As machine learning projects get more complex, with subtle variants to identify, it becomes crucial to have training data that is human-annotated in a completely unbiased way. Human bias when training data can wreak havoc on the accuracy of your machine learning model. Using the washer/dryer mo...
If gender bias runs deep in the corporate world, that means HR policies are often rife with bias too. Wittenberg-Cox writes that many large companies consider “ambition” to be an important character trait for their leadership candidates. When candidates are seen as “ambitious,” they’re us...
How To Remove Gender Bias From the Hiring ProcessYakowicz, Will
The Augean Stables of Academe: How to Remove the Authoritarian Bias in Universitiesdoi:10.2139/ssrn.3471363Academeauthoritarianismlibertarianismfree worldThe "free world" was the political rhetoric used during the Cold War in contrast to the "communist" countries. However, the "free world" was ...
Here’s how we can reframe thisNPS surveyquestion to remove the unintentional bias: “On a scale of 1-10 (1 being terrible and 10 being incredibly delicious), what do you think of pineapple pizza?” How to avoid:Avoid using vocabulary that conveys specific emotions and try to frame neutral...
Using Free OCR To Copy Text From a PDF With Smallpdf We’ll first show you how to extract text from a PDF using Smallpdf’s online PDF OCR tool. We start here not just because we built the tool and think you’ll love it (yes, we fully acknowledge our bias)—but because it’s...
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The goal of a good client-facing AI model is to deliver a great user experience. There are strategies we can adopt to remove unintentional bias from AI models at several points in the AI development process. Top Eight Ways to Overcome and Prevent AI Bias Algorithmic bias in AI is a pervas...
Many of these processes should have been streamlined right in the app development phase, but little things can slip through unnoticed due to various factors (being too close to the product to evaluate it without bias, being unaware of user expectations, or not having an app quality control syst...
Having either duplicate entries or inconsistent data in your dataset can cause problems with your data analysis. They can introduce bias to your conclusion, which may lead to faulty business decisions. To tackle such errors, you’ll want to identify and remove the duplicate and incomplete entries...