We read your mail on AI-proof jobs and how to fix crime labs

Summary

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Podcast Summary: The Indicator from Planet Money

Episode Title: We read your mail on AI-proof jobs and how to fix crime labs
Date: September 11, 2025
Hosts: Darian Woods & Waylon Wong
Duration: ~10 minutes

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Overview

In this audience-driven episode, Darian Woods and Waylon Wong open the listener mailbag to explore two big questions sent in by thoughtful listeners:

• Why are older software engineers less affected by AI-driven job displacement than their younger counterparts?
• What could improve the inconsistent accreditation of forensic crime labs in the U.S.?

Listeners share insider perspectives on the resilience of experienced software developers and an urgent need for universal crime lab oversight. The hosts discuss important economic lessons and share memorable insights straight from the audience.

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Key Discussion Points & Insights

1. Listener Mailbag: AI and Job Security for Software Engineers

[02:10–05:16]

The AI Impact Study Recap

• Darian references a recent study that found younger individuals in AI-exposed professions suffered a 13% higher drop in employment than older colleagues, especially among software developers.

John Cox’s Perspective

• John Cox (software professional with a decade of experience) offers a firsthand view:
  • Less experienced (often younger) developers who rely on AI tools often don’t understand the codebase deeply enough to fix problems.
  • Experienced engineers, in contrast, play a critical role maintaining and repairing complex systems.
  • Even if AI can rapidly generate new code, it’s seasoned professionals who “rescue software from a fire” when things break.

Quote:
“For someone new coming on who does not really understand software, they might understand the tools used to generate new software, but if they can't figure out how to fix it if it broke, that is much less valuable.”
– John Cox [03:05]

• Experienced engineers’ comfort with advanced AI coding assistants (like Claude, Copilot) further increases their value—if, crucially, they know how to guide and fix AI output.

Quote:
“The ability to rescue software from a fire is extremely valuable.”
– John Cox [04:16]

The Future of Software Development

• John warns of potential changes ahead:
  • Some firms may treat software as a disposable commodity, with little emphasis on quality or long-term maintenance.
  • This could create an environment of unstable, insecure software reminiscent of “dystopian cyberpunk futures.”

Quote:
“We may start getting to a point where there's a large segment of the software industry that starts treating software as a throwaway commodity... not maintained and secured and made into greater quality.”
– John Cox [04:34]

• Hosts’ Reaction:
  • Waylon jokes about wanting an “analog future” in response to bleak predictions.
  • Both note the ongoing need for thoughtful, experienced tech talent.

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2. Listener Mailbag: Fixing Crime Lab Accreditation

[05:19–08:21]

The U.S. Crime Lab Accreditation Problem

• Brian Gestring (forensic scientist, Albany, NY, 35+ years’ experience) raises concerns about:
  • Most U.S. crime labs operating under fragmented, poorly regulated local authorities.
  • Inconsistent accreditation standards, with two private firms (primarily ANAB) dominating the field—over 90% handled by one.
  • Lack of transparency and effective oversight.

Quote:
“I feel uncomfortable with two private companies and really one private company being the de facto regulator of all forensic science in the United States.”
– Brian Gestring [06:47]

A Path Forward: National Standards & Federal Oversight

• Drawing from history, Brian points to the FBI’s DNA database rollout as a proof-of-concept:

  • Access to the DNA database required labs to be accredited (federal law).
  • Some labs only accredited their DNA units, not the entire operation.

• Brian proposes:

  • Universal, national accreditation of all crime labs within five years, using federal grant funding as both carrot and stick.
  • This would set clear, uniform standards for all, fixing existing gaps.

Quote:
“What that will allow us to do is the concerns we have, we can now have a voice to fix them.”
– Brian Gestring [08:09]

• Hosts highlight incentives as the key economic lever for systemic reform.

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3. Listener Feedback & Show Engagement

[08:21–08:50]

• The hosts appreciate thoughtful listener feedback, mentioning lively responses to a recent Gen Z and money episode.
• They encourage ongoing comments—email and Spotify—crediting the input for improving the show.

