All harmful technologies are a product of unethical design, yet, like car companies in the '70s, today's tech companies would rather blame the user
Lizzie O'Shea / Longreads : Tweets: @carnage4life , @longreads , @sesmith , and @longreads Tweets: Dare Obasanjo / @carnage4life : This is a great read that contains an analogy I really ❤️. Lack of progress in addresing abuse on social media sites & bias in algorithms is a deliberate cost/benefit choice the same way lack of seat belts vs paying out lawsuits was for car OEMs in 1970shttps://t.co/HVOEJiOW79 @longreads : “...these engineers and designers were operating in a business-driven context... They also operated in a fiercely competitive market, where regulators were asleep at the wheel or, worse, captured by the industry.” @Lizzie_OShea @VersoBooks https://longreads.com/... S. E. Smith / @sesmith : We have a long and glorious history of making things that are bad and then blaming the people who use them when they blow up, sometimes literally. https://longreads.com/... @longreads : “Why shouldn't we have crash testing for artificial intelligence? Or a certification process for machine learning? Why shouldn't we have a panel of experts who are required to remain independent from industry...?” @Lizzie_OShea @VersoBooks https://longreads.com/...
Context & Ripple Effects
Lizzie O'Shea's Longreads essay lands in a month when the ethics debate was already turning skeptical: a Slate argument that ethics boards can raise awareness but can't implement good tech had just warned against treating them as moral cover. O'Shea sharpens that into an accusation — slow progress on social media abuse and algorithmic bias isn't inertia but a deliberate cost–benefit choice, with the '70s car industry's refusal to fit seat belts as the template.
The framing echoes the case made in [[a:934779|three recent books arguing big tech grew powerful by ducking regulation rather than through software disruption]], and Dare Obasanjo's amplification of the seat-belt analogy shows the argument traveling beyond academic circles into industry commentary.
First-order effects
- Tech companies leaning on user-blame narratives for abuse and biased algorithms now face a competing account that names their own design and business decisions as the cause — making inaction look like a priced-in choice rather than an unsolved problem.
Second-order effects
- O'Shea's proposed remedies — crash testing for AI, machine-learning certification, independent expert oversight panels — give regulators and legislators a concrete playbook borrowed from auto safety, shifting the burden of proof onto firms that claim self-governance works.
- Ethics boards inside companies come under sharper scrutiny: per the Slate critique, they either gain implementation power or get read as cover, forcing firms to choose between real oversight and reputational exposure.
Third-order effects
- If the auto-industry parallel holds, platform accountability migrates from individual users to designers and regulators — the same trajectory visible as products become inseparable from their makers' conduct, as with the Essential Gem unveiling resurfacing allegations against Andy Rubin.
- The longer pattern points toward formal safety regimes for software — certification and testing bodies analogous to crash standards — replacing the current regime where, as the books argue, growth depended on regulation staying absent.
The trend: Responsibility for technology's harms is migrating from users to the companies and regulators who shape the design itself, with auto-safety-style certification emerging as the model for AI oversight.