Remove 10
Remove 2013 Remove Article Remove Insurance Remove IT
article thumbnail

Chronicle of a Records Manager: Controlling the Chaos of Disaster Response and Recovery

ARMA International

This article will focus on the latter and will reflect on my experiences, observations, and insights as well as the trials and tribulations of the project. I have been a member of the OAR staff at the ANO since March 2013. The plan was to meet the insurance coordinator at the Howard Avenue office at 8:30 a.m. Background.

article thumbnail

The debate on the Data Protection Bill in the House of Lords

Data Protector

What follows below is an edited version of the debate in the House of Lords of the Second Reading of the Data Protection Bill, held on 10 October. New technologies have started innumerable economic revolutions, and the pace of change continues to accelerate. Data is not just a resource for better marketing, better service and delivery.

GDPR 120
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

An Approach to Cybersecurity Risk Oversight for Corporate Directors

Data Matters

* This article first appeared in In-House Defense Quarterly on April 3, 2018. While there may be no perfect path to cybersecurity, this article provides a roadmap for organizations to consider when seeking to mitigate cyber risk. Its prescription can be understood as an enterprise-level, targeted guidance approach.

article thumbnail

Top Cybersecurity Startups to Watch in 2022

eSecurity Planet

This article looks at the top 40 cybersecurity startups to watch in 2022 based on their innovations in new and emerging technologies, length of operation, early funding rounds, scalability, and more. We’ll start with the top 10 overall and then look at other noteworthy startups in a number of markets. Series B SECURITI.ai

article thumbnail

Ethical Use of Data for Training Machine Learning Technology - Part 1

AIIM

NIST's report found "a wide range inaccuracy across developers," and identified two disturbing issues: Higher rates of false positives in US-developed systems for Asian, African American, and "native group" demographics (especially American Indian") faces for one-to-one matching (used for ID verification purposes) of 10 to 100 times.

Insurance 111