Quote:
“We read all of your feedback. It makes us have a better show. So thank you very much.”
– Darian Woods [08:44]

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Notable Quotes & Moments

• "Take that, robots." – Waylon Wong jokes about experienced engineers’ edge over AI [04:25]
• "Number one economic lesson." – Waylon succinctly sums up the importance of incentives in policy design [08:24]

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Timestamps for Key Segments

• 02:10 – Listener question: AI and jobs for software engineers
• 02:53 – John Cox explains why experience trumps AI know-how
• 04:34 – John warns about software as a disposable commodity
• 05:19 – Listener email on crime lab accreditation, Brian Gestring’s background
• 06:47 – The monopoly in crime lab accreditation
• 07:43 – The FBI DNA database case study and proposal for national standards
• 08:21 – Hosts discuss economic incentives and listener engagement

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Summary

This episode reveals the deep value of experience in the age of AI—where older software engineers, able to fix what AI breaks, are harder to replace—and exposes the invisible crisis of crime lab oversight, calling for national, federally incentivized standards. Listener expertise, real-world stories, and host commentary connect economics theory to urgent workplace and public sector dilemmas, making for a fast-paced, thought-provoking listen.

Transcript

[Announcer]

Npr.

[Darian Woods]

This is the Indicator from Planet Money. I'm Darian Woods.

[Waylon Wong]

And I'm Waylon Wong.

[Darian Woods]

You know, Waylon, they say don't read the comments, but indicator listeners actually leave us with some pretty thoughtful ones.

[Waylon Wong]

They do. We get a lot of emails and actually we pipe those emails into a special Slack channel where we leave like a light bulb emoji for the ones that make us go, aha, yes.

[Darian Woods]

And if they point out that we, I don't know, pronounced the local town wrong, that gets a grimace emotion.

[Waylon Wong]

No, but that never happens. Darian, how dare you. But today on the show, we sift through the listener mailbox to learn from you, our audience members. We'll hear why older software engineers may have more job security against AI. And from a forensic consultant on one idea of how to improve credentialing for crime labs.

[Darian Woods]

Crime labs. Well, I'm listening.

[Waylon Wong]

We dust for fingerprints after the break.

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[Waylon Wong]

Is time to open up the listener mailbag. Who did you pick, Darian?

[Darian Woods]

John Cox recently wrote to us about our episode where we talked about this eye opening new study on the potential impact of artificial intelligence on the workforce. And for young people in jobs that were highly exposed to AI, their own employment dropped 13% more than their older colleagues since late 2022. And the study's authors found that younger software developers were taking a hit and they suggested that AI was a big part of this. At the same time, this was a bit of a puzzle because it didn't seem to be happening for the older software engineers. And it turns out that John knows a little bit about this.

[John Cox]

I work in a combination of software development and it. But I've been in the software industry for about a decade now.

[Darian Woods]

John has a potential explanation for why more experienced software engineers are holding onto their jobs.

[John Cox]

For someone new coming on who does not really understand software, they might understand the tools used to generate new software, but if they can't figure out how to fix it, if it broke, that is much less valuable.

[Darian Woods]

In plainer terms, it sounds like there are vibe coders, as in people who are just writing without knowledge of code. They write a piece of software. What then happens with the more senior.

[John Cox]

Software engineers, older engineers, more experienced engineers are still required to fix and maintain systems.

[Darian Woods]

And John says if these same engineers are also comfortable using the new large language models like Claude Code and Copilot, that could make their job even more valuable.

[John Cox]

As I've been using some of these models, I try to carefully think about everything I'm doing and try to very carefully and prescriptively tell it exactly what kind of functionality I want, where I want it, how to go about organizing it. Major difference is that I can repair it if something goes wrong, and I have.

[Darian Woods]

And you're saying you've observed more senior engineers have to fix mistakes that are made by perhaps more junior engineers or vive coders?

[John Cox]

Yes. The ability to rescue software from a fire is extremely valuable.

[Darian Woods]

So AI can generate a lot of code, but fixing it requires experience.

[Waylon Wong]

Yeah. Take that, robots.

[Darian Woods]

Well, John says although his job is secure for now, he can see a future where software is treated less preciously.

