This is a collection of possible “new and revised” legislation that I’d like for our Missouri state representatives and senators to consider (Data Center issues are near the end).

• Balcony solar
• Ban Law Enforcement Masks (all persons wearing masks must be clearly labeled with an ID name/number)
• Deepfakes: see Chapter 1, “The New Age of Slut Shaming,” in “The New Age of Sexism: How AI and Gender Bias Are Reinventing Misogyny” (2025) by Laura Bates. https://amzn.to/4xoT1nUw
• Broken windows: Changes to legislation to speed up compliance process? City of Springfield has these changes in its legislative priorities list (community involvement committee, Callie Carroll).
• Ranked-Choice Voting
• Popular Vote Compact
• Proportional Representation
• Improve Campaign Finance Laws
• Fairer Income Tax: more progressive, higher ratesfor the 1%.
• ​Bar corporations from political donations (Hawaii model)
• ​End Gerrymandering – citizen-led neutral redistricting
• ​Auto loan APR cap: https://www.facebook.com/share/p/18xqQZernH/
• ​Abandoned housing: https://www.facebook.com/share/193ZqtdaJ7/
• ​Protect Knowledge – don’t allow deletion of archive data at state, local level
• ​Ban right-to-work rules
• ​Prioritize Climate Change, transition to cleaner fuels
• ​Mandate DNA evidence testing for possible exoneration of persons challenging convictions.
• Ban Warrantless Surveillance: “Private data and tracking shouldn’t be the price of driving down our streets. Let’s pass a statewide constitutional ban on Flock cameras and automated mass tracking tools unless backed by a proper search warrant.” (Greg W. Elder)
• Resource Reclamation & Citizen Sharing: “Missouri’s wealth, public lands, and natural resources belong to us. Let’s look at ways to share and protect our state’s bounty directly with Missouri citizens, rather than corporate extraction.” (Greg W. Elder)
• Protect the Initiative Petition: “The legislature shouldn’t be able to overturn or gut the will of the voters. Let’s make it harder for politicians to tamper with laws passed by the people.” (Greg W. Elder)
• Respect initiatives: Require supermajority for any Legislative attempts to reverse citizen Amendments or initiatives (e.g. Amendment 3 in 2026, wage sick leave in 2024).
• Limit PAC & Special Interest Money: “Real representation means politicians answer to their constituents, not out-of-state donors. Let’s severely limit or eliminate PAC money—from groups like AIPAC and other heavy-hitting special interests—from buying influence in our local elections.” (Greg W. Elder)
• “Regular 20-Year Citizen Reviews & Ethics Reform: Let’s institute mandatory citizen-led check-ins every two decades to modernize our constitution, end dark money, and ban politicians from becoming lobbyists the minute they leave office.” (Greg W. Elder)
• Voting & Voter Registration:
• ​No sharing of voter lists with USPS & Feds.
• ​Do not honor any biased/fabricated requests to de-register legitimate citizens.
• Restrict presence of ICE at polling places. (Maybe?) bar masks in polling places.

AI/algorithmic discrimination:

• See Chapter 7,”The New Age of Discrimination,” in “The New Age of Sexism: How AI and Gender Bias Are Reinventing Misogyny” (2025) by Laura Bates. https://amzn.to/4xoT1nU
• Require that all algorithms be evaluated and scored based on specific, known biases; bar the use of known-biased training data.
• ​Hiring: Bar the automation of discrimination by age, race, gender. (Known biases: blocking all resumes showing a college graduation date > 10 years ago; using past-reject applicant data to automatically filter out candidates by race or gender)
• ​Facial recognition: Known biases: (such as training data of “criminals” with an unfair proportion of black people due to discriminatory arrest, charging, and prosecution histories; vastly different accuracy and false-positive rates for black women)
• ​Education: Algorithms used for evaluation, feedback, assessment & scoring must be validated. Any AI used in the classroom (by students or faculty) must be evaluated for bias.

