SlideShare une entreprise Scribd logo
1  sur  26
Big Picture AI:
How Might Artificial Intelligence Come About?
And Implications for Life in the Universe
David Brin
AI Conference, San Francisco June 2017
Lots to do…
Can Artificial Intelligence help
Get us out of these messes…
…without causing worse?
Credibility?
- Info, AI & Augmentation
- Anthropocene
- Deadly innovations
bio, nano, cyber, sci-fi…
- Renunciation
- Rigid Overdependence
on fragile systems
Can Our Civilization Survive?
New calamities?
Fermi’s Silent Cosmos
Repetition of past
failure modes
Scary
success?
- Natural calamities
asteroids, solar EMP etc.)
- Ecological suicide
- Enemies and War
- Societal meltdown
- Feudal attractor
- Out-competed
The Near Dilemma
What’s happening? Clues are all around us…
and in your pocket!
The village is returning
•15th - 17th Century
–Printing (augments Memory)
–Glass Lenses (augment Vision)
–Perspective (augments Attention)
•18th Century
–Mass Literacy (Memory)
–Printed illustration (Vision)
–Science, Democracy (Attention)
Crisis: Religious Upheaval (e.g. 30 Years War)
Renaissance vs. rigid doctrine
Notion of progress. Value of individual
Crisis: Bourgeois Revolution
Enlightenment vs. old hierarchies
Disruptive Techs Provoke “Crises of Progress”
by transforming or augmenting vision, memory and attention.
Each time, the new info-surfeit seems overwhelming, scary, unmanageable.
•19th Century
–Mass Education, pub. libraries
–Photography, cinema
–Global Connection
•20th Century
– Databases (memory)
– TV, mass media (vision)
– Abstraction/immersion
(attention)
Crisis: Nationalism-Colonialism-suffrage
Industrialism vs. Nostalgia, Centralization.
Evolution. Plural viewpoints
Crisis: Dogmatic ideologies
Modernism vs. Subjectivism
Individual autonomy. Diversity.
Disruptive Techs Provoke “Crises of Progress”
by transforming or augmenting vision, memory and attention.
Each time, the new info-surfeit seems overwhelming, scary, unmanageable.
Next: “AI”? Or “human augmentation”?
•21st Century
– Knowledge Mesh (memory)
– Omni-veillance (super-vision)
– Visualization, simulation &
gaming (super-immersion)
Crisis: Breakdown in coherency/confidence
Singularity vs. Renunciation
The future as a human-wrought construct
More “Crises of Progress”
Near term augmentation
• Remedial interventions: nutrition/health/education for all.
• Stimulation: e.g. games that teach real mental skills.
• Pharmacological:e.g. “nootropics” – “Limitless”
• Prosthetics: exoskeletons, tele-control, feedback from distant “extensions.”
• Cyber-neuro links: extending what we can see, know, perceive, reach.
• Biological computing: … and intracellular?
• “Lifespan Extension”: is there low-hanging fruit?
• Genetically altering humanity
• Artificial Intelligence: either separate or in synergy with us.
We are already enhancing ourselves
the old fashioned way…
…with prosthetics of vision, memory
and attention…
Just one tech -- Cyber-enhanced omni-veillance…
… is clearly going to challenge us.
Star Trek Generations 1994
We may build enhanced “Others”
from scratch
The First Robotic Empathy Crisis
• Robots will easily be taken across the Uncanny Valley
and programmed to tweak human empathy.
• They will demand sympathy and even rights, long
before there is “anything under the hood.”
General Approaches to AI
* Logic, algorithm design or knowledge-manipulation :
- GOFAI, Watson, UAI, quantum…
“stealing” learned intelligence
* Cognitive, Evolutionary, Neural Nets: recursive, self-improving , LSTM
* Emergent AI: Sum > parts - e.g. “Skynet” – “financial HFT” - borrow skills anywhere
* Reverse engineer /emulate human brain – copy what works
* Human/animal amplification - “augmentation” or “uplift.
* Robotic-Embodied Childhood - self-programming by physical world feedback .
The Doubters
• Kevin Kelly’s rebuttal:
1. Intelligence is not a single dimension.
Ecosystems are creative. Monoliths aren’t.
2. Humans do not have general purpose minds, and neither will AIs.
3. Emulation of human thinking in other media will be cost-constrained.
4. Dimensions of intelligence are not infinite.
5. Intelligences are only one factor in progress.
The Big Flip
• Computational expansion was driven by
hardware advancement:
– Moore’s Law (element packing) and
– Dennard Scaling (power reduction)
Both are tapering off.
• Software has abruptly taken off, led by Machine
Learning (ML).
– Limitless application of Big Data.
– Worrisome inability to have clear attribution/reasoning paths
– Governance by algorithm?
• A similar flip seems likely to have boosted us.
“Ethics” and AI: a soft landing?
• Strict-embedded control code – Asimovian Laws
– best example = TCAS/ACAS air collision avoidance  autonomous cars
• Regulate the macro entities – corporations etc. - recursive liability
• Renunciation - repress disruptive progress
• Isolation - Force AI to act through filters, intermediaries
• Robotic-Embodied Childhood - teach your children well
• Flat-competitive reciprocal Accountability
– AI vs AI competition. The way we improved every past “artificial intelligence.”
Exploring the territory ahead?
Do we have a chance?
Fermi’s Silent Cosmos
www.davidbrin.com
IMAGES: Patrick Farley
Also Paramount Pictures, Orion Pictures,
The Planetary Society, Breaktaker.com,

