Observed Signal · Feb 18, 2026 · Brand Safety Strategy · Source: AdExchanger · Impact: 2/5 · Sentiment: Positive
Star Tribune Balances Reporting and Advertiser Trust Amid Controversy
The Minnesota Star Tribune balanced aggressive reporting on ICE and CBP actions with proactive brand-safety steps to protect advertiser relationships and revenue. Brian Kennett, VP and head of digital advertising and agency services, says the publisher paused direct campaigns on especially sensitive breaking-news pages, used keyword filters and Slack alerts, and is developing AI-driven sentiment analysis (with an OpenAI grant) as part of a three-layer system that includes human review. The paper’s diversified demand mix—about 80% digital revenue, a 60/40 split of direct vs. indirect on its site, large national/regional advertisers, and a substantial agency-services business—helped offset local revenue declines. The Star Tribune finished January up year‑over‑year in revenue and reports a 92% client retention rate, underscoring how brand-safety processes, first‑party data use and demand diversification support local journalism during sensitive coverage.
Practical publisher case study showing how brand-safety protocols, demand diversification and nascent AI sentiment tools can preserve revenue and advertiser relationships during sensitive news coverage; informative to publishers and ad buyers but not industry‑shifting.
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Key Takeaways & Evidence Grounding
- Minnesota Star Tribune paused direct advertiser campaigns on pages with especially sensitive breaking coverage.
- About 80% of the Star Tribune’s advertising revenue is digital; print accounts for roughly 20%.
- On StarTribune.com, revenue mix is approximately 60% direct and 40% indirect/programmatic.
- The Star Tribune is developing AI-driven sentiment analysis tools funded by an OpenAI grant to augment brand-safety decisions.
- Brian Kennett manages about $40 million a year in client ad spend and reports a 92% client retention rate.
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Related Market Signals & Shifts
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Fired OpenAI Researchers Dispute Misconduct Claims, Warn of Chilling Effect
Three OpenAI safety researchers, Jasmine Wang, Tomek Korbak, and Mikita Balesni, who were fired last week, have published an open letter denying allegations of mishandling sensitive information. They warn that their dismissal creates a chilling effect that stifles AI safety work and open dialogue within the company. The researchers say they acted in good faith and within company norms, and that the reasons for their firing are unclear. They urge OpenAI to uphold its commitments to third-party safety auditors and maintain a transparent culture. OpenAI responded with an internal memo denying retaliation and stating that employees are not terminated for raising concerns, but did not address specific policy violations or circumstances of the dismissal. The dispute highlights tensions between internal safety research and company communication policies at a time when OpenAI faces scrutiny over safety incidents.
Ben Affleck's AI Knowledge Goes Viral
Ben Affleck, the actor who sold his AI filmmaking startup to Netflix for a reported $587 million, has gone viral for demonstrating deep understanding of AI technology in recent interviews. He discussed machine learning, neural networks, and even admitted to writing Python scripts. Affleck detailed his journey from analog to digital film, his use of AI in visual effects, and his creation of a proprietary dataset for ethical AI filmmaking. He also visited OpenAI and used his celebrity status to access emerging tech. Affleck addressed AI's potential, expressing concerns about its effect on education and learned helplessness rather than existential threats. He used AI in his movie 'Animals' and emphasized the additive nature of AI in filmmaking.
AI Leaderboard Arena Raises $200M at $3.1B Valuation
Arena, the AI leaderboard platform that originated as a UC Berkeley research project, has raised a $200 million Series B round at a $3.1 billion valuation. The round was led by Lightspeed Venture Partners and Khosla Ventures, with participation from Salesforce Ventures, 01 Advisors, Dell Technologies Capital, Endeavor Catalyst, a16z, Felicis, and others. This follows the company's announcement in June that it reached $100 million in annualized run-rate revenue. Arena provides a crowdsourced platform where users rate AI model outputs, and it has introduced a commercial product called AI Evaluations to offer detailed performance analytics. The company has also added a new 'alignment' category to its leaderboard, ranking models on issues like unauthorized actions and deceptive completion. Arena's valuation has nearly doubled in about 10 months, from $1.7 billion post-money in January to $3.1 billion now.
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