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Tag: Bias

Researcher Develops Algorithm to Make Artificial Intelligence Fairer
A researcher from Queen’s University Belfast has developed an innovative new algorithm that will help make artificial intelligence (AI) fairer and less biased when processing data. Companies often use AI technologies to sift through huge amounts of data in situations such as an oversubscribed job vacancy or in policing when …
Methods of Study Design – Experiments
We all are familiar with experiments, we read about them in books or newspapers. Researchers/ scientists perform experiments to validate their hypothesis/ statements or to test a new product. Unlike …
Methods of Study Design – Experiments
We all are familiar with experiments, we read about them in books or newspapers. Researchers/ scientists perform experiments to validate their hypothesis/ statements or to test a new product. Unlike observational studies, experiments are performed in a controlled environment so that the effect of other external factors/variables can be eliminated …
Bias-Variance Tradeoff Explained
Understanding the Bias-Variance tradeoff at three different levels: simple, intermediate and advanced.In this post, we explain the bias-variance tradeoff in machine learning at three different levels: simple, intermediate and advanced. We will follow up with some illustrative examples and discuss some practical implications in the end.If you can’t explain it …
DataRobot Reports that Nearly Half of AI Professionals are Very to Extremely Concerned about AI Bias
DataRobot, the leader in enterprise AI, released new research revealing that nearly half (42%) of AI professionals across the U.S. and U.K. are “very” to “extremely” concerned about AI bias. The research -- based on a survey of more than 350 U.S. and U.K. executives involved in AI and machine …
Detecting Bias with SHAP
StackOverflow’s annual developer survey concluded earlier this year, and they have graciously published the (anonymized) 2019 results for analysis. They’re a rich view into the experience of software developers around the world — what’s their favorite editor? how many years of experience? tabs or spaces? and crucially, salary. Software engineers’ …
Justified Algorithmic Forgiveness?
Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit deeper into some of the publicly available research regarding algorithmic accountability and forgiveness, specifically around a proprietary black box model used to predict the risk of recidivism, …
Themes and Conferences per Pacoid, Episode 2
Paco Nathan‘s column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI and Economics. Introduction Welcome back to our new monthly series! September has been the busiest part of “Conference Season” with excellent new material to review. Three themes jump out recently. …
On Ingesting Kate Crawford’s “The Trouble with Bias”
Kate Crawford discussed bias at a recent SF-based City Arts and Lectures talk and a recording of the discussion will be broadcast, May 6th, on KQED and local affiliates. Members of Domino were in the live audience for the City Arts talk. This Domino Data Science Field Note provides insights …
Bias: Breaking the Chain that Holds Us Back
Speaker Bio: Dr. Vivienne Ming was named one of 10 Women to Watch in Tech by Inc. Magazine, she is a theoretical neuroscientist, entrepreneur, and author. She co-founded Socos Labs, her fifth company, an independent think tank exploring the future of human potential. Dr. Ming launched Socos Labs to combine …
Detecting Algorithmic Bias and Skewed Decision Making
If we took a hard look at every model ever built for classifying who is the optimal candidate for- -a credit loan -a job promotion -a free scholarship -or any other opportunity, would we see a pattern in certain groups of people being granted these opportunities over others?
Detecting Algorithmic Bias and Skewed Decision Making
If we took a hard look at every model ever built for classifying who is the optimal candidate for- -a credit loan -a job promotion -a free scholarship -or any other opportunity, would we see a pattern in certain groups of people being granted these opportunities over others?
A Challenge to Data Scientists
As data scientists, we are aware that bias exists in the world. We read up on stories about how cognitive biases can affect decision-making. We know that, for instance, a resume with a white-sounding name will receive a different response than the same resume with a black-sounding name, and that …