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Record Nr. |
UNINA9911011858403321 |
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Autore |
Mehan Julie |
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Titolo |
Digital Ethics in the Age of AI : Navigating the Ethical Frontier Today and Beyond |
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Pubbl/distr/stampa |
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Ely : , : IT Governance Ltd, , 2024 |
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©2024 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (152 pages) |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Technology - Social aspects |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Cover -- Title -- Copyright -- Foreword -- About The Author -- Acknowledgements -- Contents -- Introduction -- Chapter 1: A digital world and ethics -- The 'digital world' -- What are digital and AI ethics? -- Digital chaos without ethics -- Who are the stakeholders in digital and AI ethics? -- Digital citizenship - a subset of ethics -- Chapter 2: 2024 - Digital technology disruption and AI -- What makes AI a disruptive technology? -- Is generative AI a disruptive technology? -- Chapter 3: An overview of AI and generative AI - setting the stage -- What is AI? -- How does AI learn? -- Pros and cons of advances in AI -- What is generative AI and what makes it unique? -- Chapter 4: The role of AI and generative AI in misinformation and disinformation -- What is misinformation, disinformation, and fake news? -- The role played by AI in misinformation, disinformation, and deepfakes -- Digital doppelgängers - a mirror image of you -- What are the potential ethical implications of the increase in misinformation, disinformation, and deepfakes? -- Strategies for identifying and combatting mis-, disinformation and fake news/deepfakes -- Chapter 5: AI and online disinhibition -- What are some of the most common sources of online disinhibition? -- Does AI increase the emergence of online disinhibition? -- What are the possible implications of disinhibition? -- Strategies for addressing toxic online disinhibition -- Chapter 6: Biased brains - Challenging all types of bias -- How does AI bias occur? -- |
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What is the role of algorithmic curation in creating bias? -- Cognitive bias -- What makes individuals vulnerable to bias and misinformation? -- The effects of AI bias -- Strategies to address AI-based bias -- Chapter 7: AI and job displacement -- Job displacement and the cognitive class -- Why is the cognitive class at risk? -- AI and inequality. |
Strategies to reduce the effects of AI-generated job displacement -- Chapter 8: AI imitation is not a form of flattery -- Let's talk about intellectual property and copyright law -- Why is the protection of IP and copyright important? -- How has the digital age and AI impacted IP and copyright protection? -- AI and education -- Strategies to avoid inappropriate AI imitation -- Chapter 9: Digital technology, AI, and privacy - Is anything really private anymore? -- AI and its effect on privacy -- Generative AI and privacy -- Monitoring and surveillance -- The privacy paradox -- Strategies to protect personal privacy in the age of AI -- Chapter 10: AI and autonomous things -- AI and smart devices -- Self-driving vehicles -- Drones -- Autonomous lethal weapons -- AI, the IoT and IoAT, and health care -- Strategies to mitigate the potential negative effects of the IoAT -- Chapter 11: AI is rewiring our society - And our behavior -- Strategies to mitigate the effect of AI on our society, our behavior, and our abilities -- Chapter 12: AI regulation and policy - 2024 and beyond -- Moore's and Moor's law( s) and our relationship to AI -- What steps are organizations taking toward more effective governance of AI? -- What's happening in 2024 and beyond in terms of AI legislation and policy? -- Why is legislation and policy so hard? -- Chapter 13: What's next in AI? -- Utopian or dystopian? -- AI and Pandora's box -- Appendix: AI terms you probably need to know -- Further reading. |
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Sommario/riassunto |
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Explores the ethical implications of the transformative power of AI in general and the new and disruptive AI technologies, such as generative AI. |
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2. |
Record Nr. |
UNINA9910584486503321 |
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Autore |
Bouwer Laurens M |
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Titolo |
Integrating Data Science and Earth Science : Challenges and Solutions / / edited by Laurens M. Bouwer, Doris Dransch, Roland Ruhnke, Diana Rechid, Stephan Frickenhaus, Jens Greinert |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (158 pages) |
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Collana |
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SpringerBriefs in Earth System Sciences, , 2191-5903 |
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Classificazione |
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COM004000COM031000MAT000000MAT029000SCI019000 |
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Altri autori (Persone) |
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DranschDoris |
RuhnkeRoland |
RechidDiana |
FrickenhausStephan |
GreinertJens |
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Disciplina |
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Soggetti |
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Earth sciences |
Artificial intelligence - Data processing |
Statistics |
Mathematics |
Earth Sciences |
Data Science |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Data Science and Earth System Science -- The Digital Earth project: focus and agenda -- Data analysis and exploration with visual approaches -- Data analysis and exploration with computational approaches -- Data analysis and exploration with scientific workflows -- The Digital Earth SMART monitoring concept and tools -- Interdisciplinary collaboration -- Evaluating the success of the Digital Earth project -- Lessons learned in the Digital Earth project. |
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Sommario/riassunto |
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This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and |
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