On May 11, 2017 Steve Omohundro joined Christopher Allen, Brian Behlendorf, Mark Miller, and Simone Syed on a panel on blockchains in San Francisco.
https://foresight.org/event/building-better-futures-blockchains/
https://www.hyperledger.org/event/building-better-futures-on-the-blockchain
Here’s the video:
On May 5, 2017, Steve Omohundro gave the TiEcon 2017 Machine Learning Keynote in Santa Clara, California on “The Social Impact and Ethics of AI”. Here are the slides: 170505TIE – Social Impact and Ethics of AI.
On April 8, 2017, Steve Omohundro spoke in the 4th LAST Festival in San Jose, California on “Blockchain for a society based on truth”. Here is the video:
Here are the slides: LAST Blockchain for a Society Based on Truth.
On March 13, 2017, Steve Omohundro gave the concluding talk at the Hive 2017 Annual Summit in Palo Alto, California on “The Social Impact and Ethics of AI”. Here is the video of the talk:
and here are the slides:
On February 15, 2017, Steve Omohundro spoke to the Million AI Startups group about the opportunities in “AI and Games”:
Here is a pdf of the slides for the talk.
Video games are now a $100 billion industry. For comparison, global movie box office revenues for 2017 are estimated at $41.2 billion.
Blizzard’s “Overwatch” has generated $1 billion in revenue (from their Q1 2017 financial statement). It is their fastest growing franchise with 30 million registered players.
AI characters, like Cortana in Halo, are becoming more important to games. DeepMind and Blizzard are about to release a version of StarCraft II as an AI research tool.
There are at least 5 ways in which AI will improve games:
Voting (and other forms of social decision making) are fundamental to our society. Today’s voting machines and technologies are antiquated, inefficient, and insecure. Here’s an excellent 8 minute description by Ron Rivest of how homomorphic encryption could help implement a better system:
Several groups are working to implement this kind of cryptographically secure voting on the blockchain:
In addition to better implementation technology, there are also a number of voting systems which are far superior to the one used in the US. Here’s a nice video describing the problems with “First Past the Post Voting”:
Eric Posner says (http://ericposner.com/quadratic–voting/):
Glen Weyl has uploaded a new version of his paper, QuadraticVoting (written with Steven Lalley), to SSRN, which now includes the completed proofs. Quadratic voting is the most important idea for law and public policy that has emerged from economics in (at least) the last ten years.
Quadratic voting is a procedure that a group of people can use to jointly choose a collective good for themselves. Each person can buy votes for or against a proposal by paying into a fund the square of the number of votes that he or she buys. The money is then returned to voters on a per capita basis. Weyl and Lalley prove that the collective decision rapidly approximates efficiency as the number of voters increases. By contrast, no extant votingprocedure is efficient. Majority rule based on one-person-one-votenotoriously results in tyranny of the majority–a large number of people who care only a little about an outcome prevail over a minority that cares passionately, resulting in a reduction of aggregate welfare.
The applications to law and public policy are too numerous to count. In many areas of the law, we rely on highly imperfect votingsystems (corporate governance, bankruptcy) that are inferior to quadratic voting. In other areas of the law, we require judges or bureaucrats to make valuations while knowing they are not in any position to do so (environmental regulation, eminent domain). Quadratic voting can be used to supply better valuations that aggregate private information of dispersed multitudes. But the most important setting is democracy itself. An incredibly complicated system of institutional self-checking (separation of powers, federalism) and judicially enforced constitutional rights try to correct for the defects of one-person-one-vote, but do so very badly. Can quadratic voting do better? Glen and I argue that it can.
On August 17, 2016 Steve Omohundro spoke to the “Million AI Startups” group about “AI and Human Safety”:
AI and robotics will create $50 trillion of value over the next 10 years according to McKinsey. This is causing their rapid development but six recent events show the need to be careful as they are integrated into human society. In the past few weeks we’ve seen three Tesla autopilot crashes, the Dallas police using a robot to kill a suspect, a Stanford Shopping Center security robot running over a small child, and the first “Decentralized Autonomous Organization” losing $56 million due to a bug in a smart contract. As we move forward with these technologies, we will need to incorporate human values and new principles of security so that their human benefits can be fully realized.
The TED conference, started in 1984, has become the standard bearer for hosting insightful talks on a variety of important subjects. They have made videos of over 1,900 of these talks freely available online and they have been watched more than a billion times! In 2009 they extended the concept to “TEDx Talks”in the same format but hosted by independent organizations all over the world.
On January 6, 2016 Mountain View High School hosted a TEDx event on the theme of “Next Generation: What Will It Look Like?”. They invited both students from the school and external speakers to present. I spoke on “What’s Happening With Artificial Intelligence?”. A video of the talk is available here:
and the slides are available here:
tedx-whats-happening-with-artificial-intelligence
I talked about the multi-billion dollar investments in AI and robotics being made by all the top technology companies and the 50 trillion dollars of value they are expected to create over the next 10 years. The human brain has 86 billion neurons wired up according to the “connectome”. In 1957 Frank Rosenblatt created a teachable artificial neuron called a “Perceptron”. Three-layer networks of artificial neurons were common in 1986 and much more complex “Deep Learning Neural Networks” were being studied by 2007. These networks started winning a variety of AI competitions besting other approaches and often beating human performance. These systems are starting to have a big effect on robot manufacturing, self-driving cars, drones, and other emerging technologies. Deep learning systems which create images, music, and sentences are rapidly becoming more common. There are safety issues but several institutes are now working to address the problems. There are many sources of excellent free resources for learning and the future looks very bright!
