Overcoming information overload with circular attention economies - Cosmik Labs

Rethinking the cognitive foundations of the attention economy

The attention economy is the economic system in which human attention is the scarce resource. This literature takes a particular passage in Herbert Simon’s seminal Chapter Designing Organization fo...

How to reclaim your attention from the distraction economy | Psyche Videos

Could you watch this video on full screen, 1x speed, with no distractions? Here are five steps to rebuild your attention span

The Attention Economy and the Collapse of Cognitive Autonomy

Check out the first in a series on social media from Denny Center Student Fellow Rai Hasen Masoud (F'27) to learn more about the attention economy and it's impacts on our democracy.

The engineering manager's attention budget

Every Engineering Manager has 5 jobs - most distribute their 100 'attention points' across only 2-3 of them

Deficient executive control in transformer attention

Abstract Although transformers in large language models (LLMs) effectively implement a self-attention mechanism that has revolutionized natural language processing, they lack an explicit architecture for the executive control of attention found in humans, which is essential for resolving conflicts and selecting relevant information in the presence of competing computations and is critical for adaptive behavior. To investigate the impact of this limitation in LLMs, we employed the classic color Stroop task, widely regarded as the gold standard, to test the executive control of attention in these models. Our results revealed a typical conflict effect of underperformance in terms of accuracy in the incongruent condition (e.g. naming the color of the word RED in blue) compared with the congruent condition (e.g. naming the color of the word RED in red), in short word lists, similar to human performance. However, as the length of the word lists increased, performance on the incongruent condition degraded toward near-total performance collapse, even as accuracy in the congruent condition remained excellent, and word reading (e.g. reading the word RED [in red] or RED [in blue], ignoring the color) was near-perfect. These findings demonstrate that transformer attention mechanisms are fundamentally limited in their capacity for conflict resolution across extended contexts, and a failure to up-regulate control adaptively under rising interference. We suggest that incorporating executive control mechanisms akin to those in biological attention is crucial for achieving artificial general intelligence.

The Great Attention Heist | Los Angeles Review of Books

A new book on how attention became a commodity.

Attention and the Relevance Problem

ABSTRACT The relevance problem is the problem of how cognitive systems can be sensitive to what is relevant despite relevance being holistic, open‐ended, and context‐sensitive. The problem has typically been applied to higher‐order cognitive processes. In this paper, I argue that there is a hitherto unrecognized relevance problem for perceptual attention. This problem becomes apparent when considering the functions of attention: attention must not only support ongoing task performance but also remain sensitive to opportunities for task switching, latent learning, and context checking. Existing treatments of the relevance problem have largely focused on its task‐relative form: given a task, what is relevant? I argue that attention faces a more general problem that includes sensitivity to factors relevant to other interests and to cues indicating that another activity may be worth pursuing. For such features of the environment to stand out as salient, salience cannot be determined solely by bottom‐up factors and a limited set of occurrent top‐down factors, such as current goals and intentions. Rather, it must reflect the wider (if not the entire) range of an agent's latent interests in a context‐sensitive way. This motivational unencapsulation of attention poses a challenge for both contemporary accounts of attention and suggests that passive attention is much more intelligent than commonly thought.

Attention and the Relevance Problem

ABSTRACT The relevance problem is the problem of how cognitive systems can be sensitive to what is relevant despite relevance being holistic, open‐ended, and context‐sensitive. The problem has typically been applied to higher‐order cognitive processes. In this paper, I argue that there is a hitherto unrecognized relevance problem for perceptual attention. This problem becomes apparent when considering the functions of attention: attention must not only support ongoing task performance but also remain sensitive to opportunities for task switching, latent learning, and context checking. Existing treatments of the relevance problem have largely focused on its task‐relative form: given a task, what is relevant? I argue that attention faces a more general problem that includes sensitivity to factors relevant to other interests and to cues indicating that another activity may be worth pursuing. For such features of the environment to stand out as salient, salience cannot be determined solely by bottom‐up factors and a limited set of occurrent top‐down factors, such as current goals and intentions. Rather, it must reflect the wider (if not the entire) range of an agent's latent interests in a context‐sensitive way. This motivational unencapsulation of attention poses a challenge for both contemporary accounts of attention and suggests that passive attention is much more intelligent than commonly thought.

An attention economic perspective on the future of the information age

In this paper, we apply an attention economic perspective to explain current and predict future trends in our society. We first describe the rise of the attention economy, and we highlight one important mechanism of this economy: a spiral of attention scarcity. Second, we show that an attention economic perspective provides glimpses of a potential future. In particular, we predict an information environment that increasingly targets citizens with attention-grabbing content, form, and technology; a continuing trend toward excessive media consumption levels; and a continuing trend toward inattentive uses of information. We also predict increasing problems of public misinformation and misconceptions; an increased prevalence of certain mental and physical health issues; and an increased reliance on technology to perform mental tasks. At the end of this paper, we show why and how despite these predictions, alternative futures are conceivable. These alternatives largely depend on the behavior of various social actors. We discuss resistance to the attention economy by consumers and producers, a laissez-faire policy toward the attention economy, a policy of taxing attention-seeking efforts, and the promotion of public values in regulatory policies toward the internet.

Searching for explanations: How the Internet inflates estimates of internal knowledge.

Why It's So Hard to Focus at Work (Hint: It's not you, it's your workplace)

The workplace is overloaded with distractions. Here's why (and how) companies should protrect their most important asset – their team's attention.

Deficient executive control in transformer attention

Abstract. Although transformers in large language models (LLMs) effectively implement a self-attention mechanism that has revolutionized natural language p

If You are Asking for Human Attention, Demonstrate Human Effort | Tom Bedor's Blog

An ever-increasing volume of debug investigations, document writing, and code is written by robots. This has created a new etiquette question when working with a team - when is it OK to forward the output of an AI to another human to read?