Balaji Says ‘Zcash Or Communism’ As He Warns AI Supercharges Surveillance

bitcoinistPublished on 2026-02-20Last updated on 2026-02-20

Abstract

Balaji Srinivasan argues that the rise of AI-powered surveillance creates an urgent need for financial privacy, framing the choice as “Zcash or communism.” He warns that AI enables any state or individual to compile extensive personal dossiers from online data, surpassing historical surveillance capabilities. Encryption, particularly through Zcash, is presented as a critical defense, making individuals “sovereign” and invisible to targeting. Srinivasan also positions Zcash as a scalable, privacy-focused blockchain with Solana-like throughput, using zero-knowledge proofs for private transactions. He suggests Zcash can coexist with transparent chains like Bitcoin, serving different needs while addressing the growing threat of AI-driven wealth seizure and control.

Balaji Srinivasan is once again making the most provocative version of a privacy argument and he’s pinning it to a specific chain: Zcash. In a Feb. 18 video shared on X, Srinivasan framed the stakes in stark terms: “The choice is clear. It’s Zcash or communism,” tying the rise of AI-enabled surveillance to what he described as a renewed appetite for wealth seizure.

In a follow-up post, he argued that AI has shifted surveillance from a state-scale project to something closer to an on-demand service. “Any scrap of information online can now be integrated, digested, and synthesized...by any state or stalker capable of running an AI model...to form a dossier more complete than anything the Soviets could ever dream of,” he wrote.

Srinivasan’s prescription was blunt: “There will be no single silver bullet. But anything you haven’t encrypted can and will be used against you.”

Srinivasan anchored his “communism requires surveillance” claim in an historical example meant to make a modern point about data exhaust. “In 1918, in the midst of the Bolshevik Revolution, Lenin gave an order to murder 100 nearby ‘kulaks,’” he said, emphasizing that such an order “required a list”: names, locations, and a population that couldn’t easily move.

His argument is that the internet reverses that asymmetry if encryption becomes the default. “Today, neo-communism is rising once again. But the Internet could change the game,” he said. “No full list, if we encrypt it. No fixed location, either. They can’t hit what they can’t see.”

Those themes carried into a longer discussion on the Never Say Podcast, where Srinivasan connected privacy to basic operational freedom. “If you’re under surveillance, you’re not sovereign,” he said. “If every move is being tracked...you don’t have the advantage of surprise. You can never launch something. You can never have private deliberations.”

Arjun Khemani, a 19-year-old Zcash researcher on the episode, echoed the AI angle from the user side: “Especially with AI, being able to recognize where you are exactly...you can’t have freedom without privacy,” he said, arguing that broadcasting every transaction and context signal is “not... the world that I want to live in.”

Zcash As A Scaling Bet, Not Just A Privacy Stance

Srinivasan’s pitch wasn’t limited to privacy-by-principle. He positioned Zcash as a technical response to where he thinks the market has landed on scalability: on-chain throughput wins, and routing complexity loses.

Asked why “Zcash must scale” is a “moral imperative,” Srinivasan contrasted Bitcoin’s scaling reality: exchanges, custodians, and database entries with the decentralization promise many users think they’re buying. “Lightning...they’ve been saying, ‘Lightning is going to be there any day now’ for 10 years,” he said, arguing that real-world deployments tend toward “a hub and spoke topology” resembling traditional finance rails. “Within a bank, it’s fast...between banks, they do settlement,” he added, describing a dynamic he sees mirrored in major Lightning implementations.

From there, he argued crypto has effectively segmented into layers: Bitcoin for immutability and brand, Ethereum for programmability, and Solana for straightforward on-chain execution at scale. The opening he sees for Zcash is combining “Solana-like scalability” with private transactions, leaning on zero-knowledge proofs as “compression technology” as much as secrecy. “It’s what a lot of people wanted Bitcoin to be,” he said.

Srinivasan also stressed that privacy doesn’t necessarily replace transparency, it complements it. He argued that Bitcoin’s public ledger can be a feature for proof-of-reserves narratives, while Zcash’s private-by-default design targets a different threat model. His bottom line is coexistence, not conquest: “It’s possible that Bitcoin... and Zcash coexist because Bitcoin is transparent and Zcash is private,” he said, while suggesting “this could be Zcash’s moment.”

At press time, ZEC traded at $259.18.

ZEC price remains below the 0.786 Fib, 1-week chart | Source: ZECUSDT on TradingView.com

Related Questions

QWhat is the main argument Balaji Srinivasan makes about the relationship between privacy, Zcash, and communism?

