Emma Pierson and Kowe Kadoma, for Fred Hutchinson Cancer Center, have a short…Tags: algorithm, bias, Coursera, Fred Hutchinson Cancer Center
For The Washington Post, Nitasha Tiku, Kevin Schaul and Szu Yu Chen demonstrate…Tags: AI, bias, Washington Post
Artificial Intelligence (AI) is advancing rapidly, but with great power comes great responsibility. Recognizing the potential pitfalls of bias and discrimination within AI systems, the United Kingdom is taking a proactive step in addressing these challenges. In a groundbreaking move, the UK government has unveiled the Fairness Innovation Challenge, a …
Rotten Tomatoes aggregates movie reviews to spit out a freshness score for each…Tags: bias, movies, ratings, Rotten Tomatoes, Vulture
In this contributed article, Philip Miller, a Customer Success Manager for Progress, discusses the emergence of data bias in AI and what steps business leaders and IT teams can take to avoid it. Specifically, Philip discusses the ways in which data bias arises due to lackluster datasets and how human …
As we continue to rely more on AI-powered technologies, it’s mandatory to address the issue of bias in machine learning. Bias can be present in many different forms, ranging from subtle nuances to more obvious patterns. Unfortunately, this bias can easily seep into machine learning algorithms, creating significant challenges when …
Perhaps to no one’s surprise, generative artificial intelligence models contain bias rooted in…Tags: AI, bias, Bloomberg, Stable Diffusion
Nathaniel Yellin, a 16-year-old student, has concluded a new study that reveals the significant gender bias in the sports media coverage of female athletes and, in particular, college basketball players. Yellin has pursued his passions for sports, data science and inspiring change through the creation of an organization and interactive …
Jenka Gurfinkel discusses the appearance of the American smile in AI-generated images and…Tags: AI, bias, images, midjourney
In this contributed article, Ken Payne, Hyland’s Product Manager for Automation, discusses how organizations can avoid the associated risks when working to implement AI, mitigate data bias, improve data relevance, increase transparency, bolster trust and ultimately lead you on the path to more ethical AI.
Lensa is an app that lets you retouch photos, and it recently added…Tags: AI, bias, images, Lensa, MIT Technology Review, Stable Diffusion
Humans are stupid. We all are, because our brain has been made that way. The most obvious evidence of this built-in stupidity is the different biases that our brain produces. Even so, at least we can be a bit smarter than average, if we are aware of them. This is …
In this contributed article, Alexandra Ebert, Chief Trust Officer at MOSTLY AI, discusses 7 important ways that machine learning models become biased along with techniques for prevention. The power of AI is that it can scale processes so effortlessly that they can amplify both the good and the bad way …
Many colleges use virtual proctoring software in an effort to reduce cheating on…Tags: bias, privacy, proctoring, YR Media
Yuhao Du, Jessica Nordell, and Kenneth Joseph used simulations to study the effects…Tags: bias, gender, New York Times, work
Data is always incomplete.Tags: bias, missing data
This article originally appeared on VentureBeat and is reproduced with permission. Even state-of-the-art automatic speech recognition (ASR) algorithms struggle to recognize the accents of people from certain regions of the world. That’s the top-line finding of a new study published by researchers at the University of Amsterdam, the Netherlands Cancer …
In this start-up highlight piece, we discuss how a CMU professor and his former grad student are ushering in a new era of responsible AI, and helping companies address bias in their AI models. This is a short story of the genesis of Truera.