A perspective on future physical AI

From Autonomous Agents to Cognitive Symbionts

Toward AI-Augmented Human Intelligence (AHI)

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Future physical AI will exist as two kinds of individual

AI-augmented human

A person with a cognitive symbiont, an AI that strengthens their own thinking. Through wearables and other devices it talks with them in private and with the world on their behalf, helping with everything from errands to memory, decisions and relationships.

AI as individual

An embodied robot. The AI has a cognitive core, a body and goals of its own, and senses and acts in the world in its own right.

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2023 pilot · 72% retained · n = 410
six months agoNot while the cohort study is running.
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Two questions for the future of AI

Artificial General Intelligence (AGI)

asks how intelligent a machine can be.

chatbotsautonomous agents

scored on what the AI completes

AI-Augmented Human Intelligence (AHI)

asks how much intelligence a machine can enable in a person.

reactive assistantsCognitive Symbionts

scored on what the person can now do

The Cognitive Symbiont

An AI that lives alongside one person. It senses what they sense, keeps their life, models their world and their mind, and brings back the right part of their own context at the right moment.

Its measure is the cognitive gap: what a person could achieve with everything they know, minus what they achieve with the little they can hold in mind at once.

Six properties

  • lifelong
  • embedded
  • real-time
  • private
  • low-friction
  • proactive
  1. Sense and interactBorrowed senses and voice, through the devices a person wears and the traces of their digital life.
  2. KeepLive context, working state and lifelong knowledge, held as one record of a life.
  3. UnderstandA model of the person's situation, mind, relations and goals, on a replaceable backbone.
  4. Live alongsideReal-time, private, proactive participation, with silence as one of its choices.
  5. Act and think withFrom errands to decisions, learning, feelings and other people.
  6. GrowLearning from outcomes, and updating the record, the model and the policy.

Trust around the loop: authorization, privacy, correction, exit

Read the perspective paper for more.