Is AI Reasoning Right for the Wrong Reasons? | Quanta Magazine

The idea that artificial intelligence can “reason” is more intuitive than ever. But intuitions can be wrong, and the science is far from settled.

Exploitative Game Design: Beyond the F2P Debate

The past few months have seen a torrent of articles about Free-to-Play business models, often discussed alongside issues of ethics in games (for example: 1, 2, 3, 4, 5). These pieces have addressed the effect on addiction-prone players or children, the possibility of corrupting artistic intent, the sheer amount of money being spent, and other advantages and dangers of F2P. While all of this is relevant, I fear that we’re focusing too much on F2P and glossing over the wider ethical issues in game design.

Play is doing its work even if we’re not keeping score | Aeon Essays

We are most human when we play freely, imaginatively, pointlessly. Gamification risks atrophying that most precious capacity

Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From an Explainable AI Competition · Issue 1.2, Fall 2019

In 2018, a landmark challenge in artificial intelligence (AI) took place, namely, the Explainable Machine Learning Challenge. The goal of the competition was to create a complicated black box model for the dataset and explain how it worked. One team did not follow the rules. Instead of sending in a black box, they created a model that was fully interpretable. This leads to the question of whether the real world of machine learning is similar to the Explainable Machine Learning Challenge, where black box models are used even when they are not needed. We discuss this team’s thought processes during the competition and their implications, which reach far beyond the competition itself.

Training AI models doesn't emit that much

If we just make reasonable comparisons instead of crazy ones

GameSpot's SIMply Divine: The Story of Maxis Software

GameSpot   action   adventure   driving   puzzle   role-playing   simulation   sports   strategy   hardware

Look-ahead Reasoning with a Learned Model in Imperfect Information Games

Test-time reasoning significantly enhances pre-trained AI agents' performance. However, it requires an explicit environment model, often unavailable or overly complex in real-world scenarios....

7 Reasons Why Video Gaming Will Take Over — MatthewBall.co

It’s replicating the most lucrative entertainment businesses on earth… and then adding a lot more.

Propagation and preservation of AI-discovered problem-solving strategies in human culture

Intelligent machines have the potential to uncover problem-solving strategies beyond human discovery. Emerging evidence from competitive gameplay, such as Go and chess, demonstrates that AI systems are evolving from mere tools to sources of cultural innovation adopted by humans. However, the conditions under which intelligent machines transition from tools to drivers of persistent cultural change remain unclear. We identify three key dimensions that modulate machine influence on human problem-solving: the discovered strategies must be non-trivial, learnable, and offer a clear advantage. Using a cultural transmission experiment, we demonstrate that when these conditions are met, machine-discovered strategies can be transmitted, understood, and preserved by human populations, leading to enduring cultural shifts. Conversely, using agent-based simulations, we show how machine influence is constrained in the absence of these conditions. These findings provide a framework for understanding how machines can persistently expand human cognitive skills and underscore the need to consider their broader implications for human cognition and cultural evolution.

There’s a Reason Women Aren’t Swooning Over AI Like Men Are

Or rather, a great many reasons

Specification gaming: the flip side of AI ingenuity

Specification gaming is a behaviour that satisfies the literal specification of an objective without achieving the intended outcome. We have all had experiences with specification gaming, even if not by this name. Readers may have heard the myth of King Midas and the golden touch, in which the king asks that anything he touches be turned to gold - but soon finds that even food and drink turn to metal in his hands. In the real world, when rewarded for doing well on a homework assignment, a student might copy another student to get the right answers, rather than learning the material - and thus exploit a loophole in the task specification.

Quickly Training Game-Playing Agents with Machine Learning

Posted by Leopold Haller and Hernan Moraldo, Software Engineers, Google Research In the last two decades, dramatic advances in compute and connecti...

Jevons Paradox: A personal perspective

What if the most game-optimal play in the new system is actually to become relentlessly, unapologetically you?

Generative AI’s crippling and widespread failure to induce robust models of the world

LLM failures to reason, as documented in Apple’s Illusion of Thinking paper, are really only part of a much deeper problem

Go Lives

The greatest Go player of all time just did something amazing. What can this tell us about life in the era of superhuman AI?

The Danger Of Superhuman AI Is Not What You Think

The rhetoric over “superhuman” AI implicitly erases what’s most important about being human.