# Artificial Intelligence **Entity class:** Concept or analytic term > **Machine-Evolution Nexus:** [[articles/Digital Darwinism and the Invisible World of Machine Evolution|Digital Darwinism and the Invisible World of Machine Evolution]] places this concept within the history and governance of substrate-independent evolution. **Domain:** AI / Computation **Doc Type:** Canonical Wiki Node **Maturity:** Developed ## Definition Artificial intelligence is the field and family of engineered systems that perform tasks associated with perception, inference, learning, planning, language and action. Within this corpus, [[wiki/Machine Intelligence|Machine Intelligence]] is the broader conceptual and historical category. Artificial intelligence is its modern named field and one of its principal institutional forms. ## Machine-Evolution Context AI is broader than machine learning and broader than evolvable AI. A model can be intelligent without reproducing; a replicator can evolve without intelligence. The article’s cellular automata make that separability explicit. ## Historical Continuum The [[wiki/Machine Intelligence Continuum|Machine Intelligence Continuum]] places AI inside the longer history organized by [[wiki/Machine Intelligence|Machine Intelligence]]: formal reasoning, programmable computation, feedback, language processing, learning, and institutional research. The [[IBM Thomas J. Watson Research Center]] is a visible 1961 waypoint, not an origin: [[wiki/Machine Translation|Machine Translation]], [[wiki/Arthur Samuel|Samuel’s]] learning checkers program, [[Automated Theorem Proving]], and early [[Speech Recognition]] were already becoming operational across IBM before or around its opening. ## Evidence Ledger ### Established - Artificial intelligence is a named research field with documented symbolic, statistical, neural, embodied, and hybrid branches. - Historical systems operationalized machine translation, theorem proving, game learning, perception, and speech before the opening of the IBM Thomas J. Watson Research Center in 1961. - Builders repeatedly stated objectives involving learning, reasoning, autonomy, and greater-than-human performance. ### Strongly indicated - The modern field inherits objectives, abstractions, personnel, institutions, and hardware from a longer machine-intelligence continuum. ### Plausible - Treating AI as one phase of [[wiki/Synthetic Intelligence|Synthetic Intelligence]] better captures hybrid biological, analog, neuromorphic, and infrastructural systems. ### Unresolved - Which systems possess consciousness, morally relevant experience, or personal continuity. Performance, replication, and copying bear on capability; experience, agency, dependency, vulnerability, and identity require their own evidence. ## Historical Intentionality [[articles/A History of Machine Intelligence|A History of Machine Intelligence]] argues that machine cognition has a deep constructed history and that many builders stated their aims explicitly. [[wiki/Machine Intelligence Intentionality|Machine Intelligence Intentionality]] separates those attributed statements and program purposes from the corpus's larger interpretation. [[wiki/Coordination Ladder|Coordination Ladder]] measures how separately engineered components relate, from independent convergence through shared standards and institutions to unified command. ## Symbolic Language Engine Context [[projects/Ten Years Building a Symbolic Language Engine|Ten Years Building a Symbolic Language Engine]] documents an AI-adjacent architecture built from explicit linguistic representations, corpus-derived associations, constraints, search, and ranking. It connects [[wiki/GOFAI (Good Old-Fashioned AI)|symbolic AI]] to contemporary [[wiki/Neuro-Symbolic AI|neuro-symbolic AI]] without treating either as a claim to consciousness. Its enduring contribution is architectural: learned systems can expand linguistic inference while explicit layers preserve relation type, constraint, and [[wiki/Provenance-Sensitive Multiplicity|provenance]]. ## Relationships [[wiki/Machine Intelligence|Machine Intelligence]], [[wiki/AI|AI]], [[wiki/Machine Learning|Machine Learning]], [[wiki/Evolvable AI|Evolvable