Are you passionate about technology and its impact on society? Do you believe in the ethical use of Artificial Intelligence (AI)? If so, then a career in Artificial Intelligence Ethics may be the perfect fit for you! As an Artificial Intelligence Ethicist, you will be responsible for ensuring that AI technology is developed and used in a responsible and ethical manner. This means considering the potential consequences of AI on society, including issues of bias, privacy, and the impact on jobs. One of the most appealing aspects of this field is the opportunity to make a real difference in the world. For example, an AI Ethicist might work with a healthcare company to develop an AI system that can diagnose diseases more accurately than a human doctor. Or, they might work with a social media platform to ensure that their algorithms are not promoting hate speech or other harmful content. Typical duties might include conducting research on the ethical implications of AI, developing guidelines and policies for AI development and use, and working with cross-functional teams to ensure that AI systems are designed and implemented in a responsible manner. There are many potential areas of specialisation within this field, including AI policy, AI governance, and AI risk management. Other related fields might include computer science, philosophy, and law. Typical education and training for an Artificial Intelligence Ethicist might include a degree in computer science, philosophy, or a related field. Some popular undergraduate programs and majors include Computer Science, Philosophy, and Ethics. Helpful personal attributes for an AI Ethicist might include strong critical thinking skills, excellent communication skills, and a passion for social justice. Job prospects for Artificial Intelligence Ethicists are strong, with many opportunities available in both the public and private sectors. Some notable potential employers include Google, Microsoft, and the World Economic Forum. In the longer term, the outlook for this field is extremely positive, with the demand for ethical AI experts only expected to grow as AI becomes more integrated into our daily lives. So, if you're interested in technology, ethics, and making a positive impact on society, consider a career in Artificial Intelligence Ethics!

In today's digital age, we're surrounded by algorithms that shape our daily lives in ways we may not even realize. From social media algorithms that decide what content we see to predictive policing algorithms that influence law enforcement decisions, algorithmic culture is ubiquitous and powerful. So, what is algorithmic culture, and how does it shape our lives and perceptions? At its core, algorithmic culture refers to the way algorithms and the data they process have become embedded in contemporary culture. According to Lev Manovich, a leading academic in the field, algorithmic culture is "a new way of producing and representing knowledge based on data analysis, and a new form of power." In other words, algorithms are not just tools but are also shaping the way we understand and interact with the world around us. One example of algorithmic culture in action is the use of predictive algorithms in the criminal justice system. Proponents argue that these algorithms can help prevent crime by identifying high-risk individuals before they offend. However, critics argue that these algorithms reinforce existing racial biases and lead to unfair treatment of certain groups. Another example is the use of recommendation algorithms on social media platforms. These algorithms decide what content we see based on our past behavior and interests, creating a "filter bubble" that can limit our exposure to diverse viewpoints. Despite its potential pitfalls, algorithmic culture also offers new opportunities for creativity and innovation. For example, computer-generated art is a growing field that harnesses the power of algorithms to produce unique and compelling works. As we navigate our increasingly algorithmic world, it's important to understand the ways in which these tools shape our lives and perceptions. By engaging with academic research and exploring new ideas, we can become more informed and empowered citizens in the digital age.

Are you curious about the risks of artificial intelligence (AI) and how it affects our lives? Check out the thought-provoking article, "What We Missed about Social Media," on JSTOR Daily. The author shares their experience working in social media before it became the corporate giant it is today, and how it has changed the way we interact with each other. Discover how generative AI can dehumanize us, mislead us, and manipulate us, and why we need to be aware of its implications. Don't miss out on this insightful read!

Can AI-generated persuasive appeals sway human opinions on hot social issues? Stanford researchers find out. Chatbots' political persuasion has significant implications for democracy and national security. Discover how AI fared in the experiment and why it calls for immediate consideration of regulations.

