On the Origin of Synthetic Information by Means of Steganographic Inheritance
Quick Take
The article proposes a steganographic mechanism for tracing the lineage of synthetic information, akin to genetic inheritance. This method allows for the extraction and comparison of hidden traits from AI-generated offspring, enhancing the understanding of their origins and impacts on society. Empirical evaluations confirm the viability of this approach across various processing operations.
Key Points
- Introduces a steganographic method to trace synthetic information lineage.
- Enables extraction of hidden traits from AI-generated offspring.
- Empirical evaluations show viability across various processing operations.
- Highlights the moral implications of synthetic information on society.
- Compares traits against a reference pool for parentage identification.
Article Content
From source RSS / original summaryarXiv:2605. 27551v1 Announce Type: new Abstract: The origin of species has been the mystery of mysteries in natural science. By analogy, the origin of synthetic information, we suggest, is the mystery of mysteries in information science. The question carries a moral weight that a technical account can neither fully resolve nor responsibly ignore, as its impact on truth, trust, and human intellect extends deep into the broader economy and society.
The very power of artificial intelligence makes the evolutionary lineage of synthetic information grow ever harder to trace, for a sufficiently capable model may generate offspring that bear little resemblance, at either the structural or signal level, to the parent source from which they were derived. As in genetics, two individuals may share the same phenotype mirroring each other in outward appearance, yet differ fundamentally in their genotype.
We propose, by means of steganography, a mechanism analogous to heredity. At the moment an offspring is reproduced, a projector derives a trait from the parent, and a steganographic encoder invisibly hides it within the offspring. This trait persists throughout the offspring's life cycle in a cyber ecosystem. When parentage is queried, a steganographic decoder extracts the trait from the offspring and compares it against the traits of candidate parents in a reference pool, thereby nominating the most likely one.
A theoretical analysis characterises phylogenetic accuracy as a function of projector and stegosystem properties, whilst empirical evaluations across multiple projectors and stegosystems demonstrate the viability of the proposed methodology under a broad spectrum of processing operations and semantic modifications. We envision a cyber ecosystem in which synthetic information, endowed with hidden yet traceable lineage traits, branches from a simple beginning into endless forms that have been, and are being, evolved.
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