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Artificial intelligence refers to machines being able to plan, create, decide, and learn in a way analogous to human minds. This concept has been anticipated and discussed for decades, well before computers had the processing power. We still do not have true artificial intelligence, despite how many things are being labeled as such.
The 21st century has seen an explosion in AI applications with varying degrees of success thus far -- for instance, self-driving cars are increasingly improving but still struggle with certain conditions. The law notoriously lags behind technological progress and questions of content ownership and liability will have to be decided in the future.
| Applications | Related Issues |
|---|---|
| AI art, computer-generated art, generative AI |
copyright moral rights of artists creativity |
| automation |
(un)employment, downsizing productivity |
| chatbots |
ChatGPT [GPT = generative pretrained transformer] plagiarism, academic integrity misinformation |
| deepfakes |
misinformation, propaganda reputation right of publicity or personality rights |
| facial recognition |
privacy security advertising |
| medical diagnosis |
detection accuracy, misdiagnosis false positives, false negatives patient communication, telemedicine document transcription, analytics |
| self-driving or autonomous vehicles/cars/ trucks |
transportation industry independence for elderly, disabled public safety liability |
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Who Wrote This?: How AI and the Lure of Efficiency Threaten Human Writing by
Would you read this book if a computer wrote it? Would you even know? And why would it matter? Today's eerily impressive artificial intelligence writing tools present us with a crucial challenge: As writers, do we unthinkingly adopt AI's time-saving advantages or do we stop to weigh what we gain and lose when heeding its siren call? To understand how AI is redefining what it means to write and think, linguist and educator Naomi S. Baron leads us on a journey connecting the dots between human literacy and today's technology. From nineteenth-century lessons in composition, to mathematician Alan Turing's work creating a machine for deciphering war-time messages, to contemporary engines like ChatGPT, Baron gives readers a spirited overview of the emergence of both literacy and AI, and a glimpse of their possible future. As the technology becomes increasingly sophisticated and fluent, it's tempting to take the easy way out and let AI do the work for us. Baron cautions that such efficiency isn't always in our interest. As AI plies us with suggestions or full-blown text, we risk losing not just our technical skills but the power of writing as a springboard for personal reflection and unique expression. Funny, informed, and conversational, Who Wrote This? urges us as individuals and as communities to make conscious choices about the extent to which we collaborate with AI. The technology is here to stay. Baron shows us how to work with AI and how to spot where it risks diminishing the valuable cognitive and social benefits of being literate.
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Artificial Intelligence: The Insights You Need From Harvard Business Review by
From making faster, better decisions to automating rote work to enabling robots to respond to emotions, AI and machine learning are already reshaping business and society. What should you and your company be doing today to ensure that you're poised for success and keeping up with your competitors in the age of AI? Artificial Intelligence: The Insights You Need from Harvard Business Review brings you today's most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution.
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Robot-Proof: Higher Education in the Age of Artificial Intelligence by
How to educate the next generation of college students to invent, to create, and to discover--filling needs that even the most sophisticated robot cannot. Driverless cars are hitting the road, powered by artificial intelligence. Robots can climb stairs, open doors, win Jeopardy, analyze stocks, work in factories, find parking spaces, advise oncologists. In the past, automation was considered a threat to low-skilled labor. Now, many high-skilled functions, including interpreting medical images, doing legal research, and analyzing data, are within the skill sets of machines. How can higher education prepare students for their professional lives when professions themselves are disappearing? In Robot-Proof, Northeastern University president Joseph Aoun proposes a way to educate the next generation of college students to invent, to create, and to discover--to fill needs in society that even the most sophisticated artificial intelligence agent cannot. A "robot-proof" education, Aoun argues, is not concerned solely with topping up students' minds with high-octane facts. Rather, it calibrates them with a creative mindset and the mental elasticity to invent, discover, or create something valuable to society--a scientific proof, a hip-hop recording, a web comic, a cure for cancer. Aoun lays out the framework for a new discipline, humanics, which builds on our innate strengths and prepares students to compete in a labor market in which smart machines work alongside human professionals. The new literacies of Aoun's humanics are data literacy, technological literacy, and human literacy. Students will need data literacy to manage the flow of big data, and technological literacy to know how their machines work, but human literacy--the humanities, communication, and design--to function as a human being. Life-long learning opportunities will support their ability to adapt to change. The only certainty about the future is change. Higher education based on the new literacies of humanics can equip students for living and working through change.
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How Smart Machines Think by
Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs. The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these things work? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world--and to play Atari video games better than humans. He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution--at least for now. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing readers to many of the researchers involved, and keeping technical details to a minimum. Science and technology buffs will find this book an essential guide to a future in which machines can outsmart people.
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Augmented Exploitation: Artificial Intelligence, Automation and Work by
Augmented Exploitation explores the reality of the impact of AI on workers' lives. While the consensus is that AI is a completely new way of managing a workplace, the authors show that, on the contrary, AI is used as most technologies are used under capitalism: as a smokescreen that hides the deep exploitation of workers. Going beyond platform work and the gig economy, the authors explore emerging forms of algorithmic governance and AI-augmented apps that have been developed to utilise innovative ways to collect data about workers and consumers, as well as to keep wages and worker representation under control. They also show that workers are not taking this lying down, providing case studies of new and exciting form of resistance that are springing up across the globe.
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First published: Sept. 2023
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