“As a leading researcher on the ethics of artificial intelligence, Timnit Gebru has long believed that machine-learning algorithms could one day power much of our lives,” writes Emily Bobrow in this profile for the The Wall Street Journal.
“Because machine-learning systems adopt patterns of language and images scraped from the internet, they are often riddled with the internet’s all-too-human flaws” and Gebru is well-known for her work in trying to change that. As Bobrow points out:
“For years, Dr. Gebru earned notoriety as an in-house AI skeptic at big tech companies. In 2018, while she was working at Microsoft, she co-authored a study that found that commercial facial-analysis programs were far more accurate in identifying the gender of white men than Black women, which the researchers warned could lead to damaging cases of false identification. Later, while working at Google, called on companies to be more transparent about the errors baked into their AI models.”
Gebru “hopes for laws that push tech companies to prove their products are safe, just as they do for car manufacturers and drug companies.”
At Distributed Artificial Intelligence Research Institute (DAIR), a non-profit she launched in 2021, “Dr. Gebru is working to call attention to some of the hidden costs of AI, from the computational power it requires to the low wages paid to laborers who filter training data.”
Read the full article here.
Reblogger 