Infants outperforming AI

A new study shows that babies are better than artificial intelligence at detecting the motivation behind other people’s actions.

Researchers from New York University said the results of the study suggest shortcomings in AI technology, and they believe improvements are needed for AI to fully replicate human behaviour.

“Adults and even infants can easily make reliable inferences about what drives other people’s actions,” said Moira Dillon, an assistant professor in New York University’s Department of Psychology and the senior author of the paper, which appears in the journal Cognition.

“Current AI finds these inferences challenging to make. The novel idea of putting infants and AI head-to-head on the same tasks is allowing researchers to better describe infants’ intuitive knowledge about other people and suggest ways of integrating that knowledge into AI,” she said.

“If AI aims to build flexible, common-sense thinkers like human adults become, then machines should draw upon the same core abilities infants possess in detecting goals and preferences,” said Brenden Lake, an assistant professor in NYU’s Center for Data Science and Department of Psychology and one of the paper’s authors.

It’s been well-established that infants are fascinated by other people — as evidenced by how long they look at others to observe their actions and to engage with them socially. In addition, previous studies focused on infants’ “common-sense psychology” — their understanding of the intentions, goals, preferences and rationality underlying others’ actions — have indicated that infants are able to attribute goals to others and expect others to pursue goals rationally and efficiently. The ability to make these predictions is foundational to human social intelligence.

Conversely, “common-sense AI” — driven by machine-learning algorithms — predicts actions directly. This is why, for example, an ad touting San Francisco as a travel destination pops up on the computer screen after the user read a news story on a newly elected city official. However, what AI lacks is flexibility in recognising different contexts and situations that guide human behaviour.

To develop a foundational understanding of the differences between human and AI abilities, the researchers conducted a series of experiments with 11-month-old infants and compared their responses to those yielded by state-of-the-art learning-driven neural-network models.

To do so, they deployed the previously established “Baby Intuitions Benchmark” (BIB) — six tasks probing common-sense psychology. BIB was designed to allow for testing both infant and machine intelligence, allowing for a comparison of performance between infants and machines and, significantly, providing an empirical foundation for building human-like AI.

Specifically, infants on Zoom watched a series of videos of simple animated shapes moving around the screen — similar to a video game. The shapes’ actions simulated human behaviour and decision-making through the retrieval of objects on the screen and other movements. Similarly, the researchers built and trained learning-driven neural-network models — AI tools that help computers recognise patterns and simulate human intelligence — and tested the models’ responses to the exact same videos.

Their results showed that infants recognise human-like motivations even in the simplified actions of animated shapes. Infants predict that these actions are driven by hidden but consistent goals — for example, the on-screen retrieval of the same object no matter what location it was in, and the movement of that shape efficiently even when the surrounding environment changes. Adopting a “surprise paradigm” to study machine intelligence allows for direct comparisons between an algorithm’s quantitative measure of surprise and a well-established human psychological measure of surprise — infants’ looking time. The models showed no such evidence of understanding the motivations underlying such actions, revealing that they are missing key foundational principles of common-sense psychology that infants possess.

“A human infant’s foundational knowledge is limited, abstract and reflects our evolutionary inheritance, yet it can accommodate any context or culture in which that infant might live and learn,” Dillon said.

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