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.
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....
Building games that can be understood at a glance
Building games that can be understood at a glance - Zach Gage, GDC 2018
Building games that can be understood at a glance
Building games that can be understood at a glance - Zach Gage, GDC 2018
Code Was Never the Asset - The Phoenix Architecture
Why AI makes the hidden economics of software unavoidable
Learning to solve complex tasks by growing knowledge culturally across generations
Knowledge built culturally across generations allows humans to learn far more than an individual could glean from their own experience in a lifetime. Cultural knowledge in turn rests on language: language is the richest record of what previous generations believed, valued, and practiced, and how these evolved over time. The power and mechanisms of language as a means of cultural learning, however, are not well understood, and as a result, current AI systems do not leverage language as a means for cultural knowledge transmission. Here, we take a first step towards reverse-engineering cultural learning through language. We developed a suite of complex tasks in the form of minimalist-style video games, which we deployed in an iterated learning paradigm. Human participants were limited to only two attempts (two lives) to beat each game and were allowed to write a message to a future participant who read the message before playing. Knowledge accumulated gradually across generations, allowing later generations to advance further in the games and perform more efficient actions. Multigenerational learning followed a strikingly similar trajectory to individuals learning alone with an unlimited number of lives. Successive generations of learners were able to succeed by expressing distinct types of knowledge in natural language: the dynamics of the environment, valuable goals, dangerous risks, and strategies for success. The video game paradigm we pioneer here is thus a rich test bed for developing AI systems capable of acquiring and transmitting cultural knowledge.
Reify This
The authors contend that contemporary efforts to render AI systems interpretable rest on a mistake: reification, the process of treating abstractions and statistical artifacts as if they were concrete realities.…
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
Game Theory
Game theory is the study of the ways in which interactingchoices of economic agents produce outcomeswith respect to the preferences (or utilities) ofthose agents, where the outcomes in question might have been intendedby none of the agents. The meaning of this statement will not be clearto the non-expert until each of the italicized words and phrases hasbeen explained and featured in some examples. Doing this will be themain business of this article. First, however, we provide somehistorical and philosophical context in order to motivate the readerfor the technical work ahead.
How Claude marks AI-generated content | Claude Help Center
Anthropic has signed the EU AI Act's Article 50(2) Code of Practice on Transparency of AI-Generated Content, as a provider of both generative AI models and generative AI systems. This article describes how we’re planning to put those commitments into practice, how marking works, and what its limitations are. We’ll update this article and publish more detailed technical guidance as it becomes available.
AI Quests
AI Quests: A game-based learning experience for middle schoolers (11-14) on AI. Code-free quests use real Google projects to solve societal issues.
The antidote to AI fatigue — Answer.ai Solveit
Society-in-the-loop: programming the algorithmic social contract
Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’
GameSpot's SIMply Divine: The Story of Maxis Software
GameSpot action adventure driving puzzle role-playing simulation sports strategy hardware
On Taste, Effort & Curiosity - again
When AI collapses how long it takes to ship, what’s left is judgment, experimentation, and knowing what not to build.
New schemes teach the masses to build AI
Treating it like a craft is paying dividends
Keating — The Hyperteacher
Socratic AI that forces you to reconstruct understanding from memory. No hand-holding. No spoon-feeding. Free and open source.
