Abstract

This paper shares my takeaways, best practices and mitigation steps to mitigate unfairness and bias while designing machine learning algorithms.

Data science projects go wrong either due to flawed models or insufficiently/ incorrectly trained algorithms or emergent bias on new/ unanticipated contexts. Fairness is a human, not a mathematical decision, grounded in shared ethical beliefs. While machine learning does not make decisions based on feelings and emotions, it does inherit a lot of human biases leading to disparate impact. In this era where consequential decisions are algorithm-based it is imperative that they are fair, not perpetuated without users knowledge. …

Preface

This paper utilizes Fargo Health Group dataset to forecast the demand for heart examinations expected in 2014 for Abbeville Health Center. It outlines how a business problem can be solved using a data-driven decision making approach and explains the methodology, model leveraged, ethical implications and recommendations for Fargo Health Group.

1 Problem Statement

Fargo Health Group faces the following business problems:

• Health Center (HC) staffing is not optimal to meet the overall demand. HCs do not have the capacity to meet the deadline of <30 days for examinations due to lack of examining physicians and human resource constraints.
• Significant amount of revenue is…

Diamond pricing involves a complex mechanism influenced by multiple factors such as carat, cut, color, and price. This article analyzes the correlation between these factors and depicts with visualizations.

Exploratory data analysis
R diamond.csv dataset includes approximately 54K observations with 10 variables including carat, cut, color, clarity, depth, table, price, x (length in mm), y (width in mm), and z (depth in mm). Overall a clean dataset with no missing values or messy data.

Structure of the dataset (R lang)

People v. Collins was a 1968 American robbery trial noted for its misuse of probability and as an example of the prosecutor’s fallacy. (Wikepedia, 2021)

Trial (Source: Wikipedia, 2021)

After a mathematics instructor testified about the multiplication rule for probability, though ignoring conditional probability, the prosecutor invited the jury to consider the probability that the accused (who fit a witness’s description of a black male with a beard and mustache and a Caucasian female with a blond ponytail, fleeing in a yellow car) were not the robbers, suggesting that they estimated the odds as:

Black man with beard 1 in 10
Man with mustache1 in…

Major customers served by Transport for London include domestic and international passengers on all the modes of transportation for its overground, underground services from cycles to river services and everything in between. In addition, TfL customers include contract operators of a bus, river services, and tram.

With TfL’s slogan of “Every journey matters,” they have leveraged Big Data analytics to improve customer engagement. Few ideas include:

• Guide customers on choosing the most efficient and cost-saving route, especially important for international visitors. Make it easier to get cash back on Oyster Card balance at the end of their trips.
• Provide staff…

Two major customer groups of Airbnb include travelers (guests) looking for accommodation and patrons (hosts) looking to offer temporary property rentals.

Ideas to improve customer experience:

• A name could help infer race ad lead to bias in booking decisions. To protect privacy, reconsider hostname and profile picture requirements at the time of booking, with options to be anonymous.
• Implement standards on uploading property pictures and descriptions. Mailbox number, neighborhood description should not be public information.
• Establish automated scans for detecting fraudulent, and suspicious listings.
• Inform hosts of “high-risk” bookings.
• Ensure reviews are not “fudged” and that a majority of those…

In today’s era, any company can become a Big Data company. This article explores similarities between John Deere and Apple Big Data strategies. Few areas are:

Commitment to Revolutionize Lifestyles

John Deere’s strategy with ag-analytics focuses on manufacturing farm equipment that is essentially software with engines. Farm equipment is now more loaded than a standard car. John Deere’s vision is to leverage Big Data analytics and AI so one day farmers will be able to use a fleet of autonomous robotic tools from a command room assisted with a smaller workforce. …