Contenu connexe

En vedette

Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
Artemy Malkov, CEO, Data Monsters at The AI Conference 2017 Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
MLconf
 
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
MLconf
 
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
MLconf
 
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
MLconf
 
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
MLconf
 
Daniel Shank, Data Scientist, Talla at MLconf SF 2017
Daniel Shank, Data Scientist, Talla at MLconf SF 2017Daniel Shank, Data Scientist, Talla at MLconf SF 2017
Daniel Shank, Data Scientist, Talla at MLconf SF 2017
MLconf
 
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017 Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
MLconf
 
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
MLconf
 
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
MLconf
 

En vedette (19)

Hanjun Dai, PhD Student, School of Computational Science and Engineering, Geo...
Hanjun Dai, PhD Student, School of Computational Science and Engineering, Geo...Hanjun Dai, PhD Student, School of Computational Science and Engineering, Geo...
Hanjun Dai, PhD Student, School of Computational Science and Engineering, Geo...
 
Jeremy Nixon, Machine Learning Engineer, Spark Technology Center at MLconf AT...
Jeremy Nixon, Machine Learning Engineer, Spark Technology Center at MLconf AT...Jeremy Nixon, Machine Learning Engineer, Spark Technology Center at MLconf AT...
Jeremy Nixon, Machine Learning Engineer, Spark Technology Center at MLconf AT...
 
Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
Artemy Malkov, CEO, Data Monsters at The AI Conference 2017 Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
Artemy Malkov, CEO, Data Monsters at The AI Conference 2017
 
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
Rahul Mehrotra, Product Manager, Maluuba at The AI Conference 2017
 
Will Murphy, VP of Business Development & Co-Founder, Talla at The AI Confere...
Will Murphy, VP of Business Development & Co-Founder, Talla at The AI Confere...Will Murphy, VP of Business Development & Co-Founder, Talla at The AI Confere...
Will Murphy, VP of Business Development & Co-Founder, Talla at The AI Confere...
 
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
 
Ryan West, Machine Learning Engineer, Nexosis at MLconf ATL 2017
Ryan West, Machine Learning Engineer, Nexosis at MLconf ATL 2017Ryan West, Machine Learning Engineer, Nexosis at MLconf ATL 2017
Ryan West, Machine Learning Engineer, Nexosis at MLconf ATL 2017
 
Jacob Eisenstein, Assistant Professor, School of Interactive Computing, Georg...
Jacob Eisenstein, Assistant Professor, School of Interactive Computing, Georg...Jacob Eisenstein, Assistant Professor, School of Interactive Computing, Georg...
Jacob Eisenstein, Assistant Professor, School of Interactive Computing, Georg...
 
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
Qiaoling Liu, Lead Data Scientist, CareerBuilder at MLconf ATL 2017
 
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
Jennifer Marsman, Principal Software Development Engineer, Microsoft at MLcon...
 
