What are the elements of digital ethics?

Axbom.com has comprehensively charted moral considerations when developing digital products and services that span six foundational categories and comprise of 32 sub-elements. Organisation Machine Environment Supervision Society Human Downloadable PDF, PNG charts available on DropBox.

Responsible AI jobs

Below is a list of responsible AI job boards for individuals interested in pursuing global career opportunities for companies and organizations that strive to prohibit conflicts of interest, require objectivity and are cognizant of bias in AI outcomes. GENERAL (DATA SCIENCE, ENGINEERING, STRATEGY, RESEARCH & GOVERNANCE) Responsible Tech Job Board Tech Jobs for Good Tech […]

188 cognitive biases are at the core of all modern AI/data bias

“AI bias is a bias that mirrors the prejudice of its creators or data, meaning that cognitive biases essentially are the root of all modern AI and data biases”- Kristoffer Gordon Clausen, Data Scientist Cognitive Bias = AI Bias  (for high resolution image of  the 188 cognitive bias codex) Source: Visual Capitalist      

Data Cleaning: DIY or outsource for reducing bias in AI?

“Data’s value hinges on diversity in both the sets of information that make it up and the perspectives necessary to comprehensively interpret it.”– Srujana Kaddevarmuth, Data Science & Value Realization Director at Walmart Labs “The most challenging part of building a new AI system isn’t the algorithms or the models but rather collecting the right […]

Who should be responsible for reducing bias in AI on tech product development teams?

In a utopian world, the answer should be everyone. But, the reality is ownership often defaults to the data science team, where numerous AI projects are in R&D, beta or pilot phase. However, beyond data science/engineering stakeholders, there are increasing opportunities for project managers or QA to help root out bias within the development-design process, […]

What are the dangers of facial recognition?

Facial recognition is already being used to gain entrance to office/apartment buildings, board airplanes, cross international borders, start car engines, unlock mobile phones and, even offer a second layer of biometric identification for digital wallet/payment systems. Below are some resources to understand dangers of facial recognition as their use cases become more widely adopted. 1. […]

What does the future of AI crime look like?

An August 2020 study by Crime Science (which was funded by the Dawes Centre for Future Crime at UCL) identified twenty ways AI could be used to facilitate crime over the next 15 years. These were ranked in order of concern – based on the harm they could cause, the potential for criminal profit or […]

Where can I report Bias in AI incidents or harmful AI outcomes?

“What we really need to do is make sure that life continues into the future. […] It’s best to try to prevent a negative circumstance from occurring than to wait for it to occur and then be reactive.” – Elon Musk The Federal Drug Administration (FDA) has a postmarketing safety surveillance program for all approved […]

Bias in AI GitHub Open Source Toolkits

Toolkits are intended to be supplemental to data scientist accountability AND governance processes required to identify, define, detect and correct potential biases, not stand alone.  This bias in ai/ML fairness github list only serves to provide link references to toolkits being used by companies, research departments and organizations today; it does not endorse or vouch […]