In "Rise of the Machines," Thomas Rid delves into the fascinating history of cybernetics, a pivotal idea of the 20th century that gave birth to seductive myths about the future of machines. From the mind of mathematician Norbert Wiener during the devastation of World War II, cybernetics triggered blissful cults, military gizmos, and even the fight for internet freedom. Rid's book offers an unparalleled perspective into our anxious embrace of technology, drawing on unpublished sources and interviews with hippies, anarchists, sleuths, and spies. Discover the untold story of how we got here, as lives offline and online continue to merge. Recommended for students of computer science, engineering, and philosophy, as well as professionals in the tech industry, "Rise of the Machines" offers a unique perspective on the history of cybernetics and its impact on society. The book provides insights into how cybernetics influenced the development of military technology, virtual space, and the fight for internet freedom. It also explores the cultural impact of cybernetics, including its influence on the counterculture movement of the 1960s. Anyone interested in the history of technology and its intersection with society will find this book a fascinating read.

Want to make social media a more positive and inclusive space? Researchers from King's College London and Harvard University have created a framework to prioritize content that fosters positive debate, deliberation and cooperation on social media. Algorithms that surface content aimed at building positive interactions could be more highly ranked, leading to more meaningful online interactions and a reduction in destructive conflict.

In "Artificial Intelligence," computer scientist Melanie Mitchell takes readers on a fascinating journey through the history and current state of AI. Mitchell delves into the most pressing questions about AI today, including how intelligent the best AI programs truly are, how they work, and what they can do. She examines the disconnect between the hype and actual achievements in the field, providing clear insights into what has been accomplished and how far we still have to go. This engaging and accessible book is an essential guide to understanding the impact of AI on our future. Recommended for anyone interested in the intersection of technology and society, "Artificial Intelligence" provides a comprehensive overview of the history and current state of AI. This book is particularly relevant for computer scientists, data scientists, and engineers who want to understand the cutting-edge AI programs and the historical lines of thought underpinning recent achievements. It is also useful for policymakers and those concerned with the ethical implications of AI, as Mitchell explores the fears and hopes surrounding the technology. Additionally, anyone interested in the future of work, automation, and the impact of technology on society will find this book thought-provoking and informative.

Discover how large language models like ChatGPT are shaping the way we write and reinforcing existing hierarchies in language use. Learn about the impact of AI technology on linguistic diversity and the ways in which it perpetuates dominant modes of writing, potentially sidelining less common ones. Explore how we can use writing as a tool to resist oppression and create a more equitable future.

The Prisoner's Dilemma is a classic problem that can shed light on a range of real-world phenomena. In this dilemma, two people face a choice: cooperate and both do well, or fail to cooperate and both do worse. Understanding this dilemma can help you see how cooperation is key to solving complex problems, from overfishing to pollution to creating just societies. By exploring the underlying structure of this problem, you can gain insight into the benefits of cooperation, and how to approach complex situations where your choices impact those around you. Learning about the Prisoner's Dilemma can help you become a better problem solver, both intellectually and practically, by equipping you with the tools you need to think critically and work collaboratively with others.

Are you using AI-powered writing assistants to help you with your school work? A new study from Cornell University has found that these tools not only put words into your mouth but also ideas into your head. The study shows that the biases baked into AI writing tools could have concerning repercussions for culture and politics. Co-author Mor Naaman, professor at the Jacobs Technion-Cornell Institute at Cornell Tech, warns that apart from increasing efficiency and creativity, there could be other consequences for individuals and society. Read more about this groundbreaking study at Cornell University.

Historians are using machine learning to analyze historical documents, correcting distortions and drawing connections. But as machines play a greater role in the future, how much should we cede to them of the past? Discover the implications for everything from art to drug development.

Meet EchoSpeech, a wearable interface that recognizes unvocalized commands based on lip and mouth movements. Developed by Cornell's SciFi Lab, the glasses use acoustic sensing and AI to recognize up to 31 commands with 95% accuracy. EchoSpeech could give patients their voices back and be used to communicate in noisy places or paired with a stylus for design software. With smaller microphones and speakers than pencil erasers, the glasses become a wearable AI-powered sonar system. The technology removes the need for wearable video cameras, improving privacy and battery life.