Data centers, Planning Process

• ​Non-Disclosure Agreements: Prohibit city staff from signing, release any data disclosed under NDAs that should be public.
• Data center transparency (owner/operator), including prohibitions of assignment of responsibilities to new/different entities without bond & proof of adequate capital & insurance.​
• Data Center Issue Checklist?
• Data center legislation: https://www.techpolicy.press/data-center-discontent-drives-state-legislation-surge/
• Data Centers – analysis by Mark J. Welch: https://www.markwelchblog.com/2026/08/15/data-centers-analysis-by-mark-j-welch-aug-2026/
1. Enron. That’s the most important keyword when evaluating AI data centers. https://en.wikipedia.org/wiki/Enron_scandalHow many of the hyperscale data centers are owned, operated, controlled and contracted entirely through Enron-style style LLC & REIT shell companies, which could default on all environmental, power, water & community commitments?
2. “Why Big Tech’s AI Spending Is $3 Trillion Higher Than It Seems: Massive spending commitments for
   data-center leases and chips aren’t shown on companies’ balance sheets” (Wall Street Journal, Aug. 16, 2026) https://www.wsj.com/tech/ai/why-big-techs-ai-spending-is-3-trillion-higher-than-it-seems-e1067bb2
3. Do not rely on names of “ultimate customer(s).” It is critical to understand that all the big-tech companies are customers, investors, guarantors, and competitors of each other. (Facebook/Meta Apple Amazon Nvidia Google/Alphabet Microsoft Oracle OpenAI Anthropic etc.). The US government now also holds equity in some of these companies. Who is promising what, to whom?
4. Who is: the legal property owner; tenant; sub-tenants; customer(s); lenders; guarantors; insurers.
5. What happens when someone attempts to shift ownership/control/liability to different entities?
6. No government officials or employees should sign any non-disclosure agreement (NDA). Do not allow the applicant/operator to conceal information as “proprietary.”
7. What insurance & bond requirements, legal liability, hold-harmless demands? Who can enforce?What happens if facility fails to renew bond, insurance?
8. What if the facility defaults on payment of utility bills, taxes, etc.?
9. Government must clearly ask about all infrastructure requirements for the intended use of the property, during planning + construction (phases) + startup + operation. Overhead wiring, trenching for pipes and conduit, water supply and discharge, drainage, grading, permanent and temporary roadways for construction.
10. What services are required but conditional?
11. Anticipate shutdown/closure options (recycling, ewaste, clearing/cleanup, etc.)
12. What specific monitoring and supervision is required?

Some other data-center-related documents to review:

1. “Local Guidelines for Data Center Development” (Urban Land Institute Data Center Product Council; Hannah Miet) https://knowledge.uli.org/-/media/files/research-reports/2024/uli-data-center-whitepaper_hm_2024-11-12_final-final-round.pdf
• ​​p.7-8: Reasonable explanation of the difference between data center types (corporate/enterprise, colocation/retail, wholesale, telecom, and hyperscale).
• ​​p.15: “Power purchase agreements (PPAs): long-term contracts with renewable energy providers (the sellers) to purchase electricity from specific wind or solar farms.”
• ​​p.17 and 21: Sound mitigation
• ​​p.19: “Regulations developed for office or warehouse uses often impose excessive parking and plumbing fixture counts on data centers, which necessitate variances and complicate the planning process.” Yes, but: what if the property is later converted to a different use?
• ​​p.19: Fire Department considerations: Battery fires? Diesel fuel storage; generators.
• ​​p.26: Glossary of terms.
2. “AI Infrastructure Community Evaluation Framework (AICEF)” (appears to be a crude AI-generated template; the checklist on page 12 might be useful). https://www.lindenwood.edu/files/future-caucus/ai-community-evaluation-aicef3.pdf

Mark J. Welch is a former journalist, attorney, teacher, and data center salesperson. From 2011-2021, Mark worked for Hurricane Electric, which converted two former factories in Fremont, California into colocation data centers. HE is also one of the world’s largest global internet bandwidth providers, selling connectivity globally at 320 major exchange points and at telecom data center in more than 200 cities worldwide. https://pop.he.net/