how facebook spreads hate--12/4/24

04 Dec 2024

how facebook spreads hate--12/4/24

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Today's selection--from Nexus by Yuval Noah Harari. How Facebook’s algorithms fueled hate in Myanmar.

“Facebook itself relied on this rationale to deflect criticism. It publicly acknowledged only that in 2016-17 ‘we weren't doing enough to help prevent our platform from being used to foment division and incite offline violence.’ While this statement may sound like an admission of guilt, in effect it shifts most of the responsibility for the spread of hate speech to the platform's users and implies that Facebook's sin was at most one of omission—failing to effectively moderate the content users produced. This, however, ignores the problematic acts committed by Facebook's own algorithms.

“The crucial thing to grasp is that social media algorithms are fundamentally different from printing presses and radio sets. In 2016-17, Facebook's algorithms were making active and fateful decisions by themselves. They were more akin to newspaper editors than to printing presses. It was Facebook's algorithms that recommended Wirathu's hate-filled posts, over and over again, to hundreds of thousands of Burmese. There were other voices in Myanmar at the time, vying for attention. Following the end of military rule in 2011, numerous political and social movements sprang up in Myanmar, many holding moderate views. For example, during a flare-up of ethnic violence in the town of Meiktila, the Buddhist abbot Sayadaw U Vithuddha gave refuge to more than eight hundred Muslims in his monastery. When rioters surrounded the monastery and demanded he turn the Muslims over, the abbot reminded the mob of Buddhist teachings on compassion. In a later interview he recounted, ‘I told them that if they were going to take these Muslims, then they'd have to kill me as well.’

“In the online battle for attention between people like Sayadaw U Vithuddha and people like Wirathu, the algorithms were the kingmakers. They chose what to place at the top of the users' news feed, which content to promote, and which Facebook groups to recommend users to join. The algorithms could have chosen to recommend sermons on compassion or cooking classes, but they decided to spread hate-filled conspiracy theories. Recommendations from on high can have enormous sway over people. Recall that the Bible was born as a recommendation list. By recommending Christians to read the misogynist 1 Timothy instead of the more tolerant Acts of Paul and Theda, Athanasius and other church fathers changed the course of history. In the case of the Bible, ultimate power lay not with the authors who composed different religious tracts but with the curators who created recommendation lists. This was the kind of power wielded in the 2010s by social media algorithms. Michael the aid worker commented on the sway of these algorithms, saying that ‘if someone posted something hate-filled or inflammatory it would be promoted the most—people saw the vilest content the most. ... Nobody who was promoting peace or calm was getting seen in the news feed at all.’

969 Movement Flag, led by Ashin Wirathu

“Sometimes the algorithms went beyond mere recommendation. As late as 2020, even after Wirathu's role in instigating the ethnic cleansing campaign was globally condemned, Facebook algorithms not only were continuing to recommend his messages but were autoplaying his videos. Users in Myanmar would choose to see a certain video, perhaps containing moderate and benign messages unrelated to Wirathu, but the moment that first video ended, the Facebook algorithm immediately began auto-playing a hate-filled Wirathu video, in order to keep users glued to the screen. In the case of one such Wirathu video, internal research at Facebook estimated that 70 percent of the video's views came from such auto-playing algorithms. The same research estimated that, altogether, 53 percent of all videos watched in Myanmar were being auto-played for users by algorithms. In other words, people weren't choosing what to see. The algorithms were choosing for them.’

“But why did the algorithms decide to promote outrage rather than compassion? Even Facebook's harshest critics don't claim that Facebook's human managers wanted to instigate mass murder. The executives in California harbored no ill will toward the Rohingya and, in fact, barely knew they existed. The truth is more complicated, and potentially more alarming. In 2016-17, Facebook's business model relied on maximizing ‘user engagement.’ This referred to the time users spent on the platform, as well as to any action they took such as clicking the like button or sharing a post with friends. As user engagement increased, so Facebook collected more data, sold more advertisements, and captured a larger share of the information market. In addition, increases in user engagement impressed investors, thereby driving up the price of Facebook's stock. The more time people spent on the platform, the richer Facebook became. In line with this business model, human managers provided the company's algorithms with a single overriding goal: increase user engagement. The algorithms then discovered by experimenting on millions of users that outrage generated engagement. Humans are more likely to be engaged by a hate-filled conspiracy theory than by a sermon on compassion. So in pursuit of user engagement, the algorithms made the fateful decision to spread outrage.

“Ethnic-cleansing campaigns are never the fault of just one party. There is plenty of blame to share between plenty of responsible parties. It should be clear that hatred toward the Rohingya predated Facebook's entry to Myanmar and that the greatest share of blame for the 2016-17 atrocities lies on the shoulders of humans like Wirathu and the Myanmar military chiefs, as well as the ARSA leaders who sparked that round of violence. Some responsibility also belongs to the Facebook engineers and executives who coded the algorithms, gave them too much power, and failed to moderate them. But crudely, the algorithms themselves are also to blame. By trial and error, they learned that outrage creates engagement, and without any explicit order from above they decided to promote outrage. This is the hallmark of AI—the ability of a machine to learn and act by itself. Even if we assign just 1 percent of the blame to the algorithms, this is still the first ethnic-cleansing campaign in history that was partly the fault of decisions made by nonhuman intelligence. It is unlikely to be the last, especially because algorithms are no longer just pushing fake news and conspiracy theories created by flesh-and-blood extremists like Wirathu. By the early 2020s algorithms had already graduated to creating by themselves fake news and conspiracy theories.

“There is more to say about the power of algorithms to shape politics. In particular, many readers may disagree that the algorithms made independent decisions, and may insist that everything the algorithms did was the result of code written by human engineers and of business models adopted by human executives. This book begs to differ. Human soldiers are shaped by their genetic code and follow orders issued by executives, yet they can still make independent decisions. The same is true of AI algorithms. They can learn by themselves things that no human engineer programmed, and they can decide things that no human executive foresaw. This is the essence of the AI revolution: The world is being flooded by countless new powerful agents.”