Using Friction As A Feature In Machine Learning Algorithms &

Friction often has a negative connotation in user experience design, but it actually has many benefits. Its best-known use case is mitigating unintended consequences in high-risk scenarios, yet it has a new place in the age of artificial intelligence. Adding strategic friction to interfaces can lead to profound efficiency gains in machine learning algorithms.

Related Keywords

New York , United States , Maggie Appleton , Jakob Nielsen , Maximillian Piras , Marc Andreessen , Joas Pambou , Joel Spolsky , Shane Duggan , Daniel Kahneman Amos Tversky , Archana Madhavan , Adriano Raiano , Steve Krug , Christina Perricone , Lyndon Cerejo , Deanna Alcorn , Adam Mosseri , Netflix , Apple Machine Learning Research Department , Facebook , Linkedin , Instagram , Youtube , New York Times , Twitter , Norman Nielsen Group , Microsoft , Feature In Machine Learning , Senior Product Designer , With The , How To Use , Dont Make Me Think , Ultimate Guide , Product Design Manager , Stitch Fix , Machine Learning Research Department , Reinforcement Learning , Large Language , Pareto Principle , Intent Based Outcome , Peak End Rule , Daniel Kahneman , Amos Tversky , Detect Sentiment In Audio Files , Skills Of Designers That ,