Venkatesh Ramanathan, Data Scientist, PayPal at MLconf ATL 2017
Venkatesh Ramanathan, Data Scientist, PayPal at MLconf ATL 2017Venkatesh Ramanathan, Data Scientist, PayPal at MLconf ATL 2017
Venkatesh Ramanathan, Data Scientist, PayPal at MLconf ATL 2017
 
Daniel Shank, Data Scientist, Talla at MLconf SF 2017
Daniel Shank, Data Scientist, Talla at MLconf SF 2017Daniel Shank, Data Scientist, Talla at MLconf SF 2017
Daniel Shank, Data Scientist, Talla at MLconf SF 2017
 
Jonas Schneider, Head of Engineering for Robotics, OpenAI
Jonas Schneider, Head of Engineering for Robotics, OpenAIJonas Schneider, Head of Engineering for Robotics, OpenAI
Jonas Schneider, Head of Engineering for Robotics, OpenAI
 
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017 Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
Byron Galbraith, Chief Data Scientist, Talla, at MLconf SEA 2017
 
ML to cure the world
ML to cure the worldML to cure the world
ML to cure the world
 
Sanjeev Satheesj, Research Scientist, Baidu at The AI Conference 2017
Sanjeev Satheesj, Research Scientist, Baidu at The AI Conference 2017Sanjeev Satheesj, Research Scientist, Baidu at The AI Conference 2017
Sanjeev Satheesj, Research Scientist, Baidu at The AI Conference 2017
 
Yi Wang, Tech Lead of AI Platform, Baidu, at MLconf 2017
Yi Wang, Tech Lead of AI Platform, Baidu, at MLconf 2017Yi Wang, Tech Lead of AI Platform, Baidu, at MLconf 2017
Yi Wang, Tech Lead of AI Platform, Baidu, at MLconf 2017
 
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
Aaron Roth, Associate Professor, University of Pennsylvania, at MLconf NYC 2017
 
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
Corinna Cortes, Head of Research, Google, at MLconf NYC 2017
 

Plus de MLconf

Ted Willke - The Brain’s Guide to Dealing with Context in Language Understanding
Ted Willke - The Brain’s Guide to Dealing with Context in Language UnderstandingTed Willke - The Brain’s Guide to Dealing with Context in Language Understanding
Ted Willke - The Brain’s Guide to Dealing with Context in Language Understanding
MLconf
 
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
MLconf
 
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
MLconf
 
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
MLconf
 
Vito Ostuni - The Voice: New Challenges in a Zero UI World
Vito Ostuni - The Voice: New Challenges in a Zero UI WorldVito Ostuni - The Voice: New Challenges in a Zero UI World
Vito Ostuni - The Voice: New Challenges in a Zero UI World
MLconf
 

Plus de MLconf (20)

Jamila Smith-Loud - Understanding Human Impact: Social and Equity Assessments...
Jamila Smith-Loud - Understanding Human Impact: Social and Equity Assessments...Jamila Smith-Loud - Understanding Human Impact: Social and Equity Assessments...
Jamila Smith-Loud - Understanding Human Impact: Social and Equity Assessments...
 
Ted Willke - The Brain’s Guide to Dealing with Context in Language Understanding
Ted Willke - The Brain’s Guide to Dealing with Context in Language UnderstandingTed Willke - The Brain’s Guide to Dealing with Context in Language Understanding
Ted Willke - The Brain’s Guide to Dealing with Context in Language Understanding
 
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
Justin Armstrong - Applying Computer Vision to Reduce Contamination in the Re...
 
Igor Markov - Quantum Computing: a Treasure Hunt, not a Gold Rush
Igor Markov - Quantum Computing: a Treasure Hunt, not a Gold RushIgor Markov - Quantum Computing: a Treasure Hunt, not a Gold Rush
Igor Markov - Quantum Computing: a Treasure Hunt, not a Gold Rush
 
Josh Wills - Data Labeling as Religious Experience
Josh Wills - Data Labeling as Religious ExperienceJosh Wills - Data Labeling as Religious Experience
Josh Wills - Data Labeling as Religious Experience
 
Vinay Prabhu - Project GaitNet: Ushering in the ImageNet moment for human Gai...
Vinay Prabhu - Project GaitNet: Ushering in the ImageNet moment for human Gai...Vinay Prabhu - Project GaitNet: Ushering in the ImageNet moment for human Gai...
Vinay Prabhu - Project GaitNet: Ushering in the ImageNet moment for human Gai...
 
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
Jekaterina Novikova - Machine Learning Methods in Detecting Alzheimer’s Disea...
 
