A New Red Line for Crypto? Washington Targets On‑Chain “Death Bets” In Prediction Markets

bitcoinistPublicado em 2026-03-11Última atualização em 2026-03-11

Resumo

A new U.S. bill called the DEATH BETS Act, introduced by Senator Adam Schiff and Representative Mike Levin, aims to explicitly ban prediction market contracts related to terrorism, assassination, war, or an individual’s death on CFTC-regulated platforms. The legislation responds to concerns over platforms like Kalshi and Polymarket offering contracts tied to events such as assassinations, military actions, or political removals. Critics argue these markets allow unethical profiting from real-world violence and human suffering. If passed, the law would push such trading to unregulated offshore platforms while allowing conventional prediction markets (e.g., elections or economic data) to continue. The move signals broader regulatory scrutiny over what crypto-based prediction markets can offer.

A Democratic U.S. Senator from California is introducing new legislation targeting crypto‐driven prediction markets

An Act Against Death

On March 10, Democrat U.S. Senator Adam Schiff (California) and Representative Mike Levin (CA-49) introduced the DEATH BETS Act, a bill aimed explicitly at banning prediction market contracts tied to terrorism, assassination, war or an individual’s death on any platform registered in the Commodity Futures Trading Commission (CTFC). This includes regulated venues like Kalshi or Polymarket’s newly U.S. licensed arm, plus other designated contract markets (DCM) that list event contracts via brokers.

The current law, the Commodity Exchange Act, gives authority to the CFTC to bar contracts tied to terrorism, war or assassination if they are deemed to be “contrary to the public interest”. Schiff’s proposed bill would revoke such flexibility: the senator argues that the agency has too much discretion as it rewrites prediction‐market rules under Chair Mike Selig:

At a time when CFTC Chair Selig has indicated that he will rewrite the rules on prediction markets, the CFTC can no longer be granted this discretion. The DEATH BETS Act will unequivocally ban these contracts.

The DEATH BETS Act And The Crypto World

The proposed bill follows the Senate Democrats pressure to the CFTC to “halt prediction contracts that involve betting on physical injury, death or war”, as stated on a letter sent to Chair Michael Selig in February 23. The letter specifically quotes Polymarket’s on-chain “dangerous prediction contracts” on whether the Artemis II would explode, if Venezuela’s former regime head Nicolás Maduro would be removed from power and if Ukraine’s Myrnohad would be captured by Russian forces.

“The Wild West”

In Senator Schiff’s words, the prediction markets have turned into “the Wild West”:

There is no justification for gambling on lives, or public benefit to be derived by such a market. With regulators turning a blind eye, prediction markets have rapidly become the Wild West.

Now, the Iran war episode takes the spotlight, as the Senator’s office highlights that a bet on whether Iran’s Ali Khamenei would be “out as Supreme Leader” had $54 million in trading volume on Kalshi before it was paused. There are hundreds of millions in Iran‐related bets, with a reported 10 wallets making over $1.2–1.4 million in profit right before U.S. strikes.

Rep. Levin stressed the importance of not letting “someone make money off the outbreak of war or the deaths of American service members”.

We already saw what that looks like: over half a billion dollars was wagered on the timing of U.S. military strikes on Iran alone. That is unacceptable, and this legislation puts a stop to it.

What The DEATH BET Act Means For Traders

Under the DEATH BET Act, CFTC‐supervised platforms will likely become safer but more limited, while riskier war/death flows are pushed further into offshore or permissionless crypto venues, where legal and reputational risks spike. Bets on elections, inflation points and macro data will continue to be safe game, but Washington aims to draw the line on banally “gambling” with the lives of real people.

The DEATH BET Act isn’t a ban on crypto prediction markets, but it is a signal that the next regulatory battles in crypto won’t just be over Bitcoin or ETFs: they’ll be over what the industry considers acceptable to let people bet on.

BTC’s price trends to the downside on the daily chart. Source: BTCUSDT on Tradingview

Cover image from Perplexity, BTCUSDT chart from Tradingview

Perguntas relacionadas

QWhat is the main purpose of the DEATH BETS Act introduced by Senator Schiff?

AThe DEATH BETS Act aims to explicitly ban prediction market contracts tied to terrorism, assassination, war, or an individual's death on any platform registered with the CFTC.

QWhich specific examples of prediction contracts did Senate Democrats cite in their letter to CFTC Chair Michael Selig?

AThe letter cited Polymarket's on-chain contracts on whether the Artemis II would explode, if Venezuela's Nicolás Maduro would be removed from power, and if Ukraine's Myrnohad would be captured by Russian forces.

QHow does Senator Schiff characterize the current state of prediction markets in his statement?

ASenator Schiff characterized prediction markets as 'the Wild West' where regulators have been turning a blind eye to gambling on lives.

QWhat significant trading activity was mentioned regarding Iran-related prediction markets?

AA bet on whether Iran's Ali Khamenei would be 'out as Supreme Leader' had $54 million in trading volume on Kalshi before being paused, with reported profits of $1.2-1.4 million for some traders before U.S. strikes.

QWhat will be the practical effect of the DEATH BET Act on trading platforms according to the article?

ACFTC-supervised platforms will become safer but more limited, while riskier war/death betting will be pushed to offshore or permissionless crypto venues, increasing legal and reputational risks there.

Leituras Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHá 1h

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHá 1h

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHá 1h

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHá 1h

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHá 1h

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHá 1h

Trading

Spot
活动图片