Eileen Clegg did wonderful real time visual representations of the talks as they were being given. Here is her drawing of my talk:
Each year Edge, the online “Reality Club”, asks a number of thinkers a question and they publish the short essay answers. This year the question was “What do you consider the most interesting recent scientific news? What makes it important?” The responses are here:
My own essay on “Deep Learning, Semantics, And Society” is here:
On December 8, 2015 Steve Omohundro will be the special guest speaker at the VLAB Annual Holiday Party speaking about “AI, Deep Learning, and the Future of Business”. Followed by the “Chocolate Heads Movement Band”! See you there!
https://www.vlab.org/2015/11/30/celebrate-the-holidays-with-vlab/
Here are the slides:
VLAB – AI, Deep Learning, and the Future of Business
On Saturday, November 28, 2015 at 2:00PM (Santiago, Chile time) Steve Omohundro will speak (remotely) at the Exosphere event “AI Nexus” on:
2:00 PMRemote Speaker: Steve Omohundro – Semantics, Deep Learning and the Transformation of Business
A pdf of the slides is here:
Chile – Semantics, Deep Learning, and the Transformation of Business
The SlideShare version is here:
McKinsey predicts that AI and robotics will create $50 trillion of value over the next 10 years. Many predict that the recent technology of “deep learning” will be a big part of the transformation. Over 250 deep learning startup companies have attracted more than $1 billion of venture investment in the past year. Deep learning systems have recently broken records in speech recognition, image recognition, image captioning, translation, drug discovery and other tasks. Why is this happening now and how is it likely to play out? We review the development of AI and the pendulum swings between the “neats” and the “scruffies”. We describe traditional approaches to semantics through logics and grammars and the new deep learning vector semantics. We relate it to Roger Shepard’s cognitive geometry and the structure of biological networks. We also describe limitations of deep learning for safety and regulation. We show how it fits into the rational agent framework and discuss what the next steps may be.
On November 2, 2015, Steve Omohundro will speak at the Deep Learning Applications Meetup at the Mixtile Lab in Mountain View about “Semantics, Deep Learning, and the Transformation of Business”:
The event is free and all are welcome!
Here are the slides: Semantics, Deep Learning, and the Transformation of Business
by Steve Omohundro, Ph.D.
Deep learning is likely to have a big impact on business. McKinsey predicts that AI and robotics will create $50 trillion of value over the next 10 years. Over $1 billion of venture investment has gone to 250 deep learning startups over the past year. Deep learning systems have recently broken records in speech recognition, image recognition, image captioning, translation, drug discovery and other tasks. Why is this happening now and how is it likely to play out? We review the development of AI and the pendulum swings between the “neats” and the “scruffies”. We describe traditional approaches to semantics through logics and grammars and the new deep learning vector semantics. We relate it to Roger Shepard’s cognitive geometry and the structure of biological networks. We also describe limitations of deep learning for safety and regulation. We show how it fits into the rational agent framework and discuss what the next steps may be.
Vincent Everts is a fascinating Dutch technologist who also travels around the world interviewing interesting people. He has a Tesla car whose software just got a “self-driving” update. We discussed the social impact of autonomous vehicles. On the one hand, it is likely to have positive effects such as reducing car accidents, eliminating parking problems, ameliorating traffic jams, etc. On the other hand, it brings up moral and ethical issues related to autonomous technology: How can we be sure these vehicles will drive safely? How should they decide whose safety to prioritize? Will current truck drivers, taxi drivers, and Uber drivers soon be out of a job? Military drones bring these questions into even sharper focus. And recent reports of Russia developing nuclear-armed drone submarines make them even more pressing.
Vincent asks why, after many failed promises, we should believe AI is really happening now. The history of AI is definitely a cautionary tale: what we thought was easy (eg. vision, language, manipulation) turned out to be hard and what we thought was hard (playing chess, solving logic puzzles) turned out to be easy. But it really does seem like today is different. Recent advances in deep learning neural networks have met or surpassed human performance in a variety of tasks like character recognition, speech recognition, translation tasks, image labeling tasks, drug discovery, etc. McKinsey predicts that the economic impact of these new systems could reach $50 trillion over the next 10 years.
We played with the Amazon Echo and discussed the idea that, like the Tesla, it periodically gets software upgrades which make it smarter and more capable. We talk about the possibility for using new technologies like cryptocurrencies and smart contracts for regulating the new AI systems and extending today’s laws to them. Here’s the video:
And here’s an English version of Vincent’s page about the discussion.
On Wednesday, September 23, 2015 Steve Omohundro will present a talk on “Regulating AI and Robotics” to the “Robotics, Artificial Intelligence, and the Law” Meetup Group led by Stephen Wu, Silicon Valley Law Group:
Here are the slides, here is a link to the audio of the talk, and here is the description:
We are delighted to have Steve Omohundro, Ph.D. present at our Meetup this month. This is a Meetup of the Artificial Intelligence and Robotics Interest Group of the Santa Clara County Bar Association High Technology Law Section, and the Artificial Intelligence Committee of the American Bar Association Section of Science & Technology Law.
About our speaker:
Steve Omohundro has been a scientist, professor, author, software architect, and entrepreneur doing research that explores the interface between mind and matter. He has degrees in Physics and Mathematics from Stanford and a Ph.D. in Physics from U.C. Berkeley. He was a computer science professor at the University of Illinois and cofounded the Center for Complex Systems Research. He published the book “Geometric Perturbation Theory in Physics”, designed the programming languages StarLisp and Sather, wrote the 3D graphics system for Mathematica, and built systems which learn to read lips, control robots, and induce grammars. He is president of both Possibility Research and Self-Aware Systems, a think tank working to ensure that intelligent technologies have a positive impact. His work on positive intelligent technologies was featured in James Barrat’s book “Our Final Invention” and has generated international interest. He serves on the advisory boards of the Cryptocurrency Research Group, the Institute for Blockchain Studies, Design Economics, Dfinity, Cognitalk, and is the chair of the Silicon Valley ACM Artificial Intelligence SIG.
See his TED talk here:
https://www.youtube.com/watch?v=1O2l1dc_ohA
Intro to this month’s topic:
Robot manufacturing, self-driving cars, 3-d printed houses, agricultural drones, etc. are poised to dramatically improve human life and eliminate drudgery. McKinsey predicts that AI and Robotics will create $50 trillion in value over the next 10 years. But these systems also create many new regulatory challenges. We will need new technological and legal governance strategies to receive the benefits without causing harm. When a self-driving car kills someone, who is liable? If I create a harmful robot, I am liable, but if I create an AI system which creates a harmful robot, am I still liable? Already humans are avoiding liability by using automated systems for price fixing, insider trading, discrimination, downloading illegal content, and making illegal drug purchases. Many robotic systems can easily be made anonymous but anonymous drones, self-driving cars, and online bots can be used for extortion, assassination, blackmail, theft, terror, etc. And intelligent systems can behave in unpredictable ways. Recent “deep learning” neural networks create models with huge blindspots. The behavior of advanced autonomous systems will be even less predictable by their creators. Rational systems with simplistic goals exhibit “rational drives” toward self-preservation, resource acquisition, replication, and self-improvement. What is the liability for creating harmful systems? We need to develop new technologies to reliably control these systems and a new regulatory regime to incentivize safe and beneficial behavior. We describe Ethereum’s “Smart Contracts” as a possible technological component. But many additional new ideas are clearly needed.
