Steal Your First $100 Million
How Sinwashing Helps Startups Survive Infancy
Starting in the 1990s, venture investors focused heavily on network effects in markets with the potential to be very large. Markets with “network effects” benefit current users as the platform grows. For example, owning the world’s only phone is useless, but the phone becomes valuable as others get them. The same is true of social networks and marketplaces that bring together buyers and sellers. VCs understood that companies with these increasing returns economics would either die fast or dominate a winner-take-all market. This created a powerful incentive to grow fast, even if it meant cutting corners.
A startup that hopes to capture network effects confronts a potentially lethal cold start problem: How to attract buyers without any sellers or sellers without any buyers? Why will anyone check a social network if nobody else uses it? In short, who will buy the first telephone?
To the startup, these are questions of life and death. Strong network effects create a powerful incentive to break legal and ethical norms in order to grow and beg for forgiveness later if and when they survive. (Of course, strong network effects are only one incentive. A handful of startups have always tried to lie, cheat, and steal their way to profitability.)
Call it sinwashing – the practice of violating legal and ethical norms while you are small and apologizing only when you are big enough to pay the fines. Sinwashing falls into some predictable categories.
Scraping Private Data. Early in its existence, Facebook grew fast by prompting users to upload their email contact lists to “find friends,” who were then sent unsolicited invitations that violated spam and privacy laws. Plaxo, Google+, LinkedIn, Clubhouse, and Path accessed or scraped users’s email contacts without explicit consent. Illegally tapping into user’s networks fueled exponential growth for many of these companies. Similarly, Clearview AI collected billions of images from social media without users’ consent to train its facial recognition algorithms because accessing large datasets quickly and cheaply helped them develop machine learning models and scale a large user base.1
Ignoring Regulations. Airbnb violated local regulations in many cities with strict short-term rental laws, such as New York City and Barcelona, where many listings violated local regulations. Tesla skipped regulatory approvals for its Autopilot features in some vehicles to enter markets quickly. Uber scaled rapidly by entering cities worldwide without regulatory approval or taxi licenses. Bird did it with scooters, PayPal studiously avoided banking regulators, and for its first decade, Amazon employed hundreds of lawyers to avoid charging customers sales taxes.
Stealing Intellectual Property. In its early days, Uber built software called “Hell” to obtain driver names from competitors like Lyft and then declared them trade secrets. ZeniMax credibly accused Facebook and Oculus of stealing proprietary technology for its VR headsets to speed up product development. YouTube grew much faster than Google Video because it was dominated by pirated movie content. Canadian publishers and the New York Times sued OpenAI and Anthropic for scraping copyrighted materials to train their AI models. Waymo sued Uber for hiring Anthony Levandowski, who showed up for work with more than 14,000 confidential Waymo files.2
Anti-Competitive Behavior. Uber built a tool called “Greyball” that ringfenced regulators to prevent the detection of behavior Uber knew to be illegal. Facebook used its Onavo VPN system to illegally track its users when accessing Snapchat and other competitors’ apps to suppress competition. Game maker Zynga made real money on “offer walls,” which let players earn in-game currency by completing offers from advertisers that often included hidden subscriptions or services that were difficult to cancel.
Exploiting Labor. DoorDash and Uber classified workers as independent contractors to minimize costs and maximize operational flexibility. Especially in its early days, Amazon pushed intense workloads in fulfillment centers with limited safety protocols. Zynga ran a famously abusive workplace.
Deceiving Funders. Before it collapsed, WeWork used overhyped growth metrics to mislead investors about its business model’s sustainability. Theranos raised $700 million for a technology falsely claiming to revolutionize blood testing by using a few drops of blood to perform hundreds of tests.3
This is hardly an exhaustive list. Companies trying to solve a cold start problem are desperately trying get their flywheel turning. Entrepreneurs figure that the legal and reputational consequences of lying to funders, breaking the law, or violating privacy regulations are easier to deal with than losing their company.
Sinwashing works because in Silicon Valley, rapid growth washes many slates clean. Assuming its leadership stays out of prison, companies typically adhere more closely to laws and ethical norms as they become financially stable. Most face only minor damage to their reputation once the narrative shifts to the company’s achievements.
Sinwashing is a paradox. America distrusts big companies that live long enough to steer more or less within the confines of the law. But too often, we reward desperate startups for picking pockets. They deserve more scrutiny.
In 2018, Uber paid Waymo $245 million and Leveandowski was sentenced to 18 months in federal prison. On his last day in office in January 2020, Trump granted Levandowski a presidential pardon.
The device never worked as claimed, so CEO Elizabeth Holmes is serving an 11-year federal sentence in Texas. Perhaps she was a beat early. Since the Theranos trial, small-volume blood testing that measures thousands of molecules from a single drop of blood has been demonstrated at Stanford and elsewhere.