz
Algorithm Hash digest
SHA256 01b7c9b9c4798c04f8dcf29487f3f35c501e92eeeb6c204f02b49805b899210b
MD5 954739e81d57ee19ff997a3c710e889d
BLAKE2b-256 45537b7213596b41f845e9ed0dca333dfd3244636ce0fd69abb11ebe8802732e

See more details on using hashes here.

File details

Details for the file realitydrift-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: realitydrift-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 3.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.5

File hashes

Hashes for realitydrift-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 216848c877ffb761d52c22974278dccdb30aad8961a1bba8c303b131bc2d30f8
MD5 2fc0d5ab084feab6f20980d399864030
BLAKE2b-256 2126d56d7eb3ebb27061b1de0141daea06e9c5e8d7fa3f6ffddbf3dc233d5a72

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page