A dial-in number will be provided no later than the morning of the talk.
Slides: Right before the talk, a link to see any slides the speaker wants to present will be provided. (There may or may not be slides.) This link will expire at the end of the talk, but we will distribute a pdf of the slides by download afterwards.
Please RSVP and let us know by a comment if you are planning to attend in person.
On Thursday, September 24, 2015 at 6:00, ACG Silicon Valley hosted a discussion of “Artificial Intelligence – Potential and Risks” moderated by Mike Malone and with panelists Richard Socher, Steve Omohundro, Moshe Looks, and Douglas Stay:
http://acgsv.org/event/artificial-intelligence-potential-and-risks/
Here’s a video of the highlights of the discussion.
Their description of the evening:
Why did Peter Norvig, Elon Musk, Steve Wozniak, and Stephen Hawking all sign a letter about the “remarkable successes in … speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems?” Because “we cannot predict what we might achieve when [human] intelligence is magnified by the tools Artificial Intelligence may provide.” Deep learning and Convolutional Neural Networks are revolutionizing search, natural language processing and computer vision. Join us to learn what every executive needs to know about Artificial Intelligence.
On September 17, 2015, the psychologist Tom Guarriello interviewed me for his “RoboPsych” podcast:
http://www.robopsych.com/robopsychpodcast/8182015
We talked about the newly-emerging psychology of humans interacting with robots and AI. And, *SPOILER WARNING*, we discussed the first season of the excellent recent AMC/BBC show “Humans”.
The flood of recent movies and TV shows exploring the impact of robots and AI. Early shows like Terminator and Robocop focused on “Us vs. Them”. More recent shows like “Her” and “Humans” explore subtler aspects of the interaction.
The archetype of the “Out of Control Creation”. The Sorcerer’s Apprentice. Stories of Genies giving three wishes but with unintended outcomes. King Midas. The “Uh-Oh!”. Even if you get what you think you want, it may not be what you really want. Adam and Eve as the first out of control creation story. We ourselves are out of control. Fear of the other is a projection of our own darker inner drives.
“Humans” takes place in the present but with a more advanced “Synth” android robot technology. Family dynamics with Synths. The little girl sees the synth as a mother figure. The mother is jealous of the synth. The teenage boy is sexually attracted to the synth. Synths as a memory prosthetic. Synths with consciousness. Synths with subpersonalities.
How close is today’s technology to anything like this? Economic drivers for building AIs that recognize human emotional facial and vocal expressions. Recent Microsoft AI to judge the humor of New Yorker cartoons. Artificial empathy. Jibo and Pepper. Things are moving extremely rapidly. McKinsey estimates $50 trillion dollars of impact in the next 10 years. Deep Learning is used for many functions. Baidu using it for Chinese. If understanding human emotions has economic value, it will soon be in the marketplace.
Humans are not good at determining how emotionally intelligent an entity is. Eliza was an early 1960’s AI system. It used simple pattern matching to mimic a Rogerian therapist. Yet people spent hours talking to it! Deep tendency for people to form attachments to objects. People naming their Roombas. Soldiers attached to their IED-detecting robots. Synths can behave more maturely than humans! Non-Violent Communication.
Synths in the service of marketing for a brand? “Hidden Persuaders” and sexuality in advertising. Brands adopt the “Jester” archetype when they ride on deep primal urges like sexuality. Japan and virtual girlfriends. Japan’s relationship to robots. Robots for elder-care. Belief in robot euthanasia hoax. The uncanny valley. Elder’s experience with robotic companions. Robot pets. Tamagotchi. Sony stopping Aibo robot dog support. Kids don’t learn how to handwrite anymore. Horse riding becoming less common. Future shock. Visions of the future from the past. Approach/Avoidance conflicts.
Creators of these systems want them to have intelligence and creativity but they also want to retain control of them. Are they alive, what rights do they have? Building in safeguards. How can we have confidence that these systems won’t run amok? In Humans, the Synths exhibit ambiguity about their own consciousness. Give the code for consciousness to a human for safekeeping. But Niska secretly keeps her own copy and may want to spread it in Season Two! The Synth’s experiences affect their behavior.
What happens when a system can change its own structure? What is the nature of goals and behavior? Unintended consequences. Basic Rational or AI Drives for self-preservation, resource acquisition, replication, efficiency. We need to be careful as we build systems with their own intentions. Deep mind system that adapts to play video games. When will systems start exhibiting unexpected behavior? Robot “Fail” videos. “Whistling past the graveyard?” When we see goofy behavior, it assuages our fear: “Nothing to see here. Move along.”
Robot soldiers, South Korean autonomous gun turret, drones, etc. “How can we be very sure that these systems are safe?” A conservative strategy: The “Safe-AI Scaffolding Strategy”. Regardless of how smart they are, these systems have to obey the laws of mathematics and physics. Create mathematical proofs of properties of behavior. But proofs are hard. Need AI systems to help us establish safety guarantees. Start with very constrained systems like biohazard labs. Err on the side of caution because we are toying with very powerful forces here.
Psychoanalytic aspects of the Beatrice Synth. Suicidal synths? Humanity vs. being human. Ending of the first season with an anti-synth “We are human” protest and the conscious synths escape by blending in with the humans.
On July 30, 2015 Dan Faggella wrote an article for the Lifeboat Foundation on an interview he did with Steve Omohundro about the implications of AI for the future of industry:
We discussed the huge near term impact on a number of industries. McKinsey estimates $50 trillion of value created over the next 10 years. Gartner predicts one-third of current jobs to be automated in the same time period. Internet of Things, automated cars, automated 18-wheel semis. Heathcare, medicine, 3D printed houses, the legal profession. E-discovery, patent searches, automated contract creation. Liability questions when robots or automated vehicles harm someone. Big data, bots that commit insider trading, price fixing, or purchase illegal items on the darknet. With careful thought and introspection about values we can expand today’s legal and business environment to include automated systems and create a much more efficient and humane future.
