Artificial intelligence (AI) refers to systems that perform tasks traditionally requiring human cognition, such as learning, decision-making, and communication. Adoption is exploding: ChatGPT reached 100 million users just two months after launch, making it the fastest‑growing consumer app in history.

Get to know how AI operates through the National Science Foundation’s overview (10 minutes):

We’re now entering an era where AI-powered digital agents operate alongside humans. Companies like Bank of New York Mellon are already deploying these digital agents. They have system logins, autonomously write code, validate payments, and may soon send emails or collaborate in Microsoft Teams. AI is already transforming industries and public services. As AI becomes more embedded in industries and public services, essential questions arise around governance, workflows, access control, and accountability.

We can’t put our heads in the sand. We have to define new ways of working, create new rules, and shape policy frameworks that reflect this shift. Navigating the age of artificial intelligence means living in the future, continuously learning, and stepping into leadership roles in our homes, workplace, communities, and state governments.

UNDERSTANDING AI TERMS

As AI tools become increasingly integrated into daily life, work, and public services, having a basic understanding of key terms can help us follow developments more clearly and ask more informed questions.

Artificial Intelligence (AI), as noted earlier, powers systems that mimic human abilities, such as understanding language and making decisions. There are different types of AI:

• Narrow AI is designed to perform specific tasks with remarkable efficiency, but only within a defined scope. These systems excel at targeted functions and are already integrated into many aspects of daily life.  For example:
  • Voice Assistants: Tools like Siri and Alexa use Narrow AI to enable natural-sounding, responsive interaction between humans and machines.
  • Recommendation Engines: Platforms such as Netflix and Spotify tailor suggestions by analyzing user behavior and preferences.
  • Customer Service Chatbots: Deployed on websites, these bots efficiently handle specific customer queries, improving response time and user experience.
  • Image Recognition Tools: From facial recognition to medical imaging, Narrow AI enables the precise identification of patterns and anomalies.
  • Fraud Detection Software: Financial institutions rely on AI to monitor transactions and flag suspicious activity in real time.
  • Language Translation Tools: Services like Google Translate provide quick and increasingly accurate translations, bridging global communication gaps.
  • Autonomous Vehicle Functions: Self-driving technology uses narrow AI for tasks such as obstacle detection and route planning, pushing the boundaries of transportation innovation.
• Generative AI creates new text, images, or code (e.g., ChatGPT, Claude, DeepSeek) and understands the broader context of the tasks it is being asked to perform.
• Predictive AI analyzes data to forecast future events, behaviors, or outcomes. Examples include Google Maps suggesting the fastest route or weather predictions.

Many essential systems and processes enable AI, but here are some of the ones most frequently discussed:

• Machine Learning finds patterns in large datasets to make predictions or decisions, such as filtering spam or identifying health risks. Today, most AI relies on machine learning.
• Large Language Models (LLMs) are powerful AI systems trained on vast amounts of text, like books and websites, to understand and generate language, answer questions, or draft reports. Examples include ChatGPT4, Claude, and DeepSeek. Freely available LLMs can help brainstorm, summarize, and create images. They analyze data, draft reports, and support planning in the workplace. For ideas to use in your own daily life, see our blog on “How AI Impacts Your Daily Life, Civic Engagement, and Career.”
• Algorithmic bias occurs when AI systems produce flawed results that reinforce inaccurate trends, often due to skewed data or design choices. Watch Elizabeth Adams give a TedTalk on responsible AI and her experience with algorithmic bias (10 minutes).

Follow up from reading over these terms with IBM’s overview of how they interact (10 minutes):

Data centers are physical facilities that house powerful computer servers used to store, process, and manage vast amounts of digital information. While data centers have been around for decades, supporting everything from email to e-commerce, the rise of artificial intelligence and its demand for computing power has significantly increased their importance.

Data centers are the backbone of the growth of artificial intelligence and its application in all industries. AI workloads involve complex calculations, rapid data retrieval, and massive energy consumption. This has led to a growing need for:

• More powerful servers;
• Larger data center footprints;
• Increased energy capacity and cooling infrastructure.

AI systems, especially large language models like ChatGPT, require immense computing power to function. Each time someone interacts with an AI tool, their input is sent to a data center, where high-performance servers process the request and generate a response in real time.

