Attention

In cognitive psychology, attention is the concentration of awareness on some phenomenon to the exclusion of other stimuli.

In artificial intelligence research, attention is a machine learning method that determines the relative importance of each component in a sequence relative to the other components in that sequence.

Read More

• 3Blue1Brown - Attention in Transformers
• Incredible AI - Sequence to Sequence with Attention

Relevance of Attention to Risk Management

Attention is relevant to risk management because it is part of decision-making. Identifying, assessing, and communicating risks requires attention to be directed at the right problems.

Decision-Making

Two athletes are engaged in System 1.

In Decision-Making, information is gathered by our senses and cognitively processed so we can act.

For example, when you're playing Ping Pong, you need to make many quick decisions in response to your opponent. At least the range of options is relatively limited.

Thinking Fast and Slow.

Decisions can be differentiated in many ways. One common categorization was popularized by influential behavioral scientist Daniel Kahneman, in Thinking Fast and Slow (2011):

• System 1 can described by words like Fast, Operational, Unconscious, Flow, In-the-moment, Improvisational, Intuitive, Instinctual, Emotional, Test-Time.
• System 2: Slow, Strategic, Conscious, Effortful, Logical, Deliberate, Factual, Step-by-Step, Reasoned.

In System 1, we make decisions quickly, without new deliberation. In System 2, we make slower decisions by generating and testing sequences of logical arguments.

System 1 and 2 can be distinguished by the role of attention in decision-making.

1. React to Attention: In System 1, decisions are made in reaction or response to stimuli. Attention is guided by the environment.
2. Direct Attention: In System 2, decisions are made by effortfully guiding attention to the right questions to construct a logical argument or plan.