On July 22, 2015, Marty Wasserman interviewed Steve Omohundro about “AI, Robots, and Drones” for the local Palo Alto TV cable show “Future Talk TV”. Here is the interview on YouTube:
We discussed the huge economic impact that AI and Robotics are likely to have over the next 10 years, especially manufacturing robots, medicine, business processes, self-driving cars, and military applications. Narrow AI vs. General AI. The 420 Chinese robot companies and manufacturers like Foxconn who are in the process of automating manufacturing and assembly. What should be the balance between robots and human workers? “Any job a robot can do is probably a job you don’t want to do!” Will huge productivity gains from automation be used to uplift everyone? Robot brain surgery and hair replacement surgery. Data mining for improvements in health diagnosis and treatment. Self-driving cars, Uber, moral choices, uses for shipping. Drones for agriculture, detecting forest fires, lifesaving, and medicine delivery. Military drones, drone swarms, mosquito drones, drone boats, drones with guns. Robots to help disabled people, modifying the human body. Bitcoin and the underlying blockchain as a mechanism for decentralized contracts between parties that don’t know or trust one another. The nature of money, there is a quadrillion tons of gold at the center of the earth, what has value? Bitcoin mining, bitcoin millionaires, bubbles, Ethereum, fixing internet security, preparing for the AI Society.
The results suggest that each additional contribution a subject makes to the public good in the first period is tripled over the course of the experiment by other subjects who are directly or indirectly influenced to contribute more as a consequence.
The contagious effect in the study was symmetric; uncooperative behavior also spread, but there was nothing to suggest that it spread any more or any less robustly than cooperative behavior, Fowler said.
Many studies have shown that mindfulness meditation that includes LKM (loving-kindness meditation) can rewire your brain. Practicing LKM is easy. All you have to do is take a few minutes everyday to sit quietly and systematically send loving and compassionate thoughts to: 1) Family and friends. 2) Someone with whom you have tension or a conflict. 3) Strangers around the world who are suffering. 4) Self-compassion, forgiveness and self-love to yourself.
Doing this simple 4-step LKM practice literally rewires your brain by engaging neural connections linked to empathy. You can literally feel the tumblers in your brain shift and open up to empathy by spending just a few minutes going through this systematic LKM practice.
To go along with the film “Terminator Genisys”, Taylor & Francis (the publisher of a popular AI risks paper of mine) created a comic strip about possible risks associated with a sophisticated chess robot:
On April 26, 2015 Daniel Faggella interviewed Steve Omohundro about ethical and safety issues related to AI systems and approaches to developing them safely:
An mp3 of the show is available here:
We talked about several ethical issues that are starting to be relevant today. McKinsey estimates that $50 trillion of value will be created by AI and robotics in the next 10 years. Self-driving cars are being created by lots of companies and look like they may become economically important in the next 10 years. They also introduce a number of ethical issues: Who’s liable when they get into an accident? How should they prioritize who to protect?
3D printed houses are being created by several companies. The legal profession is starting to be impacted by automated discovery, automated patent search, automated contract construction, and many other disruptive technologies. Gartner predicts 1/3 of all jobs will be automated in the next 10 years.
Big data and machine learning is transforming consumer businesses. Recently there was a price fixing lawsuit against several companies selling posters on the internet. It turns out that they were all running bots to algorithmically determine their prices based in part on the prices currently being charged by the other companies. Who’s liable when a bot is colluding to commit price fixing? What about bots committing insider trading? “The AI did it!”
A Swiss artist created a bot to randomly buy things on the darknet using bitcoin. Many of its purchases were illegal and were displayed as part of the art exhibit. The Swiss police waited for the art exhibit to finish and then arrested the bot! They carted the computer away.
We have 3 waves of change coming: AI that transforms the economy, AI that transforms the military, and AI that transforms society in general. AI drones, AI subs, AI soldiers. Concentration of power via robot armies. What is the ethics of all this? I advocate developing these technologies slowly and carefully. But will economic and military arms races force their rapid development?
Over the longer term what will be the role of humans and AI systems in future society? Will there be a rapid singularity? I argue that it would be better to carefully consider our values and to design systems that reflect the kind of future that we want. We are building these systems and there is nothing inevitable about what we create. Our only limit is our imagination.
Doing this will probably be the biggest challenge that humanity has ever faced. Nuclear technology is another dual use technology and we can look at that history to see how we managed to avoid unintended detonations (though we did drop two live hydrogen bombs on North Carolina, fortunately they didn’t go off). The realization that AI could be a dangerous technology is just starting to dawn on large numbers of people. One challenge is that an AI system could in principle be developed on a standard computer in somebody’s basement. Once the technology becomes standard, the analog of “script kiddies” might create versions with harmful goals.
The “Safe-AI Scaffolding Strategy” is an approach to careful development which provides a high confidence of safety at every stage. A future variation of today’s cryptocurrencies like Bitcoin may provide a secure infrastructure for the future AI internet. Safety First!
In the June, 2015 issue of the AI Matters newsletter, George Gregory, Tuna Oezer, and I describe the formation of the ACM SIGAI Bay Chapter. We’ve had some fantastic speakers on natural language understanding, deep learning systems, and the DeepDive machine learning project. A great community is growing which currently has over 600 members. Join us at the next meeting!
On March 26, 2015 Steve Omohundro spoke at the IBM Research Accelerated Discovery Lab in Almaden in the 2015 Distinguished Speaker Series about “AI, Robotics, and Smart Contracts”. There was a lively discussion about the positive and negative impacts of automation and where it is all going. The video is available here:
and the slides are here.
I recently had the privilege to be interviewed about artificial intelligence by teens Henna Hundal and Asya Gonzalez on Express Yourself Teen Radio, the #1 top rated young adult radio program in the world on the Voice America Kids Network:
http://www.voiceamerica.com/episode/85387/the-gift-of-challenges
We had a great discussion the impact of robots on jobs, self-driving cars, AI morality, bitcoin, and what all of this will teach us about consciousness and what it is to be human. Gartner predicts that 1 in 3 jobs will be automated in the next 10 years. “That’s a huge change in society. There are two ways to look at it: One is to say, oh my goodness, all the jobs are going away. What are we going to do? How is it going to work? The other is to say: Any job that a robot can do is probably a job you don’t want to be doing. Let the robots do those jobs! We’ll do more interesting things!”
