Why All Data Scientists Should Understand Behavioral Economics

Why All Data Scientists Should Understand Behavioral Economics

Understanding behavioral economics can help data scientists create better, more effective machine learning models.In1975 Herbert A. Simon was awarded the Turing Award by the Association for Computing Machinery. This award, given to “an individual selected for contributions of a technical nature made to the computing community” is considered to be the Nobel Prize for computing.

In 1975 Herbert A. Simon was awarded the Turing Award by the Association for Computing Machinery. This award, given to “an individual selected for contributions of a technical nature made to the computing community” is considered to be the Nobel Prize for computing.

Simon and co-recipient Allen Newell made basic contributions to artificial intelligence, the psychology of human cognition, and list processing.

It is interesting to note that amongst his contributions to artificial intelligence and list processing, he is also being recognised for his contribution to human cognition. At first glance, one would think that understanding how humans think is about as far from computer science as you can get!

However, there are two key arguments that explain why human cognition is important for any advancements in computer science, and especially AI.

Imitating Humans

In his 1950 seminal paper “Computing Machinery and Intelligence,” Alan Turing introduced what became known as the Turing test. A computer and a human have a written dialogue and in this “imitation game” the computer tries to fool the human participant into thinking it is also a human by devising responses that it thinks a human would make.

One of the key aims of AI is to train computers to make decisions like humans, whether labelling pictures or responding to questions. Even if the aim is task-specific, not centred around replicating humans in their entirety, it is crucial that developers of AI have some understanding of human cognition, so that they can replicate it.

artificial-intelligence data-science machine-learning psychology human-behavior

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Most popular Data Science and Machine Learning courses — July 2020

Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant

Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science

Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science: Artificial intelligence is a field where set of techniques are used to make computers as smart as humans. Machine learning is a sub domain of artificial intelligence where set of statistical and neural network based algorithms are used for training a computer in doing a smart task. Deep learning is all about neural networks. Deep learning is considered to be a sub field of machine learning. Pytorch and Tensorflow are two popular frameworks that can be used in doing deep learning.

Artificial Intelligence vs Machine Learning vs Data Science

Artificial Intelligence, Machine Learning, and Data Science are amongst a few terms that have become extremely popular amongst professionals in almost all the fields.

AI(Artificial Intelligence): The Business Benefits of Machine Learning

Enroll now at CETPA, the best Institute in India for Artificial Intelligence Online Training Course and Certification for students & working professionals & avail 50% instant discount.

Data science vs. Machine Learning vs. Artificial Intelligence

In this tutorial on "Data Science vs Machine Learning vs Artificial Intelligence," we are going to cover the whole relationship between them and how they are different from each other.