[John Cox]

What I see as a possible outcome is that we may start getting to a point where there's a large segment of the software industry that starts treating software as a throwaway commodity, not something to be maintained and secured and made into greater quality. This is kind of like the basis for, you know, those dystopian cyberpunk futures where there's some very big and powerful software that's very good, but software in general is prevalent and not very secure and not very stable.

[Waylon Wong]

Well, that sounds terrible. I would like to live in an analog future.

[Darian Woods]

So you're throwing away your devices, Waylon?

[Waylon Wong]

Well, let me put it that way.

[Darian Woods]

So, Waylon, what caught your attention in the inbox?

[Waylon Wong]

Well, this one comes to us from Albany, New York. Brian Gestring wrote to us with a very interesting episode idea. It's about a problem and solution for accrediting crime labs in the US and our producer, Julia, recently spoke to him.

[Brian Gestring]

I've been a forensic scientist for over 35 years now, and I've worked in every aspect of forensic science from being A scene investigator to being a crime lab executive.

[Waylon Wong]

As a kid, were you interested in forensics?

[Announcer]

Did you watch a lot of Law and Order? Like, what led you to this?

[Brian Gestring]

I'm gonna date myself, but Law and Order didn't exist when I was growing up.

[Waylon Wong]

Okay, okay, so maybe more of a Sherlock Holmes guy. Brian writes us that in most of the US Crime labs are typically housed under law enforcement and or health departments. Brian says they often don't get a lot of attention. And over time, that's led to a piecemeal approach to how the industry gets accreditation.

[Brian Gestring]

I started realizing that sometimes the guardrails for quality were not as strong as I thought they were when I was on the front line. So as I started moving up, I started looking and I started seeing gaps where things could fall through the cracks. And it's not gaps out of maliciousness or anything like that. It's just kind of how the field has evolved.

[Waylon Wong]

Brian says standards vary widely state to state, and there are two private companies that provide the bulk of accreditation for forensic labs. Brian ran the numbers and found that One of those, ANSI National Accreditation Board, also known as ANAB, accounts for more than 90% of the accreditation business.

[Brian Gestring]

I'm not saying they're doing a bad job, but I feel uncomfortable with two private companies and really one private company being the de facto regulator of all forensic science in the United States.

[Waylon Wong]

We reached out to ANAB to ask whether they would be in favor of federal oversight, but they did not get back to us before our deadline.

[Darian Woods]

Brian says this raises issues of transparency and accountability. He wrote a paper called the Invisible Crisis facing Forensic Providers in the United States about the lack of federal oversight of forensic lab. He believes forensics quality problems stem from poor regulation, not bad science.

[Waylon Wong]

What we really liked about this paper though, is his ideas for solutions, including the idea of universal accreditation. Brian envisions a five year window to accredit all crime labs using federal grant funding as both carrot and stick. He says, we saw a version of this when the FBI launched its national DNA database in the 90s.

[Brian Gestring]

The National DNA Data bank came in, a law went into effect to federal law, and it said that in order to access that DNA data bank, you had to be accredited.

[Waylon Wong]

The FBI also provided some support for labs. Bryan says the only problem was that some jurisdictions chose to only accredit the DNA portions of their crime labs, not their entire department. Brian says a national standard could help by incentivizing existing federal funding.

[Brian Gestring]

I'm trying to migrate this idea from one end of the economy to forensic science and say we can start setting standards. And what that will allow us to do is the concerns we have, we can now have a voice to fix them.

[Darian Woods]

Okay, so Waylon, it all comes down to incentives.

[Waylon Wong]

Number one economic lesson.

[Darian Woods]

And our listeners know this. Very thoughtful people. And you know, we don't just get comments in our inbox. You can actually leave comments on Spotify episodes these days.

[Waylon Wong]

Oh yes, I'm well aware. One episode in particular about Gen Z and money troubles sparked a flurry of unhappy messages. And we did see those.

[Darian Woods]

Yes, we read all of your feedback. It makes us have a better show. So thank you very much.

[Waylon Wong]

And if you want to leave us more feedback, you can send us a [e-mail] this episode was produced by Julia Ritchie with engineering by Kwesi Lee, as Fact Checked by Sierra Juarez and edited by Paddy Hirsch. Kicking Cannon is the show's editor and the Indicator is a production of npr.

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