Erik Moshe interviewed me about “The New Drone Order is Only Beginning: All is Buzzing on the Geopolitical Front”:
Very rapid developments in drones from this $600 hobby drone that can fly 90 miles an hour, to this hobby drone with an attached submachine gun (hmm, that one appears to be CGI, but this one with a handgun is apparently real), to this tiny 18 gram surveillance drone. Lots of important social questions arising from these and from versions with more intelligent control that are now being developed. Even today, they’re pretty hard to shoot down.
On January 27, 2015 Jenn Webb interviewed Steve Omohundro for the O’Reilly Radar Podcast about AI, cryptocurrencies, the blockchain, and ensuring a safe future for humanity:
Bitcoin piqued Omohundro’s interest from the very start, but his excitement built as he started realizing the disruptive potential of the technology beyond currency — especially the potential for smart contracts. He began seeing ways the technology will intersect with artificial intelligence, the area of focus for much of his work:
I’m very excited about what’s happening with the cryptocurrencies, particularly Ethereum. I would say Ethereum is the most advanced of the smart contracting ideas, and there’s just a flurry of insights, and people are coming up every week with, ‘Oh we could use it to do this.’ We could have totally autonomous corporations running on the blockchain that copy what Uber does, but much more cheaply. It’s like, ‘Whoa what would that do?’
I think we’re in a period of exploration and excitement in that field, and it’s going to merge with the AI systems because programs running on the blockchain have to connect to the real world. You need to have sensors and actuators that are intelligent, have knowledge about the world, in order to integrate them with the smart contracts on the blockchain. I see a synthesis of AI and cryptocurrencies and crypto-technologies and smart contracts. I see them all coming together in the next couple of years.
Omohundro spends a great deal of time thinking about how to mitigate the potential dangers of AI. In James Barrat’s book Our Final Invention, Omohundro expressed concerns about those dangers, and he noted in an interview that “we should think carefully about what values we put in or we’ll get something more along the lines of a psychopathic egoistic self-oriented entity.” Omohundro told me he thinks blockchain technology might provide at least part of a solution for avoiding a dystopian future:
I think cryptocurrency has the promise of potentially transforming every aspect of society. One of my concerns about artificial intelligence is that as intelligent systems come into society, they can provide tremendous benefits, but they could also potentially provide harm. I’ve been looking at ways to regulate and make sure that these systems are safe. Some of these technologies, like the blockchain technologies we’ve been talking about here, show the potential for being powerful enough to regulate AI systems so that they behave in good, positive ways.
To help ensure our future AI systems do more good than harm, Omohundro has founded a think-tank project called Self Aware Systems. I asked how the group was approaching the problems and what kinds of solutions they’re formulating:
The key insight was that even very simple, harmless-sounding systems — I like to use the example of something whose goal is to play chess — can give rise to harmful sub goals. In other words, if a system that plays chess can get more compute power, it can play better chess. But, unless it has some reason not to, it will have a sub goal of breaking into other computers and running itself on other machines.
The first step is to realize that, ‘Oh my goodness, something that looks like it’s harmless may actually have dangerous sub goals in it.’ Once you understand that, you can begin to design and choose the goals very, very carefully to make sure that they behave in a good way. If you look at human evolution, the human moral emotions is one example. If somebody behaves in a sociopathic way, people stop wanting to interact with them, and there’s social pressure that pushes them to behave in a more compassionate, cooperative way.
I think we need the same kinds of structures in these AI systems. It’s emerging now, so we don’t have any experience with it. Yet, it’s coming very rapidly. They’re estimating something like $50 trillion of value in the next 10 years from AI and robotics. This technology is likely to be all over our society, and we have to make sure that it behaves in positive and desirable ways.
On Tuesday, April 21, 2015 at 4:00 PM Steve Omohundro will speak at the Artificial Intelligence Center at SRI in Menlo Park hosted by Richard Waldinger.
AI, Robotics, and Smart Contracts
| Steve Omohundro | Possibility Research and Self-Aware Systems | [Home Page] |
Notice: Hosted by Richard Waldinger
Date: Tuesday April 21st, 4pm
Location: EJ228 (SRI E building) (Directions)
Webex:
WebEx and VTC available upon request
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Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating “arms races” in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial “rational drives” of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the “Safe-AI Scaffolding Strategy” for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by the laws of physics, mathematical proof, and cryptographic complexity. “Smart contracts” are a promising decentralized cryptographic technology used in Ethereum and other second-generation cryptocurrencies. They can express economic, legal, and political rules and will be a key component in governing autonomous technologies. If we are able to meet the challenges, AI and robotics have the potential to dramatically improve every aspect of human life. |
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Steve Omohundro has been a scientist, professor, author, software architect, and entrepreneur doing research that explores the interface between mind and matter. He has degrees in Physics and Mathematics from Stanford and a Ph.D. in Physics from U.C. Berkeley. He was a computer science professor at the University of Illinois at Champaign-Urbana and cofounded the Center for Complex Systems Research. He published the book “Geometric Perturbation Theory in Physics”, designed the programming languages StarLisp and Sather, wrote the 3D graphics system for Mathematica, and built systems which learn to read lips, control robots, and induce grammars. He is president of both Possibility Research and Self-Aware Systems, a think tank working to ensure that intelligent technologies have a positive impact. His work on positive intelligent technologies was featured in James Barrat’s book “Our Final Invention” and has generated international interest. He serves on the advisory boards of the Cryptocurrency Research Group, the Institute for Blockchain Studies, and Pebble Cryptocurrency. |
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Please arrive at least 10 minutes early as you will need to sign in by following instructions by the lobby phone at Building E. SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors may park in the parking lots off Fourth Street. Detailed directions to SRI, as well as maps, are available from the Visiting AIC web page. There are two entrances to SRI International located on Ravenswood Ave. Please check the Builing E entrance signage. |
On April 9, 2015, Steve Omohundro spoke to the Stanford Graduate School of Business “High Tech Club” (thank you Damien and Naamah) about “AI, Robotics, and Smart Contracts”. Here are the slides as a pdf file. Many interesting questions and issues were explored. Lots of discussion of the impact for FinTech as AI systems build better models of actual economic activity in the world and act autonomously to trade on information. Discussion on the impact for new venture creation, valuation, and assessment of the likelihood of success. Discussion of “Decentralized Autonomous Organizations” (DAOs) and their impact on the future of business. These autonomous collections of “smart contracts” can buy and sell goods and services and create contracts with other participants in an economy. Emerging blockchain-based platforms like Ethereum (which should launch in the next few months) will enable a whole range of “machine to machine” transactions making up what economist Brian Arthur calls the “second economy”. Lots of discussion of how to regulate this new economy and who should and will be the regulator. Governments tend to avoid proactive governance and to wait until problems arise to begin dealing with them. But these new technologies are being developed so rapidly that we probably need a coherent vision for them well in advance of their deployment.