ABalaji Srinivasan argues that the rise of AI-enabled surveillance creates a stark choice: 'Zcash or communism.' He claims that communism requires extensive surveillance for wealth seizure and control, and that encryption, specifically through privacy-focused cryptocurrencies like Zcash, is the technological solution to prevent this by making individuals sovereign and their information private.

QHow does Srinivasan claim AI has changed the nature of surveillance?

ASrinivasan states that AI has shifted surveillance from a large-scale state project to an on-demand service. He argues that any state or individual with an AI model can now integrate, digest, and synthesize any scrap of online information to create a more comprehensive dossier than was ever possible before, surpassing even the capabilities of historical surveillance states like the Soviet Union.

QBesides privacy, what other technical advantage does Srinivasan attribute to Zcash?

ABeyond its core privacy feature, Srinivasan positions Zcash as a scaling bet. He argues it combines 'Solana-like scalability' with private transactions by using zero-knowledge proofs as a form of 'compression technology.' This addresses what he sees as the market's preference for on-chain throughput over complex routing solutions like the Lightning Network.

QWhat historical example does Srinivasan use to support his claim that 'communism requires surveillance'?

ASrinivasan uses the historical example of Lenin during the 1918 Bolshevik Revolution ordering the murder of 100 'kulaks.' He emphasizes that such an order 'required a list'—names, locations, and a population that couldn't easily move—to illustrate how surveillance is foundational to state control and seizure of assets.

QHow does Srinivasan view the potential coexistence of Bitcoin and Zcash?

ASrinivasan believes Bitcoin and Zcash can coexist because they serve different purposes. He states that Bitcoin's transparent ledger is a feature for narratives like proof-of-reserves, while Zcash's private-by-default design addresses a different threat model. His view is one of complementary coexistence, not conquest, suggesting 'this could be Zcash's moment.'

Related Reads

The Recursive AI Anthropic Warned About: Tian Yuandong's New Company Has Just Taken the "First Step"

Anthropic recently highlighted the rapid progress toward "recursive self-improvement," where AI systems autonomously design and train their successors. In response, Recursive Superintelligence, a new company co-founded by former Meta researcher Tian Yuan Dong, has publicly demonstrated its first step toward automating AI research. The company released a system designed to autonomously execute the full AI research cycle: generating ideas, implementing code, running experiments, and learning from results. It validated this approach by achieving state-of-the-art results on three diverse benchmarks: 1. **NanoChat Autoresearch:** Optimizing a small language model's validation loss under a fixed 5-minute GPU budget, improving upon the community's best result. 2. **NanoGPT Speedrun:** Reducing the time to train a GPT model to a specific loss on 8 H100 GPUs from 79.7 seconds to 77.5 seconds, beating a highly optimized, human-driven community effort. 3. **SOL-ExecBench:** Improving the overall score on NVIDIA's suite of 235 GPU kernel optimization tasks by 18%, closing the gap to the hardware limit. The system discovered novel optimizations in this highly specialized domain without direct human expertise. Recursive's system operates as a general framework, capable of parallel exploration and cross-task knowledge transfer while incorporating safeguards against reward hacking. The company, backed by $650M in funding and a star-studded team including Richard Socher and Alexey Dosovitskiy, aims to create AI that recursively enhances its own research capabilities. This development represents an early but concrete move toward a new paradigm where AI accelerates its own advancement. It occurs alongside Anthropic's warnings about the need for industry coordination and potential pauses when recursive self-improvement thresholds are reached, highlighting the dual trajectory of rapid technical progress and growing calls for careful stewardship.

marsbit4m ago

The Recursive AI Anthropic Warned About: Tian Yuandong's New Company Has Just Taken the "First Step"

