Spend any time in academia, especially in higher ed, and you’ll see that LLMs have taken over. Most students don’t use them as aids. They use them as full replacements, outsourcing the work entirely. It’s rampant. There’s also a growing gap between students who can afford premium models at $200 or more per month and those who can’t.

I’m done fighting it. The pull is too strong. I’m now looking for creative, appropriate ways to incorporate AI into the classroom and study process. (Hint: you’re still taking an in-class final exam.)

AI Tools I am experimenting with for the college classroom

I am a fan of Goolge’s notebookLM.  Upload the presentation, class notes, class readings (after you have done them) and then ask for a podcast summary or quizzes.

I’ve also been using Character.ai, where you can build and interact with custom characters.  I’ve created detailed versions of John Adams, George Washington, and James Madison.  You can type with them, or you can “call” them and have a conversation.  (but we all know no current student is going to make a phone call—ever!)  So far, the conversations have been engaging.  Most interesting, John Adams’ voice sounds exactly like Paul Giamatti.  (EXACTLY!)

Today, I’ve been experimenting with ChatGPT by asking it to translate the Federalist Papers into Gen Z speak. It’s going gloriously.

I present to you: Federalist 10.

Federalist 10: The TL;DR in Gen Z Slang

Yo so here’s the sitch:
Big Jimmy M (aka James Madison) is lowkey stressed about the drama factions bring to the group chat of America. Like, people form cliques over money, power, vibes, and petty beefs – and when one squad gets too extra, it wrecks the whole party (aka democracy).

Why this matters:
Humans gonna human. We’ve got opinions. We’ve got feelings. We’ve got beef. So factions? Inevitable.
Trying to ban factions? That’s like telling people to stop having hot takes. Not gonna happen.
So Jimmy’s like: “We can’t delete drama. But we can make sure it doesn’t cancel the entire system.”

Enter: The ✨lit✨ idea
Direct democracy? Kinda sus. Too chaotic. Imagine if every time there was a poll, the loudest TikTokers decided national policy. Pass.
A republic tho? That’s the move.
Elect some chill, educated reps who filter out the nonsense and make sure no one squad hijacks the group chat.

Bonus points for bigness
Small governments? Too easy for cliques to run wild. Big republic = more vibes, more people, more diff POVs. Harder for one squad to dominate.
Like, if Karen’s HOA ran the country? Nightmare. But scale it up to 13 colonies and a whole continent? Karen’s influence gets nerfed.

Big picture:
The Constitution = faction-proof armor. It doesn’t stop drama, but it keeps it from crashing the whole system. Madison’s just trying to ghost tyranny and leave toxic group dynamics on read.

Final Thoughts

The genie isn’t going back in the bottle. AI is here, and students are using it, for better or worse.   Rather than pretending it doesn’t exist, we should teach students how to use it responsibly and critically. The goal is not to replace thinking but to sharpen it.  Not to replace reading or understanding, but deepen them.

If we (educators) do this right, AI won’t be a crutch.  Yes, they will still need to show up and write the in-class final, which will make clear who used AI to learn and who used it to coast.

A conversation I recently had with a friend who is exasperated with the current political scene: “Politician X has abysmal approval ratings!  Why don’t they seem to care?  Why aren’t they terrified of the voters?  Why does nothing change when voters clearly disapprove?

It’s a fair question.  In a democracy, shouldn’t widespread disapproval translate directly into electoral consequences, forcing politicians to course-correct or face removal?  The reality, as frustrating as it might be for some, is far more complex and nuanced.  While a politician certainly prefers a higher approval, low numbers don’t automatically signal an impending career change.  The key insight, drawn from decades of voter behavior research, can be summed up like this: Disapproval is Necessary, Not Sufficient for vote switches.

This isn’t a direct quote you’ll find in a single academic paper.   Instead, it’s a distillation of a broader understanding.   It means that while negative feelings towards a party or candidate are usually a prerequisite for a voter to even consider switching their allegiance, those feelings alone often aren’t enough to make them take the leap.

