Think about this one. It illustrates how much Amazon knows about everyone with a phone or email address.
https://www.makeuseof.com/how-to-send-a-gift-to-someone-on-amazon-without-knowing-their-address/
How to Send a Gift to Someone on Amazon Without Knowing Their Address
Need to send a gift to someone but don’t know their address? Amazon has a new feature to help you with that You can now send someone a gift using their phone number or email address instead of their mailing address.
For the time being, this feature is only available to Amazon Prime members and can only be used when browsing Amazon from a mobile device. The recipient’s delivery address must also be in the continental United States.
Legal complexity? Will every court need permanent tech representatives from every technology company? Is ignorance automatic grounds for a mistrial? (If it is ignorance and not a deliberate lie.)
Judge buys Rittenhouse lawyer’s inane argument that Apple’s pinch-to-zoom manipulates footage
As Kyle Rittenhouse took the stand to answer questions about the sequence of events before he shot and killed a man in Kenosha, Wisconsin, the jury was forced to watch the video evidence play out in miniature — because Rittenhouse’s defense lawyer came up with the wild notion that Apple has “artificial intelligence” that manipulates footage when you pinch-to-zoom on an iPad, and Judge Bruce Schroeder totally bought into that possibility.
“iPads, which are made by Apple, have artificial intelligence in them that allow things to be viewed through three-dimensions and logarithms,” the defense insisted. “It uses artificial intelligence, or their logarithms, [algorithms? Bob] to create what they believe is happening. So this isn’t actually enhanced video, this is Apple’s iPad programming creating what it thinks is there, not what necessarily is there,” they added.
While it’s unclear from a full video of the proceedings (via The Washington Post) whether the judge actually prohibited the prosecution from using an iOS device or otherwise zooming into the footage, the result was the same: instead of using an iPad, the jury wound up watching the original, zoomed-out clips on a Windows machine hooked up to a large TV in the courtroom. The images didn’t fill the TV’s entire screen.
Judge Schroeder argued that it was the prosecution — not the defense — that had the burden of proving that Apple doesn’t use artificial intelligence to manipulate footage, demanding that they provide an expert to testify, and didn’t allow the prosecution to adjourn to find that expert before bringing Rittenhouse up for cross-examination.
Another perspective. (Assumes we still need a human.)
https://hbr.org/2021/11/managing-ai-decision-making-tools
Managing AI Decision-Making Tools
The nature of micro-decisions requires some level of automation, particularly for real-time and higher-volume decisions. Automation is enabled by algorithms (the rules, predictions, constraints, and logic that determine how a micro-decision is made). And these decision-making algorithms are often described as artificial intelligence (AI). The critical question is, how do human managers manage these types of algorithm-powered systems. An autonomous system is conceptually very easy. Imagine a driverless car without a steering wheel. The driver simply tells the car where to go and hopes for the best. But the moment there’s a steering wheel, you have a problem. You must inform the driver when they might want to intervene, how they can intervene, and how much notice you will give them when the need to intervene arises. You must think carefully about the information you will present to the driver to help them make an appropriate intervention.
Your business’s use of AI is only going to increase, and that’s a good thing. Digitalization allows businesses to operate at an atomic level and make millions of decisions each day about a single customer, product, supplier, asset, or transaction. But these decisions cannot be made by humans working in a spreadsheet.
We call these granular, AI-powered decisions “micro-decisions” (borrowed from Taylor and Raden’s “Smart Enough Systems:). They require a complete paradigm shift, a move from making decisions to making “decisions about decisions.” You must manage at a new level of abstraction through rules, parameters, and algorithms. This shift is happening across every industry and across all kinds of decision-making. In this article we propose a framework for how to think about these decisions and how to determine the optimal management model.
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