AI Institute: Planning: From Biological Intelligence to Human Intelligence to Artificial General Intelligence (B2A)

人工智能(AI)正在推动美国经济的相当大一部分，几乎影响到每一个工业部门和科学部门。然而，这些系统的“智能”仍然比不上即使是简单的生物系统的灵活性和广度。该项目的目标是开发一个革命性的AI新类别，通过专注于来自动物生物智能(BI)的四个洞察力，与目前的AI代理不同，(1)不是从白板开始，(2)不要忘记当他们学习新事物时(3)具有好奇心，(4)用因果关系解释世界。这个项目汇集了来自不同学科和不同背景的杰出科学家来解决这个问题。通过计划会议和协作演习，该团队将生成初步数据，并为未来的中心做准备工作，重点是重新构建“情报”这一根本问题。推广工作将通过大规模的在线教学吸引许多不同的参与者。在人工智能成立之初，艾伦·图灵提出了一种测试，以确定人工智能何时表现得像商业智能，特别是人类智能(HI)。这项测试为接下来70年的人工智能发展奠定了基础。它在很大程度上已经被旨在模仿人类完成特定任务的狭隘竞争所取代，比如玩某些游戏、识别物体或翻译语言。但无论是图灵测试还是今天的人工智能竞赛，都没有使用现代概念来定义什么是智能。很明显，智能进化到包括几个复杂的能力，这些能力在今天的人工智能中严重缺失：(1)预编程偏差和基线行为，(2)不断利用许多以前的经验来改进新遇到的任务的决策，(3)积极寻找对未来决策有用的信息，即使这些信息与过去的决策不同，最后，(4)构建与决策相关的因果模型，并与这些模型交流。该项目汇集了一个真正了解人工智能和BI/HI的独特团队，以弥补这一差距。该小组的目标是定义与BI/HI相关的人工智能中缺失的东西，并确定哪些研究路径可以增强未来的方法。在第一年，该项目将开发一种测试，以衡量在动物身上发现的智力的特定方面，但不是目前的人工智能。这项测试将非常简单，可以由几个不同的生物分类群、人类以及人工智能来执行。在第二年，参与者将进行试点实验，以量化这些测试的当前性能水平，并从BI/HI中提取对人工智能的见解。由此产生的基准将为最终的研究所提供明确和定量的里程碑，其目标将是开发在新的智力测试中与HI匹配的人工智能。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Artificial Intelligence (AI) is driving considerable parts of the US economy, influencing almost every industrial and scientific sector. Yet, the "intelligence" of these systems still cannot match the flexibility and breadth of even simple biological systems. The objective of this project is to develop a revolutionary new class of AI by focusing on four insights from the biological intelligence (BI) of animals that, unlike current AI agents, (1) do not start as blank slates (2) do not forget when they learn new things (3) have curiosity, and (4) interpret the world in terms of cause and effect. This project brings together outstanding scientists from a wide variety of disciplines and diverse backgrounds to tackle this problem. Through planning meetings and collaborative exercises, the team will generate preliminary data, and preparatory work for a future center focused on reframing the fundamental question of "intelligence." Outreach efforts will engage many diverse participants through large-scale online teaching.At the founding of AI, Alan Turing proposed a test to determine when an AI behaves like a BI, and specifically human intelligence (HI). This test set the stage for the following 70 years of AI development. It has largely been replaced by narrow competitions aimed at imitating humans at specific tasks, such as playing certain games, identifying objects, or translating languages. But neither the Turing test nor today’s AI competitions utilize modern conceptualizations of what it means to be intelligent. It has become clear that intelligence evolved to incorporate several complex capabilities, which are critically missing from today’s AI: (1) preprogramming biases and baseline behaviors, (2) continually leveraging of many previous experiences to improve decision making in newly encountered tasks, (3) actively seeking out information that is useful for future decisions even if these differ from past decisions, and, finally, (4) constructing causal models relevant to decisions and communicating these models. This project brings together a unique group that truly understands both AI and BI/HI to address this gap. This group aims to define what is missing in AI relative to BI/HI, and to determine which research paths can enhance future approaches. In year one, the project will develop a test to measure a specific aspect of intelligence found in animals, but not current AI. This test will be sufficiently simple that it can be performed by several different biological taxa, humans, as well as AI. In year two, the participants will conduct pilot experiments to quantify current levels of performance on these tests and distill insights from BI/HI for AI. The resulting benchmarks will provide explicit and quantitative milestones for the eventual institute, whose goal will be to develop AI that matches HI on the new tests of intelligence.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.