First, What Do We Mean by “Disapproval”?

In the context of political polling and voter behavior, “disapproval” generally refers to a negative assessment of a politician’s job performance, their character, their policies, or the general direction they are leading (e.g., “disapprove of the President’s handling of the economy”). It’s a sentiment, an opinion, an evaluation.

Link: https://news.gallup.com/interactives/507569/presidential-job-approval-center.aspx

Consider historical polling data as an illustration. According to the Roper Center, President Trump’s highest recorded job approval rating during his term was 49% (McLaughlin & Associates, March 2019).
This indicates that for all of his presidencies so far, a significant of those polled expressed disapproval, a situation often described as a president being “upside down” in their ratings.

Another relevant measure, the generic congressional ballot, gauges public preference for which party should control Congress. There have been periods where this indicator has shown one party, such as the Democrats, consistently leading, even if by relatively small margins.

Link: https://www.realclearpolling.com/polls/state-of-the-union/generic-congressional-vote

Such leading indicators might suggest potential challenges for the President or the party perceived negatively. But opinions and sentiments, however strongly held or clearly indicated in polls, don’t always seamlessly convert into the behavior of voting for someone else. Why?

I am told that the best political discussions come while sharing a beer.  Let’s test that theory.

I was having a beer with a political science student, and the topic was how difficult it is to change minds in the hyper-partisan atmosphere.  We went through the psychological underpinnings of political decision-making and agreed influence is extremely difficult, especially as political involvement increases.

Then the kicker: “If individual opinions are so difficult to change, then why does public opinion change quickly on some issues, for example, same-sex marriage and marijuana legalization?”

It feels like a paradox: individual rigidity, collective change.  It’s not.  It just means persuasion works differently at different levels.

Not a Paradox, Just Different Layers

The seeming contradiction dissolves when you separate levels of influence:

Micro: Individuals defend their identities and beliefs. Persuasion is rare and hard.

Macro: Groups shift through cohort turnover, social pressure, elite signaling, media narratives, or events.

Think of a forest: each tree resists bending, but the whole forest can sway with the wind.

What This Means for Persuasion and Politics

Understanding the difference between individual resistance and collective change clears up what only looks like a contradiction.

Your crazy uncle may never budge in a political argument, but that doesn’t mean the electorate stands still.   That alone should provide hope to all those who feel like they are banging their heads against a wall.  

Public opinion does change.  It shifts when generational turnover, social norms, elite cues, media framing, or major events realign the context.  

Change rarely happens through argument alone.   It happens when the ground beneath our feet moves, and moving that ground is difficult.  

But move it, you can.

A recent discussion about AI and virtual agents led to an intriguing question: Could they be trained to predict public opinion?

There are companies attempting to train agents by census data, voter files, and other assorted data then spinning them up and polling the agents with typical political polling.  It’s wild.  

This, naturally, spiraled into jokes about living in a simulation. But the idea stuck with me, fueling my curiosity about AI’s role in politics.

I then came across this paper that explores whether large language models (LLMs) can simulate senatorial decision-making and, more importantly, whether they can identify conditions that encourage bipartisanship.

Researchers Zachary Baker and Zarif Azher created AI-driven agents representing real U.S. Senators, placing them in a virtual simulation of the Senate Intelligence Committee.

The results suggest that under certain conditions, these agents exhibit realistic debate patterns and even compromise across party lines.

Introduction

Political gridlock and polarization defines modern legislative processes, with bipartisan cooperation often seeming elusive.

This study explores whether large language models (LLMs) can simulate senatorial decision-making and, more importantly, whether they can identify conditions that encourage bipartisanship.

Researchers Zachary Baker and Zarif Azher created AI-driven agents representing real U.S. Senators, placing them in a virtual simulation of the Senate Intelligence Committee.

The results suggest that under certain conditions, these agents exhibit realistic debate patterns and even compromise across party lines.