On April 8, 2015 Steve Omohundro and Cynthia Brian discussed the social and personal implications of artificial intelligence and robotics for the VoiceAmerica internet radio show “Star Style”:
The mp3 is available here:
We discussed a variety of technologies that are on the verge of transforming our lives: self-driving cars, 3D-printed houses, manufacturing robots, and ultimately artificial superintelligences. We talked about how to make sure these systems behave in moral and beneficial ways. We also discussed how to stay positive and constructive when thinking about challenging future possibilities. And the need for people with a wide range of backgrounds and insights to contribute towards creating a positive vision for our human future.
Here is a press release about the show:
http://vapresspass.com/2015/04/10/artificial-intelligence-dr-steve-omohundro-plus-body-shaming/
On Tuesday, April 14, 2015 Steve Omohundro spoke to the Silicon Valley Round Table of the National Association for Business Economics about “Cryptocurrencies, Smart Contracts, and the Future of Economic Interaction”. A pdf file of the slides is here. They presented him with this beautiful plaque:
And we had a fun and insightful discussion. Will cryptocurrencies impact credit card services like Visa? Is bitcoin really money? Is it possible to create cryptocurrencies without huge volatility? Are cryptocurrency derivatives possible? The current world derivatives market has been estimated to be as large as $1.2 quadrillion dollars! Will cryptocurrency derivatives become as large and what effect will that have? Most analyses of the security of cryptocurrencies assume that an attacker is trying to make money. Is it possible to have security against entities, like nation-states, who may have other motivations than making money? Are irreversible smart contracts workable in society (given the possibility of contracts toward antisocial ends)? There are 1.6 quadrillion tons of gold at the center of the earth. Does that impact gold’s value? Will AI-driven high frequency trading impact other markets than just securities?
by Steve Omohundro, Ph.D.
Contracts are society’s programming language. Corporations are defined by contracts with investors, employees, customers, etc. Countries are defined by social contracts with citizens, representatives, corporations, etc. But today’s contracts are confusing and expensive to create and enforce. They are written in bad programming languages and enforced by slow, complex, expensive, and unpredictable mechanisms.
In 1993, Nick Szabo proposed machine executable “Smart Contracts” which can be self-enforcing. The introduction of the “Bitcoin” cryptocurrency in 2008 provided the decentralized “blockchain” infrastructure for implementing these smart contracts. Bitcoin spawned over 500 alternative “altcoin” cryptocurrencies and they have generated both enormous interest and huge volatility.
New “Bitcoin 2.0″ technologies like Ethereum are just about to be released. These will support powerful smart contracting mechanisms and may transform many areas of human interaction. We describe these new technologies and their connection to the “Internet of Things” and emerging AI systems.
Bio: Steve Omohundro has been a scientist, professor, author, software architect, and entrepreneur doing research that explores the interface between mind and matter. He has degrees in Physics and Mathematics from Stanford and a Ph.D. in Physics from U.C. Berkeley. He was a computer science professor at the University of Illinois at Champaign-Urbana and cofounded the Center for Complex Systems Research. He published the book “Geometric Perturbation Theory in Physics”, designed the programming languages StarLisp and Sather, wrote the 3D graphics system for Mathematica, and built systems which learn to read lips, control robots, and induce grammars. He is president of both Possibility Research and Self-Aware Systems, a think tank working to ensure that intelligent technologies have a positive impact. His work on positive intelligent technologies was featured in James Barrat’s book “Our Final Invention” and has generated international interest. He serves on the advisory boards of the Cryptocurrency Research Group, the Institute for Blockchain Studies, and Pebble Cryptocurrency.
The Silicon Valley Chapter of NABE (National Association for Business Economics http://www.Nabe.com) was founded in 1984. If you are interested in Business Economics, please join us – pay for your lunch plus $10 meeting fee, participate in discussions, meet an intelligent, interesting people…
More information at http://svnabe.wordpress.com/
Directions to Palo Alto Golf Course Clubhouse:
Take 101 to the Embarcadero Rd/Oregon Expwy exit
Head east on Embarcadero.
After 0.2 miles, golf course and the restaurant will be on the left.
On March 24, 2015, Steve Omohundro spoke in the Stanford Blockchain Workshop about Smart Contracts and the Internet of Things:
http://crypto.sabir.cc/?page_id=237
IDC predicts the global Internet of Things market will be $7 trillion by 2020 and will include more than 26 billion devices. It will create value through more detailed sensing, tracking, optimization, and decision making. But there are many issues. Do you want to risk hackers controlling the lock on your front door? Your nanny cam? Your stove? Your stereo at 3AM? You can have the best encryption in the world but if a camera watches you type your password, it’s useless. Passwords can also be extracted from audio recordings of you typing on a keyboard. I have an Amazon Echo which I love, but it has seven microphones which are always listening. Perhaps you want your refrigerator to automatically reorder milk when you need it, but what are the rules governing this? A Swiss artist recently created a bot to randomly order possibly illegal things from the darknet. If your devices reveal information, take harmful actions, or behave in illegal ways, who’s liable? The Swiss authorities ended up arresting the bot and taking its hardware into custody! Information, value, constraints, and rules of interaction will need to flow between large numbers of devices from many manufacturers. Cryptocurrencies and smart contracts are natural technologies for securely implementing these transactions but there are many challenging issues to resolve. We need to extend the human legal code to smart contracts, DAOs, and autonomous entities and to better understand the economic consequences of the machine to machine “second economy”.
Thanks Tim Swanson for the photo:
On March 26, 2015 Steve Omohundro gave a talk in the IBM Research 2015 Distinguished Speaker Series at the Accelerated Discovery Lab, IBM Research, Almaden. Here are the slides as a pdf file.
