Governors association partners on $1M AI workforce project 27%

By Colin Wood46%

8/3/2026, 12:24:01 PM

BS Summary: This article contains 15 faulty reasoning types, including Optimism Bias, Appeal to Authority, and Recency Bias, with Attempt to Sell a Product or Service as the most egregious example at 25.7% saturation with 86 hits. Analysis detected 538 faulty-reasoning hits from 334 analyzed words, generating a BS Score of 31.6% and a BS Rank of 27% (21,767 of 29,795 articles). This article is better (less manipulative) than 73.10% of the article peer group.

The National Governors Association on Friday announced a new partnership with RAISE US, a nonprofit workforce initiative launched in June by two former governors, aimed at helping states develop effective AI workforce initiatives. 
According to a press release, the new, $1 million project will “identify and amplify new policy models that help states design and pilot new corporate incentives to retrain and redeploy workers, support people through job transitions, and develop training models tied to real employer demand.” 
Gina Raimondo, the former Rhode Island governor who served as Joe Biden’s commerce secretary, who is also serving as RAISE US’ co-chair and chief executive, said in the release that workers need “a system” to succeed in a changing workforce. 
The two groups, she said, will combine their strengths to develop that system: “NGA has the relationships with governors, and RAISE US has the coalition, the data, and the proof points of what is working on the ground. 
Together, we will make sure that workers have access to the tools and the programs that give them a real shot at a good job in an AI economy.” 
Organizers said the group is working with governors in Arkansas, Connecticut, Maryland, and Utah to “reorient public workforce and education infrastructure for a shifting labor market,” through paid apprenticeships, short-term credential programs and incentive programs for employers designed to retrain workers. 
Eric Holcomb, a Republican who served two terms as Indiana’s governor, and the nonprofit’s co-chair, said in the release that “the best workforce ideas almost never originate in Washington. 
They first scale in a statehouse, or a community college, or an employer’s HR department. 
Then, they spread nationally because governors talk to each other and share what is working.” 
Regardless of where the group’s new workforce ideas originate, they will be disseminated from the nation’s capital: RAISE US has said it plans to publicize the results of its early work during the NGA’s winter conference, next February, in Washington, D.C. 
Article reasoning-pattern comparisonThis article: 8.7%Colin Wood: 2.4%StateScoop: 1.2%Confirmation Bias8.7%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.2%Anchoring Bias0.0%This article: 4.5%Colin Wood: 3.6%StateScoop: 2.6%Availability Heuristic4.5%This article: 0.0%Colin Wood: 1.8%StateScoop: 1.4%Representativeness Heuristic0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.2%Hindsight Bias0.0%This article: 0.0%Colin Wood: 2.1%StateScoop: 1.4%Overconfidence Bias0.0%This article: 12.0%Colin Wood: 1.9%StateScoop: 4.1%Framing Effect12.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.9%Loss Aversion0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.5%Status Quo Bias0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.3%Sunk Cost Effect0.0%This article: 22.2%Colin Wood: 3.1%StateScoop: 3.4%Optimism Bias22.2%This article: 0.0%Colin Wood: 2.9%StateScoop: 2.2%Pessimism Bias0.0%This article: 0.0%Colin Wood: 2.9%StateScoop: 4.6%Negativity Bias0.0%This article: 0.0%Colin Wood: 0.9%StateScoop: 0.4%Self-Serving Bias0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.3%Fundamental Attribution Error0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Actor-Observer Bias0.0%This article: 11.4%Colin Wood: 0.9%StateScoop: 0.5%In-Group Bias11.4%This article: 0.0%Colin Wood: 1.2%StateScoop: 0.4%Out-Group Homogeneity Bias0.0%This article: 11.4%Colin Wood: 4.2%StateScoop: 1.2%Halo Effect11.4%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Horn Effect0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Dunning-Kruger Effect0.0%This article: 12.3%Colin Wood: 3.2%StateScoop: 0.8%Recency Bias12.3%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Primacy Effect0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Blind-Spot Bias0.0%This article: 0.0%Colin Wood: 0.6%StateScoop: 0.1%Ad Hominem0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.1%Straw Man0.0%This article: 13.5%Colin Wood: 7.5%StateScoop: 1.9%Appeal to Authority13.5%This article: 0.0%Colin Wood: 0.0%StateScoop: 1.5%False Dilemma0.0%This article: 0.0%Colin Wood: 0.5%StateScoop: 0.4%Slippery Slope0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.2%Circular Reasoning0.0%This article: 8.7%Colin Wood: 6.3%StateScoop: 3.3%Hasty Generalization8.7%This article: 0.0%Colin Wood: 0.9%StateScoop: 0.2%Red Herring0.0%This article: 4.5%Colin Wood: 0.4%StateScoop: 0.3%Bandwagon4.5%This article: 0.0%Colin Wood: 5.1%StateScoop: 3.2%Appeal to Emotion0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.3%Begging the Question0.0%This article: 4.5%Colin Wood: 2.6%StateScoop: 0.8%Post Hoc (False Cause)4.5%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Tu Quoque0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.2%Burden of Proof0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Appeal to Nature0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Composition/Division0.0%This article: 4.5%Colin Wood: 0.9%StateScoop: 0.9%Anecdotal4.5%This article: 8.7%Colin Wood: 0.7%StateScoop: 0.2%No True Scotsman8.7%This article: 0.0%Colin Wood: 1.7%StateScoop: 1.0%Ambiguity (Equivocation)0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Middle Ground0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Personal Incredulity0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Special Pleading0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Genetic Fallacy0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 1.9%Unattributed Quote0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.6%Quote-first Misdirection0.0%This article: 0.0%Colin Wood: 1.0%StateScoop: 1.0%Biased Writer Voice0.0%This article: 8.7%Colin Wood: 1.9%StateScoop: 1.4%Indoctrination8.7%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Colin Wood: 0.0%StateScoop: 0.0%Politically Right Leaning Bias0.0%This article: 25.7%Colin Wood: 2.0%StateScoop: 0.2%Attempt to Sell a Product or S…25.7%

334 words analyzed.

Speakers

4speakers72%attributed speech94writer words
Selected voice

Eric Holcomb

100%flagged-word coverage
59 attributed words25% of attributed speech48% writer coverage
0%25.0%50.0%Attempt to Sell a Product -47.9 ptsWriter: 47.9%Eric Holcomb: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.