Methodology

• U.S. aid to Ukraine.
• A general discussion on necessary legislative actions./li>

Results and Findings

AI Agents Could Engage in Realistic Debate

The agents demonstrated an ability to recall prior discussion points, build arguments, and reflect on their positions. Their reflections aligned with their initial stances, reinforcing the validity of the simulation.

For example:

Agent Rubio: “During the committee meeting, I strongly advocated for substantial military aid to Ukraine… I believe we can’t afford to wait, and our response needs to be swift and decisive.”

Agent Wyden: “I raised concerns about balancing domestic needs with the urgency of supporting Ukraine. While I understand the gravity of the situation, I stressed the importance of accountability.”

Expert Evaluations Showed Moderate to High Believability

The expert reviewers assigned mean believability scores above 5 across all tested scenarios. The funding-for-Ukraine debate received an average score of 7.45, suggesting that the AI agents’ discussions mirrored real-world legislative arguments convincingly.

Bipartisanship Emerged When External Factors Shifted

One of the study’s most intriguing findings was how agents reacted to external perturbations. When the simulation introduced new intelligence indicating an imminent Russian breakthrough in Ukraine, previously hesitant senators became more willing to compromise. This shift suggests that real-world bipartisanship may hinge on clear, immediate external threats.

Critiques and Areas for Further Study

Limited Scope and Sample Size

The study only included six senators from one committee, limiting its generalizability. Future research should expand to larger legislative bodies and different committees to test whether similar bipartisan trends emerge.

Lack of Real-World Verification

While the AI agents’ actions were rated as “believable,” the study did not compare their decisions to real-world legislative outcomes. A follow-up study could test whether historical simulations align with actual votes and policy developments.

Simplified Agent Memory and Interaction

More sophisticated training structures and multi-agent training could enhance realism.

Chat GPT 3.5 Was Used

AI Senators were created with ChatGPT 3.5. Noting the expendential improvement with later models.

Conclusion

For me, this study is less about specific findings and more of a proof of concept—an early glimpse into what AI-driven simulations could mean for legislative analysis and decision-making. The possibilities are vast.

Imagine a public affairs specialist training an AI model on a government official. The technology is nearly there. Could one use Google’s Notebook LM to upload hundreds of sources on a policymaker and their key issues, then query against it? Absolutely. Could one simulate meetings? Likely. Predict outcomes? Maybe not yet, but it’s coming.

What if you trained agents on entire legislative bodies? Florida’s regular legislative session just started this week. Predicting legislative outcomes of floor votes is relatively straightforward—partisanship and leadership preferences dictate much of the process. But the real power isn’t in forecasting final votes; it’s in modeling committee member markups, where deals are made and policies are shaped. Could AI map those interactions? That’s where this research gets interesting.

My head is spinning with what makes the most sense in training data and what other factors to consider.  

As AI agents and models improve, these simulations could become invaluable for political research, policy development, lobbyists, and public affairs officials.

The ability to test legislative scenarios before they unfold could transform how decisions are made and policies are shaped.

In political theory, two dominant models attempt to explain how power and public policy are shaped within a democracy.

The first is pluralism, the idea that a diverse array of interest groups competes within the political arena, with policies emerging as a compromise reflecting the public’s competing demands.

The second is elitism, which argues that a small, concentrated group of individuals or entities—typically those with significant economic or institutional power—dominates decision-making, often to the exclusion of broader societal interests.

But, as they say, “all models are wrong, but some are useful.”

Reality is rarely so clear-cut. Enter elite pluralism, a hybrid model that offers a more nuanced perspective. This theory acknowledges the competitive nature of pluralism but emphasizes that not all interest groups are created equal. While many groups may vie for influence, certain “elite” groups—those with disproportionate access to resources, networks, and institutional power—inevitably hold a stronger hand.

Elite pluralism explains why some voices, despite the principles of democratic competition, resonate more loudly in the halls of power.  It’s not just about having a seat at the table; it’s about owning the table—or at least the most valuable seats around it.  While competition exists it is just not a fair fight among equals.

