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Chapter VI: Computational Technics

Nicholas A. Fattu · 1951 · Review of Educational Research

paper 2 of 19 on this spine peer review →

Can machines think, or are they just clever tricks?

THE ITCH THE FIELD HAD, BEFORE THIS PAPER

1

The Problem of Automata

Imagine a skilled puppeteer controlling intricate marionettes, but the puppets begin to improvise and adapt to their environment, blurring the line between puppet and puppeteer.

IN PLAIN TERMSThe question of whether machines can truly think or if they are just programmed to mimic human behavior is a central concern in the development of computational technics.
2

The Move to Algorithmic Thinking

In our puppeteer world, the puppeteer starts to write down the intricate dance steps, allowing others to replicate the performance. This written code becomes the blueprint for the marionettes' movements, enabling the creation of more complex and adaptive performances.

IN PLAIN TERMSAlan Turing's concept of the universal Turing machine and the development of algorithmic thinking mark a significant shift in the field, enabling the creation of more complex and adaptive machines.
3

The Future of Automata

As the puppeteer continues to refine the dance steps, the marionettes begin to take on a life of their own, adapting to new situations and learning from their environment. The puppeteer's role evolves from controller to facilitator, enabling the marionettes to explore new possibilities.

IN PLAIN TERMSThe future of computational technics holds the promise of machines that can learn, adapt, and evolve, blurring the line between machine and human intelligence.
[ THE MODEL TO WALK AWAY WITH ]

The mental model of computational technics is that of a dynamic, adaptive system where machines can learn, evolve, and interact with their environment, much like a skilled puppeteer and their marionet

Reach for it when

  • Designing intelligent systems that can adapt to changing environments — The mental model of computational technics is pa
  • Developing machines that can interact with humans in a more natural way — The mental model of computational technics can
  • Exploring the boundaries of artificial intelligence and machine learning — The mental model of computational technics is

It misleads when

  • Designing simple, rule-based systems — The mental model of computational technics may not be applicable when designing s
  • Creating systems that require precise, deterministic behavior — The mental model of computational technics may not be su
  • Developing systems that rely on human intuition or expertise — The mental model of computational technics may not be app

Try it in your world

Founder

Develop a minimum viable product (MVP) that can learn and adapt to user behavior

WHY · The mental model of computational technics justifies this step by enabling the creation of machines

ProductLeader

Integrate machine learning algorithms into the product to enable personalized recommendations

WHY · The mental model of computational technics justifies this step by enabling the creation of machines

Researcher

Explore the use of neural networks to develop more sophisticated machine learning models

WHY · The mental model of computational technics justifies this step by enabling the creation of machines

Engineer

Implement a feedback loop to enable the machine to learn from user interactions

WHY · The mental model of computational technics justifies this step by enabling the creation of machines

← 1950 · I.—COMPUTING MACHINERY AND INTELLIGENCE 1952 · “The Status of Brain in the Concept of Mind” →
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