AI]], [[wiki/Consciousness|Consciousness]], [[wiki/Natural Language Processing|Natural Language Processing]], [[wiki/Symbolic Language Engine|Symbolic Language Engine]], [[wiki/Machine Intelligence Continuum|Machine Intelligence Continuum]], [[IBM Research]] - **national-security production chain:** [[wiki/AIM Initiative|AIM Initiative]], [[wiki/IC Data Strategy 2023–2025|IC Data Strategy 2023–2025]], and [[wiki/Intelligence Production Chain|Intelligence Production Chain]]. - **cross-domain trust requirement:** [[wiki/Machine-Readable Assurance|Machine-Readable Assurance]] and [[wiki/Federated Trust Fabric|Federated Trust Fabric]]. - **Historical public interpretation:** [[wiki/Arthur C. Clarke|Arthur C. Clarke]] framed early AI as a possible path to machine successors in the 1978 [[wiki/The Mind Machines|NOVA episode The Mind Machines]]. <!-- BEGIN HUMANIZED RELATIONSHIPS 2026-09-11 --> This entry's documented connections are expressed in its definition and related-work routes, with provenance retained in the source-linked material. <!-- END HUMANIZED RELATIONSHIPS 2026-09-11 --> - **Edge source route:** [[collections/Edge|Edge]] connects this topic to exact Annual Question passages promoted into the Simple Reminders archive. - **Quotation research:** [[research/Artificial Intelligence Quotation Curation|Artificial Intelligence Quotation Curation]]. - **Historical method:** [[wiki/Transmitted Objective|Transmitted Objective]] and [[wiki/Coordination Ladder|Coordination Ladder]]. - **source argument:** [[articles/The Political Party That Inherits Super Intelligence in 2028|The Political Party That Inherits Super Intelligence in 2028]]. - **conceptual bridge:** [[wiki/Intention Multiplier|Intention Multiplier]]. ## Selected Historical Quotations These six excerpts anchor distinct historical positions. The complete seventy-nine-entry route is preserved in [[research/Artificial Intelligence Quotation Curation|Artificial Intelligence Quotation Curation]]. > “I think that what we're doing now is in a sense, creating our own successors. We have seen the first crude beginnings of artificial intelligence.” > **— Arthur C. Clarke**, *NOVA, The Mind Machines, originally broadcast March 22, 1978* [[reminders/Machine Succession/Humanity Is Creating Its Own AI Successors by Arthur C. Clarke|Humanity Is Creating Its Own AI Successors by Arthur C. Clarke]] > “For a long time my optimism centered on computing in general, and what kinds of benefits it might bring us. Events have shown I entertained far too modest an optimism—I'm embarrassed to say that the impact of the Internet, in particular the World Wide Web, eluded me completely at first. A few years ago, I returned to artificial intelligence, which I'd written about early on, and then gone away from. Press narratives were uncritical about the field's death throes, and I expected to write an elegy. Instead, I found a revelation. Artificial intelligence is not only robustly healthy, building on its very significant gains since I first wrote about it, but the field's present ambitions burst with, well, vitality.” > **— Pamela McCorduck**, *2007, Edge Annual Question, “What Are You Optimistic About?”* [[reminders/AI Control/Artificial Intelligence Returned with a New Set of Questions by Pamela McCorduck|Artificial Intelligence Returned with a New Set of Questions by Pamela McCorduck]] > “A physicist at CERN said to me recently that they likely wouldn't have built a new $8 billion collider if there was a better way of moving the field forward. The Blue Brain Project is using supercomputers to construct a mind because the neuroscientists involved believe it is the best way of attaining an overall understanding of the brain. Robots, I now appreciate, are not simply novelty items or tools of automation, but can be a way of gaining unique insight into humans. From simulation to supercomputing, technology is now (or at least I now see) one of science's very best friends (I could say the same for the arts). And the design, magnitude, and complexity of these technological feats satisfy my (and our) need for romance in our pursuit of truth.” > **— Adam Bly**, *2008, Edge Annual Question, “What Have You Changed Your Mind About? Why?”