Let’s begin by removing ‘black box’ algorithms from core public agencies
Core public agencies, such as those responsible for criminal justice, healthcare, welfare, and education (e.g “high stakes” domains) should no longer use ‘black box’ AI and algorithmic systems.
Source: The 10 Top Recommendations for the AI Field in 2017
In his epic anti-A.I. work from the mid-1970s, “Computer Power and Human Reason,” Mr. Weizenbaum described the scene at computer labs. “Bright young men of disheveled appearance, often with sunken glowing eyes, can be seen sitting at computer consoles, their arms tensed and waiting to fire their fingers, already poised to strike, at the buttons and keys on which their attention seems to be as riveted as a gambler’s on the rolling dice,” he wrote. “They exist, at least when so engaged, only through and for the computers. These are computer bums, compulsive programmers.”
He was concerned about them as young students lacking perspective about life and was worried that these troubled souls could be our new leaders. Neither Mr. Weizenbaum nor Mr. McCarthy mentioned, though it was hard to miss, that this ascendant generation were nearly all white men with a strong preference for people just like themselves. In a word, they were incorrigible, accustomed to total control of what appeared on their screens. “No playwright, no stage director, no emperor, however powerful,” Mr. Weizenbaum wrote, “has ever exercised such absolute authority to arrange a stage or a field of battle and to command such unswervingly dutiful actors or troops.”
Welcome to Silicon Valley, 2017.
Source: Silicon Valley Is Not Your Friend
Three rules for ensuring that A.I. systems don’t run roughshod over humans.
Source: Opinion | How to Regulate Artificial Intelligence
We need to be on guard against the prospect of governments scanning faces to determine sexuality, says author of Straight Jacket Matthew Todd
Source: Why, exactly, would anyone want to use AI to decide whether I’m gay or straight? | Matthew Todd
“If we don’t get women and people of color at the table — real technologists doing the real work — we will bias systems. Trying to reverse that a decade or two from now will be so much more difficult, if not close to impossible. This is the time to get women and diverse voices in so that we build it properly, right? And it can be great. It’s going to be ubiquitous. It’s going to be awesome. But we have to have people at the table.” — Fei-Fei Li
Source: Why we desperately need women to design AI – freeCodeCamp
Elon Musk has signed his name alongside more than 100 others to ask the UN to regulate the use of autonomous weapons systems. The group of concerned engineers, many of whom are respected in the field of AI, is asking the global body to “protect civilians” from “misuse” of AI-driven weapons. They believe that smart, self-guided kill bots would become the tool of choice for despots and tyrants.
Source: Elon Musk urges the UN to limit AI weapons
‘How much should we let algorithms shape our lives?’ is the question at the heart of Ed Finn’s recent book “What Algorithms Want: Imagination in the Age of Computing”. Scanning Silicon Valley, computer science, and the cultural sphere alike it offers a smart and accessible reading of our current moment.
Source: What Algorithms Want – Reflecting on (Human) Agency in an Age of Automation / @mitpress
In 10 years, because AI will make so much money for humanity, we will enter the Age of Plenty, making strides to eradicate poverty and hunger, and giving all of us more spare time and freedom to do what we love.
In 10 years, because AI will replace half of human jobs, we will enter the Age of Confusion, and many people will become depressed as they lose the jobs and the corresponding self-actualization. And many of you will become parents concerned with how to improve education in order to prevent your children from being replaced by AI.
Source: An Engineer’s Guide to the Artificial Intelligence Galaxy | The Fu Foundation School of Engineering & Applied Science – Columbia University
Welcome to the Apple Machine Learning Journal. Here, you can read posts written by Apple engineers about their work using machine learning technologies to help build innovative products for millions of people around the world.
Source: Apple Machine Learning Journal