Rosie Graham
Investigating Google's Search Engine
Ethics, Algorithms, and the Machines Built to Read Us
Rosie Graham
Investigating Google's Search Engine
Ethics, Algorithms, and the Machines Built to Read Us
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What do search engines do? And what should they do? These questions seem relatively simple but are actually urgent social and ethical issues. The influence of Google's search engine is enormous. It does not only shape how Internet users find pages on the World Wide Web, but how we think as individuals, how we collectively remember the past, and how we communicate with one another. This book explores the impact of search engines within contemporary digital culture, focusing on the social, cultural, and philosophical influence of Google. Using case studies like Google's role in the rise of fake…mehr
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What do search engines do? And what should they do? These questions seem relatively simple but are actually urgent social and ethical issues. The influence of Google's search engine is enormous. It does not only shape how Internet users find pages on the World Wide Web, but how we think as individuals, how we collectively remember the past, and how we communicate with one another. This book explores the impact of search engines within contemporary digital culture, focusing on the social, cultural, and philosophical influence of Google. Using case studies like Google's role in the rise of fake news, instances of sexist and misogynistic Autocomplete suggestions, and search queries relating to LGBTQ+ values, it offers original evidence to intervene practically in existing debates. It also addresses other understudied aspects of Google's influence, including the profound implications of its revenue generation for wider society. In doing this, this important book helps to evaluate the real cost of search engines on an individual and global scale.
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Produktdetails
- Produktdetails
- Bloomsbury Studies in Digital Cultures
- Verlag: Bloomsbury Publishing PLC
- Seitenzahl: 256
- Erscheinungstermin: 12. Januar 2023
- Englisch
- Abmessung: 231mm x 154mm x 15mm
- Gewicht: 402g
- ISBN-13: 9781350325197
- ISBN-10: 1350325198
- Artikelnr.: 63762857
- Bloomsbury Studies in Digital Cultures
- Verlag: Bloomsbury Publishing PLC
- Seitenzahl: 256
- Erscheinungstermin: 12. Januar 2023
- Englisch
- Abmessung: 231mm x 154mm x 15mm
- Gewicht: 402g
- ISBN-13: 9781350325197
- ISBN-10: 1350325198
- Artikelnr.: 63762857
Rosie Graham is Lecturer in Contemporary Literature and the Digital at the University of Birmingham, UK and co-director of its Digital Cultures Research Centre.
Introduction: Investigating Google's Search Engine 1.0 Google's Dominance
2.0 The Three Steps of How Search Engines Work: Crawling, Ranking, and
Query Results 1.1 Step One: Crawling 1.2. Step Two: Ranking 1.3 Step Three:
Query Results 3.0 Five Key Challenges of Studying Google's Search Engine
3.1: Multiple Actors: Search Engine Optimisation and Economic Incentives
3.2: Moving Targets 3.3: Each Search a Partial Viewpoint 3.4: No Real
Alternatives 3.5: The Myth of Black Boxes 4.0 Chapter Outlines 5.0 Notation
and Examples Chapter One: Understanding Google Queries and the Problem of
Intentions Introduction 1.0 Categorising How and What People Search 1.1 The
Roles of Search Engines and Information Retrieval's Question of Why 1.2
Query Length and the Problems of Intention 1.3 All Information is Ethical:
Searching for [food for snakes] 2.0 Predicting Intentions with a Lack of
Information: Plato, Gadamer, and Derrida 2.1 Gadamer's Hermeneutics and
Plato's Fears of Deception 2.2 Google's Algorithms and Derrida's Monster
3.0 What Kinds of Things Do People Search Google For? 3.1 Google Trends,
Brexit, and "Frantically" Googling after the EU Referendum Conclusion
