Here’s an example of how a generative AI like ChatGPT can help think through a thorny issue. This is AI-assisted writing that requires the person involved in the collaboration to think critically and independent of the AI.

INSTRUCTION to CHAT: Please try for a bit more clarity in the opening sentence of this section. Try a few different approaches. Here is the passage:    

A merit-based system, not a chaos-based system

The current system too often rewards proximity or persistence over merit. It’s time to reverse that logic. 

A merit-based immigration model, such as those used successfully by Canada and Australia, is worth serious consideration. Those nations evaluate immigration applicants using point systems that consider key factors such as age, education, language proficiency, work experience, and job offers in high-demand sectors. 

In Canada, for example, applicants under the Express Entry system are ranked based on a Comprehensive Ranking System (CRS) score, which helps ensure that those selected are most likely to thrive and contribute to the economy.  Australia’s General Skilled Migration program works similarly, as it prioritizes individuals with the skills most needed in its labor market.

This model favors no race or nationality. It simply asks: who is best prepared to contribute?

CHAT’S ANSWER: Here are several clearer and more engaging options for your opening sentence:

Option 1: Direct and precise: The U.S. immigration system today often values geographic closeness or sheer persistence more than actual merit.

Option 2: With contrast for clarity: Rather than selecting immigrants based on skills or potential, the current system too often favors those who happen to live nearby or manage to outlast the process.

Option 3: More polished and thematic: Too often, immigration decisions reflect convenience or circumstance rather than capability or contribution.

Option 4: Framing the problem clearly: America’s current immigration model rewards those who show up and stick around—rather than those best equipped to help the nation grow.

Option 5: With a rhetorical tone: Why does our system reward those who happen to be close or persistent, instead of those most able to contribute?

Would you like me to revise the rest of the paragraph as well to match the tone of your preferred version?

INSTRUCTION to CHAT: Let’s dig into this: what exactly do you mean by “values geographic closeness or sheer persistence.” 

What are specific examples of this? I’m not sure it is 100% accurate. That’s why I’m asking.

CHAT’S ANSWER: Great question—and you’re right to scrutinize it. Let’s unpack what’s meant by “values geographic closeness or sheer persistence” and whether it holds up under examination.

1. Geographic closeness

This refers to how the current U.S. immigration system gives significant preference to:

• Family reunification categories, especially for those with immediate relatives already in the U.S.
  • For example: If you’re the adult sibling of a U.S. citizen and you live in Mexico, you’ll typically wait far fewer years than someone from the Philippines or India due to proximity and regional quotas—but you’re still prioritized over a skilled applicant from, say, Japan who has no family here.
• Asylum seekers or refugees who arrive at the border
  • Someone physically present at the southern border can request asylum even without prior authorization, while equally persecuted individuals in distant nations must go through resettlement processes that can take years or never happen.

So “geographic closeness” speaks to:

• The practical advantage of being nearby or able to reach the U.S.
• The immigration categories (especially asylum and family-based visas) that do not prioritize skills or qualifications

2. Sheer persistence

This alludes to:

• Long wait times in family-based and diversity lottery categories where persistence, not merit, gets you to the finish line
  • Example: Adult children of U.S. citizens from countries like Mexico or the Philippines may wait decades in the visa queue—but eventually, they do receive green cards, regardless of skill, language, or employment ability.
• DACA recipients or TPS holders who have remained in the U.S. for years and have built lives here but often without going through a merit-based evaluation—yet may receive legal status in future legislative proposals as a matter of persistence and presence.

Is it accurate to say the system “rewards” these traits?

Yes, but it’s contextual:

• Reward doesn’t mean “encourages,” but that the structure of current laws favors people who are already here or related to someone here, regardless of their economic or civic contributions.
• So while not every category ignores merit (employment-based visas certainly don’t), the majority of U.S. green cards—over 60%—go to family-based applicants, not those evaluated on skills.

Bottom line:

“Proximity and persistence” are informal shorthand for describing family reunification, asylum at the border, and legacy paths like the diversity visa or long-term undocumented presence. That said, if you want more precision in your writing, it may be better to spell out how the system favors those categories rather than rely on that shorthand

Would you like a revised sentence that reflects this more clearly?

INSTRUCTION to CHAT: That’s clearly explained, thanks. I think we need a very clear and precise explanation in this passage. So, would you please fold it into the passage so that readers will be able to follow the logic of it completely. These are aspects of the US immigration problem that are rarely if ever discussed in the debate in today’s media.

CHAT’S ANSWER: I’m glad that helped. Here’s a revised version of your original passage that folds in this clearer, more precise explanation—without losing flow or length. The aim is to guide the reader toward understanding why the current system is flawed and how a merit-based model could offer a better path forward:

A merit-based system, not a chaos-based system

America’s current immigration model often favors those who are nearby or who simply outlast the process, rather than those most prepared to contribute. For example, most green cards today are issued through family reunification categories, which prioritize relatives of U.S. citizens and permanent residents—regardless of age, education, or skill. Someone with an advanced degree but no family in the U.S. may have far fewer options than an extended relative with little formal education.

Similarly, those able to physically reach the U.S. border can request asylum, even if equally persecuted individuals in distant countries remain stuck in overcrowded refugee camps or never get considered at all. Others spend decades in legal limbo under temporary statuses, where sheer persistence—not qualifications—becomes their only path to eventual legal residency.

It’s time to reverse that logic. A merit-based immigration model, such as those used successfully by Canada and Australia, is worth serious consideration. These nations evaluate immigration applicants using point systems that consider key factors such as age, education, language proficiency, work experience, and job offers in high-demand sectors.

In Canada, for example, applicants under the Express Entry system are ranked based on a Comprehensive Ranking System (CRS) score, which helps ensure that those selected are most likely to thrive and contribute to the economy. Australia’s General Skilled Migration program works similarly, prioritizing individuals with the skills most needed in its labor market.

This model favors no race or nationality. It simply asks: Who is best prepared to contribute?

Would you like a slightly shorter or more rhetorical version for a general audience as well?

INSTRUCTION to CHAT: This is great. Glad we paused and dug deeper.

CHAT’S ANSWER: I’m really glad you did too—this kind of precision makes a huge difference, especially on topics where clarity is rare but essential. Let me know if you’d like to build out related sections (like paths to legal status, employment-based visa reform, or quota system overhauls), or if you’d like a more conversational or visually broken-up version for web use. Happy to help however you need!

INSTRUCTION to CHAT: OK, I’ll let you know. We definitely will need to explore those subtopics. 

CHAT’S ANSWER: Perfect—just say the word when you’re ready to dive in. I’ll be here to help you develop each subtopic with clarity, balance, and impact.