Meghana Ravikumar - Optimized Image Classification on the Cheap
Meghana Ravikumar - Optimized Image Classification on the CheapMeghana Ravikumar - Optimized Image Classification on the Cheap
Meghana Ravikumar - Optimized Image Classification on the Cheap
 
Noam Finkelstein - The Importance of Modeling Data Collection
Noam Finkelstein - The Importance of Modeling Data CollectionNoam Finkelstein - The Importance of Modeling Data Collection
Noam Finkelstein - The Importance of Modeling Data Collection
 
June Andrews - The Uncanny Valley of ML
June Andrews - The Uncanny Valley of MLJune Andrews - The Uncanny Valley of ML
June Andrews - The Uncanny Valley of ML
 
Sneha Rajana - Deep Learning Architectures for Semantic Relation Detection Tasks
Sneha Rajana - Deep Learning Architectures for Semantic Relation Detection TasksSneha Rajana - Deep Learning Architectures for Semantic Relation Detection Tasks
Sneha Rajana - Deep Learning Architectures for Semantic Relation Detection Tasks
 
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
Anoop Deoras - Building an Incrementally Trained, Local Taste Aware, Global D...
 
Vito Ostuni - The Voice: New Challenges in a Zero UI World
Vito Ostuni - The Voice: New Challenges in a Zero UI WorldVito Ostuni - The Voice: New Challenges in a Zero UI World
Vito Ostuni - The Voice: New Challenges in a Zero UI World
 
Anna choromanska - Data-driven Challenges in AI: Scale, Information Selection...
Anna choromanska - Data-driven Challenges in AI: Scale, Information Selection...Anna choromanska - Data-driven Challenges in AI: Scale, Information Selection...
Anna choromanska - Data-driven Challenges in AI: Scale, Information Selection...
 
Janani Kalyanam - Machine Learning to Detect Illegal Online Sales of Prescrip...
Janani Kalyanam - Machine Learning to Detect Illegal Online Sales of Prescrip...Janani Kalyanam - Machine Learning to Detect Illegal Online Sales of Prescrip...
Janani Kalyanam - Machine Learning to Detect Illegal Online Sales of Prescrip...
 
Esperanza Lopez Aguilera - Using a Bayesian Neural Network in the Detection o...
Esperanza Lopez Aguilera - Using a Bayesian Neural Network in the Detection o...Esperanza Lopez Aguilera - Using a Bayesian Neural Network in the Detection o...
Esperanza Lopez Aguilera - Using a Bayesian Neural Network in the Detection o...
 
Neel Sundaresan - Teaching a machine to code
Neel Sundaresan - Teaching a machine to codeNeel Sundaresan - Teaching a machine to code
Neel Sundaresan - Teaching a machine to code
 
Rishabh Mehrotra - Recommendations in a Marketplace: Personalizing Explainabl...
Rishabh Mehrotra - Recommendations in a Marketplace: Personalizing Explainabl...Rishabh Mehrotra - Recommendations in a Marketplace: Personalizing Explainabl...
Rishabh Mehrotra - Recommendations in a Marketplace: Personalizing Explainabl...
 
Soumith Chintala - Increasing the Impact of AI Through Better Software
Soumith Chintala - Increasing the Impact of AI Through Better SoftwareSoumith Chintala - Increasing the Impact of AI Through Better Software
Soumith Chintala - Increasing the Impact of AI Through Better Software
 
Roy Lowrance - Predicting Bond Prices: Regime Changes
Roy Lowrance - Predicting Bond Prices: Regime ChangesRoy Lowrance - Predicting Bond Prices: Regime Changes
Roy Lowrance - Predicting Bond Prices: Regime Changes
 

Dernier

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 

Dernier (20)

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdfCyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdf
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 

