Q&A with journalist and software developer Meredith Broussard
https://newhumanist.org.uk/articles/5286...mmon-sense
EXCERPT: . . . When do computers get it wrong?
For one thing, computers aren’t capable of using common sense. They are also constrained by hardware and software—in other words, they break. Computational systems are only as good as the people who make them. As humans, we are all slightly flawed—and so are our technological systems.
Should we be concerned about the way that technology is infiltrating so many areas of life?
I’m concerned that we need more nuance to how we talk about tech. The term “artificial intelligence” is vague. When you say “AI,” you might be talking about computational statistics (which are real), or about Arnold Schwarzenegger as the Terminator (which is imaginary). The linguistic confusion gets in the way of understanding each other and also gives rise to a lot of magical thinking around computers. In the book, I show readers exactly what it looks like when someone is “using AI”. Usually when someone says they are using AI, it means they are deploying a specific kind of AI called machine learning. I demonstrate using machine learning to predict who survived the Titanic disaster.
I’m also concerned that we don’t have enough diversity among the people who make technological decisions. In the US, Silicon Valley is overwhelmingly controlled by affluent white libertarian men of a certain age. This lack of diversity tends to emerge in tech systems in unexpected ways. For example, have you seen the viral video about the racist soap dispenser? Someone with light skin waves their hand under the optic sensor on the soap dispenser, and the soap comes out. Someone with dark skin waves their hand under the sensor, and the soap doesn’t come out. Then, the dark skinned person gets a white paper towel and waves it under the sensor—and the soap comes out. The sensor doesn’t pick up the dark skinned person because nobody on the tech team bothered to make sure that the system worked for people with dark skin. As a person of color who’s worked in tech, I have no problem believing that on the entire team of designers, developers, testers, sales and marketing folks, there probably wasn’t a single dark skinned person—and nobody thought this was a problem.
It’s a problem.
This is very similar to the problem of Kodak film in the 1950s, where the film stock was optimised for a colour palette printed on what were called “Shirley cards,” which were photos of a white woman (the first model was called Shirley). Basically, if you had dark skin, up until the 1970s your skin wouldn’t look good on film, because the people who made the ubiquitous technology had decided that your experience with the technology didn’t matter. Remember, this issue with film happened in the 1950s. Now, in 2018, we have new technology—the soap dispenser—that has exactly the same problem of representation, and also bias embedded in the technology. I don’t think that repeating mistakes is the way to move us all toward a better world....
MORE: https://newhumanist.org.uk/articles/5286...mmon-sense
https://newhumanist.org.uk/articles/5286...mmon-sense
EXCERPT: . . . When do computers get it wrong?
For one thing, computers aren’t capable of using common sense. They are also constrained by hardware and software—in other words, they break. Computational systems are only as good as the people who make them. As humans, we are all slightly flawed—and so are our technological systems.
Should we be concerned about the way that technology is infiltrating so many areas of life?
I’m concerned that we need more nuance to how we talk about tech. The term “artificial intelligence” is vague. When you say “AI,” you might be talking about computational statistics (which are real), or about Arnold Schwarzenegger as the Terminator (which is imaginary). The linguistic confusion gets in the way of understanding each other and also gives rise to a lot of magical thinking around computers. In the book, I show readers exactly what it looks like when someone is “using AI”. Usually when someone says they are using AI, it means they are deploying a specific kind of AI called machine learning. I demonstrate using machine learning to predict who survived the Titanic disaster.
I’m also concerned that we don’t have enough diversity among the people who make technological decisions. In the US, Silicon Valley is overwhelmingly controlled by affluent white libertarian men of a certain age. This lack of diversity tends to emerge in tech systems in unexpected ways. For example, have you seen the viral video about the racist soap dispenser? Someone with light skin waves their hand under the optic sensor on the soap dispenser, and the soap comes out. Someone with dark skin waves their hand under the sensor, and the soap doesn’t come out. Then, the dark skinned person gets a white paper towel and waves it under the sensor—and the soap comes out. The sensor doesn’t pick up the dark skinned person because nobody on the tech team bothered to make sure that the system worked for people with dark skin. As a person of color who’s worked in tech, I have no problem believing that on the entire team of designers, developers, testers, sales and marketing folks, there probably wasn’t a single dark skinned person—and nobody thought this was a problem.
It’s a problem.
This is very similar to the problem of Kodak film in the 1950s, where the film stock was optimised for a colour palette printed on what were called “Shirley cards,” which were photos of a white woman (the first model was called Shirley). Basically, if you had dark skin, up until the 1970s your skin wouldn’t look good on film, because the people who made the ubiquitous technology had decided that your experience with the technology didn’t matter. Remember, this issue with film happened in the 1950s. Now, in 2018, we have new technology—the soap dispenser—that has exactly the same problem of representation, and also bias embedded in the technology. I don’t think that repeating mistakes is the way to move us all toward a better world....
MORE: https://newhumanist.org.uk/articles/5286...mmon-sense