Well-resourced groups have mastered this interplay between pluralism and elitism, creating systems where competition seemingly exists, but the winners are often predetermined. The audacious tactics they use to shape policy and public opinion are worth exploring.

The Audacious Public Affairs Playbook

A deeper dive into tactics used to shape the political battleground by any means necessary.

Machiavelli is often misquoted or misunderstood as saying, “It is better to be feared than loved.” That’s not exactly what he wrote.

In The Prince, he actually wrote: “Whether it is better to be loved than feared, or the reverse. The answer is, of course, that it would be best to be both loved and feared.”

However, he acknowledged that ideal conditions rarely exist, and when forced to choose, one should resort to being feared. Why? Because people are fickle. Love persists only as long as it aligns with self-interest, but the fear of pain and punishment remains constant.

In the world of public affairs, these principles are alive and well. I’ve generally categorized the tactics in the audacious playbook into two main camps: Buying Your Love or Beating It Out of You.

“Buying Your Love” Public Affairs Tactics

Tactic:  Campaign Contributions & PACs

Financial support for political candidates or causes can buy access, influence, and loyalty. Well-resourced groups often make substantial donations to ensure that their voices are heard in the policy-making process.  This is especially true in the era of super pacs and in the wake of the Citizens United decision.

Example: Elon Musk spends $277 million to back Trump and Republican candidates

Example2: Why some California Democrats take Big Oil money and vote against environmental laws

Tactic: Astroturfing

Creating the illusion of grassroots support to sway public opinion or influence policymakers. By creating a citizens group with little no to citizens “public” support can be seemingly manufactured for a cause, and groups can seem more popular or legitimate than they truly are.

Example:  Microsoft accuses Google of secretly funding regulatory astroturf campaign

Tactic: Lobbying

Direct interaction with lawmakers, regulators, and government officials to push for favorable policies. This often involves offering expertise, research, and sometimes personal incentives to sway decisions.  For example, the pharmaceutical industry spent $293,701,614 in 2024.

Example:  Lobbying Data Summary

Example2:  Lobbying Top Spenders by Sector

Example3:  Lobbying Top Spenders by Industry

Tactic: Think Tanks & Research Funding

Well-resourced groups can fund research from “intellectually” aligned groups or universities, or even establish think tanks to produce research supporting their agenda. These tactics lend credibility and shape public discourse by presenting biased information as fact.

Example:The Secret Donors Behind the Center for American Progress and Other Think Tanks

Example2:  Public Universities Get an Education in Private Industry

Tactic: Partnerships with Charities or Foundations

Donations to charitable organizations or foundations can help create positive public relations, align with a specific cause, and gain goodwill among key stakeholders. This can also be a form of indirect influence and sometimes leads to implicit quid pro quo.

Example:  Strings Attached: How utilities use charitable giving to influence politics and increase investor profits

Tactic: Revolving Door Employment

Hiring former government officials to serve in advisory roles or as lobbyists. This builds connections and ensures that former decision-makers continue to champion the interests of the group they once regulated.

Example: Video: Jack Abramoff: The lobbyist’s playbook on 60min 

Tactic: Cultural Influence

Sponsorships and partnerships with media outlets, celebrities, and influencers can shape public opinion and create a favorable cultural narrative around the group’s goals.

 Example:  Influencers are playing a big role in this year’s election. There’s no way to tell who’s getting paid for their endorsements

Tactic: Political Endorsements and Strategic Alliances

Aligning with influential political figures or organizations can boost credibility and secure powerful allies in decision-making.

Example:  LeBron James Shares Strong Political Message On New Nike Sneakers

Example2:  Harris Grabs Green New Deal Network Endorsement That Eluded Biden  

Example 3: Fossil fuel firms ‘spent £4bn on sportswashing’ says report

Tactic: Event Sponsorships

Hosting or sponsoring high-profile events (e.g., policy conferences, galas) to gain access to influential stakeholders and enhance visibility.

