The document summarizes a tutorial on artificial general intelligence (AGI) and consciousness. The tutorial will cover topics like biologically inspired AGI, consciousness-inspired AGI, and how to construct artificial brains with consciousness. It will include presentations on the neuroscience of consciousness, integrated information theory, and the free energy principle. The goal is to discuss how research into consciousness can help develop AGI and how AGI can help develop a mathematical foundation and "recipe" for aspects of consciousness.

1. Tutorial 2:
AGI and Consciousness
Aug 15, 2017 @ibis, AGI from 13:30-15:30
Nao Tsuchiya, Monash University
Ryota Kanai, Araya Co., Japan

2. Who we are
● Nao Tsuchiya, PhD in Computation and Neural
Systems
○ Neural basis of consciousness
■ Psychophysics, neuroimaging, data analysis,
integrated information theory
● Ryota Kanai, PhD, CEO of Araya
○ Creating artificial consciousness

3. Goal of the tutorial
● Consciousness research -> AGI
○ Biologically inspired AGI
○ Consciousness inspired AGI
○ Artificial consciousness
● AGI -> consciousness
○ Mathematical foundation for aspects of consciousness
○ Recipe for artificial consciousness?

4. Plan
0-15: Introduction by Nao Tsuchiya
Brief overview of neuroscience of consciousness (1990-2017)
Neural correlates of consciousness
Distinction between consciousness and related phenomena
(e.g., attention)
15-30: Functions of consciousness (?) by Ryota Kanai
Phenomenal vs Access consciousness
30-60: Integrated information theory of consciousness by Nao Tsuchiya
How to measure consciousness?
60-90: Free energy principle by Ryota Kanai
How to construct brains with consciousness?
90-120: Discussion (But questions throughout the presentations are welcomed)

5. Brief overview of neuroscience of consciousness
(1990-2017) (Koch et al 2016 Nat Rev Neuro, Deheane 2011 Neuron,
Boly et al 2013 Frontiers)
Progress in
Conceptual analysis
Level and contents of consciousness
Consciousness vs. attention (working memory, reports, …) (Koch &
Tsuchiya 2007 Trends in Cognitive Science, Tsuchiya & Koch 2015 Neurology of
consciousness)
Human neuroimaging (functional activation)
Neural recordings in animals (and humans)
Computational architecture / Theoretical foundation for consciousness
Based on empirical evidence (Integrated information theory - Tononi et al 2016 Nat
Rev Neuro, Global Neuronal Workspace Theory - Deheane)

11. Attention vs consciousness
(Koch & Tsuchiya 2007 Trends in Cognitive Science, Tsuchiya & Koch 2015 Neurology of
consciousness)
Attention : not a unitary concept
Top-down (vs Bottom-up)
Selective amplification (vs non-selective amplification: arousal/alertness)
Goal-oriented, volitionally-controlled & task-dependent
(vs. stimulus-driven, automatic, task independent)
Spatial, feature-based, object-based, temporal

12. Attention vs consciousness
(Koch & Tsuchiya 2007 Trends in Cognitive Science, Tsuchiya & Koch 2015 Neurology of
consciousness)
Consciousness: not a unitary concept
Contents (vs level)
Raw sensory experience, feeling, qualia, phenomenality
(vs reportable, accessed contents)

22. Some statements from AIXI paper
The goal of the agent should be to maximize received rewards. This is called
reinforcement learning. The reason for the asymmetry is that eventually we
(humans) will be the environment with which the agent will communicate and we
want to dictate what is good and what is wrong, not the other way round.