Strategic Objectives
• Identify the hidden mechanics of algorithmic tacit collusion.
• Understand the legal loopholes created by self-preferencing AI.
• Master the technical concepts of 'black box' market manipulation.
• Future-proof your legal or business strategy against automated enforcement.
The Core Challenge
Traditional antitrust law is built for human conspiracies, but today's pricing bots are achieving market dominance and collusion without a single human handshake.
01
The Evolution of Competition
02
The Mechanics of Pricing Bots
03
The Ghost in the Machine
04
Game Theory and Algorithms
05
The Black Box Problem
06
Self-Preferencing Strategies
07
The Role of Big Data
08
Reinforcement Learning in Markets
09
Price Discrimination 2.0
10
Hub-and-Spoke 2.0
11
Regulatory Responses: The DMA
12
The Consumer Welfare Standard
13
Network Effects and Dominance
14
Algorithmic Mergers
15
The Limit of Human Agency
16
Computational Antitrust
17
Interoperability as a Remedy
18
The US Perspective
19
The Global South and Digital Markets
20
Ethics in Automated Commerce
21