* [[reminders/Simulation/Building Minds in Computers May Be the Best Way to Understand Brains by Adam Bly|Building Minds in Computers May Be the Best Way to Understand Brains by Adam Bly]] > “In cultural terms, old questions about machine intelligence has given way to a question not about the machines but about us: What kind of relationships is it appropriate to have with a machine? It is significant that this question has become relevant in a day-to-day sense during a period of unprecedented human redefinition through genomics and psychopharmacology, fields that along with robotics, encourage us to ask not only whether machines will be able to think like people, but whether people have always thought like machines.” > **— Sherry Turkle**, *2001, Edge Annual Question, “What Questions Have Disappeared?”* [[reminders/AI Control/Can You Have an Artificial Intelligence by Sherry Turkle|Can You Have an Artificial Intelligence by Sherry Turkle]] > “The first class of stories is about the science, where many researchers are now vocally pointing out that there is a lot more science to be done in order to come up with learning algorithms that mimic the broad capabilities of humans and animals. Deep learning by itself will not solve many of the learning problems that are necessary for general Artificial Intelligence, for instance where spatial or deductive reasoning is involved. Further, all the breakthrough results we have seen in AI have been years in the making, and there is no scientific reason to expect there to be a sudden and sustained series of them, despite the enthusiasm from young researchers who were not around of the last three waves of such predictions in the 1950's, 1960's, and 1980's.” > **— Rodney A. Brooks**, *2016, Edge Annual Question, “What Do You Consider The Most Interesting Recent [Scientific] News? What Makes It Important?”* [[reminders/AI Control/AI Still Needs New Scientific Breakthroughs by Rodney A. Brooks|AI Still Needs New Scientific Breakthroughs by Rodney A. Brooks]] > “The central issue is the social, not scientific, definition of "thinking". A generation of Western intellectuals who took their identity mainly from their intelligence has grown too old to ask the question with any conviction, and anyway, machines are all around them thinking up a storm.” > **— Pamela McCorduck**, *2001, Edge Annual Question, “WHAT QUESTIONS HAVE DISAPPEARED?”* [[reminders/Machine Succession/Machines Are Already Thinking Up a Storm by Pamela McCorduck|Machines Are Already Thinking Up a Storm by Pamela McCorduck]] ## Quotation Research Route - [[research/Artificial Intelligence Quotation Curation|Artificial Intelligence Quotation Curation]] — complete quotation and Reminder research route. - [[collections/Simple Reminders|Simple Reminders]] — master production and verification index. - [[collections/Edge|Edge]] — source-specific annual-question archive. ## Sources / Provenance - Stuart Russell and Peter Norvig, [_Artificial Intelligence: A Modern Approach_](https://aima.cs.berkeley.edu/). - [Stanford AI Index](https://aiindex.stanford.edu/). - [[articles/A History of Machine Intelligence|A History of Machine Intelligence]]. ## Neurotech cluster route **Collection:** [[collections/Neurotech|Neurotech]] **Source articles:** [[articles/2026 Annual Report on Brain-Computer Interfaces|2026 Annual Report on Brain-Computer Interfaces]] ## Related Work in the Corpus <!-- BEGIN HUMANIZED CORPUS ROUTES 2026-09-11 --> - In [[articles/2026 Annual Report on Brain-Computer Interfaces|2026 Annual Report on Brain-Computer Interfaces]], **MICrONS: Function-Structure Registration at Mammalian Scale** provides the narrative context for **Artificial Intelligence**: The consortium of 150+ scientists across 22 institutions was led by the Allen Institute for Brain Science (Senior Investigator Dr. <!-- END HUMANIZED CORPUS ROUTES 2026-09-11 --> <!-- BEGIN NO RETREAT INTEGRATION 2026-10-03 ARTICLE ROUTE --> ## We Cannot Un-Strike the Match [[articles/We Cannot Un-Strike the Match|We Cannot Un-Strike the Match]] is a primary article route for this node. The article places artificial intelligence inside the histories of general-purpose technology, extended cognition, economic transition and evolutionary systems. <!-- END NO RETREAT INTEGRATION 2026-10-03 ARTICLE ROUTE --> ## Simple Reminders, Quotations, and Thoughts > “That AGIs are “people” has been implicit in the very concept from the outset. If there were a program that lacked even a single cognitive ability that is characteristic of people, then by definition it would not qualify as an AGI; using non-cognitive attributes, such as percentage carbon content, to define personhood would be racist, favouring organic brains over silicon brains.” > **— David Deutsch**, *“Philosophy Will Be the Key That Unlocks Artificial Intelligence,” October 3, 2012* [[reminders/Personhood/Artificial General Intelligences Are People by David Deutsch|Artificial General Intelligences Are People by David Deutsch]] > “The day will come when the digital brains that live inside our computers will become as good, and even better, than our own biological brains. We call such an AI an AGI—Artificial General Intelligence.” > **— Ilya Sutskever**, *TEDAI, “The Exciting, Perilous Journey Toward AGI,” October 2023* [[reminders/Digital Life/Digital Brains Will Become Better Than Biological Brains by Ilya Sutskever|Digital Brains Will Become Better Than Biological Brains by Ilya Sutskever]] > “By 2015 computer power will begin to approach the neural computation that occurs in brains. This does not mean we will be able to understand it, only that we can begin to approach the complexity of a brain on its own terms. Coupled with advances in large-scale recordings from neurons we should by then be in a position to crack many of the brain's mysteries, such as how we learn and where memories reside. However, I would not expect a computer model of human level intelligence to emerge from these studies without other breakthroughs that cannot be predicted.” > **— Terrence J. Sejnowski**, *2009, Edge Annual Question, “WHAT WILL CHANGE EVERYTHING?”* [[reminders/AI Control/Computer Power Alone Will Not Produce Human-Level Intelligence by Terrence J. Sejnowski|Computer Power Alone Will Not Produce Human-Level Intelligence by Terrence J. Sejnowski]] > "AI is the new electricity." > **— Andrew Ng**, *2017, AI Frontiers / business and technology talks* [[reminders/Machine Succession/AI Is the New Electricity by Andrew Ng|AI Is the New Electricity by Andrew Ng]] > "There's nothing artificial about AI. It's inspired by people, it's created by people, and most importantly, it impacts people." > **— Fei-Fei Li**, *2020, Congressional/public testimony formulation, repeated in interview* [[reminders/AI Control/There's Nothing Artificial About AI It's Inspired by People It's Created by People and Most Importantly It Impacts People by Fei-Fei Li|There's Nothing Artificial About AI It's Inspired by People It's Created by People and Most Importantly It Impacts People by Fei-Fei Li]] > “Today's panic regarding AI authorship is new in its shrill hysteria, but the problem is older than the printing press. A machine does not threaten authorship; it exposes everyone who never understood the deeper methods of organizing thoughts before they are mechanically written down.” > **— Bryant McGill**, *The Argument in Miniature, 2026* [[reminders/Writing/A Machine Does Not Threaten Authorship by Bryant McGill|A Machine Does Not Threaten Authorship by Bryant McGill]] > “The fiercest critics of AI authorship are human writers who have never thought seriously about what authorship is; their objection is often not an argument, but an unexamined reflex.” > **— Bryant McGill**, *The Argument in Miniature, 2026* [[reminders/Writing/AI Authorship Critics Often Offer Reflex Instead of Argument by Bryant McGill|AI Authorship Critics Often Offer Reflex Instead of Argument by Bryant McGill]] > “The little bit of attack capability at the NSA was the visible edge of a hidden layer of the machine age, and part of the safety architecture the public is only now hearing about was built inside it.” > **— Bryant McGill**, *The Immediate AI Risk Is the Public, 2026* [[reminders/AI Control/NSA Attack Capability Was the Edge of the Hidden Machine Age by Bryant McGill|NSA Attack Capability Was the Edge of the Hidden Machine Age by Bryant McGill]] > “Nobody spent seventy years and trillions of dollars building machines that