Steve Omohundro has been a scientist, professor, author, software architect, and entrepreneur doing research that explores the interface between mind and matter. He has degrees in Physics and Mathematics from Stanford and a Ph.D. in Physics from U.C. Berkeley. He was a computer science professor at the University of Illinois at Champaign-Urbana and cofounded the Center for Complex Systems Research. He published the book “Geometric Perturbation Theory in Physics”, designed the programming languages StarLisp and Sather, wrote the 3D graphics system for Mathematica, and built systems which learn to read lips, control robots, and induce grammars. He is president of both Possibility Research and Self-Aware Systems, a think tank working to ensure that intelligent technologies have a positive impact. His work on positive intelligent technologies was featured in James Barrat’s book “Our Final Invention” and has generated international interest. He serves on the advisory boards of the Cryptocurrency Research Group, the Institute for Blockchain Studies, and Pebble Cryptocurrency.
by Steve Omohundro, Ph.D.
Contracts are society’s programming language. Corporations are defined by contracts with investors, employees, customers, etc. Countries are defined by social contracts with citizens, representatives, corporations, etc. But today’s contracts are confusing and expensive to create and enforce. They are written in bad programming languages and enforced by slow, complex, expensive, and unpredictable mechanisms.
In 1993, Nick Szabo proposed machine executable “Smart Contracts” which can be self-enforcing. The introduction of the “Bitcoin” cryptocurrency in 2008 provided the decentralized “blockchain” infrastructure for implementing these smart contracts. Bitcoin spawned over 500 alternative “altcoin” cryptocurrencies and they have generated both enormous interest and huge volatility.
New “Bitcoin 2.0” technologies like Ethereum are just about to be released. These will support powerful smart contracting mechanisms and may transform many areas of human interaction. We describe these new technologies and their connection to the “Internet of Things” and emerging AI systems.
On January 29, 2015 Steve Omohundro participated in a discussion of the interaction between AI and machine learning with cryptocurrencies and smart contracts. with Kieren James-Lubin, Mathew Wampler-Doty, Matt Liston, and Ethan Buchman. It was a fun, wide-ranging discussion with great questions from the audience. It was part of the Cryptoeconomicon 1 conference which had a great set of speakers on new cryptocurrency and smart contract ideas.
Here’s a nice summary of the conference by Tim Swanson:
http://www.ofnumbers.com/2015/01/30/cryptoeconomics-for-beginners-and-experts-alike/
On January 27, 2015, Steve Omohundro will speak on “Smart Contracts” at the O’Reilly Radar Summit on “Bitcoin and the Blockchain”. It looks like a great lineup of speakers and there should be lots of fascinating discussions.
The ACM Special Interest Group on Artificial Intelligence recently started publishing a quarterly newsletter called “AI Matters”. We submitted this article to describe some topics that our Bay Area SIGAI Chapter is currently exploring:
Recent developments in “cryptocurrencies” and “smart contracts” are creating new opportunities for applying AI techniques. These economic technologies would benefit from greater real world knowledge and reasoning as they become integrated with everyday commerce. And cryptocurrencies and smart contracts may provide an infrastructure for ensuring that AI systems follow specified legal and safety regulations as they become more integrated into human society.
Humans have attempted to create secret codes since the invention of writing but modern mathematical cryptography has been developed over the past 50 years. Public key cryptography was introduced in 1976 and the first cryptocurrencies were attempted in the early 1980’s (Griffith, 2014). Digital signatures can guarantee that a transfer of digital cash was authorized by its owner, but cannot prevent the owner from spending cash twice.
Several solutions for the double-spending problem have been proposed but the 2008 posting of the “Bitcoin” paper (Nakamoto, 2008) by pseudonymous author(s) Satoshi Nakamoto described the first system which has become widely used. Bitcoin solves the double-spending problem by creating a global decentralized ledger called the “blockchain” which records all transactions and prevents bitcoins from being spent twice. The current value of all bitcoins now exceeds 5 billion U.S. dollars. The bitcoin source code is freely available and 507 other cryptographic coins called “altcoins” have been created on the same principles (Coin Market Cap, 2014). A flurry of bitcoin and altcoin based businesses have also been created ranging from coin miners and exchanges to coffee houses and flower stores (Coin Desk, 2014).
The bitcoin blockchain establishes a decentralized consensus about the order of transactions among a large number of agents who don’t know or trust one another. If this were attempted with a simple consensus mechanism like voting, then dishonest agents could create many copies of themselves to manipulate the vote. Bitcoin prevents this kind of “Sybil” attack by requiring the agents involved in consensus formation to perform expensive computational work called “bitcoin mining”. To manipulate the consensus, a dishonest bitcoin miner would need to perform as much computational work as all the other miners combined. The miners are willing to perform the consensus function because they are rewarded in bitcoins for their efforts.
Bitcoin supports some forms of transaction that go beyond simple transfers of coins from one party to another. For example, it is possible to implement “multi-signature” transactions in which two out of three (or, in general, m out of n) participants must validate a transfer (Bitcoin Wiki, 2014). But bitcoin’s facility for defining contracts is limited.
Contract law has been critical to the formation of sophisticated human societies. Digital, self-enforcing “smart contracts” were proposed by Nick Szabo in 1993 (Szabo, 1997) but the economic and communications infrastructure at that time weren’t adequate to support them.
With the success of Bitcoin, several groups have proposed successor “Bitcoin 2.0” designs that incorporate more sophisticated forms of smart contracts. The most developed of these systems is called “Ethereum” (Ethereum, 2014). It has a blockchain similar to bitcoin’s but has a Turing complete contracting language which executes on the blockchain. This capacity allows complex contracts to be created and automatically enforced.
Ethereum’s facility for complex contracts allows financial exchanges, insurance contracts, financial derivatives, and many other kinds of transactions to be precisely defined and executed. Digital services like the rental of digital storage, computational power, and communication bandwidth are also easy to implement. There are also proposals for extending contracts to include information and interactions in the physical world. These include reputation management, “smart property” ownership records for real estate and vehicles, earthquake or weather insurance, and automated room rental (Buterin, 2014).
Modern corporations are defined by a set of contracts with investors, management, employees, customers, and suppliers. If these contracts are automated, then “Distributed Autonomous Organizations” (DAOs, sometimes also called “Decentralized”) become possible. These entities might buy and sell things, make decisions, and hire and fire contractors without human management. It is also possible to create human-run organizations which make decisions by voting on the blockchain. Adam Levine has proposed “Self-bootstrapped” organizations which issue cryptoequities to investors based on a mission statement and then create themselves using contractors guided by decentralized blockchain voting (Levine, 2014).
