Could LLMs Help Generate New Concepts in Human Language?
Pekka Lampelto
AI Expert | Data Compliance Expert | Entrepreneur | Advisor. AIGP & CIPP/E. #AI-governance #dataprotection #GDPR #DPIA #riskassessments. Pioneering master's thesis on knowledge work automation with AI (2013, 168 pages).
Concepts are the central part of language. I would argue that concepts serve as condensed linguistic representations of concrete or abstract entities, aimed at enhancing the precision and efficiency of thinking and communication.
I found it fascinating to ponder how new concepts have emerged in human language. One could argue that the entire history of the development of human language is essentially a series of births of new concepts and their enrichment and connotation with existing concepts. Thus, the development of human language is in one part the development of concept systems.
When the basis of the language had already been born, people arguably had the need to conceptualize and name more and more things in the world around them.
Let's time travel to the Stone Age. When the basis of the language had already been born, people arguably had the need to conceptualize and name more and more things in the world around them. Some of the first concepts and words probably were related to concrete things like family members ("mother", "father", "brother", " "sister" and "child"), animals ("man", "bear", "cat", "dog") and tools ("stick", and "axe"). Those then were followed by perhaps a slightly more abstract concepts such as actions and verbs like "sleeping", "eating", "talking", "jumping". As thinking and language developed further, yet more challenging and abstract concepts arose, for example, those related to feelings and intentions such as "joy ", "love", "sorrow", "hate" and community roles such as "chief", "shaman". Once the agrarian revolution and organized society emerged, a need arose for even more abstract concepts such as "nation", "story", "culture", "rules" , "law", "religion" and "war". Even later, as societies grew and developed, whole systematically organized areas of knowledge emerged, such as "administration", "economy", "the art of warfare", "mathematics", "philosophy", and "astronomy".
The creation and naming of concepts can be thought as innovations in language to fulfill thinking and communication gaps.
It could be argued that concepts and their names have arisen out of need as the human environment changed, culture, and thinking developed. The creation and naming of concepts can be thought as innovations in language to fulfill thinking and communication gaps. These gaps in linguistic thinking can be almost said to summon the birth of a new concept and word.
A question arose in my mind: Could large language models help humanity recognize and even name new valuable concepts? I decided to try, whether ChatGPT-4 could be used for coming up of new concepts and words.
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Prompt: "Invent a whole new useful concept like 'human rights', 'religion', 'principle', 'technology', or 'principle' and explain it."
Some ChatGPT-4 answers:
1. Internal networking: Internal networking is a method of personal and professional growth in which an individual focuses on building deep and meaningful relationships in his own life circle, such as with family, friends, colleagues and local networks. It differs from traditional networking, which emphasizes the creation of new contacts and often expands the social or professional circle outward.
2. Thought Ecology: Thought ecology is an approach to mental and emotional well-being that focuses on the "ecological" balance of a person's world of thought. It refers to how an individual's thoughts, beliefs, attitudes and feelings affect each other and form a complex, dynamic system that can affect a person's overall well-being.
In my opinion, while quite interesting, these concepts lacked significant novelty, and the words themselves were compound words, as often newly created words nowadays typically are formed by combining two existing words into one.
Some questions arose from this thought experiment:
Toimitusjohtaja at Jalo IT Oy
11 个月Olen hieman saman tyyppist? ajatusta jahdannut itse, sanastosta tuntuu puuttuvan paljon aika olennaisiakin sanoja. Voisiko ajattelua boostata keksim?ll? sanoja? GPT muodostaa n?m? konseptit (tavallaan) keskim??r?isen www-datan perusteella, n?in l?hdedata on t?ss? esimerkiss? v?h?n kehno. Ajatustasi my?t?illen, parempi data ehk? mahdollistaisi tavan tunnistaa vaikka kaikki puuttuvat "tunteita kuvaavat sanat" ja LLM voisi my?s tekaista n?m? n?pp?r?sti siin? samalla. Lopputulos voisi olla liuta ihan loogisia sanoja, joiden avulla ymm?rrys meist? itsest?mme voisi muuttua todella radikaalisti.