![]() ![]() New research challenged those concerns, suggesting that the perceived emergent abilities of AI models are a result of specific metrics used in evaluation. In recent years, people have raised concerns about the unpredictable and potentially harmful nature of large language models. This story ricocheted around academic Twitter (er, X). ![]() AI’s Ostensible Emergent Abilities Are a Mirage The tool aims to provide transparency in an era where discerning the source of information has become increasingly important, offering potential applications in education, journalism, and society at large. DetectGPT, in its early stages, demonstrated impressive accuracy in differentiating between human- and AI-generated text across various models. Stanford scholars developed DetectGPT, a tool designed to distinguish between human- and large language model-generated text. Human Writer or AI? Scholars Build a Detection ToolĮarly in 2023, we were just beginning to understand what tools like ChatGPT were capable of, and many of us already saw the need for oversight and tools to identify machine-generated content. This year’s AI index captured much of this shakeup, and this story offered a snapshot of what was happening in AI research, education, policy, hiring, and more. ![]() The sixth annual AI Index hit in early 2023 at a time when generative tools were taking off, industry was spinning into an AI arms race, and the slowly slumbering policy world was waking up. While emphasizing the potential benefits of AI in education, such as providing feedback to teachers, aiding skill assessments, and promoting self-confidence in learners, the summit also highlighted significant risks, including the lack of cultural diversity in model output, the non-optimization of responses for student learning, the generation of incorrect responses, and the potential to exacerbate a motivation crisis among students. The summit addressed a range of possibilities, including personalized support for teachers using AI, changing priorities for learners, learning without fear of judgment through AI interfaces, and improving learning and assessment quality. The AI+Education Summit, hosted by the Stanford Accelerator for Learning and Stanford HAI, focused on exploring how AI can be effectively employed to enhance human learning. Let’s Get it Right.Ī major conversation of the generative AI year was how it would impact teaching and learning. Here are the top research papers and thought leadership pieces of 2023. As generative AI became woven into the fabric of daily life, policymakers, researchers, and the public grappled with the need for robust regulations and ethical guidelines to navigate the evolving landscape of artificial intelligence, ensuring responsible and accountable use in the years to come.īoth AI’s technical capabilities and growing concerns captured our readers’ attention this year. However, with this power came concerns about transparency, bias, and the ethical implications of deploying such sophisticated models in real-world applications. The year saw models match or surpass human performance in some intricate tasks, such as answering complex medical exam questions, generating persuasive political messages, and even choreographing human dance animations to match diverse pieces of music. Driven by remarkable progress in large language models, the technology showcased impressive abilities in domains ranging from healthcare and education to creative arts and political discourse. In 2023, the field of artificial intelligence witnessed a significant transformation - generative AI emerged as the most prominent and impactful story of the year.
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