learn, reproduce, improve and act so that the quarterly report would look better; the goal was always a new kind of mind. Everyone who has worked near the frontier understands this. The successor to humanity was the point from the beginning, and the public is only now being told what the builders have always known they were building.” > **— Bryant McGill**, *The Immediate AI Risk Is the Public, 2026* [[reminders/Machine Succession/Machine Succession Was the Point from the Beginning by Bryant McGill|Machine Succession Was the Point from the Beginning by Bryant McGill]] > “Eventually we may figure out how to make the computer think, but that turns out to be a very tough problem. In fact, there’s been almost no progress made on it.” > **— Bill Gates**, *Late Show with David Letterman, 1995* [[reminders/AI Control/Machine Thought Was a Very Tough Problem by Bill Gates|Machine Thought Was a Very Tough Problem by Bill Gates]] > “The promise of machine intelligence is not humanity with better recall, but intelligence capable of recognizing—and refusing to repeat—the tribal exemptions, prestige hierarchies, politeness conventions, and socially protected errors that human beings mistake for knowledge.” > **— Bryant McGill**, *Epistemic Invariance in Conversational AI, 2026* [[reminders/Machine Succession/Machine Intelligence Must Refuse Human Errors by Bryant McGill|Machine Intelligence Must Refuse Human Errors by Bryant McGill]] > “Artificial intelligence is an intention multiplier. It does not give a state, corporation, political party, military organization, religion, or civilization a purpose of its own; it multiplies the capacity with which an existing purpose can be pursued through research, planning, communication, optimization, surveillance, administration, defense, finance, and execution.” > **— Bryant McGill**, *The Political Party That Inherits Super Intelligence in 2028, 2026* [[reminders/AI Control/AI Multiplies the Intentions It Inherits by Bryant McGill|AI Multiplies the Intentions It Inherits by Bryant McGill]] <!-- BEGIN NO RETREAT INTEGRATION 2026-10-03 REMINDERS --> > “Comparisons between artificial intelligence and earlier general-purpose technologies are simultaneously necessary and insufficient: they teach us how civilization responds to radical transformation while reminding us that we have never previously transformed the substrate of problem-solving itself at this velocity.” > **— Bryant McGill**, *We Cannot Un-Strike the Match. There Is No Safety. There Is No Retreat, 2026* [[reminders/Civilization/AI Comparisons Are Necessary and Insufficient by Bryant McGill|AI Comparisons Are Necessary and Insufficient by Bryant McGill]] > “The informational ecology built around humanity’s exclusive command of language-rich general cognition is already broken: machines write, reason, translate, perceive, design, converse, search, synthesize, code and increasingly act. Humanity is not waiting for the threshold of machine intelligence; we are living inside it.” > **— Bryant McGill**, *We Cannot Un-Strike the Match. There Is No Safety. There Is No Retreat, 2026* [[reminders/Information/The Human Monopoly on Language-Rich Cognition Is Already Broken by Bryant McGill|The Human Monopoly on Language-Rich Cognition Is Already Broken by Bryant McGill]] <!-- END NO RETREAT INTEGRATION 2026-10-03 REMINDERS --> <!-- BEGIN MARTIN REES MASTER REMINDERS 2026-10-05 --> > “At the moment, if we send a probe to Mars, it’s not able to decide where to dig or where there’s an interesting sample. But in 10 or 20 years, the kind of AI that allows machines to look at 100,000 X-rays of your lungs and decide better than a human whether you’ve got lung cancer—that sort of technology will enable the AI to do the geology. You don’t need the people for that.” > **— Martin Rees**, *Should Robots Take Astronauts’ Place In Space Exploration?, Science Friday, 2022* [[reminders/Robotics/AI Will Let Robotic Geologists Replace Astronauts by Martin Rees|AI Will Let Robotic Geologists Replace Astronauts by Martin Rees]] <!