Example: The Davos Forum and its role in networking

Tactic: Educational Initiatives or Scholarships

Funding educational programs or scholarships that align with policy goals to build goodwill and influence future thought leaders.

Example: Koch Foundation Criticized Again For Influencing Florida State

“Beating it Out of You” Public Affairs Tactics

A quick note on the use of the “dark arts” in public affairs: Sponsoring groups rarely engage in these tactics directly (especially if they are a public company). Instead, they often employ a layered strategy.

The key is to establish plausible deniability by structuring operations through cutouts often consultants and/or trade associations. By creating multiple layers, those funding the efforts (often to the tune of millions of dollars) can testify under oath that while their money may have been used to advance their interests, they had “no knowledge” of the specific tactics or details. They can then claim with a straight face, “Yes, we spent millions.  We also always follow the law at XYZ group, have a dedicated compliance department, and firmly believe in our right to participate in the political process.  We control no 501c(4) nor do we have a record of ever funding said group.  XYZ has broken no laws.”

“So far as he is able, a prince should stick to the path of good but, if the necessity arises, he should know how to follow evil.”  ― Niccolò Machiavelli, The Prince

Tactic: Opposition Research

In-depth digging into the backgrounds, records, and personal lives of political opponents or critics. This can be used to discredit individuals, create scandal, or shift public opinion against adversaries.

Example: Definers tries to reboot after Facebook oppo research controversy

Tactic: Corporate Espionage

In some cases, organizations may resort to stealing trade secrets, confidential information, or engaging in sabotage to gain a competitive or political edge.

Example:  Linwei Ding was a Google software engineer. He was also a prolific thief of trade secrets, say prosecutors.

Tactic: Smear Campaigns

Negative campaigning or information warfare designed to destroy reputations, spread misinformation, or stoke fear. This can be targeted at individuals, organizations, or entire movements that oppose the group’s interests.

Example: Facebook resorts to old smear tactics against TikTok
Example2: Facebook exposed in Google smear campaign

Tactic: Threats of Retaliation

Using threats, whether economic (such as pulling investments) or political (such as targeting re-election campaigns), to punish or coerce opponents into submission.  The old “you’ll never work in this town again” threat.

Example:  Trump has made more than 100 threats to prosecute or punish perceived enemies

Tactic: Legal Pressure and Litigation

Filing lawsuits or using the legal system to intimidate or financially drain opponents. Well-resourced groups may use legal battles as a form of harassment, knowing that smaller groups lack the resources to fight back.

Example: Frivolous suits stalk journalists in states without anti-SLAPP laws

Example2: Appeals court upholds Rick Wilson win over Michael Flynn in defamation case 

Tactic: Astroturfing as a Coercive Tool

While also used to manufacture support, astroturfing can be deployed in a more aggressive form to attack and drown out opposition voices, overwhelming public discourse with misleading or false narratives.

Example: Mad at MADD

Tactic: Media Manipulation

Using media to create fear, confusion, or resentment toward certain groups, issues, or individuals. This can include planting stories, leaking confidential information, or directly influencing journalists to push a particular narrative.

We are now in the phase with media becoming so fractured that certain organizations are attempting to purchase media outlets outright or fund them via advertising / sponsorships as to co-opt any ‘journalistic’ standards.  

Example: Powerbrokers: How FPL secretly took over a Florida news site and used it to bash critics

Example:  In the Southeast, power company money flows to news sites that attack their critics

Tactic: Monetary and Economic Leverage

Threatening to withdraw funding or financial support from entities that don’t align with the group’s interests. This tactic uses economic influence as a means of forcing compliance or silence.

Example:  Harvard and UPenn donor revolt raises concerns about big money on campuses

Tactic: Political Bullying and Intimidation

Using the power of government or other institutional levers to punish or pressure opponents. This can involve public shaming, threats of regulatory crackdowns, or direct threats of political retaliation.

