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I wrote a book about Design Ethics called Tragic Design

Hacker News

I wrote a book about Design Ethics called Tragic Design

Hey everyone! After two long years of writing along side my co-author, we have finally released the book: Tragic Design. It's about the true impact of bad design and how to fix it. We felt there was a need to shed light on the discussion of Design Ethics by exploring the ways bad design can harm people and offering up solutions. When most of us think about bad design, we think the worst case is lost customers. This book explores the very real impact it has: physical harm, emotional harm, and more. We are excited to have John Maeda writing the Foreword to the book, who has been a long supporter of inclusive design. The book is out right now and I made this website for it: http://www.tragicdesign.com/ Were excited to finally have this out in the hands of designers, engineers, and others making products, and start making an impact on this important issue. Thanks HN - Jonathan

Visit productView on Hacker NewsMay 10, 2017
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: physical · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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