Chapter Two: Google's Impact on Cognition and Memory: Histories, Concepts,
and Technosocial Practices Introduction 1.0 Google's Impact on the
Cognition and Memory 1.1 Metaphors of Recall from Extended Minds to
Transactive Memory 2.0 Technosocial Memory Practices from Oral Culture to
Digital Literacy 3.0 The Legacy of Naturalised Technologies 3.1 Truth and
Knowledge for Plato 3.2 Aristotle's Sensory Approach 4.0 Technosocial
Memory Before Google: The Ars Memoria 4.1 The Science and Magic of Search
5.0 Treating the Mind as Technology: Bacon, Hooke, and Modern Psychology
Conclusion Chapter Three: Autocomplete: Stereotypes, Biases, and Designed
Discrimination Introduction 1.0 The Desire for a Digital Oracle 1.1
Autocomplete's Minimal Academic Attention 2.0 The Biases of Autocomplete:
Stereotypes and Discrimination 3.0 Predicting and Shaping User Attitudes:
The Origins of Autocomplete 3.1 So, How Does Autocomplete Operate? 4.0
Second-Order Stereotyping: Sexist Suggestions for Female Scientists 4.1
RankBrain and the Biases of Machine Learning 4.2 Automated Misogyny for
Every Individual 5.0 Speed 5.1 Speed and Judgment: Time to Reflect
Conclusion Chapter Four: Google's Search Engine Results: What is a Relevant
Result? Introduction 1.0 "Quantifiable Signals" and Malawian Witch Doctors
2.0 What Should Search Engine Results Be? 2.1 The Idealists: Search Is
Democratic, Relevance Can Be Measured Objectively, and Answers Can Exist
Independently of Bias 2.2 The Difficulty with Measuring Relevance 2.3 The
Contextualists: Search Is Undemocratic, Relevance Is a Measure of
Personalisation, and All Answers Are Inherently Biased 2.4 Are Search
Results Personalised? 3.0 Methodological Challenges of Studying Search
Engines 3.1 Particular Considerations for Collecting Search Engine Results
4.0 Variables that Matter: Search Experiments in 2015, 2017, and 2021 4.1
The Rationale Behind Focusing on Same-Sex Sexual Orientation 4.2 Queries
Used 4.3 Capturing the Spread of Results from the First Page 4.4 Evaluation
Method 5.0 Google's Public Position on How They Provide Results 6.0 The
Importance of Language and Location in Search Results (2015) 6.1 How Do
Variations in Terminology and Phrasing Alter Search Results? 6.2
Unimaginable Communities 7.0 How Search Results Change Throughout Time:
2015, 2017, 2021 7.1 Longitudinal Overview: Official Languages in Each
Domain 7.2 Terminology Throughout Time: "Homosexual" vs. "Gay" 6.3 Phrasing
Throughout Time: "Good" vs. "Wrong" Conclusion Chapter Five: The Real Cost
of Search Engines: Digital Advertising, Linguistic Capitalism, and the Rise
of Fake News Introduction 1.0 The Economics of Google 2.0 The Context of
Post-Fordism 3.0 AdWords: Organic vs. Sponsored Results 3.1 AdWords: The
Multilingual Linguistic Market and an Economy of Bias 3.2 Google's
Institutionalisation, Data-Collection, and Advertising 3.3 AdWords in the
Context of "The Magic System" 3.4 AdWords and the General Intellect 4.0 The
Economic Profits of Discrimination 5.0 Private Profits and Public Loses 5.1
Google's International Expansion 6.0 AdSense and Post-Fordism: The Cost of
Google's Billboards 6.1 AdSense and Fake News in the 2016 US Presidential
Election 6.2 The Reciprocal Relationship Between AdSense and Facebook
Conclusion Conclusion: What if Search Engines Were Actually Built to
Benefit Users?
2.0 The Three Steps of How Search Engines Work: Crawling, Ranking, and
Query Results 1.1 Step One: Crawling 1.2. Step Two: Ranking 1.3 Step Three:
Query Results 3.0 Five Key Challenges of Studying Google's Search Engine
3.1: Multiple Actors: Search Engine Optimisation and Economic Incentives
3.2: Moving Targets 3.3: Each Search a Partial Viewpoint 3.4: No Real
Alternatives 3.5: The Myth of Black Boxes 4.0 Chapter Outlines 5.0 Notation
and Examples Chapter One: Understanding Google Queries and the Problem of