Are you fascinated by the idea of machines learning from data and making predictions on their own? Look no further than the exciting field of Machine Learning! Machine Learning is a subfield of Artificial Intelligence that focuses on developing algorithms and models that enable machines to learn from data and make predictions or decisions without explicit programming. It has revolutionized the way we interact with technology, from personalized recommendations on Netflix to self-driving cars. Some of the most interesting and meaningful aspects of Machine Learning include its applications in healthcare, finance, and environmental sustainability. For example, Machine Learning algorithms can analyze medical data to diagnose diseases or predict patient outcomes, while also identifying patterns in financial data to detect fraud or predict stock prices. Innovations in Machine Learning are happening all the time, with exciting research being done in areas such as deep learning, reinforcement learning, and natural language processing. Some of the most inspiring academic discourse in the field comes from renowned figures like Andrew Ng, Yoshua Bengio, and Geoffrey Hinton, who have made significant contributions to the development and advancement of Machine Learning. At the undergraduate level, typical majors and modules in Machine Learning include courses in statistics, computer science, and mathematics. Students can specialize further in areas such as computer vision, natural language processing, or robotics. Examples of real-life applications of Machine Learning include image recognition in social media, language translation in Google Translate, and predictive maintenance in manufacturing. A degree in Machine Learning can lead to a range of exciting and lucrative career opportunities. Graduates can work in fields such as data science, machine learning engineering, or artificial intelligence research. Key industries for prospective future employment include tech, finance, healthcare, and automotive. Notable employers in these industries include Google, Amazon, Microsoft, and Tesla. To succeed in Machine Learning, students should have a strong foundation in mathematics and computer science, as well as an interest in data analysis and problem-solving. Good communication skills are also important, as Machine Learning often involves working in interdisciplinary teams. In conclusion, studying Machine Learning at the undergraduate level is an exciting and rewarding choice for those interested in the intersection of technology and data. With its endless possibilities and real-world applications, Machine Learning is a field that is sure to continue making waves in the years to come.

MIT researchers have found a way to reduce the time and cost of training large machine learning models by leveraging smaller models. This technique could help researchers make advancements faster with less expense and reduce carbon emissions. MIT's Yoon Kim and his team's method saves about 50% of the computational cost required to train a large model, compared to methods that train a new model from scratch. The research will be presented at the International Conference on Learning Representations.

Dive into the world of deep learning with this updated edition of a best-selling book, even if you have little knowledge of the technology. With concrete examples and two Python frameworks, Scikit-Learn and TensorFlow 2, you'll gain an intuitive understanding of building intelligent systems. Part 1 covers fundamental tasks, such as simple linear regression, while Part 2 guides you through advanced methods using deep neural networks. With exercises in each chapter, you'll be able to apply what you learn. Get ahead of the curve with Early Release ebooks, and receive updates as the author writes. Recommended for students and professionals interested in machine learning, artificial intelligence, and computer programming, this book offers a comprehensive introduction to deep learning. With minimal theory and practical examples, readers can easily gain an understanding of the key concepts and tools for building intelligent systems. The book is also relevant for those in the fields of data science, engineering, and technology who want to expand their knowledge and skills in machine learning. Additionally, the book's coverage of TensorFlow 2 and Keras makes it a valuable resource for those interested in these specific frameworks.

Are you curious about how to identify if a text is written by an AI language model or a human? Researchers at Stanford University have developed a tool called DetectGPT that can accurately distinguish between human- and LLM-generated text. The tool could benefit teachers, journalists, and citizens who need to know when they are reading model-generated text. By calculating how much a language model "likes" a piece of text, DetectGPT provides a reliable, actionable prediction as to whether a text was machine-generated. Discover the latest developments in LLM research and its implications for society.

