Artificial Intelligence - Bryant McGill

# 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. ## 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 [[Machine Intelligence Continuum]] places AI inside a longer history of 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/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]], [[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]].  This entry's documented connections are expressed in its definition and related-work routes, with provenance retained in the source-linked material.  - **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]]. ## 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  - 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.  ## Simple Reminders, Quotations, and Thoughts > “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]]