Undeciphered Code: Indus Script and Information Without Key

Approximately 400 symbols appear on Indus Valley seals, pottery, and tablets—too many for a simple alphabet, too few for a complete logographic system. For 4500 years, these marks have resisted decipherment. The information exists: inscriptions survive on durable materials, statistical patterns can be measured, symbol frequencies tabulated. Yet meaning remains inaccessible. This presents a fundamental problem in information theory: data without a decoding key is indistinguishable from noise.

Entropy Without Context

During my cryptanalysis work in World War II, I learned that even theoretically perfect ciphers like one-time pads become vulnerable when patterns emerge—when keys get reused or when underlying language structure leaks through encryption. But the Indus script presents a harder challenge: we lack the basic decoder ring. No bilingual text exists, no Rosetta Stone equivalent. The civilization vanished around 1900 BCE during the 4.2 kiloyear climate event, leaving no descendant languages to provide phonetic clues.

Entropy measurements can detect structure—distinguish random symbols from language with grammar and redundancy. The Indus script shows intermediate complexity, neither purely random nor clearly structured. But statistical analysis alone cannot reveal meaning. Information theory quantifies uncertainty reduction, measures how much selection narrows possibility spaces, yet you need a channel between sender and receiver. When civilizations collapse and contexts disappear, the channel breaks. Climate shocks disrupted Indus trade networks; rivers shifted; urban centers depopulated. Information requires continuity. Dead languages become unreadable without cultural transmission to preserve the mapping between symbol and meaning.

We cannot even confirm whether these symbols constitute writing. They might be numerical notations, religious markers, proprietary seals for trading families. The ambiguity itself carries information—about our limits, about what gets lost when societies fragment. Elite competition and generational tensions may have weakened social cohesion before the environmental crisis struck. By the time drought accelerated decline, whatever knowledge preserved these symbols’ meanings had already begun dissolving.

Representations That Resist Decoding

Modern neural networks create similar opacity. Intermediate layers transform inputs through learned geometric spaces—mapping coordinates to plane heights, folding dimensions through ReLU activations, constructing representations where complex patterns become linearly separable. These activation vectors contain information, measurably so. Yet what do they represent?

Feature visualization attempts decipherment: probe the network with carefully chosen inputs, interpret activation patterns, search for semantic meaning in abstract spaces. Some neurons respond to edges or textures. Others exhibit polysemantic behavior—activating for seemingly unrelated concepts through superposition. Many representations remain fundamentally alien, optimized for task performance rather than human interpretability.

The parallel is precise. Information exists in both cases. Entropy can be measured. Statistical patterns can be quantified. But without the key—phonetic values for ancient symbols, semantic mappings for neural activations—we face encrypted messages that resist interpretation. The Indus script died with its civilization. Neural representations emerge from training distributions that may become extinct as data shifts, leaving future researchers puzzling over activation patterns as archaeologists puzzle over seal inscriptions.

Information theory defines information as selection that influences receiving minds. But influence requires a shared context, a common channel. When that channel breaks—through climate collapse, cultural discontinuity, or architectural opacity—information persists as pattern without meaning. We can measure its existence. We cannot yet decode it.