No AI without ethics
We are long past pretending technology is a morally neutral undertaking. We neglect the development of an ethical code at our peril.
The Ethics of AI
Can data define a ghost?
Can data prove ghosts are among us?
As Halloween approaches, interest in spooky ghosties increases as much as the Golden Gate’s wind speed. So we took this opportunity to speak to three paranormal investigators, two skeptics, and a physicist in an attempt to examine the supernatural in terms of what we know best: data.
Our Bodies, Our Shelves: The Physiology of Retail and Ecommerce
Understanding How the Brain and the Body React In Data-Driven Shopping Environment
Retail operates in time and space. So although we frequently hear about the psychology of retail, the physiology of retail is often overlooked—and it matters. Both the buying and selling of goods and services operate in the same complex universe of space-time as we physical humans do.
Innovation requires risk, and risk requires leadership
The price of doing nothing is steep, and playing it safe is anything but. The only way to create a culture of innovation is from the top down.
There’s an old saying, “Nobody ever got fired for buying IBM.” Over the years, inertia has changed the meaning of that phrase from “It’s safe to buy quality” to “Nobody ever got fired for avoiding risk.”
So, while a given person may be rewarded for avoiding risks, the company itself can take severe hits for the same thing. And an individual may be rewarded for successfully taking risks, a company’s stock may tank on the basis of an unsuccessful or even just longer term risk potential.
How can we advise companies to take chances—and back their people when they do so—but distinguish between reasonable and unreasonable risk?
Delighting Customers with Data
At the end of each year, Spotify packages and presents data to its users with a marketing campaign called Spotify Wrapped. The data that Spotify gathers from its users are given back to its users in such a way that the users themselves have proven enthusiastic users of that data. This includes not just who your favorite musician or group is, but also indicates what percentile rank you fall into. For instance, you may prove to be not just a top Taylor Swift fan, but rather a “top 1% fan.” This information is sent to users in a graphically attractive package designed to share on social media.
Delight as a marketing and data strategy may seem counterintuitive, given how much hard numbers have been the coin of the realm, but several companies have proven its utility.
Google Careers
I planned and wrote the content that explained Google’s employee culture and its employment process. It united the passion of the company and its employees for design, information, and access with the structure and instructions of the hiring program.
How to Combat Cognitive Bias
Cognitive bias is a bit of a loaded term. It can be a problem for companies striving to become more data-driven, although many cognitive biases are the flip side of an often useful thought process.
A cognitive bias is what Oliver Sibony, author of You’re About to Make a Terrible Mistake!1 and professor at HEC Paris, calls a heuristic gone bad.
How to prepare your business for AI
AI experts at Hewlett Packard Enterprise share insights about where artificial intelligence is headed and how to apply the technology in the business world.
Taming data is one of humankind’s biggest challenges, and it has exceeded our ability to efficiently use reasoning or intuition to make sense of patterns within big data.
“The data flood is becoming a universal problem,” says Dr. Eng Lim Goh, vice president and chief technical officer, HPC and AI, for Hewlett Packard Enterprise. “But with artificial intelligence, a wild guess becomes an intelligent guess.”
If you’re considering AI for a key part of your IT infrastructure, pause here. A few of HPE’s AI experts share their thoughts on where AI is headed, how it can transform a business, and the steps to get started.
Just-in-Time for Real Life
When Winter Storm Uri hit Texas in February of 2021, it crashed all the state’s systems. It did grave damage to the state’s unusual power grid, but it also stressed manufacturers, retailers, and customers. It did so in part because American business has for some time relied on what is called just-in-time (JIT) logistics.
What have crises taught us about the utility and the limitations of JIT logistics? What needs to be changed to retain the virtues of the method? How can organizations insure themselves against JIT’s drawbacks? According to logistics experts, the key is to understand what JIT really means.
What is Trustworthy AI and why is everyone talking about it?
OK, perhaps I’m exaggerating. Maybe not everyone has heard of it. So we’ll tell you what it is and why everyone should be, and probably soon will be, discussing it.
The AI Research group at Hewlett Packard Labs, including Paolo Faraboschi, Hewlett Packard Enterprise Fellow and Director of the AI Research Lab, and distinguished technologists Suparna Bhattacharya and Soumyendu Sarkar, have been working on this mission and how to put it into practice. So I asked them to define it.