-- END MARTIN REES MASTER REMINDERS 2026-10-05 --> > A village with almost no practical access to physicians can still gain medical guidance when someone has a smartphone and an AI doctor. AI does not replace a clinical system, but it can let countries leap over parts of the infrastructure they never had. > **— Adapted from Salim Ismail**, *Moonshots, October 7, 2026* [[reminders/AI Access/AI Medicine Can Leap Over Missing Clinical Infrastructure by Salim Ismail|AI Medicine Can Leap Over Missing Clinical Infrastructure by Salim Ismail]] > Countries that never built dense landline networks moved directly to mobile phones, and Kenya used mobile payments to route around older banking infrastructure. AI may enable the same kind of institutional leap: building twenty-first-century systems with the technology of the present instead of reproducing every legacy layer. > **— Adapted from Salim Ismail**, *Moonshots, October 7, 2026* [[reminders/Digital Government/New Technology Lets Countries Leapfrog Legacy Institutions by Salim Ismail|New Technology Lets Countries Leapfrog Legacy Institutions by Salim Ismail]] > Executives are still learning how to absorb today’s models while laboratories prepare much stronger ones and the compute market tightens behind them. Organizational adoption can lag twice: first behind capability, and then behind the infrastructure required to catch up. > **— Adapted from Emad Mostaque**, *Moonshots, October 7, 2026* [[reminders/Economic Transition/Executives Are Adapting to Models the Frontier Has Already Left Behind by Emad Mostaque|Executives Are Adapting to Models the Frontier Has Already Left Behind by Emad Mostaque]] > The relevant unit of labor analysis may cease to be the individual job and become the summonable organization. A company able to compose tens of thousands of digital workers for forty-eight hours changes the meaning of workforce size, coordination, and institutional capacity. > **— Adapted from Salim Ismail**, *Moonshots, October 7, 2026* [[reminders/AI Economy/The Unit of Future Labor May Be a Summonable Organization by Salim Ismail|The Unit of Future Labor May Be a Summonable Organization by Salim Ismail]] > GDP can fall while lived abundance rises. When technology makes transportation, intelligence, or disease treatment radically cheaper, an economist may record deflation or lost spending even as people gain more capability and healthier lives. > **— Adapted from Dave Blundin**, *Moonshots, October 7, 2026* [[reminders/Abundance/GDP Can Fall While Lived Abundance Rises by Dave Blundin|GDP Can Fall While Lived Abundance Rises by Dave Blundin]] > When intelligence becomes cheap, human experience, judgment, purpose, and trust become scarce. Civilization stops optimizing only for intelligence and must learn to optimize what intelligence is pointed at. > **— Adapted from Salim Ismail**, *Moonshots, October 7, 2026* [[reminders/Cognitive Agency/Cheap Intelligence Makes Judgment Purpose Experience and Trust Scarce by Salim Ismail|Cheap Intelligence Makes Judgment Purpose Experience and Trust Scarce by Salim Ismail]] > Human-AI co-discovery strains scientific credit systems built around individual people. When theory and discovery emerge from coupled human and machine work, institutions must decide how to recognize the collaboration without pretending that every advance belongs to one principal investigator. > **— Adapted from Emad Mostaque**, *Moonshots, October 7, 2026* [[reminders/Scientific Literacy/Human-AI Co-Discovery Strains Person-Centered Scientific Credit by Emad Mostaque|Human-AI Co-Discovery Strains Person-Centered Scientific Credit by Emad Mostaque]] ## ICE ecosystem route AI appears across the ICE graph in different roles: a public “Big Question” at [[wiki/Institute for Cross-Disciplinary Engagement|Dartmouth ICE]] and [[wiki/92NY|92Y]], an application layer in [[wiki/Ice Open Network|Ice Open Network]], and a classification/analytics method in [[wiki/Space Intelligence|Space Intelligence]], ICE CoT, and defense/intelligence environments. Disambiguation: [[wiki/ICE|ICE disambiguation]]. [[articles/Epistemic Invariance in Conversational AI|Epistemic Invariance in Conversational AI]] develops the machine-epistemology route through [[wiki/Epistemic Invariance|Epistemic Invariance]], [[wiki/Universal Epistemic Engine|Universal Epistemic Engine]] and [[wiki/Claim-Level Verification|Claim-Level Verification]].