OpenAI proposes using reciprocity to encourage AI agents to work together

Many real-world problems require complex coordination between multiple agents — e.g., people or algorithms. A machine learning technique called multi-agent reinforcement learning (MARL) has shown success with respect to this, mainly in two-team games like Go, DOTA 2, StarCraft, hide-and-seek, and capture the flag. But the human world is far messier than games. That’s because humans face social dilemmas at multiple scales, from the interpersonal to the international, and they must decide not only how to cooperate but when to cooperate.

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Facebook’s redoubled AI efforts won’t stop the spread of harmful content

Facebook says it’s using AI to prioritize potentially problematic posts for human moderators to review as it works to more quickly remove content that violates its community guidelines. The social media giant previously leveraged machine learning models to proactively take down low-priority content and left high-priority content reported by users to human reviewers.

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Data Science skills matrix: Why Critical Thinking is most in-demand

Whether you’re brand new to data science, have gotten your feet wet in this field or are an expert, you should know that working with data is all about generating knowledge. There are many handfuls of ways data can make things better. Consider these…

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World Economic Forum: How AI can help combat slavery and free 40 million victims

Despite legalised slavery being abolished in the UK in 1833 and the US fighting a Civil War that culminated in the Abolition Act of 1863, the practice has evolved to thrive all over the modern world. Today, organized criminal networks profit an estimated $150 billion a year from the indentured labour of as many as 40 million victims worldwide.

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