The Fellows embarked on their first scientific trip for ICA4 and were hosted by Ecole Normale Superieure de Paris-Saclay **throughout Day 4. The sessions at Saclay included two thought-provoking talks by Xiao-Jing Wang** and Jay McClelland, both of which touched upon the principles underlying cognitive behaviours, as well as the difference between human and machine intelligence. These were followed by a symposium on AI at University Paris-Saclay. The symposium was followed by a half-day event with multiple workshops in which ICA4 mentors discussed major advances and issues surrounding AI with other world-class researchers such as Stanislas Dehaene. Finally, the intellectually intense day came to an end with a talk in which Zaven Paré raised important questions regarding how we will interact with AI algorithms and intelligent robotics in the decades to come...

Efforts to understand the computational principles underlying cognition

Presented by Xiao-Jing Wang

Deep neural networks, despite their recent success, differ from human cognition because they have no internal mental life - instead, they act as complex, nonlinear input-output functions. In humans, the prefrontal cortex (PFC) is known to be crucial for cognitive functions such as working memory, decision making, and executive function. An early avenue of this research involved understanding how persistent neural activity may underlie working memory by sustaining stimulus information in the brain after the sensory cue has disappeared. Such persistence is linked to recurrent connectivity, which is lacking in most deep networks. Wang described his previous research using spiking networks and tools from dynamical systems to understand the attractor dynamics behind this form of memory. In the second half of the talk, he showcased his more recent work which uses recurrent neural networks (RNNs) as a form of a model organism to probe how the PFC may perform multiple cognitive tasks simultaneously. These RNNs can then be used to address questions such as whether the PFC encodes cognitive building blocks in a compositional manner, similar to the psychological concepts of schema.

A different distinction between human intelligence and AI...

Presented by James McClelland

While the latter (in particular machine learning algorithms) learns from statistics on large-scale input data, humans learn to learn from explanations structured by culturally invented systems. Indeed, humans fail to perform in systematic ways, which we would expect if the structure were built into our cognitive functionality. But, McClelland points out that simply building in structure, as proposed by the pioneers of GOFAI, limits flexibility. This structure, McClelland argued, is built by culture. For example, he described a classic study by Scribner and Cole in 1973 which showed that non-Western cultures often lack a concept of absolute number and tend to classify objects based on concrete situations rather than abstract category membership. These authors proposed that Western education creates a context in which certain abstract relational concepts are learned, consistent with McClelland’s later work correlating sudoku puzzle performance to mathematical education level. McClelland closed by reiterating that AI learns by examples but humans learn by explanations and that his explanation-based learning (rather than built-in structure) may underlie our propensity for one-shot learning.

Upon completion of the talks by ICA4 Mentors, Paris-Saclay hosted a half-day event with multiple workshops in which ICA4 mentors and Paris-Saclay researchers discussed major advances and issues surrounding AI. Stanislas Dehaene presented a series of fMRI, MEG, and behavioural evidence that humans use symbolic and recursive strategies on prediction tasks with complex sequences, as compared with monkeys which seem to use a picture-based strategy. In a session focusing on AI and ethics, Paola Tubaro revealed the hidden human workers who provide the hand-labelled training data for products such as Siri. This is due to companies and corporations needing a cheap workforce in the same language, ultimately reproducing historic colonial patterns.

Finally, the intellectually intense day came to an end with a talk in which Zaven Paré discussed his artistic works based on electronic marionettes and his collaborations with robotics specialists in Japan. Paré’s conception of automaton-centred theatre enchants audiences while challenging our tendency towards anthropomorphisation. This raises important questions regarding how we will interact with AI algorithms and intelligent robotics in the decades to come...

Scribe: Alex Cayco Gajic

Chair: Diego Frassinelli