marsbit4m ago

The Gold Buy-on-the-Dip Guide: Watch Interest Rates, Not Just War

"Gold Buying Guide: Focus on Interest Rates, Not Just War" Four months ago, gold buyers likely didn't anticipate buying at a peak that even a war couldn't sustain. After hitting a record high of $5,596 on January 29, gold entered a bear market just 91 days later, its fastest decline since 2008. A key trigger was the Fed's hawkish shift, highlighting that monetary policy, not geopolitics, is the primary driver. The article argues that the traditional "buy gold in turmoil" script has changed. While the US-Iran conflict initially boosted prices, the sustained rally in oil prices heightened inflation fears, forcing central banks to maintain or consider tighter policy. Since gold yields no interest, higher rates increase its opportunity cost, eroding its appeal. This dynamic was evident when gold fell sharply on May 18 despite positive peace talks, as lower oil prices eased inflation and thus rate hike pressures. The recent sell-off is also part of a broader market deleveraging. Correlations between gold, Nasdaq, and Bitcoin spiked as leveraged investors sold liquid assets to cover losses, creating a synchronized downturn. Historically, gold bottoms align with policy shifts, not conflict resolutions. The 2008 and 2022 bear markets ended with shifts to extreme easing and peak inflation expectations, respectively. For potential buyers, the author suggests monitoring three signals: 1) Peak interest rate hike expectations, 2) Reopening of the Strait of Hormuz (to ease oil/inflation pressure), and 3) A return to net inflows for Gold ETFs, indicating the end of forced selling. While predicting the exact bottom is impossible, the author's personal strategy involves scaling into a position across price levels like $4000, $3700, and $3500, committing no more than 30% of the intended total allocation initially, and adding the remainder only if key signals emerge. The core conclusion: In turbulent times, watching interest rates is more crucial than watching wars.

marsbit10m ago

The Gold Buy-on-the-Dip Guide: Watch Interest Rates, Not Just War

marsbit10m ago

Recent On-Chain Review: No Clear Narrative Under U.S. Stock Market Pressure, Just Hype

This article analyzes the current state of the Solana meme coin and community token ecosystem, highlighting a market caught between two dominant forces: attention-based PvP and a gradual return to community-centric projects. The first part explores the "Attention PvP" dynamic, where success is driven by celebrity endorsements, viral events, and speed. Examples include $JOTCHUA, which surged after its meme creator's social media activity, and $WORLDCUP, which outperformed a similar Base chain project ($PITCH) largely due to influencer support. The recent "pump.fun GO" feature, allowing bounty tasks for token promotion, is critiqued for fostering sensationalist and often negative stunts—like people getting token tickers tattooed on their bodies for rewards—reminiscent of old internet shock content. In contrast, the article points to a resurgence of organic, community-driven tokens that survive market volatility through strong holder bases and shared ideology, not just hype. Influencer Ansem is cited, arguing that durable meme coins rely on communities willing to endure losses and promote their core message daily. Examples given are older tokens like $neet (anti-work ethos), $troll, $buttcoin, and $triplet, which have maintained relative price stability. A prime example of this community-build model is the new project $KINS, the token for the browser-based MMORPG Kintara. Its success stems not from advanced graphics but from consistently delivering updates, fostering player trust, and creating genuine engagement (e.g., in-game economies, events, property auctions). It has attracted a growing player base and even notable KOLs as participants, demonstrating that sustainable growth can come from building trust rather than orchestrating pumps. The article concludes by questioning whether the market is ultimately a game of mutual trust or mutual deception, expressing hope that such reflection might lead to a healthier ecosystem.

marsbit10m ago

Recent On-Chain Review: No Clear Narrative Under U.S. Stock Market Pressure, Just Hype

marsbit10m ago

On-Chain Scene on Opening Day: $20 Billion Already Staked, How Do On-Chain Contracts Know Who Wins?

On the opening day of the 2026 World Cup, over $2 billion had already been wagered on just the "tournament winner" contracts on platforms like Polymarket and Kalshi. This article explores how these blockchain-based prediction markets actually function once the games begin. It breaks down the massive volume and explains how single-game and tournament-long contracts are priced, with values moving between 1-99 cents to reflect implied probabilities. A key mechanism highlighted is "elimination zeroing," where a team's "champion yes" contract immediately settles to zero once they are mathematically eliminated. The core technical question answered is: how does a smart contract "know" who won a real-world match? The answer lies in oracles. The article details two primary paradigms: UMA's "optimistic oracle" (used by most of Polymarket), which allows a challenge period after a proposed result, and Chainlink's multi-source data aggregation (used by FIFA partners like ADI Predictstreet), which automates settlement with minimal dispute windows. Finally, the article injects a note of caution, citing research estimating that a significant portion of historical trading volume on these platforms might be "wash trading" to inflate numbers. It concludes by contrasting the legal status of these "event contracts" under CFTC rules in the U.S. versus traditional, state-regulated sports betting. As the tournament progresses, the real-time operation of this multi-billion dollar machine—its settlements, eliminations, and underlying mechanisms—becomes a story as compelling as the football itself.

marsbit25m ago

On-Chain Scene on Opening Day: $20 Billion Already Staked, How Do On-Chain Contracts Know Who Wins?

marsbit25m ago

Trading

Spot
Futures
活动图片