Information Management Blog

The AIIM Blog

Keep your finger on the pulse of Intelligent Information Management with industry news, trends, and best practices.

Blog Feature

AIIM on Air  |  Artificial Intelligence (AI)

[Podcast] The Future of AI is Today

The notion of Artificial Intelligence has pervaded both the business world and popular culture. And, while Hollywood often portrays AI in a future world of smart robots with super-human characteristics, the truth is that AI technologies are already at work fueling important changes in the way business is conducted every day.

Read More

Blog Feature

AIIM on Air  |  Artificial Intelligence (AI)

[Podcast] How Will Humanity Survive the AI Revolution?

How will humanity survive the AI revolution? Simple—we become superhuman. That is the subject of our new AIIM On Air interview with author and researcher Alex Bates.

Read More

14 Steps to a Successful ECM Implementation

Making an ECM implementation successful requires planning and attention to detail. The best way to create the right solution is to identify organizational goals and priorities. Learn how to manage a successful implementation in our free guide.

Blog Feature

AIIM on Air  |  Artificial Intelligence (AI)  |  Cloud

[Podcast] How AI and the Next Generation of the Cloud will Radically Transform Business

The notion of Artificial Intelligence has pervaded both the info and tech worlds. Indeed, it's difficult to have a discussion or a webinar without the topics of AI and Robotic Process Automation coming up. And while it might be tempting to dismiss the implications as something from a Hollywood movie of a future world populated by smart robots with super-human characteristics, the truth is that these technologies are already at work today, fueling important changes in the way we do business.

Read More

Blog Feature

Artificial Intelligence (AI)  |  Robotic Process Automation (RPA)

Why Should You Care About Bots?

Growing up, my parents taught me that there are some questions that aren’t appropriate to ask. Generally, it’s safe to avoid asking people their age, their salary, their weight, their politics, etc. Some questions can make the people being asked feel uncomfortable and so should be avoided.

Read More

Blog Feature

Artificial Intelligence (AI)  |  Privacy

Could a Mobile App Help Contain COVID-19? Balancing Privacy Rights & Public Interest

As the COVID-19 pandemic continues to accelerate, there are some innovative efforts to minimize its impact. In one such approach, a multidisciplinary group of computer scientists, mathematicians, and epidemiologists at the Big Data Institute at Oxford University have developed a mathematical model instantiated in a mobile application that traces contact. Those involved in the project believe it's "..possible to stop the epidemic…if contact tracing is sufficiently fast, sufficiently efficient, and happens at scale." Typically, contact tracing is the most effective way to contain an outbreak. However, with a virus like COVID-19, that's preponderantly transmitted by asymptomatic patients, "classical contact tracing will not be enough to achieve the speed and efficiency needed, but it could be achieved by a contact tracing mobile app if used by a sufficiently large proportion of the population."

Read More

Blog Feature

Artificial Intelligence (AI)  |  Machine Learning

Ethical Use of Data for Training Machine Learning Technology - Part 3

This is the third part of a 3-part series on the Ethical Use of Data for Training Machine Learning Technology by guest authors Andrew Pery and Michael Simon. You can also check out Part 1 and Part 2 from this series. Part 3: Regulatory Efforts in the U.S. Present a Bleak Perspective In the United States, governmental efforts to examine AI have made far less progress as compared to the E.U. The most recent effort at the federal level, the Algorithmic Accountability Act of 2019 (S.1108) sponsored by Senator Ron Wyden (D-OR) and Senator Cory Booker (D-NJ)(with a parallel House bill, H.R.2231, sponsored by Representative Yvette Clark (D-NY)), seeks "To direct the Federal Trade Commission to require entities that use, store, or share personal information to conduct automated decision system impact assessments and data protection impact assessments." The proposed law would require the Federal Trade Commission to enact regulations within the next two years to require companies that make over $50 million per year or collect data on more than 1 million people to perform an "automated decision system impact assessment." However, unlike the GDPR's transparency requirements (no matter how debatable), the proposed bill would not require those assessments to be made public. Despite this lack of a transparency provision, the bill was quickly endorsed by a number of civil rights groups.

Read More