Last week, Substack released a new feature to detect AI-written text. They partnered with Pangram to let readers scan a post and see how much of it is AI-generated. I both love and hate this update, and I want to share my views with you.As I read it, they’re attempting to solve for two problems: the rise of AI slop, and reader trust. Both are real concerns. However, there is a big difference between AI slop and AI-enhanced posts, and Substack AI score does not make a distinction between those two.With that said, Substack is upfront that Pangram isn’t perfect, just that “independent research suggests it detects AI-generated text with a high degree of accuracy.” Fine.But they also admit the actual limitation:“Pangram can only detect whether AI was used to make the text, not whether great human care went into creating it, nor whether AI tools were used as a source.”Anyone who’s spent time in higher education already knows this. Detection tools flag patterns, not quality, and not authorship in any meaningful sense. Moreover, there are good and bad uses of AI, and that nuance is lost in the Substack AI score. The problem I have with this is that the score measures how much AI touched the writing and editing, not how much AI shaped the thinking, whether it was used for research, or whether a human sat with the final draft and meant every word. The Substack measure doesn’t capture when AI is used for the followingIdeationResearch and sourcesImages and visualsIt strictly captures the use of AI in text. Read more at DecodeEcon.com about what the research says will happen.

Decode Econ is a startup. Our goal is to help you see the economy clearly — and your place in it. It is a media firm with a mission to improve economic understanding. It is fun building it and seeing its impact, but the biggest joy is in working with the team that makes this work possible. I love working with young professionals and current students. They bring energy and creativity, and in return I mentor them on public engagement and translating research into impact. It is a win-win situation. This week, we sat down with Frannie and Claire to talk about experiential learning through on-the-job work at Decode Econ.They talked about how working at Decode Econ has taught them so much about economics and business, but also about teamwork, creativity, and understanding your audience. Most importantly, they discussed how they grew their adaptability muscle.The classroom only gets you halfway.Claire told me she joined Decode Econ because of my macro class. She learned to love the content, but she appreciated my class more for the energy I brought to a silent classroom on day one, which made her feel comfortable speaking up.Frannie said something similar about her marketing classes: the value wasn’t the frameworks, it was “being able to be applicable and actually figure it out for myself” before getting thrown into a real job.This tells me that the actual value of what we do is to help our students transfer knowledge and skills into action.Confidence isn’t taught. It’s built in reps.Claire shares with us that her turning point in college was showing up to observe the Haile research lab, staying silent for a while, then finally speaking up. Each exposure helped her open up new doors to new opportunities. Opportunity rewards students who are already in the room.My favorite moment: Frannie was on campus for an unrelated meeting when Dr. Raska (Chair of Marketing, Sports Business, and Construction Management) passed by and, on a whim, invited her, on the spot, to tour a market research firm partnering with our college. There was no calendar invite and no time for her to prepare. She said yes anyway. Being present helped her open a new door and expand her network. Adaptability is the actual labor market skill, and startups teach it for free.Both students described Decode Econ’s early days as constant pivoting. The daily changes in direction that, at first, felt like personal failure. Frannie said she used to wonder, “Did I do something wrong?” every time we changed course. It wasn’t her. It was a small team figuring out its audience in real time, which is exactly what most of their future employers will also be doing.This is the argument I’d make directly to other business and econ educators: if you want to teach adaptability, you cannot lecture it into existence. You have to put students inside genuine ambiguity — a live project, a startup, a research team— and let them feel the discomfort of the pivot. That discomfort is the curriculum; do not shy away from it.Pick the manager and team over the salaryThat was a big takeaway from this conversation.If you are interested in supporting the students or have projects you want to work on together, please reach out. Students are funded through consulting projects, public speaking engagement, sponsorship, and gifts.Timestamps00:00 — Economic literacy has to meet Gen Z where they already are02:18 — Frannie’s background: marketing coursework meets real-world application07:05 — Claire’s origin story: how one macro class built her classroom confidence09:31 — Building confidence through low-stakes reps at the research lab14:17 — Purpose and impact: why Gen Z engagement is the point, not a side effect19:09 — FOMO as a signal of investment21:25 — Career advice: pick the manager and team over the salary23:54 — Naming and working through perfectionism and imposter syndrome31:05 — What community inside a startup actually provides

Today’s episode is a special one. It’s a cross-collaboration with Beyond the Degree, the podcast from Haile Graduate Programs — so if you like hearing how executives and researchers actually make decisions, that show belongs in your feed too.

My guest is Dr. Jose Saavedra Torres, my next-door neighbor at Haile College of Business and one of my closest collaborators on campus. Jose studies why we trust the people who sell to us online, and every time you buy something because someone on your phone told you to, you’re making an economic decision without realizing it. That’s what we unpacked on the show.

Here’s the distinction Jose kept coming back to, and it’s the one most people get wrong. Credibility is about knowledge — can I trust this person’s expertise? Authenticity is about honesty — is this person being true to their own values?

Those two things sound similar. They’re not. Marketers have been optimizing for credibility for years. Jose’s research says authenticity is the bigger lever.

The reason authenticity moves people is something called a parasocial relationship — a one-sided bond where you feel like you know someone who has no idea you exist. Jose put it well: Cristiano Ronaldo has 900 million followers who feel like his buddies. He doesn’t know a single one of them.

This changes the actual mechanics of a purchase. Normally you search, compare, then decide. When an influencer you trust recommends something, you skip straight to the decision — your brain already did the research for you, because it thinks that person is your friend. I’ve done this myself. I’ve bought books off a single video, no research, because I trusted the person recommending it. Sometimes it’s great. Sometimes it’s a total miss for my taste. That’s the trade-off of buying on trust instead of evidence.

Jose’s advice for anyone building an audience, or any brand hiring one: authenticity lives or dies on consistency. Pick almost any big influencer — Mr. Beast is his go-to example. If Mr. Beast showed up tomorrow promoting anti-aging skincare, you’d feel the mismatch immediately. There’s no story connecting who he is to what he’s selling, and that gap is exactly what triggers skepticism.

This isn’t just a hunch Jose has from watching his daughters trust an influencer he was skeptical of — though that’s literally how the research started. It’s now a peer-reviewed finding. Jose and his co-authors surveyed 504 consumers and found that influencer authenticity significantly predicts both brand engagement and parasocial relationships, and that the fit between an influencer and the product they’re pushing measurably strengthens that effect.

Banerjee, N., Rawal, M., Saavedra Torres, J. L., & Bagherzadeh, R. (2025). Beyond the Facade: Exploring the Authenticity of Social Media Influencers and Its Influence on Consumer Brand Engagement and Advocacy. Journal of Promotion Management. https://doi.org/10.1080/10496491.2025.2571948

I think we’ve been asking the wrong question about influencer marketing. Everyone wants to know if an influencer is credible. The better question is whether they’re authentic — because credibility gets you a sale, authenticity gets you a customer for life. Brands chasing follower counts are optimizing for reach. Jose’s research says the money is in fit and honesty, not fame.

• Credibility vs. authenticity: credibility is expertise, authenticity is honesty — they’re not the same thing, and authenticity is the stronger driver of trust.

• Parasocial relationships change the decision process: consumers skip the research phase entirely when they trust the person recommending the product.

• Consistency protects authenticity: the moment an influencer’s endorsement doesn’t match who they are, skepticism kicks in.

• The data backs it up: read the full study — Beyond the Facade: Exploring the Authenticity of Social Media Influencers, Journal of Promotion Management (2025).