Watch the Wall Street Journal’s video showing AI and data center’s energy usage (7 minutes):

Digital agents or Agentic AI (also referred to as digital workers or AI agents) are systems powered by AI that can perform tasks autonomously and interact with human teams. Some companies now assign these agents logins, managers, and defined roles, such as writing code, validating transactions, or communicating through internal tools such as Microsoft Teams. These agents are designed to complement human work, often performing repetitive or technical tasks more efficiently.

Watch SandboxAQ give a general description of digital agents (3 minutes):

Blockchain is a decentralized digital ledger that records transactions or data entries in a secure, transparent, and tamper-resistant way. Each entry, or “block,” is linked to the one before it, forming a chain that cannot be altered without broad consensus across the network. As concerns about misinformation, deepfakes, and data manipulation grow, blockchain technology is increasingly seen as a tool to verify authenticity. It offers a way to trace the origin of digital assets, confirm the source of information, and build trust in online interactions. Originally developed to support cryptocurrencies like Bitcoin, blockchain is now being applied in areas such as:

• Supply chain tracking (verifying the origin of goods);
• Digital identity management;
• Voter record security;
• Intellectual property and content verification;
• Transparent public recordkeeping.

As society becomes more dependent on digital platforms, blockchain presents a path toward greater civic trust and informed decision-making through transparency, accountability, and integrity.

Learn more about blockchain from Britannica (2 minutes):

Artificial intelligence is shaped by a dynamic network of citizens, entrepreneurs, technologists, public officials, and civic leaders. From individuals advocating for privacy and transparency, to businesses and non-profits integrating AI into operations, to governments deploying it in public services, the future of AI is being written collaboratively, not behind closed doors.

Here’s a look at the core contributors shaping the age of intelligence:

• Core technology builders design and train foundational AI systems. AI model developers such as OpenAI create large language models, while academic labs like those at Stanford, MIT, and UC Berkeley work to improve safety, speed, accuracy, and efficiency. Open-source communities, for example, Hugging Face and EleutherAI, offer open models for broader access and transparency.
• Infrastructure providers supply the backbone for AI at scale: chip makers like NVIDIA and Intel produce processors vital to AI functioning. Cloud providers like Amazon Web Services, Google Cloud, and Azure host computing power.
• Energy and utility companies will need to innovate to support AI’s growth and sustainability. Energy demands for AI and data centers are exponentially growing in tandem with the demand for the technology. This is putting a strain on the current energy infrastructure and grids, often in rural areas where data centers are being built. Learn more about the impact of data centers and their energy demands on local communities in The Policy Circle’s Why Tech Policy Matters Now Insight.
• Academic institutions shape public understanding and policy, ensuring responsible development, advocating ethics, promoting interdisciplinary research, and collaborating on AI policies for transparency and public welfare. Many think tanks and advocacy groups are also active in tech and AI policy and digital literacy; see the Digging In section of this Insight for more information.
• Entrepreneurs are utilizing AI to develop new products and services that were previously impossible. One industry being revolutionized is healthcare. PathAI is improving pathology processing, helping doctors identify diagnoses more quickly. Tempus is using AI to develop targeting medicines more efficiently and quickly than ever before. Butterfly Network is increasing access to ultrasounds through portable machinery paired with AI-powered interpretations, lessening burdens on healthcare providers and giving patients more information and control over their health.

DATA THAT FUELS AI

Data brokers are companies that collect, aggregate, analyze, and sell personal and behavioral data, often without individuals’ direct knowledge or consent. They operate behind the scenes, supplying datasets that fuel targeted advertising, credit scoring, fraud detection, and AI training models.

Unlike companies that collect data as part of delivering a service (like Google or Facebook), data brokers typically buy or scrape data from a wide range of public and private sources, including social media, apps, health trackers, online purchases, location data, and public records. They package this information into profiles that may contain thousands of data points per person, from income level to political leanings.

In the AI ecosystem, data brokers:

• Feed machine learning algorithms with massive datasets for personalization and predictions.
• Influence outcomes in employment, housing, lending, and insurance through risk and behavior models.
• Raise serious concerns about privacy, accuracy, bias, and consent, especially since individuals often can’t see or correct what’s collected about them.