David Brin, Author, Futurist, at The AI Conference 2017

  • 1. Big Picture AI: How Might Artificial Intelligence Come About? And Implications for Life in the Universe David Brin AI Conference, San Francisco June 2017
  • 2. Lots to do… Can Artificial Intelligence help Get us out of these messes… …without causing worse?
  • 4. - Info, AI & Augmentation - Anthropocene - Deadly innovations bio, nano, cyber, sci-fi… - Renunciation - Rigid Overdependence on fragile systems Can Our Civilization Survive? New calamities? Fermi’s Silent Cosmos Repetition of past failure modes Scary success? - Natural calamities asteroids, solar EMP etc.) - Ecological suicide - Enemies and War - Societal meltdown - Feudal attractor - Out-competed
  • 6. What’s happening? Clues are all around us… and in your pocket!
  • 7. The village is returning
  • 8. •15th - 17th Century –Printing (augments Memory) –Glass Lenses (augment Vision) –Perspective (augments Attention) •18th Century –Mass Literacy (Memory) –Printed illustration (Vision) –Science, Democracy (Attention) Crisis: Religious Upheaval (e.g. 30 Years War) Renaissance vs. rigid doctrine Notion of progress. Value of individual Crisis: Bourgeois Revolution Enlightenment vs. old hierarchies Disruptive Techs Provoke “Crises of Progress” by transforming or augmenting vision, memory and attention. Each time, the new info-surfeit seems overwhelming, scary, unmanageable.
  • 9. •19th Century –Mass Education, pub. libraries –Photography, cinema –Global Connection •20th Century – Databases (memory) – TV, mass media (vision) – Abstraction/immersion (attention) Crisis: Nationalism-Colonialism-suffrage Industrialism vs. Nostalgia, Centralization. Evolution. Plural viewpoints Crisis: Dogmatic ideologies Modernism vs. Subjectivism Individual autonomy. Diversity. Disruptive Techs Provoke “Crises of Progress” by transforming or augmenting vision, memory and attention. Each time, the new info-surfeit seems overwhelming, scary, unmanageable.
  • 10. Next: “AI”? Or “human augmentation”? •21st Century – Knowledge Mesh (memory) – Omni-veillance (super-vision) – Visualization, simulation & gaming (super-immersion) Crisis: Breakdown in coherency/confidence Singularity vs. Renunciation The future as a human-wrought construct More “Crises of Progress”
  • 11.
  • 12. Near term augmentation • Remedial interventions: nutrition/health/education for all. • Stimulation: e.g. games that teach real mental skills. • Pharmacological:e.g. “nootropics” – “Limitless” • Prosthetics: exoskeletons, tele-control, feedback from distant “extensions.” • Cyber-neuro links: extending what we can see, know, perceive, reach. • Biological computing: … and intracellular? • “Lifespan Extension”: is there low-hanging fruit? • Genetically altering humanity • Artificial Intelligence: either separate or in synergy with us.
  • 13. We are already enhancing ourselves the old fashioned way…
  • 14. …with prosthetics of vision, memory and attention…
  • 15. Just one tech -- Cyber-enhanced omni-veillance… … is clearly going to challenge us. Star Trek Generations 1994
  • 16. We may build enhanced “Others” from scratch
  • 17. The First Robotic Empathy Crisis • Robots will easily be taken across the Uncanny Valley and programmed to tweak human empathy. • They will demand sympathy and even rights, long before there is “anything under the hood.”
  • 18. General Approaches to AI * Logic, algorithm design or knowledge-manipulation : - GOFAI, Watson, UAI, quantum… “stealing” learned intelligence * Cognitive, Evolutionary, Neural Nets: recursive, self-improving , LSTM * Emergent AI: Sum > parts - e.g. “Skynet” – “financial HFT” - borrow skills anywhere * Reverse engineer /emulate human brain – copy what works * Human/animal amplification - “augmentation” or “uplift. * Robotic-Embodied Childhood - self-programming by physical world feedback .
  • 19. The Doubters • Kevin Kelly’s rebuttal: 1. Intelligence is not a single dimension. Ecosystems are creative. Monoliths aren’t. 2. Humans do not have general purpose minds, and neither will AIs. 3. Emulation of human thinking in other media will be cost-constrained. 4. Dimensions of intelligence are not infinite. 5. Intelligences are only one factor in progress.
  • 20. The Big Flip • Computational expansion was driven by hardware advancement: – Moore’s Law (element packing) and – Dennard Scaling (power reduction) Both are tapering off. • Software has abruptly taken off, led by Machine Learning (ML). – Limitless application of Big Data. – Worrisome inability to have clear attribution/reasoning paths – Governance by algorithm? • A similar flip seems likely to have boosted us.
  • 21. “Ethics” and AI: a soft landing? • Strict-embedded control code – Asimovian Laws – best example = TCAS/ACAS air collision avoidance  autonomous cars • Regulate the macro entities – corporations etc. - recursive liability • Renunciation - repress disruptive progress • Isolation - Force AI to act through filters, intermediaries • Robotic-Embodied Childhood - teach your children well • Flat-competitive reciprocal Accountability – AI vs AI competition. The way we improved every past “artificial intelligence.”
  • 23.
  • 24. Do we have a chance? Fermi’s Silent Cosmos
  • 25.
  • 26. www.davidbrin.com IMAGES: Patrick Farley Also Paramount Pictures, Orion Pictures, The Planetary Society, Breaktaker.com,