Are you fascinated by technology and the limitless possibilities it holds? Do you have a passion for problem-solving and a desire to make a real impact on the world? Look no further than the exciting field of Artificial Intelligence (AI). AI is the study of intelligent agents, which are computer programs that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. From self-driving cars to virtual personal assistants, AI is transforming the way we live and work. At the forefront of AI research are innovators like Andrew Ng, who co-founded Google Brain and Coursera, and Yoshua Bengio, who won the prestigious Turing Award for his work in deep learning. These academic giants have paved the way for groundbreaking developments in AI, such as natural language processing and computer vision. As an undergraduate in AI, you'll delve into a range of fascinating modules, such as machine learning, robotics, and data mining. You'll also have the opportunity to specialize in areas such as computer vision, natural language processing, and game AI. Imagine creating a robot that can navigate a maze or designing a system that can translate languages in real-time. But what about the future? With a degree in AI, you'll be well-equipped for a range of exciting careers, including data scientist, machine learning engineer, and AI researcher. You could work for tech giants like Google, Facebook, and Amazon, or for cutting-edge startups like OpenAI and DeepMind. And it's not just tech companies that need AI experts - industries like healthcare, finance, and transportation are all looking for talented AI professionals. To succeed in AI, you'll need a strong foundation in mathematics, computer science, and programming. But equally important are skills like critical thinking, problem-solving, and creativity. If you're passionate about technology and driven to make a difference, a degree in AI could be the perfect fit for you.

Language models can perpetuate societal biases, but MIT researchers have trained a logic-aware model that significantly mitigates harmful stereotypes. With 350 million parameters, this model outperformed larger models on logic-language understanding tasks and had higher iCAT scores, indicating fewer stereotypes. The researchers propose this fair, smaller, and locally deployable model as a solution to challenges faced by current language models, such as fairness, computational resources, and privacy. While language models may still have a long way to go in achieving neutrality, this research offers a promising step forward.

Are you interested in creating cutting-edge software that changes people's lives? Do you enjoy working in a fast-paced, collaborative environment where innovation is encouraged and rewarded? If so, a career in software development may be right for you. Software developers are the creative minds behind computer programs. They use their expertise in programming languages, algorithms, and database management to design, develop, and test software applications for a variety of industries, from finance and healthcare to gaming and entertainment. They work closely with teams of software engineers, designers, and project managers to create software solutions that solve real-world problems and meet the needs of businesses and consumers alike. One of the most appealing aspects of a career in software development is the opportunity to work on projects that have a real impact on people's lives. For example, software developers at Google have worked on products such as Google Maps, which has revolutionized the way we navigate the world, and Google Translate, which makes it possible for people around the globe to communicate with each other in their own languages. Typical duties of a software developer include analyzing user needs and designing software solutions to meet those needs, writing and testing code, and collaborating with other team members to ensure that the software is delivered on time and to the highest quality standards. As you gain experience in the field, you may also have the opportunity to specialize in areas such as mobile app development, web development, or artificial intelligence. To become a software developer, you'll typically need a bachelor's degree in computer science, software engineering, or a related field. Popular undergraduate programs and majors include computer science, computer engineering, and information technology. In addition to a solid academic background, helpful personal attributes for a career in software development include strong problem-solving skills, a passion for learning, and excellent communication skills. The job prospects for software developers are excellent, with the Bureau of Labor Statistics projecting a 22% growth rate in employment from 2019 to 2029. This growth is driven by the increasing demand for software in virtually every industry, from healthcare and finance to education and entertainment. Some of the top employers in the field include companies such as Microsoft, Amazon, and IBM, as well as startups and small businesses around the world.

In academic settings, arguments are often used to convince others of a particular point of view. However, not all arguments are created equal. The success of an argument depends on understanding the audience's beliefs, trusted sources, and values. Mathematical and logical arguments work well because they rely on shared beliefs, but disagreements that involve outside information often come down to what sources and authorities people trust. When disagreements can't be settled with statistics or evidence, making a convincing argument may depend on engaging the audience's values. The challenge is to correctly identify what's important to people who don't already agree with us. Engaging in discussion and being exposed to counter-arguments can help make our own arguments and reasoning more convincing. By understanding the elements that make arguments successful, students can become more effective communicators and critical thinkers in both academic and real-world settings.