Deep Learning and the End of Social Science

Deep Learning and the End of Social Science

The claim that AI could undermine scientific understanding, or even make it obsolete, is far from new. Deep Learning and the End of Social Science. What happens when computers know people better than they know themselves?

Science is an algorithm. To date, it might well be the most effective and useful algorithm — or family of algorithms — that humanity ever invented. Ever-improving methods for erecting models of how the world works and then testing those models against evidence make it possible to distinguish good ideas from bad. Step-by-step, humanity’s understanding of the universe, the world, and itself, has grown. The Artificial Intelligence revolution, however, could well overturn how good ideas are sifted from bad and subvert science’s ultimate goal of understanding.

The claim that AI could undermine scientific understanding, or even make it obsolete, is far from new. Deep learning algorithms, unlike scientific ones, care not a bit about understanding. They optimize more proximate and banal quantities. More than a decade ago, Chris Anderson argued that ‘the data deluge makes the scientific method obsolete.’ He predicted the end of scientific theory.

The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all.

In 2017, David Weinberger stirred things up againwhen he asserted that ‘our machines now have knowledge we’ll never understand.’ Whether accounts of theory’s death have been exaggerated or not remains a topic of vigorous, sometimes heartening debate. Peter Sweeney suggests that the new and inexplicable insights that arise from deep learning might provide a renaissance for deeper explanations, concluding that:

Deep learning should be celebrated, not for revealing the limits of knowledge, but as a powerful observational tool.

machine-learning deep-learning society artificial-intelligence psychology

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

Artificial Intelligence, Machine Learning, Deep Learning 

Artificial Intelligence (AI) will and is currently taking over an important role in our lives — not necessarily through intelligent robots.

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.

Artificial Intelligence vs. Machine Learning vs. Deep Learning

Artificial Intelligence vs. Machine Learning vs. Deep Learning. We are going to discuss we difference between Artificial Intelligence, Machine Learning, and Deep Learning

Artificial Intelligence vs. Machine Learning vs. Deep Learning

Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different

Artificial Intelligence vs. Machine Learning vs. Deep Learning

Learn the Difference between the most popular Buzzwords in today's tech. World — AI, Machine Learning and Deep Learning