An invitation to talk about AI usage

In the fall, I was talking about AI and data centers a lot. In those discussions, I always disclosed that I used AI tools in my personal life, in my work, and in this campaign. I promised at some point that our campaign would put out a statement about that usage. This is the beginning of that conversation.

Since the fall, the public conversation has switched from AI in general to data centers specifically, and as a result, I talk about my connection to AI tools less. I want to make sure people I am talking to now have the same clarity about my usage as people who watched our livestream in the fall. 

There is some inherent tension here–On the one hand, I am campaigning against the corporations that build AI data centers and the politicians that are in their pockets. On the other hand, I use the tools that rely on those data centers on a regular basis. 

I am not opposed to the concept of AI. I believe that we can have a form of AI that serves the people and not the corporations, and that runs on local, decentralized networks, and consumer hardware that people can afford. I talk about it here and here. I am opposed to the political economy of how these tools are built, how wealthy and powerful the corporations that develop them are, and the shameless politicians who work for them and not us. But these corporate technology tools are also ubiquitous and powerful, and helpful to a small campaign like ours. 

This statement is not an attempt to resolve that contradiction, but rather an invitation to discuss it.  

Work and Career

About a year ago I was laid off from my job at the Nielsen company, a place I had worked for nearly 15 years. I started on the call center floor and moved up to a role in data, analytics, and automation. It started as an entry level job and ended as a career that provided the majority of the income for our household. 

By 2019, AI was starting to creep into regular discussion and I was warning my co-workers that we better be ready. By 2023, private equity had purchased the company and began round after round of layoffs. Each of us who wanted to keep our job were told that we needed to embrace AI and learn new ways to operate. 

By 2025, we had embraced AI and found new ways to operate, but the layoffs came for my team anyway. AI was spreading across the company and more and more long-time employees were being cut in favor of AI and lower-paying roles. I am not a bystander to this industry–I am one of the people directly impacted by it.

I spent much of 2025 and 2026 applying for jobs in the sector I had worked in, data and analytics, and all of them required advanced knowledge of AI tools. So I trained myself and got certified on many of these tools. Anyone who has seen my Linkedin can see those certificates there. I did not get any new jobs, but I picked up a lot of useful skills with a lot of corporate AI tools. 

By the fall of 2025, I had teamed up with several former colleagues to form a business that helped small organizations figure out how to use these corporate AI tools. That business ended up not working out, but one of the partners in that organization offered to bring me into her business, which was a small one-woman consulting business that helps small organizations use these tools to do their work. This is the closest thing I have had to a job offer in the last year. 

I will name the obvious tension here: The only paying work I have been able to find in the last year is helping others use the kind of tools that displaced me. But at the scale we are working, we are not giving well-resourced organizations the ability to cut staff; instead, we help small orgs who are drowning in all the work created by the digital tools they feel they are forced to use. We work on things that help people figure out their internet traffic, or write grants when they don't have a grant writer, or really just make sense of all the rapid change going on with software and technology. 

It is gig and contract work; it is not lucrative. I have made hundreds of dollars from it, not thousands, and certainly not tens or hundreds of thousands. However, it is a welcome opportunity after a year of looking for work. I appreciate the chance to take my training from the corporate world and use it to help people in mission-driven organizations trying to do the work they need to do. I also appreciate the opportunity to help them to understand the way the corporations sell hype and try to lock customers into permanent use. 

Personal Life

This training on these tools has helped me to continue a lifelong passion for learning new technology. They have also served as an accessibility tool for me. I have been diagnosed with ADHD since I was in elementary school and the corporate AI tools have helped me to focus, to prioritize, to start and to finish tasks, and to write better. AI tools can be assistive technology.

At some point it also helped me to make songs about my cats. I have drifted away from that and mostly use it as a work tool at this point.

I am a tinkerer and a learner, so I have also started exploring more open-source and local AI models. My exploration here is in the early stages but I hope in the future the work I currently do with the cloud and data center-based tools can be replaced entirely by the kind of decentralized AI I think we actually deserve. 

As with much technology over my lifetime, there are always large wealthy companies that try to dominate what people know about technology, but there are also always open source and community maintained alternatives that are designed for the people. This is absolutely true in the AI space as well and it is something I hope we can all embrace in the future. AI does not have to mean big corporations, big data centers, and big surveillance, it can be different and the sooner we can move there the better we will all be. 

The Campaign

Campaign finance laws require that we show how we spend our money. There are line items for various technology companies in our campaign finance reports and those are available for everyone to see. But I want to do more than simply say “our spending is available.” 

In the early phases of this campaign, we used AI to generate web and social media content, analyze data, conduct deep research, process video clips, analyze legislation, and write strategy documents. This let us run a bigger campaign than the resources or people we had working on the campaign. 

As we have moved forward, with a bit more money and more people, we have dialed a lot of that down and focused on how we use these tools. Some of it is principle and some of it is just practical. 

Things we never really used it for:

• Generating graphics: From the day we started the campaign we had people with design skills working on the team. Canva is plenty good for this work and we have never really given major consideration to using much AI for it.
• Original video: I don’t really like AI-generated video, and we have not needed it. We have had a person on the team who can edit and produce video for most of the last two years. 

Things we have stopped doing or cut way back on:

• Video clip editing: We’ve largely stopped using AI tools to make clips. The clipping tools were not very good, and video processing is resource-intensive, exactly the kind of heavy compute I'd rather not lean on. 
• Website content: A lot of our website content was drafted in part or mostly using AI tools. We are retiring, hand-rewriting, or archiving much of that.
• Social media content: AI-generated social media content is often just not very good for grassroots political campaigns, and it is not a secret when people are using it.
• Strategy: I have a team of people I work with on this and that is better for me than the AI tools. 

Things we still use AI tools for:

• Campaign emails and YouTube descriptions:  These are time-consuming things that have to be done and we don’t have people to do them. 
• Backend data operations: We use a lot of different campaign software–we have one system that processes credit cards, another keeps our email list and another holds information about people who have interacted with us. The AI tools build automations that connect these tools together. Once these small software scripts are written, they run locally. The AI tools are there to write them, not to consistently run them. 
• Transparency about political spending and government operations: So much of what is called government transparency comes in the form of massive data dumps that take teams of people to plow through in order to understand and interpret it. Public information act requests often produce hundreds of pages of documentation to answer a simple question. Campaign finance records are not linked to lobbying disclosures. Procurement contracts are often buried in layers of obfuscation in order to make it hard for regular people to figure out who our government is giving contracts to. AI tools can be a great leveler when it comes to these types of resources. 
• Deep policy research: So much policy writing is delivered in 100-page documents that working people and small campaigns cannot realistically process. AI tools trained properly can help to decipher this information. 
• Writing help: I still do a lot of the writing for the campaign and I use the AI tools the same way I use them in my personal life–as an accessibility tool. 

There is probably more detail to offer than this (even if this is a lot of detail!) I offer it for two reasons: First I want to be clear about what I am doing as an individual and what we are doing as a campaign. Second, it is an invitation to a discussion for people who may have questions about how the campaign’s use of these tools or my work may intersect with my advocacy and politics. 

There is more to say and good arguments to be made about how we build a movement against big tech corporations, surveillance, and the politicians who serve those interests. I believe that the movement has to be honest about how all of us actually relate to these tools, and to the corporations that profit off them. This is where I hope that conversation starts.