Analysis
podcast
A pilot series examining the intersection of tech and work
A timely show examining how algorithms, apps, and automation are reshaping the day-to-day experiences of working people.
Big Lake Data Founder Matt Schumwinger and Co-Host Alex Eckhart explore how algorithms, apps, and automation are reshaping the day-to-day experiences of working people.
What AVs Are Really Doing to Gig Work: Inside the Gridwise Data - Ep 8
Autonomous vehicles are scaling fast, but what does that mean for the people behind the wheel today? And how fast will AVs impact the market anyway?
In this special episode, Matt and Alex are joined by Ryan Green, CEO of Gridwise, whose company tracks over a million gig workers and more than $10 billion in earnings across the rideshare and delivery economy.
Drawing from Gridwise’s latest AV Impact Report, Ryan breaks down what the real data shows about utilization, trips per hour, take-home pay, and how AV markets like Los Angeles, San Francisco, and Phoenix are diverging.
They explore whether AVs are truly replacing drivers or simply adding pressure to an already oversupplied market. Are workers earning less per hour? Are they working more to compensate? And is the total rideshare “pie” actually getting bigger?
The data is still early — and noisy — but the signals are starting to form.
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From Driver's Seat to Depot Floor: What Happens to Jobs When AVs Scale? – Ep 7
Autonomous vehicles aren't going to kill every job in the ride-hail industry. But they will restructure how the rideshare workforce operates.
In this episode, Matt and Alex explore what happens when the gig economy collides with fleet operations, and why the shift to AVs means more than just swapping humans for robots. They break down how rideshare is moving from an atomized model to a centralized corporate fleet operation.
This transformation creates new jobs in vehicle maintenance, cleaning, and depot operations, but these roles look nothing like driving gigs we're used to.
The episode closes with the critical question: What happens to current drivers in this transition? New jobs don't automatically mean pathways for displaced workers, and that's where policy, advocacy, and worker protections could make all the difference.
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How AVs Will Reshape Rideshare Without Replacing It? – Ep 6
Autonomous vehicles are finally here, but they're not coming for every rideshare job. Matt and Alex break down why the future of gig work isn’t a simple "robots versus humans," but something far more nuanced.
With AV expansion accelerating in Arizona and regulatory debates heating up in Boston, they explore why AVs will likely capture the "backbone" demand while leaving humans to handle the fluctuations, and what this hybrid model could mean for driver wages and working conditions.
The episode wraps with an analysis of why the debate around AVs isn’t fitting neatly into traditional labor politics.
Is this technological inevitability, or do workers and communities have more power to shape how AVs roll out than we think?
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The Hidden Hours: Unpacking P1, P2, and P3 Time in the Gig Economy – Ep 5
You see the ads: "Earn $X per hour driving for Uber!" But what does that hourly rate really account for? Alex and Matt dissect the industry's "P1, P2, P3" time classifications, revealing how companies like Uber and Lyft categorize and compensate drivers for different phases of their work.
They unpack how "online" (P1), "en route" (P2), and "with passenger" (P3) time are defined and, crucially, how the exclusion of P1 time from advertised wages and minimum pay settlements can significantly impact driver earnings. Discover how this classification can lead to misleading income claims and lower-than-expected take-home pay for drivers, and how it plays a crucial role in legal battles and policy decisions.
Is the way ridehail companies account for driver time a matter of operational efficiency or a systemic undervaluing of their labor?
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Deactivated and Desperate: The Black Market for Gig Work Accounts – Ep 4
When Uber or DoorDash deactivates a driver, they’re not just pausing an account, they're cutting off someone's livelihood. In this episode, Matt and Alex unpack a shocking investigation by the Tech Transparency Project that uncovered a massive black market where gig work accounts are bought, sold, and rented.
But the black market is just a symptom. The real problem? A broken system.
We explore the broken appeals process, the lack of transparency, and the high stakes that push gig workers into crisis with no meaningful way to appeal. We close with a look at what needs to change — namely, transparent regulation and collective worker power to hold platforms responsible when livelihoods are on the line.
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iPhone vs. Android: Is Uber's Algorithm Pricing You Differently? – Ep 3
A viral video in India sparked an investigation: Were Uber and Ola charging iPhone users more than Android users? As officials probe consumer price discrimination, Alex and Matt ask the next logical question: What’s happening on the worker side of the app?
In this episode, they unpack how Uber’s complex algorithms might be using parameters like phone type, car model, or even ride acceptance history to shape wages, without explaining to drivers the math behind their wages. From the murky mechanics of “black box” pricing to the unequal power of information in platform work, they explore how small, invisible variables can lead to big differences in pay.
Is this just algorithmic efficiency, or something more troubling?
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Tipping Point: How DoorDash Workers Sparked a $17M Reckoning - Ep 2
DoorDash just settled for $16.75 million over allegations it used customer tips to subsidize driver pay, but is that enough to change the game? In this episode, Alex and Matt unpack what really drove this payout, and why it wasn’t an algorithm audit that made the difference — it was workers organizing.
From grassroots action to policy pressure, they explore how tech-powered gig work isolates individuals — and how breaking that isolation is the first step toward accountability.
Tune in as they ask: What does real transparency look like in the platform economy? And how do you turn individual frustration into collective power?
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Beyond Rides: How Uber’s AI Labeling is Reshaping Work - Ep 1
In this episode, Matt and Alex explore how the company has expanded into AI data labeling, a hidden yet essential task that powers machine learning models. But behind this expansion lies a deeper story of algorithmic wage discrimination, opaque labor conditions, and the growing influence of tech companies on gig work.
Tune in as they dissect the intersection of AI, automation, and worker rights in the
platform economy.
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blogs
Our Data-Driven Analyses and Insights
Impact Analysis of the Massachusetts AG Settlement
8/15/24