Intentions Introduction 1.0 Categorising How and What People Search 1.1 The
Roles of Search Engines and Information Retrieval's Question of Why 1.2
Query Length and the Problems of Intention 1.3 All Information is Ethical:
Searching for [food for snakes] 2.0 Predicting Intentions with a Lack of
Information: Plato, Gadamer, and Derrida 2.1 Gadamer's Hermeneutics and
Plato's Fears of Deception 2.2 Google's Algorithms and Derrida's Monster
3.0 What Kinds of Things Do People Search Google For? 3.1 Google Trends,
Brexit, and "Frantically" Googling after the EU Referendum Conclusion
Chapter Two: Google's Impact on Cognition and Memory: Histories, Concepts,
and Technosocial Practices Introduction 1.0 Google's Impact on the
Cognition and Memory 1.1 Metaphors of Recall from Extended Minds to
Transactive Memory 2.0 Technosocial Memory Practices from Oral Culture to
Digital Literacy 3.0 The Legacy of Naturalised Technologies 3.1 Truth and
Knowledge for Plato 3.2 Aristotle's Sensory Approach 4.0 Technosocial
Memory Before Google: The Ars Memoria 4.1 The Science and Magic of Search
5.0 Treating the Mind as Technology: Bacon, Hooke, and Modern Psychology
Conclusion Chapter Three: Autocomplete: Stereotypes, Biases, and Designed
Discrimination Introduction 1.0 The Desire for a Digital Oracle 1.1
Autocomplete's Minimal Academic Attention 2.0 The Biases of Autocomplete:
Stereotypes and Discrimination 3.0 Predicting and Shaping User Attitudes:
The Origins of Autocomplete 3.1 So, How Does Autocomplete Operate? 4.0
Second-Order Stereotyping: Sexist Suggestions for Female Scientists 4.1
RankBrain and the Biases of Machine Learning 4.2 Automated Misogyny for
Every Individual 5.0 Speed 5.1 Speed and Judgment: Time to Reflect
Conclusion Chapter Four: Google's Search Engine Results: What is a Relevant
Result? Introduction 1.0 "Quantifiable Signals" and Malawian Witch Doctors
2.0 What Should Search Engine Results Be? 2.1 The Idealists: Search Is
Democratic, Relevance Can Be Measured Objectively, and Answers Can Exist
Independently of Bias 2.2 The Difficulty with Measuring Relevance 2.3 The
Contextualists: Search Is Undemocratic, Relevance Is a Measure of
Personalisation, and All Answers Are Inherently Biased 2.4 Are Search
Results Personalised? 3.0 Methodological Challenges of Studying Search
Engines 3.1 Particular Considerations for Collecting Search Engine Results
4.0 Variables that Matter: Search Experiments in 2015, 2017, and 2021 4.1
The Rationale Behind Focusing on Same-Sex Sexual Orientation 4.2 Queries
Used 4.3 Capturing the Spread of Results from the First Page 4.4 Evaluation
Method 5.0 Google's Public Position on How They Provide Results 6.0 The
Importance of Language and Location in Search Results (2015) 6.1 How Do
Variations in Terminology and Phrasing Alter Search Results? 6.2
Unimaginable Communities 7.0 How Search Results Change Throughout Time:
2015, 2017, 2021 7.1 Longitudinal Overview: Official Languages in Each
Domain 7.2 Terminology Throughout Time: "Homosexual" vs. "Gay" 6.3 Phrasing
Throughout Time: "Good" vs. "Wrong" Conclusion Chapter Five: The Real Cost
of Search Engines: Digital Advertising, Linguistic Capitalism, and the Rise
of Fake News Introduction 1.0 The Economics of Google 2.0 The Context of
Post-Fordism 3.0 AdWords: Organic vs. Sponsored Results 3.1 AdWords: The
Multilingual Linguistic Market and an Economy of Bias 3.2 Google's
Institutionalisation, Data-Collection, and Advertising 3.3 AdWords in the
Context of "The Magic System" 3.4 AdWords and the General Intellect 4.0 The
Economic Profits of Discrimination 5.0 Private Profits and Public Loses 5.1
Google's International Expansion 6.0 AdSense and Post-Fordism: The Cost of
Google's Billboards 6.1 AdSense and Fake News in the 2016 US Presidential
Election 6.2 The Reciprocal Relationship Between AdSense and Facebook
Conclusion Conclusion: What if Search Engines Were Actually Built to
Benefit Users?
