Tuesday, October 26, 2021

Algorithms Increasingly in Sights of Lawmakers

U-S lawmakers investigating how Facebook Inc. and other online platforms shape users’ world views are considering new rules for the artificial intelligence programs blamed for spreading malicious content, reports Bloomberg.

This legislative push is taking on more urgency since a whistle-blower revealed thousands of pages of internal documents revealing how Facebook employees knew that the company’s algorithms prioritizing growth and engagement were driving people to more divisive and harmful content.

Every automated action on the internet -- from ranking content and displaying search results to offering recommendations or showing ads -- is controlled by computer code written by engineers. Some of these algorithms take simple inputs like words or video quality to show certain outputs, while others use artificial intelligence to learn more about people and user-generated content, resulting in more sophisticated sorting.

Both Republicans and Democrats agree there should be some accountability for tech companies, even though Section 230 of the 1996 Communications Decency Act provides broad legal immunity for online platforms.

After wrestling with how to write laws to allow or prohibit certain kinds of speech, which risks running afoul of the First Amendment, regulating automated algorithms is emerging as a possible strategy.

Senator Ed Markey introduced a bill in May he said would “help pull back the curtain on Big Tech, enact strict prohibitions on harmful algorithms, and prioritize justice for communities who have long been discriminated against as we work toward platform accountability.”

Several senators touted their own algorithm-focused bills while questioning Frances Haugen, the Facebook whistle-blower, when she appeared before Congress earlier this month. While Haugen didn’t endorse any specific piece of legislation, she did say the best way to regulate online platforms like Facebook is to focus on systemic solutions, especially transparency and accountability for the machine-learning architecture that powers some of the world’s biggest and most influential companies.

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