Example:  Twitter accused of bullying anti-hate campaigners

Tactic: Straight Up Bribery

The direct exchange of money, gifts, or favors to secure a specific action or decision from a government official, policymaker, or other influential figure.  R real quid pro quo.  While illegal in most democracies, bribery remains a clandestine tool used to bypass traditional lobbying and advocacy efforts when outcomes are deemed critical or urgent by well-resourced entities. (and now thanks to SCOTUS, it appears you can have a winky winky agreement and then tip after.)

Example: Indian billionaire Gautam Adani’s business empire at risk amid U.S. indictment for fraud, bribery

Example2: Supreme Court sides with mayor accused of accepting a bribe in latest ruling to limit public anti-corruption laws

Conclusion: Understanding the Audacious Public Affairs Playbook

This audacious public affairs playbook is neither exhaustive nor prescriptive. It highlights the lengths to which well-resourced groups can and will go to influence policy, perception, and power. Some tactics operate within the bounds of the law, others test its limits in legal gray areas, and a few are outright illegal. Many fall into ethical gray zones, while others blatantly cross ethical lines.

In an ideal democracy, every voice would be heard equally. Yet, as elite pluralism demonstrates, the reality is far more complex. Influence, access, and resources skew the playing field, often leaving ordinary citizens to compete against entities with disproportionate power.

Whether you admire or detest the tactics in this playbook, they reveal the raw, realpolitik side of public affairs.

However, don’t become too cynical. History is full of examples where less-resourced efforts have defied the odds to harness public opinion and achieve policy or political victories. Often, these successes come in reaction to a well-resourced group overplaying its hand or through decisive legal action.

While power and resources undeniably play significant roles in public affairs, they are not invincible.  Just as the casino doesn’t win every time…..luck and timing can lead to a winning hand.  However, continuing the casino metaphor, over time, the odds remain stacked in favor of the well-resourced. And like in a casino, the house usually wins.

As you reflect on these methods, ask yourself: Where do you draw the line between strategy and manipulation? Between fair competition and coercion? Public affairs, like democracy itself, demands constant vigilance, active participation, and critical scrutiny to ensure it serves the public good.

What’s your take? Are these tactics necessary evils, or do they erode trust in our institutions?  Most importantly, what was left out?

PS.  We must pay homage to two of the biggest contributors to the playbook.

The original OG:  The Tobacco Industry

Then the Energy Industry took tobacco’s playbook and improved upon it.

Rarely do I read an academic study that terrifies me.  Well…unfortunately my colleague sent me a study that sent chills down my spine.  The future is here, and we aren’t likely to be prepared for it.

As we have written before, persuasion is hard. If you’ve ever tried to convince a friend on any political issue or even to watch your favorite show (and failed), you know how tough it can be. Now imagine a chatbot trying to do it! Crazy, right? Well, not so much.

Recent research shows artificial intelligence (AI) might be better at persuasion than you think. Let’s dive into the science behind this surprising finding.

Introduction

This study explores whether AI, specifically GPT-3, can influence human opinions on political issues. The research tackles a simple yet profound question: Can AI persuade as effectively as humans? Spoiler alert: The answer is yes—and it’s got people talking about the implications for politics and beyond.

Conclusion

This study marks a step in understanding AI’s role in persuasion. As AI tools continue to advance, their capacity to shape opinions could significantly influence politics, advertising, and even our interpersonal communication.

While the observed effects may seem modest, the effects are small with humans.  The real power of AI lies in its scalability. When combined with automation, this technology poses a potential threat, particularly in the hands of malicious actors. The ability to produce persuasive messages at scale could amplify foreign interference in elections or facilitate widespread misinformation campaigns.

Although I hesitate to advocate for additional regulations, the immense power of these tools demands responsibility.  It is why the authors write, “Our findings call for immediate consideration of regulations of the use of AI in political activities.” 

Moreover, we cannot overlook the role of platforms like TikTok.  Our youth are unknowingly contributing to the development of AI technologies that could potentially be leveraged against us.

I agree, policymakers must remain vigilant, as the risks of unregulated use could undermine public trust.  

Reflecting on these implications, I suddenly feel a bit like a Luddite.   UGH!