In this week’s roundup, we look at one top research company that’s guiding AI principles, how AI regulations need to be strategically implemented, the increased rate of AI adoption in healthcare, and what nonprofit CEO’s need to know about leading their organization successfully through the COVID-19 pandemic.
Five AI Principles to Put in Practice
by Brandon Purcell, contributing writer for Forrester.com
There is hardly consensus on what AI principles organizations should put into practice. As a leader in the research industry, Forrester is uniquely positioned to use its data to help define these principles. This article recommends five AI principles and digs into existing and planned research to support them. Broadly, the principles address fairness and bias, trust and transparency, accountability, social benefit, and privacy and security. As Forrester further explores the future of AI, the organization is inviting discussion among interested stakeholders.
Doctors Are Using AI to Triage COVID-19 Patients. The Tools May Be Here to Stay.
by Karen Hao, contributing writer for TechnologyReview.com
The COVID-19 pandemic has sped up the rate of adoption of artificial intelligence in healthcare. The technology is helping busy hospitals manage an influx of patients and identify and treat the novel coronavirus. Across the world, healthcare systems are proving to be more open to trying and using AI than they were before the pandemic. In one British hospital, for example, a radiologist was able to fast-track a new AI technology that reads x-rays, which removed an average delay of six hours between taking an x-ray and a human reading it.
One Size Doesn’t Fit All for AI Regulation
by George Matthew, contributing writer for InformationWeek.com
Even the greatest proponents of AI understand that some level of regulation is necessary to ensure ethical practices and address serious concerns such as data privacy. However, this article argues that there should not be a one-size-fits-all approach for all industries and use cases. One of the hurdles to accomplishing this is a lack of AI knowledge depth among government regulatory agencies. The implementation of targeted regulations will require extreme cooperation among companies, regulators, and ethics and privacy experts.
Demonstrating Effective Leadership to Better Serve Your Nonprofit and Donors
by Dennis C. Miller, contributing writer for NonprofitPro.com
In these uncertain times during the coronavirus pandemic, nonprofit organizations, employees, and volunteers are understandably anxious. This is the time for CEOs and other leaders to step up and put additional thought into how you do so effectively. The author recommends strategies such as acknowledging the widespread anxiety, welcoming open communication, and, yes, even self-care. And, the article stresses, nonprofit leaders cannot over-communicate with their staff and donors throughout every stage of the crisis.
What Is Marketing Intelligence? Definition, Best Practices, Use Cases and Tools
by Katie Robbert, contributing writer for MartechAdvisor.com
Marketing intelligence fits neatly in a framework of business intelligence, which explains the “why” of marketing. Marketing intelligence, on the other hand, relates to the “what” of marketing. In advanced marketing, artificial intelligence provides the “how” of marketing and includes machine-based analytics and tracking tools. Marketing intelligence is primarily focused on understanding the data produced by AI techniques and implementing it strategically throughout marketing campaigns. The goal is to make better data-driven decisions at a faster pace and, ultimately, with better results.
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