Introduction: Investigating Google's Search Engine 1.0 Google's Dominance
2.0 The Three Steps of How Search Engines Work: Crawling, Ranking, and
Query Results 1.1 Step One: Crawling 1.2. Step Two: Ranking 1.3 Step Three:
Query Results 3.0 Five Key Challenges of Studying Google's Search Engine
3.1: Multiple Actors: Search Engine Optimisation and Economic Incentives
3.2: Moving Targets 3.3: Each Search a Partial Viewpoint 3.4: No Real
Alternatives 3.5: The Myth of Black Boxes 4.0 Chapter Outlines 5.0 Notation
and Examples Chapter One: Understanding Google Queries and the Problem of
Intentions Introduction 1.0 Categorising How and What People Search 1.1 The
Roles of Search Engines and Information Retrieval's Question of Why 1.2
Query Length and the Problems of Intention 1.3 All Information is Ethical:
Searching for [food for snakes] 2.0 Predicting Intentions with a Lack of
Information: Plato, Gadamer, and Derrida 2.1 Gadamer's Hermeneutics and
Plato's Fears of Deception 2.2 Google's Algorithms and Derrida's Monster
3.0 What Kinds of Things Do People Search Google For? 3.1 Google Trends,
Brexit, and "Frantically" Googling after the EU Referendum Conclusion
Chapter Two: Google's Impact on Cognition and Memory: Histories, Concepts,
and Technosocial Practices Introduction 1.0 Google's Impact on the
Cognition and Memory 1.1 Metaphors of Recall from Extended Minds to
Transactive Memory 2.0 Technosocial Memory Practices from Oral Culture to
Digital Literacy 3.0 The Legacy of Naturalised Technologies 3.1 Truth and
Knowledge for Plato 3.2 Aristotle's Sensory Approach 4.0 Technosocial
Memory Before Google: The Ars Memoria 4.1 The Science and Magic of Search
5.0 Treating the Mind as Technology: Bacon, Hooke, and Modern Psychology
Conclusion Chapter Three: Autocomplete: Stereotypes, Biases, and Designed
Discrimination Introduction 1.0 The Desire for a Digital Oracle 1.1
Autocomplete's Minimal Academic Attention 2.0 The Biases of Autocomplete:
Stereotypes and Discrimination 3.0 Predicting and Shaping User Attitudes:
The Origins of Autocomplete 3.1 So, How Does Autocomplete Operate? 4.0
Second-Order Stereotyping: Sexist Suggestions for Female Scientists 4.1
RankBrain and the Biases of Machine Learning 4.2 Automated Misogyny for
Every Individual 5.0 Speed 5.1 Speed and Judgment: Time to Reflect
Conclusion Chapter Four: Google's Search Engine Results: What is a Relevant
Result? Introduction 1.0 "Quantifiable Signals" and Malawian Witch Doctors
2.0 What Should Search Engine Results Be? 2.1 The Idealists: Search Is
Democratic, Relevance Can Be Measured Objectively, and Answers Can Exist
Independently of Bias 2.2 The Difficulty with Measuring Relevance 2.3 The
Contextualists: Search Is Undemocratic, Relevance Is a Measure of
Personalisation, and All Answers Are Inherently Biased 2.4 Are Search
Results Personalised? 3.0 Methodological Challenges of Studying Search
Engines 3.1 Particular Considerations for Collecting Search Engine Results
4.0 Variables that Matter: Search Experiments in 2015, 2017, and 2021 4.1
The Rationale Behind Focusing on Same-Sex Sexual Orientation 4.2 Queries
Used 4.3 Capturing the Spread of Results from the First Page 4.4 Evaluation
Method 5.0 Google's Public Position on How They Provide Results 6.0 The
Importance of Language and Location in Search Results (2015) 6.1 How Do
Variations in Terminology and Phrasing Alter Search Results? 6.2
Unimaginable Communities 7.0 How Search Results Change Throughout Time:
2015, 2017, 2021 7.1 Longitudinal Overview: Official Languages in Each
Domain 7.2 Terminology Throughout Time: "Homosexual" vs. "Gay" 6.3 Phrasing
Throughout Time: "Good" vs. "Wrong" Conclusion Chapter Five: The Real Cost
of Search Engines: Digital Advertising, Linguistic Capitalism, and the Rise
of Fake News Introduction 1.0 The Economics of Google 2.0 The Context of
Post-Fordism 3.0 AdWords: Organic vs. Sponsored Results 3.1 AdWords: The
Multilingual Linguistic Market and an Economy of Bias 3.2 Google's
Institutionalisation, Data-Collection, and Advertising 3.3 AdWords in the
Context of "The Magic System" 3.4 AdWords and the General Intellect 4.0 The
Economic Profits of Discrimination 5.0 Private Profits and Public Loses 5.1
Google's International Expansion 6.0 AdSense and Post-Fordism: The Cost of
Google's Billboards 6.1 AdSense and Fake News in the 2016 US Presidential
Election 6.2 The Reciprocal Relationship Between AdSense and Facebook
Conclusion Conclusion: What if Search Engines Were Actually Built to
Benefit Users?
