TECHNOLOGY | 4GMF

Philosophy and Ethics of AI: A Modern Approach — Summary and 2026 Analysis

In the 2026 landscape of Artificial Intelligence, Stuart Russell and Peter Norvig’s Artificial Intelligence: A Modern Approach (AIMA) remains the definitive philosophical compass for the field. In its 4th edition, the authors moved beyond the technical “how-to” of algorithms to address a more urgent question: How do we ensure that increasingly autonomous agents act in ways that are actually beneficial to humans? This article summarizes the core philosophical debates and ethical frameworks presented in the text, updated with the realities of the mid-2020s.

1. Foundational Philosophical Questions

The text begins by distinguishing between Weak AI (the quest to build machines that act as if they were intelligent) and Strong AI (the quest to build machines that actually have conscious minds).

Weak AI: The Turing Test and the “Disabilities” Argument

Historically, critics of AI relied on the “Argument from Disability,” listing things a machine would never do: be kind, have a …

Solved Exercises and Practice Problems for Artificial Intelligence: A Modern Approach (4th Edition)

January 13, 2026January 22, 2026 - by Matthew Scott

As of 2026, Stuart Russell and Peter Norvig’s Artificial Intelligence: A Modern Approach (AIMA) remains the “gold standard” for AI education. While the field has shifted toward Large Language Models (LLMs) and Generative AI, the foundational principles—search, logic, and probability—are more critical than ever for understanding how these massive systems operate.

This guide provides solved exercises and practice problems organized by the textbook’s core themes, designed to help students master the logic behind the algorithms.

1. Intelligent Agents & Problem Solving (Chapters 2–6)

The “Agent” is the central protagonist of AIMA. To understand an agent, you must first define its PEAS (Performance, Environment, Actuators, Sensors).

Solved Exercise: PEAS for a 2026 Autonomous Medical Drone

Problem: Define the PEAS for a drone designed to deliver emergency medical supplies in a dense urban environment.

Performance Measure: Delivery speed, safety (avoiding collisions), battery efficiency, and success rate of package integrity.
Environment: Urban airspace,

Artificial Intelligence

Differences between artificial intelligence a modern approach 3rd and 4th edition

December 23, 2025January 22, 2026 - by Matthew Scott

In the world of computer science, few textbooks carry as much weight as Stuart Russell and Peter Norvig’s Artificial Intelligence: A Modern Approach (AIMA). For over two decades, it has been the “Bible of AI.” However, the leap from the 3rd Edition (2009) to the 4th Edition (2020) represents much more than a routine update. It is a fundamental pivot reflecting the most explosive decade in the history of computing.

If you are an educator or a self-taught student in 2026, understanding these differences is crucial for aligning your studies with the current state of the industry.

A Tale of Two Eras

The 3rd Edition was written in 2009, an era when AI was dominated by “Good Old Fashioned AI” (GOFAI)—symbolic logic, hand-crafted knowledge bases, and expert systems. Deep learning was still a niche academic interest.

The 4th Edition, released in 2020, arrives in a post-AlexNet world. About 25% of …

15 Proven Strategies to Boost Remote Employee Engagement in 2025

December 22, 2025February 24, 2026 - by Matthew Scott

Remote work has changed how organizations construct teams, providing new flexibility and the opportunity to integrate talent from all over the world. However, challenges remain, such as feelings of isolation, blurred work-life boundaries, and more difficulty in identifying employee disengagement.

I have experience managing remote teams. I recall an example where disengaged employees demonstrated low morale and missed deadlines, and quiet quitting was pervasive. Engagement rocketed, and outcomes improved as we focused on intentional structures for connection and the trust we built.

The stakes are high, and more recent evidence emphasizes this. Fully remote employees consistently demonstrate higher levels of engagement than on-site employees, earning them autonomy (Gallup, 2025). However, hybrid work models are the most effective at 38% engagement because remote employees experience feelings of loneliness, and this can have a detrimental impact on employee well-being.

The solution: less micro-management and more meaningful assistance. Distributed team accountability can be …

Python Implementation of Algorithms from Artificial Intelligence: A Modern Approach: A Practical Guide

December 9, 2025January 22, 2026 - by Matthew Scott

Since its first publication, Stuart Russell and Peter Norvig’s Artificial Intelligence: A Modern Approach (AIMA) has served as the definitive “map” for the field. However, for a programmer in 2026, the real challenge isn’t just understanding the pseudocode on the page—it is translating those abstract concepts into efficient, readable, and “Pythonic” code.

While the textbook provides the logic, the aima-python repository (the official companion project) provides the architecture. This article explores how to implement these algorithms using a modern approach that emphasizes modularity, immutable states, and the power of the Python ecosystem.

The Infrastructure of an AI Problem

In the AIMA framework, an agent doesn’t just “run code”; it solves a Problem. To implement any search-based algorithm, we must first build a formal bridge between the textbook’s definitions and Python’s class structures.

The core of any search implementation relies on two primary classes: Problem and Node.

The Problem Class: