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The Atlas of AI
The hidden costs of artificial intelligence, from natural
resources and labor to privacy and freedom What happens
when artificial intelligence saturates political life and depletes
the planet? How is AI shaping our understanding of ourselves and
our societies? In this book Kate Crawford reveals how this
planetary network is fueling a shift toward undemocratic governance
and increased inequality. Drawing on more than a decade of
research, award-winning science, and technology, Crawford reveals
how AI is a technology of extraction: from the energy and minerals
needed to build and sustain its infrastructure, to the exploited
workers behind \"automated\" services, to the data AI collects from
us. Rather than taking a narrow focus on code and algorithms,
Crawford offers us a political and a material perspective on what
it takes to make artificial intelligence and where it goes wrong.
While technical systems present a veneer of objectivity, they are
always systems of power. This is an urgent account of what is at
stake as technology companies use artificial intelligence to
reshape the world.
eBook
Brain vs computer : the challenge of the century
\"It is well known that every animal species obeys Darwin's law of evolution, which requires permanent adaptation of animals to their environment. To be precise, every species except man, who behaves exactly contrariwise, adapting the workplace to himself in order to survive. For that he generally enjoys a particular gift of nature: intelligence. That reverse adaptation, which accumulated over centuries, led to what we call \"progress\". This was enhanced by the development of machines which began to be also intelligent and now compete fiercely with humans through the development of an \"artificial intelligence\". Some famous people in the world of science and technology recently sounded the alarm about the threats which these improvements are posing. They invoked a possible domination by the machines due to their uncontrolled superior intelligence, potentially leading us into a certain kind of slavery. In this book we take a look at this new challenge of the human brain versus the computer. The brain is a very complex organ and we are just beginning to understand how it works; many things remain mysterious and can lead to surprises. We will see how current investigations bring new information about this strange organ. We will also see how the \"artificial challenger\" plans to win the battle, how computers are getting more and more powerful and subtle as the AI advances. Would a transfer of minds in a machine be possible? Would the computer be capable of a self, nonneuromorphic intelligence? These questions are now open. Who will win? We do not know yet. But it is certain that many things are going to change in our lives in the very near future\" -- From the publisher.
Book
Artificial intelligence and increasing misinformation
With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and video information based on training data. Commercial use of generative AI is expanding rapidly and the public will routinely receive messages created by generative AI. However, generative AI models may be unreliable, routinely make errors and widely spread misinformation. Misinformation created by generative AI about mental illness may include factual errors, nonsense, fabricated sources and dangerous advice. Psychiatrists need to recognise that patients may receive misinformation online, including about medicine and psychiatry.
Journal Article
Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization
Generative AIs have been embraced by learners wishing to offload (parts of) complex tasks. However, recent research suggests that AI users are at risk of failing to correctly monitor the extent of their own contribution when being assisted by an AI. This difficulty in keeping track of the division of labor has been shown to result in placebo and ghostwriter effects. In case of the AI-based placebo effect, users overestimate their ability while or after being assisted by an AI. The ghostwriter effect occurs when AI users do not disclose their AI use despite being aware of the contribution made by an AI. These two troubling effects are discussed in the context of the conflict between cognitive externalization and anthropomorphization. While people tend to offload cognitive load into their environment, they also often perceive technology as human-like. However, despite the natural conversations that can be had with current AIs, the desire to attribute human-like qualities that would require the acknowledgment of AI contributions appears to be lacking. Implications and suggestions on how to improve AI use, for example, by employing embodied AI agents, are discussed.
Journal Article
Humans as Creativity Gatekeepers: Are We Biased Against AI Creativity?
With artificial intelligence (AI) increasingly involved in the creation of organizational and commercial artifacts, human evaluators’ role as creativity gatekeepers of AI-produced artifacts will become critical for innovation processes. However, when humans evaluate creativity, their judgment is clouded by biases triggered by the characteristics of the creator. Drawing from folk psychology and algorithm aversion research, we examine whether the identity of the producer of a given artifact as artificial intelligence (AI) or human is a source of bias affecting people’s creativity evaluation of such artifact and what drives this effect. With four experimental studies (N = 2039), of which two were pre-registered, using different experimental designs and evaluation targets, we found that people sometimes—but not always—ascribe lower creativity to a product when they are told that the producer is an AI rather than a human. In addition, we found that people consistently perceive generative AI to exert less effort than humans in the creation of a given artifact, which drives the lower creativity ratings ascribed to generative AI producers. We discuss the implication of these findings for organizational creativity and innovation in the context of human-AI interaction.
Journal Article
Brief answers to the big questions
\"Dr. Stephen Hawking was the most renowned scientist since Einstein, known both for his groundbreaking work in physics and cosmology and for his mischievous sense of humor. He educated millions of readers about the origins of the universe and the nature of black holes, and inspired millions more by defying a terrifying early prognosis of ALS, which originally gave him only two years to live. In later life he could communicate only by using a few facial muscles, but he continued to advance his field and serve as a revered voice on social and humanitarian issues. Hawking not only unraveled some of the universe's greatest mysteries but also believed science plays a critical role in fixing problems here on Earth. Now he turns his attention to the most urgent issues facing us. Will humanity survive? Should we colonize space? Does God exist? These are just a few of the questions Hawking addresses in this wide-ranging, passionately argued final book from one of the greatest minds in history. Featuring a foreword by Eddie Redmayne, who won an Oscar playing Stephen Hawking, an introduction by Nobel Laureate Kip Thorne, and an afterword from Hawking's daughter, Lucy.\" -- (Source of summary not specified)
Book
Artificial Intelligence in Utilitarian vs. Hedonic Contexts
Rapid development and adoption of AI, machine learning, and natural language processing applications challenge managers and policy makers to harness these transformative technologies. In this context, the authors provide evidence of a novel \"word-of-machine\" effect, the phenomenon by which utilitarian/hedonic attribute trade-offs determine preference for, or resistance to, AI-based recommendations compared with traditional word of mouth, or human-based recommendations. The word-of-machine effect stems from a lay belief that AI recommenders are more competent than human recommenders in the utilitarian realm and less competent than human recommenders in the hedonic realm. As a consequence, importance or salience of utilitarian attributes determine preference for AI recommenders over human ones, and importance or salience of hedonic attributes determine resistance to AI recommenders over human ones (Studies 1–4). The word-of machine effect is robust to attribute complexity, number of options considered, and transaction costs. The word-of-machine effect reverses for utilitarian goals if a recommendation needs matching to a person's unique preferences (Study 5) and is eliminated in the case of human–AI hybrid decision making (i.e., augmented rather than artificial intelligence; Study 6). An intervention based on the consider-the-opposite protocol attenuates the word-of-machine effect (Studies 7a–b).
Journal Article