The ultimate expression of these ideas is the “Distributed Autonomous Society” (DAS, sometimes also called “Decentralized”)(D’Onofrio, 2014). Many of the current functions of government might be implemented more reliably and cheaply using smart contracts. For example, BitCongress (BitCongress, 2014) is a blockchain based voting system. Other proposals suggest blockchain implementations of taxation, the Federal Reserve, intellectual property, universal basic income, real estate records, etc. (Prisco, 2014).
The social issues raised by these emerging technologies are enormous. The “Internet of Things” is predicted by Gartner to include 26 billion devices and to result in $1.9 trillion in economic value-add by 2020 (Gartner, 2013). Many are predicting the need for a corresponding “Internet of Money” to manage the transactions between these devices. This is likely to involve cryptocurrencies and smart contracts which will then come to interact with every area of our lives.
Simple and easy to write contracts appear to be sufficient for many entirely digital transactions. But as these systems start to interact with the physical world, there is likely to be a need for greater intelligence and real world knowledge in making decisions. AI systems will be needed to translate information from a wide variety of sensors into precise terms that smart contracts can act upon. In the other direction, contracts that lead to physical actions (such as delivery of items) will need to interface with human and robotic agents. For example, farmers might want insurance contracts against harmful weather conditions and a smart contract would need to determine when the payout clause is triggered.
The legal codes of many countries have become quite complex. Several AI projects are trying to create formal digital versions of legal codes (CodeX, 2014). These systems will eventually be used to resolve legal issues and perhaps even act as arbitrators or judges. Sophisticated AI systems with knowledge of the legal system will be used to help craft and simplify new legislation.
Cryptocurrencies and smart contracts may also play a role ensuring that AI systems are beneficial for human society. For example, self-driving cars need to follow the rules of the road, autonomous business creation needs to follow securities laws, and autonomous markets need to levy taxes appropriate for transactions’ jurisdictions. Over the next few decades we will need to extend many human laws and ethical norms to automated robotic and intelligent systems (Omohundro, 2014). Cryptocurrencies are a natural way to implement the economic transactions of these systems. Smart contracts are a natural way to impose legal and safety constraints on their behaviors. But many new insights and innovative ideas are needed!
Bitcoin Wiki. (2014, November 9). Contracts. Retrieved from the Bitcoin website:
https://en.bitcoin.it/wiki/Contracts
BitCongress. (2014, November 9). BitCongress – Blockchain Based Voting System.
Retrieved from the Ethereum website: https://forum.ethereum.org/discussion/110/bitcongress-blockchain-based-voting-system
Buterin, V. (2013). Ethereum White Paper. Retrieved from the Ethereum website:
https://www.ethereum.org/pdfs/EthereumWhitePaper.pdf
Coindesk. (2014, November 7). What Can You Buy with Bitcoin?. Retrieved from the
CoinDesk website: http://www.coindesk.com/information/what-can-you-buy-with-bitcoins/
CodeX. (2014, November 9). CodeX: The Stanford Center for Legal Informatics.
Retrieved from the Stanford Law School website: https://www.law.stanford.edu/organizations/programs-and-centers/codex-the-stanford-center-for-legal-informatics/projects
Coin Market Cap. (2014, November 9). Crypto-Currency Market Capitalization.
Retrieved from the Coin Market Cap website: http://coinmarketcap.com/
D’Onofrio, A. (2014, November 7). Distributed Autonomous Society. Retrieved from the
Quora website: http://distributed-autonomous-society.quora.com/
Ethereum. (2014). Retrieved from the Ethereum website: https://www.ethereum.org/
Gartner. (2013). Forecast: The Internet of Things, Worldwide, 2013. Retrieved from the
Gartner website: https://www.gartner.com/doc/2625419/forecast-internet-things-worldwide-
Griffith, K. (2014). A Quick History of Cryptocurrencies BBTC – Before Bitcoin. Retrieved
from the Bitcoin Magazine website: http://bitcoinmagazine.com/12241/quick-history-cryptocurrencies-bbtc-bitcoin/
Levine, A. (2014). Application Specific, Autonomous, Self-Bootstrapping Consensus
Platforms. Retrieved from the Bitsharestalk website: https://bitsharestalk.org/index.php?topic=1854.0
Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Retrieved from
Bitcoin website: https://bitcoin.org/bitcoin.pdf
Omohundro, S. (2014). Autonomous Technology and the Greater Human Good. Journal
of Experimental and Theoretical Artificial Intelligence, 26(3). Retrieved from the
Taylor and Francis Online
website: http://www.tandfonline.com/doi/full/10.1080/0952813X.2014.895111%20#.VGAzmPnoRuD
Prisco, G. (2014). Bitcoin Governance 2.0: Let’s Block-chain them. Retrieved from the
Cryptocoinsnews website: https://www.cryptocoinsnews.com/bitcoin-governance-2-0-lets-block-chain/
Szabo, N. (1997). Formalizing and Securing Relationships on Public Networks. First
Monday, 2(9). Retrieved from the First Monday website: http://firstmonday.org/ojs/index.php/fm/article/view/548/469
On Sunday, October 26, 2014 I spoke at the Silicon Valley Ethereum Meetup about the philosophy and technology of “Smart Contracts”. Here are the slides as a pdf file. Here is a ustream video of the first 51 minutes of the talk (unfortunately the recording stops there). There was also an audio recording but apparently interference with other audio equipment makes it hard to listen to.
599 Fairchild Drive, Mountain View, CA (map)
To kick off a series of discussions of key Ethereum concepts, Steve Omohundro will present the basics of smart contracts. He’ll discuss:
• Why contract law is society’s programming language.
• Nick Szabo‘s radical invention of smart contracts in 1993.
• The smart contract facilities in Bitcoin.
• The smart contract facilities in Ethereum.
• How to create “DAO”s (“Distributed Autonomous Organizations”) and “DAS”s (“Distributed Autonomous Societies”) using smart contracts.
These presentations are intended to be interactive with lots of questions and discussion. Ideas will be presented in a clear and easy to understand way for those new to Ethereum while still being engaging for experts.
Steve Omohundro 