From essay writing to standardized test prep and scores, navigating the higher education path involves complex twists and turns that can put students from lower socioeconomic backgrounds at a disadvantage. AI tools could provide meaningful aid, but ethical questions still loom. Although tutoring services, consultants, or essay mentors cond be beneficial, they often come with a steep cost, while educational advancement is a process that can be difficult for students who can't afford these extra resources. A new wave of AI tools has taken the world by storm and given us a vision for a new way of working and finding the information that can streamline our work and our lives. We show you the ways tools like ChatGPT and other generational AI software are making impacts on the world, how to harness their power, as well as potential risks.

I was amazed last August, when I first asked GPT-3 to write a sample article about the impact of GPT on higher education. It responded with an accurate, cogent 700-word piece in just seconds. I wrote then that "higher ed will never be the same!" However, the models and interfaces continued to improve with the GPT-3.5 and ChatGPT. We have now embarked on an ever-accelerating improvement of the technology, fueled by tens of billions of dollars of investment and a hot competition--most notably between Microsoft/Bing and Alphabet/Google.

Faculty from the Stanford Accelerator for Learning are already thinking about the ways in which ChatGPT and other generative artificial intelligence will change and contribute to education in particular. Victor Lee, associate professor of education and the faculty lead for the accelerator initiative on generative AI in education, stresses the importance of educators in harnessing this technology. "If we want generative AI to meaningfully improve education," he says, "there is the obvious step we need to take of listening to the existing expertise in education -- from educators, parents, students, and scholars who have spent years studying education -- and using what we learn to find the most pertinent and valuable use cases for generative AI in a very complicated educational system." Over the next several weeks, the Stanford Accelerator for Learning will launch listening sessions and gatherings with educators to strategize a path for generative AI. Says Lee, "We need the use of this technology to be ethical, equitable, and accountable."

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.

There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.

Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. The report aims to be the most credible and authoritative source for data and insights about AI in the world.

What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.

Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.