Cover image: Polarization by Willow Brugh (2014).
Source: Wikimedia Commons

Maurício Pinheiro

Stuart J. Russell is a Professor of Electrical and Computer Engineering at the University of California, Berkeley. He is known for his research in the field of Artificial Intelligence and has contributed significantly to the advancement of knowledge in this area for over two decades. He is co-author of “Artificial Intelligence: A Modern Approach“, which is widely regarded as the standard technical book on the subject. In addition, Stuart Russell also has a long list of publications in journals and conferences on Artificial Intelligence, and is frequently invited to speak on the subject around the world. He is an active advocate for responsible and ethical research in Artificial Intelligence, and has been a leader in the Artificial Intelligence community in promoting ethical and responsible practices.

In his book “Human Compatible: Artificial Intelligence and the Problem of Control” (2019), Russell presents and discusses the challenges in a future scenario where Artificial Intelligence becomes an essential part of our life. Like Kai-Fu Lee in “AI Superpowers: China, Silicon Valley and the New World” (2018), Russell offers suggestions on how we can minimize the negative consequences of the widespread use of AI in our society.

“If content selection algorithms on social media can lead us to political radicalization, what will happen with much more advanced and efficient AI algorithms?”

Content selection algorithms are computer programs that use information about users to select and display personalized content. The idea is to maximize users’ individual experience by increasing the time they spend on a website or application. The evaluation criterion is known as “Clickthrough“, which measures how many times a user clicks on a certain content.

Several companies use content selection algorithms, including Facebook, Google, Amazon, Netflix, and many others. Facebook, for example, uses content selection algorithms to personalize each user’s news feed, showing the content they find most relevant based on their interaction with the site. Google uses similar algorithms to personalize search results for each user. Amazon uses this technology to recommend products to its customers based on their interests and purchasing behavior. And Netflix uses content selection algorithms to recommend series and movies to its users based on their tastes and viewing history.

These algorithms work using machine learning techniques such as data analysis, data mining and content classification. They process large amounts of information, such as user browsing data, to identify patterns and preferences, and then personalize content for the user. They can lead to the formation of filter bubbles, where users are exposed to a wide variety of content that reflects their prior opinions, further amplifying their opinions. This type of limited exposure can lead to political radicalization as the user is constantly being fed opinions and information that validate their existing beliefs.

For example, imagine a user who is a communist: he will be exposed to an increasingly communist perspective, strengthening his political views. This can further reinforce his political beliefs, leading to your radicalized filter bubble. This dynamic can have serious consequences for society, as it can lead to an increasingly accentuated political polarization, where people are no longer exposed to different or contradictory points of view. This can make dialogue and the peaceful resolution of political conflicts more difficult. Furthermore, lack of exposure to differing viewpoints can increase intolerance and misinformation.

This is just one example of how content selection algorithms can lead to political radicalization. Companies like Facebook and Google use algorithms to personalize the user experience, and there are cases of people claiming to have been radicalized because of repeated exposure to extreme political perspectives on the platform. Therefore, it is important to recognize the potential of content selection algorithms to influence users’ political opinion.

Going back to Russell’s initial question, if content selection algorithms on social media can lead us to political radicalization, what will happen to much more advanced and efficient AI algorithms?

Well, if the current situation with content selection algorithms on social networks is already scary, imagine the future with even more powerful artificial intelligence controlling what we see and what we think. Sounds like a dark and disturbing scenario, doesn’t it? But unfortunately, it is a reality that can become increasingly present. And if these algorithms have a political bias in their programming, the situation could become even more worrying.

“Among the consequences of this are a resurgence of fascism, the dissolution of the social contract that underpins democracies around the world, and potentially the end of the European Union and NATO. Not bad for a few lines of code, even if they get a little human hand . Imagine then what a really smart algorithm would be able to do.”

Human Compatible: Artificial Intelligence and the Problem of Control, Stuart Russell

The Reith Lectures

In his 2021 Reith Lectures Stuart Russell explores the future of AI and asks: how can we get it right?

https://www.bbc.co.uk/sounds/series/m001216k

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