Examples of Data Broker Companies:

• Acxiom: One of the largest data brokers in the world, profiling over 2.5 billion people.
• LexisNexis Risk Solutions: Sells data for risk assessment, used in law enforcement and insurance.
• Cotality: Specializes in property and credit data, often used in housing and lending.
• TruthFinder and PeopleFinders: Consumer-facing services that aggregate personal data, often scraping public records.

This video gives a quick overview of what a data broker is and what your data reveals about you (4 minutes):

Artificial intelligence presents extraordinary opportunities but also complex tradeoffs. As large language models (LLMs) and other AI tools evolve, they increasingly depend on massive amounts of data, sophisticated infrastructure, and cutting-edge research to stay competitive on the global stage. This raises critical questions: How do we fuel innovation while preventing harm to people and critical infrastructure? 

The following areas of policy debate are emerging:

1. Transparency, Consent, and Privacy. Much of the data used to train AI models is sourced from the internet, often without individuals’ knowledge or consent. This lack of transparency not only raises concerns about privacy and the inclusion of copyrighted or personal information but also affects the accuracy, reliability, and interoperability of AI systems. Poor data practices can lead to biased or harmful outcomes and undermine trust in AI applications. As a result, advocates are calling for stronger privacy protections, clearer disclosures, robust data verification processes, and ethical standards that support both responsible use and system interoperability.

2. Innovation vs. Overregulation. Some argue that robust regulation is essential to guide the development of ethical AI and safeguard users. Others caution that overregulation could stifle innovation, slow the pace of progress, and limit the U.S.’s ability to remain globally competitive. There’s an ongoing debate about how to strike the right balance between flexibility for experimentation and guardrails for accountability. This R Street panel (1 hour) highlights core issues in that debate, featuring Katie Harbath who will be speaking at The Policy Circle Summit: Navigating Leadership in the Age of Digital Intelligence.

3. Land Use and Energy. The rapid growth of AI requires massive data centers, demanding significant land, water, and energy. This raises questions about zoning, permitting, and environmental impact, especially in regions where land or power grids are already strained. Public-private partnerships are being tested as states compete to attract AI infrastructure while balancing community needs, sustainability, and grid reliability. How should existing laws and public-private partnerships evolve to ensure adequate infrastructure, space, and energy to power the demands of the digital age?

4. Government Investment in critical infrastructure, promotion of digital literacy and access, and research. In countries like China, the government plays a direct role in AI development, funding research, infrastructure, and energy resources to power AI at scale. In the U.S., this raises questions about the federal government’s role: Should it invest more aggressively in national infrastructure for computing power, and public-private R&D partnerships to maintain leadership in this space?

The Policy Circle’s AI Insight Series explores how AI is transforming specific sectors and policy areas, offering practical guidance for anyone seeking to shape the future of innovation and civic engagement. The series explores the following topics, looking at how AI plays a role in each of them:

• Tech Policy
• Money and Currency
• Education
• Government Accountability

These resources and conversations are designed to help individuals step confidently into the future, not just as consumers of technology, but as informed, active participants in shaping how it’s used.

ARTIFICIAL INTELLIGENCE SERIES

5. Taxation and tariffs. As AI and digital platforms grow, outdated tax systems struggle to keep pace. At the federal level, policymakers face pressure to modernize tax codes to include digital services, regulate cryptocurrency transactions, and address global profit shifting by tech giants. States are exploring how to tax digital goods and incentivize responsible AI use, while local governments must adapt as automation and e-commerce shrink traditional tax bases. Globally, efforts like the OECD’s digital tax framework aim to find common ground. At the same time, debates continue over whether to tax automation or implement tariffs on AI-related hardware like semiconductors, all raising questions about innovation, and economic resilience.

These policy questions aren’t abstract, they’re unfolding in real time, in boardrooms, classrooms, local government meetings, and community spaces. That’s why now is the time to engage.