2.0 The Three Steps of How Search Engines Work: Crawling, Ranking, and
Query Results 1.1 Step One: Crawling 1.2. Step Two: Ranking 1.3 Step Three:
Query Results 3.0 Five Key Challenges of Studying Google's Search Engine
3.1: Multiple Actors: Search Engine Optimisation and Economic Incentives
3.2: Moving Targets 3.3: Each Search a Partial Viewpoint 3.4: No Real
Alternatives 3.5: The Myth of Black Boxes 4.0 Chapter Outlines 5.0 Notation
and Examples Chapter One: Understanding Google Queries and the Problem of
Intentions Introduction 1.0 Categorising How and What People Search 1.1 The
Roles of Search Engines and Information Retrieval's Question of Why 1.2
Query Length and the Problems of Intention 1.3 All Information is Ethical:
Searching for [food for snakes] 2.0 Predicting Intentions with a Lack of
Information: Plato, Gadamer, and Derrida 2.1 Gadamer's Hermeneutics and
Plato's Fears of Deception 2.2 Google's Algorithms and Derrida's Monster
3.0 What Kinds of Things Do People Search Google For? 3.1 Google Trends,
Brexit, and "Frantically" Googling after the EU Referendum Conclusion
Chapter Two: Google's Impact on Cognition and Memory: Histories, Concepts,
and Technosocial Practices Introduction 1.0 Google's Impact on the
Cognition and Memory 1.1 Metaphors of Recall from Extended Minds to
Transactive Memory 2.0 Technosocial Memory Practices from Oral Culture to
Digital Literacy 3.0 The Legacy of Naturalised Technologies 3.1 Truth and
Knowledge for Plato 3.2 Aristotle's Sensory Approach 4.0 Technosocial
Memory Before Google: The Ars Memoria 4.1 The Science and Magic of Search
5.0 Treating the Mind as Technology: Bacon, Hooke, and Modern Psychology
Conclusion Chapter Three: Autocomplete: Stereotypes, Biases, and Designed
Discrimination Introduction 1.0 The Desire for a Digital Oracle 1.1
Autocomplete's Minimal Academic Attention 2.0 The Biases of Autocomplete:
Stereotypes and Discrimination 3.0 Predicting and Shaping User Attitudes:
The Origins of Autocomplete 3.1 So, How Does Autocomplete Operate? 4.0
Second-Order Stereotyping: Sexist Suggestions for Female Scientists 4.1
RankBrain and the Biases of Machine Learning 4.2 Automated Misogyny for
Every Individual 5.0 Speed 5.1 Speed and Judgment: Time to Reflect
Conclusion Chapter Four: Google's Search Engine Results: What is a Relevant
Result? Introduction 1.0 "Quantifiable Signals" and Malawian Witch Doctors
2.0 What Should Search Engine Results Be? 2.1 The Idealists: Search Is
Democratic, Relevance Can Be Measured Objectively, and Answers Can Exist
Independently of Bias 2.2 The Difficulty with Measuring Relevance 2.3 The
Contextualists: Search Is Undemocratic, Relevance Is a Measure of
Personalisation, and All Answers Are Inherently Biased 2.4 Are Search
Results Personalised? 3.0 Methodological Challenges of Studying Search
Engines 3.1 Particular Considerations for Collecting Search Engine Results
4.0 Variables that Matter: Search Experiments in 2015, 2017, and 2021 4.1
The Rationale Behind Focusing on Same-Sex Sexual Orientation 4.2 Queries
Used 4.3 Capturing the Spread of Results from the First Page 4.4 Evaluation
Method 5.0 Google's Public Position on How They Provide Results 6.0 The
Importance of Language and Location in Search Results (2015) 6.1 How Do
Variations in Terminology and Phrasing Alter Search Results? 6.2
Unimaginable Communities 7.0 How Search Results Change Throughout Time:
2015, 2017, 2021 7.1 Longitudinal Overview: Official Languages in Each
Domain 7.2 Terminology Throughout Time: "Homosexual" vs. "Gay" 6.3 Phrasing
Throughout Time: "Good" vs. "Wrong" Conclusion Chapter Five: The Real Cost
of Search Engines: Digital Advertising, Linguistic Capitalism, and the Rise
of Fake News Introduction 1.0 The Economics of Google 2.0 The Context of
Post-Fordism 3.0 AdWords: Organic vs. Sponsored Results 3.1 AdWords: The
Multilingual Linguistic Market and an Economy of Bias 3.2 Google's
Institutionalisation, Data-Collection, and Advertising 3.3 AdWords in the
Context of "The Magic System" 3.4 AdWords and the General Intellect 4.0 The
Economic Profits of Discrimination 5.0 Private Profits and Public Loses 5.1
Google's International Expansion 6.0 AdSense and Post-Fordism: The Cost of
Google's Billboards 6.1 AdSense and Fake News in the 2016 US Presidential
Election 6.2 The Reciprocal Relationship Between AdSense and Facebook
Conclusion Conclusion: What if Search Engines Were Actually Built to
Benefit Users?