AI & Trust: It’s Complicated

In a recent report, NIST identifies nine factors it deems necessary to create or support user trust when AI is in action. I add another.
With the power it brings to complex calculations and data analysis, artificial intelligence is driving, literally and figuratively, much of what we see and do, as well as much of what goes on in the background — whether we realize it or not. In its recently released draft report on trust and AI, the National Institute of Standards and Technology (NIST) put it this way: “No longer are we asking automation to do human tasks, we are asking it to do tasks that we can’t.” But like with any newfangled technology, the capability is one thing… trusting the results is something else.

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The Problem with Z: 911 Coordinate Challenges

Here’s why getting Z-axis information has proven to be a bigger challenge than anticipated.
Most often, when calls are made to 911, time is of the essence. Getting a first responder to the right place in the least amount of time is the ultimate and unassailable goal for everyone involved in emergency calling and response. The Federal Communications Commission (FCC) defined criteria and established deadlines for wireless providers as early as 2015—with a 2021 deadline to provide not only X and Y coordinates for mobile devices making 911 calls, but also Z altitude coordinates.

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What European Data Law Changes Mean for Your Enterprise

Following EU regulation changes, enterprise organizations are left without a paddle on how best to manage personal data.
With the number of hacks, breaches and thefts of confidential data (these all sound similar but each is its own form of [insert word here (invasion/violation/hell)] on the rise (think everything from Colonial Pipeline to your local hospital), entities that store, process or, in any way,  take possession of data belonging to citizens of the European Union (from individual college student to ginormous multinational corporation) are in a bind about how such data is to be managed, treated and stored and, most importantly protected.  In two words, “good luck.”

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AI Regulation: Hold Data Bad Actors Accountable

As more entities rely on AI algorithms, governments recognize risks associated with over-reliance on automated decision-making and predictive analytics. Artificial Intelligence (AI) has been present in our professional and civilian lives for a while, but both the European Union (EU) and the U.S. Federal Trade Commission (FTC) have recently taken prominent steps to recognize its power and potential harm. As more entities choose to rely on AI algorithms to predict, recommend, or make decisions based on troves of collected data and specially created algorithms designed to generate sound results, governments recognize that there are clear perils inherent in over-reliance on automated decision-making and predictive analytics.

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Supreme Court Takes on Auto-Dialing

Decision in Facebook case lends clarity — at least for liability purposes —as to what is and isn’t an automatic telephone dial system.
Though decided on April 1, the Supreme Court’s ruling in the case of Facebook v. Duguid et. al was no April Fools for those against the business practice of sending telemarketing text or phone messages via automatic telephone dial systems (ATDS), or auto-dialers. In fact, those in the ATDS business probably uttered a collective sigh of relief — if not laughed outright —based on the court’s decision, which effectively and conclusively limits the definition of ATDS for regulatory purposes. This has been an issue for as long as ATDS matters have been litigated, with various Circuit Courts deciding the question differently. Now, at least, we have some authoritative clarity.

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