AI companies are spending millions to thwart this former tech exec’s congressional bid | TechCrunch

AI companies are spending millions to thwart this former tech exec’s congressional bid | TechCrunch

TechCrunch - AI 7 min read

About this article

A tech billionaire-backed super PAC is spending $125 million to undercut candidates pushing for AI regulation. New York's Alex Bores, a former tech executive himself, is one of them.

Loading the player…   If you’ve seen the recent ads attacking New York assembly member Alex Bores, you’ll know he used to work for Palantir, the AI company that’s powering the controversial raids and high-volume deportation efforts from U.S. Immigration and Customs Enforcement. The ads even accuse Bores of having made hundreds of thousands of dollars building the tech for ICE and “powering their deportations.” But that’s not quite the whole story. “I quit Palantir specifically over its work with ICE in 2019,” Bores told TechCrunch on last week’s episode of Equity.  Now he’s running for New York’s 12th congressional district, with Big Tech billionaires funding outside groups targeting his campaign.  The ads are funded by a super PAC called Leading the Future, which, ironically, has the backing of Palantir co-founder Joe Lonsdale, as well as OpenAI President Greg Brockman, VC firm Andreessen Horowitz, AI search startup Perplexity, and other Silicon Valley heavy-hitters. The PAC has raised $125 million to go after candidates in state elections that are introducing AI legislation and to support candidates with a light-to-no-touch approach to regulating AI.  “They have committed to spending at least $10 million against me…because they know I am their biggest threat in their quest for unbridled control over the American worker, over our kids’ minds, climate and our utility bills,” Bores said. “They’re targeting me to make an example of me.” He said his background working in tech...

Originally published on March 03, 2026. Curated by AI News.

Related Articles

[2603.14267] DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and Synchronization
Machine Learning

[2603.14267] DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and Synchronization

Abstract page for arXiv paper 2603.14267: DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and ...

arXiv - AI · 4 min ·
[2601.22440] AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations
Llms

[2601.22440] AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations

Abstract page for arXiv paper 2601.22440: AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Value...

arXiv - AI · 4 min ·
[2601.13622] CARPE: Context-Aware Image Representation Prioritization via Ensemble for Large Vision-Language Models
Llms

[2601.13622] CARPE: Context-Aware Image Representation Prioritization via Ensemble for Large Vision-Language Models

Abstract page for arXiv paper 2601.13622: CARPE: Context-Aware Image Representation Prioritization via Ensemble for Large Vision-Language...

arXiv - AI · 3 min ·
[2512.08777] Fluent Alignment with Disfluent Judges: Post-training for Lower-resource Languages
Llms

[2512.08777] Fluent Alignment with Disfluent Judges: Post-training for Lower-resource Languages

Abstract page for arXiv paper 2512.08777: Fluent Alignment with Disfluent Judges: Post-training for Lower-resource Languages

arXiv - AI · 3 min ·
More in Ai Safety: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime