The Democratic Socialists of America (DSA) candidates running for the House of Representatives and endorsed by NYC Mayor Zohran Mamdani are all but guaranteed to win their general elections this November, but that does not mean the midterm drama is over in New York. In the state's 17th congressional district, which includes the lower Hudson Valley, Democratic challenger Cait Conley, a combat veteran who served on the Biden administration's National Security Council, could unseat incumbent Republican congressman Mike Lawler in one of the most consequential races of the midterms. 

The highly contested purple district voted for former Vice President Kamala Harris in the 2024 election while reelecting Lawler for his second term. Now, Lawler is attempting to win a third term as support for President Donald Trump wanes ahead of the midterms. As of Friday, The Cook Political Report lists the race, which could determine control of the House, as a toss-up. 

If elected, Conley would have far more in common with the "Badass Women" coalition of security state and military veterans than with DSA types (think more Sen. Elissa Slotkin from Michigan than Darializa Avila Chevalier). As Judge Street Journal's Timmy Facciola notes, "Conley's candidacy is testing the viability of a tactful centrism that rebukes left-wing positions like abolishing ICE or restricting weapon shipments to Israel." Lawler is also vying for moderates, pitching himself as "one of the most bipartisan members of Congress" and emphasizing his willingness to break with Trump occasionally while still welcoming Trump's support. 

While Lawler and Conley certainly are not pure MAGA acolytes or DSA members, both have leaned into a tech-critical position, much like that of more radical populists like Lina Khan or Steve Bannon, revealing how pervasive anti-tech sentiment has become in mainstream politics. 

This tech skepticism was on full display during an October 14 debate, when each candidate made the case for why they were the most equipped to regulate AI, insisting that the industry needs guardrails. 

Conley said members of Congress do not want to regulate AI because "they want to look out for their billionaire and trillionaire backers like Elon Musk, who is pouring over $260 million into this midterm election." She then added that Musk backed Lawler in his 2024 race. 

Lawler then accused Conley, who previously consulted for Primer AI, of being "the AI candidate for the AI industry."

While Lawler and Conley disagree on specific data center regulations (Conley supports Democratic Gov. Kathy Hochul's data center moratorium while Lawler supports local zoning control over data centers), neither wants to pitch themselves as an explicitly pro-data center candidate. During the debate, Conley claimed that, "On Mike Lawler's watch there have been five data centers built in Rockland County." Lawler has said that he had no say in the decision to build the data centers, and during the debate, he pointed out that the facilities were built for financial services. Lawler also attempted to attack Conley over data centers, slamming her in an ad for saying "we need data centers." Regardless of the candidates' specific policies on data centers, their attacks on one another demonstrate that cheerleading hyperscale data center development is a political liability. In their district, data center has presumably become a dirty term. 

The candidates' tech-skeptical rhetoric did not end with unchecked data center development. After the debate, Reason asked both candidates about their positions on age-verification laws for social media and AI, since such regulations raise significant privacy and censorship concerns by age-gating the internet. Unsurprisingly, both Lawler, who voted for the controversial KIDS Act, and Conley, who has proposed stricter age verification for AI tools, parroted platitudes about why such online safety regulations are necessary to protect children. 

"We have watched how social media is literally hurting the mental health of children," Conley told Reason. "And when you talk about the power of AI and what that power could do, we have to regulate this." 

Lawler gave a similar response, telling Reason that he respects free speech but that protecting children "is paramount." 

This bipartisan consensus over social media regulation has long been brewing in Congress. The mainstream political conversations about AI and data centers, however, are relatively new this midterm election cycle. And it appears both Lawler and Conley have figured out which way Americans' sentiment toward AI is leaning, and they have waged their campaigns accordingly. 

The post Nobody Wants To Be the Pro-Tech Candidate in This New York Race That Could Flip the House appeared first on Reason Magazine.

Azeem Azhar and Paul Kedrosky debate the case for and against an A.I. bubble.

© The New York Times

"We are racing, and the question is how do we put barriers? So if a car was to fly out it doesn't kill people," IMF Managing Director Kristalina Georgieva said.

The Fields Medalist Terence Tao is on the front lines of a debate about artificial intelligence and the future of his field.

© Ariana Drehsler for The New York Times

As a free speech absolutist, Elon Musk is making a mistake going after Nitter, says Dr R P. He should instead be praising the site that helps users speak freely, uninhibited by login screens that undermine their privacy.

The post Musk’s Perplexing Battle With Nitter and the Problem With Locking the Internet Behind Login Screens appeared first on The Daily Sceptic.

“I felt like there were some moments in the film where she was just brazenly lying.”

© Photo Illustration by The New York Times; Image: Philip Cheung for The New York Times

Plus, the Friday news quiz.

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Republicans have used A.I.-generated content more often than Democrats, ranging from subtle enhancements to convincing deepfakes.

© The New York Times

A European Commission survey has found widespread adoption of artificial intelligence among smaller businesses, but considerable reluctance to allow automated systems to make decisions about employees. The findings expose a growing divide between technological investment and confidence in workplace automation.

Artificial intelligence is becoming established across European businesses, but almost half of companies remain unwilling to trust automated systems when decisions concern their employees, according to a European Commission survey published on 14th October.

The Eurobarometer findings show that 42 per cent of the small and medium-sized enterprises and mid-cap companies surveyed already use artificial intelligence or algorithmic management systems, although most deployment remains limited or experimental. A further 21 per cent intend to introduce such technologies in the future.

Despite this expanding adoption, 49 per cent of respondents said they did not trust artificial intelligence or automated systems to make staff-related decisions. The figures suggest that companies increasingly distinguish between using technology to improve business processes and delegating managerial responsibility to software.

The Commission’s survey of European businesses was conducted between March and April 2026, involving approximately 12,826 telephone interviews with company leaders across the EU’s 27 member states.

Businesses prefer assistance to automation

The survey provides a more detailed picture of workplace AI than conventional statistics measuring whether companies have adopted the technology.

Among the businesses interviewed, customer service and client relations were the most commonly reported areas of application, accounting for 47 per cent. Monitoring employee performance and productivity accounted for 36 per cent, while logistics, planning and staff scheduling represented 30 per cent.

These functions differ substantially in their consequences for workers and managers.

A system that helps organise deliveries or forecasts customer demand may improve efficiency without directly determining employees’ working conditions. Software that evaluates performance, allocates shifts or recommends staffing changes can influence employment decisions and requires a different level of organisational supervision.

The survey found that 61 per cent of companies considered AI useful in supporting decisions. However, human involvement remained central: 90 per cent of respondents reported that people continued to make decisions, while fully automated decisions accounted for only 2 per cent.

The results undermine the assumption that adopting AI necessarily means transferring control of business operations to autonomous systems.

For many companies, the immediate commercial value lies in processing information more rapidly, identifying patterns and reducing administrative workloads rather than removing human management entirely.

Investment costs remain a substantial barrier

Financial and organisational obstacles continue to limit adoption.

Half of the companies surveyed cited high investment costs, while 49 per cent identified legal uncertainty and 48 per cent pointed to insufficient expertise.

These findings are particularly relevant to small businesses, which frequently lack dedicated technology teams, extensive data infrastructure or the resources to evaluate complex software systems independently.

For such businesses, purchasing AI tools is only one component of the investment. Implementation can also require employee training, changes to internal procedures, data-security assessments and continuing technical support.

The findings add a workplace dimension to concerns raised in EU Today’s earlier examination of Europe’s AI productivity gap, which identified investment, computing capacity and organisational restructuring as obstacles to translating adoption into higher productivity.

A company may purchase sophisticated software without necessarily achieving corresponding improvements in performance. Those improvements depend on whether the technology is integrated into everyday operations and whether employees have the skills to use it effectively.

Brussels prepares further workplace legislation

The survey arrives while the European Commission is considering additional rules on algorithmic management through its proposed Quality Jobs Act.

The initiative is intended to address working conditions, workers’ rights and the increasing use of automated systems in managing employees.

A consultation launched in July asked European employers and trade unions to consider transparency in automated decisions, excessive workplace monitoring and the responsibilities of companies using AI.

The second consultation phase ended in September, allowing social partners to propose negotiated arrangements before the Commission determines its next legislative steps.

The broader regulatory framework is already changing. As EU Today explained when the AI Act entered a new enforcement phase, Brussels has begun enforcing certain obligations for general-purpose AI models, while important requirements for high-risk applications, including employment-related systems, follow a later timetable.

Stand-alone high-risk systems are scheduled to face the relevant obligations from December 2027, with another deadline in August 2028 for high-risk systems embedded in regulated products.

The distinction matters for employers planning investments today. Existing data-protection and employment obligations continue to apply, but some of the AI Act’s more specific compliance requirements remain subject to transition periods.

The Commission’s latest survey indicates that businesses are already exercising caution independently of these future obligations. Their reluctance to automate sensitive staff decisions suggests that accountability, reliability and employee confidence will remain important factors in determining how extensively artificial intelligence is deployed.

For Brussels, the challenge is to establish workable rules for that transition without making implementation prohibitively expensive for smaller companies, which account for much of Europe’s employment and commercial activity.

This week on “Uncanny Valley,” we dive into an unexpected Muse feature, shadowy spending from the largest pro-AI super PAC, and men’s tendency to lie about how much they know about AI.

Powerful AI models continue to cause chaos, but their targets aren’t widely seeking justice. Instead, they’re being encouraged to adopt those same tools.