Mary Martin

Note also that this view is consistent with and indeed emerges from the multi-component model of hippocampal contributions to episodic future simulation put forth by Addis and Schacter (2012), which links the hippocampus with distinct components of future simulations, including both retrieval of episodic details and recombining those details.

There is indirect evidence to support this idea. For instance, individuals tend to act in a way that is consistent with or constrained by how they have imagined themselves in those situations (Johnson and Sherman, 1990), implying that some record of that simulation influences later behavior. There is typically a high correspondence of stated... See more

Learned helplessness, the failure to escape shock induced by uncontrollable aversive events, was discovered half a century ago. Seligman and Maier (1967) theorized that animals learned that outcomes were independent of their responses—that nothing they did mattered – and that this learning undermined trying to escape. The mechanism of learned... See more

Our findings suggest that mindfulness may be beneficial for reducing self-reported short-term stress for English speakers from higher-income countries.

Many bad things happened in 2023. You already know them. Many tragic events were so terrible we will never forget them and we shouldn’t. You can easily find them all over the news. But the good things that happened are much harder to encounter, and it is easy to get the impression nothing good happened at all. In order to keep struggling to make... See more

Together, wanting and liking encourage us to pursue rewards. But these sensations can also stand alone, creating situations where you might know that you enjoy something but don’t want to go after it, or where you might have a strong desire for something that you don’t get much pleasure from.

Maybe AI doesn’t raise the bar. Maybe it reveals how low we’ve let the bar drop. In a world where ghosting is normal and attentiveness is rare, a chatbot that listens is radical.

This paper aims to dissect the phenomenon of AI hype in light of its core mechanisms, drawing comparisons between the current wave and historical episodes of AI hype, concluding that the current hype is historically unmatched in terms of magnitude, scale and planetary and social costs. We identify and discuss socio-technical mechanisms fueling AI... See more