• Test-Drive AI Tools: Discover how AI fits into your life by experimenting with user-friendly tools like:
  • ChatGPT-4.0: Check out this overview of what ChatGPT is capable of
  • Freespoke, a new search engine and news aggregator with AI generated summaries of perspectives
  • Canvas Magic Studio
  • See this list for more ideas.
• Try the following AI prompts for civic engagement in Gemini or ChatGPT:
  • List current AI-specific commissions, advisory boards, or task forces in [your state or city]. Include public technology, innovation, education, data privacy, or economic development groups citizens can apply for or be appointed to.
  • How can I find open seats or upcoming appointments for tech-related commissions in [your area]?
  • What public hearings or advisory groups are shaping AI policy in your area?
• Practice Digital Literacy: Avoid sharing sensitive information with AI tools and always verify essential outputs.
  • Take a look at how OpenAI approaches individual users’ and businesses’ privacy to help protect yourself, then help others do the same.
• Stay Informed and Inspired: Stay current on AI development and how they impact you by following these credible sources:
  • Take a look a the rest of The Policy Circle’s AI Insight Series:
    • AI and Government Transparency Insight
    • The Future of Money Insight
  • The AI Break focuses on digestible, high-level updates on artificial intelligence, aimed at professionals and enthusiasts who want to stay current on the latest developments without the hype or jargon;
  • Katie Harbath’s Anchor Change newsletter and podcast looks at the intersections of tech, democracy, and regulation. it offers sharp, informed insights into how governments, platforms, and voters are navigating technology, especially AI, in political and civic contexts;
  • The WSJ Tech section offers in-depth reporting and analysis on the business, policy, and societal impact of technology, with a focus on major companies, AI, cybersecurity, and digital regulation;
  • The Rundown AI is an accessible newsletter that summarizes the latest industry developments in AI, from tools and product updates to research and business news;
  • Stay up-to-date with AI legislation across the country with the IAPP US State AI Governance Legislation Tracker;
  • The MIT Technology Review provides analysis on AI trends, ethical questions, and explainers with personal relevance to readers;
  • The Decoder evaluates AI products and services and the tangible applications they can have in personal and professional settings.
• Engage with policy and advocacy groups shaping AI policy, such as:
  • Cosmos Institute: Advancing ethical AI, human flourishing, and human agency
  • Cicero Institute: Promoting innovation-friendly policy
  • The Alliance for Responsible Citizenship (ARC): Applying global insights to U.S. challenges through a human dignity framework
  • Project Liberty: Promoting decentralized social platforms and empowering users to control their own data

STEPPING INTO INFLUENCING POLICY

• There is power in convening. Host a Policy Circle using this Insight. Pair it with the Digital Landscape Brief to ground the discussion in real-world issues like access, innovation, and responsibility. Initiating an open conversation provides a forum for people in your networks to share their lens of care, experiences, and opportunities to engage.
• The Policy Circle’s Tech Policy Insight (coming soon) will provide a more comprehensive framework on what tech policy is and why it matters today. As AI is being implemented in your community, from schools to city service here are some questions to ask local leaders:
  • Where is AI being used in our community, and why? (e.g., traffic management, public safety, classroom tools, government services)
  • Who decides which tools to adopt and how is it communicated to stakeholders?
  • How is success and effectiveness being measured? How is the AI system being held accountable?
  • How are we protecting privacy, mitigating bias, and ensuring transparency when AI is being used?
  • How can we best protect individuals from potential harm?
• Step into Civic Leadership and elevate your engagement in your community, county, and state and apply for The Policy Circle’s Civic Leadership Engagement Roadmap (CLER) program.

• AI in Cities Report and Toolkit (National League of Cities)
• Arizona State University was one of the first to offer classes focused on ChatGPT and using generative AI. Learn about prompt engineering from one of the course leads and a speaker at The Policy Circle’s Summit, Andrew Maynard.
• The AI Race Accelerates: Key Insights from the 2025 AI Index Report | American Enterprise Institute (American Enterprise Institute)
• “Guardrails For AI Governance In Today’s Shifting Regulatory Landscape” (Gary Drenick, Forbes)
• Model State AI Innovation and Child Protection Act (Cicero Institute)
• Response to the Development of an Artificial Intelligence (AI) Action Plan (American Enterprise Institute)
• This Is Our Obligation.’ Project Liberty Wants to Fix the Internet
• Global Policy Watch: AI Blog