2: The Age of Algorithms
- Page ID
- 90183
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- 2.1: What are Algorithms?
- This page highlights the influence of algorithms on online experiences, detailing how they shape content and advertisements based on user data. It stresses the need for awareness of these mechanisms, especially for students, and recommends educational resources, including a TED Talk by Jennifer Golbeck, that delves into the implications of social media data in algorithmic predictions.
- 2.2: The Influence of Algorithms
- This page examines the dual role of algorithms in modern society, highlighting their advantages alongside significant issues like bias and privacy concerns. It cites examples in education, hiring, and social media, specifically mentioning the Facebook-Cambridge Analytica scandal to illustrate data misuse risks.
- 2.3: Algorithmic Bias
- This page addresses the misconception of algorithmic objectivity, emphasizing that human-created algorithms can perpetuate biases affecting marginalized groups. It discusses examples in judicial systems, hiring, and social media, citing notable figures like Dr. Safiya Noble and Joy Buolamwini, who challenge these biases. Cathy O'Neil highlights the hidden truths in 'black box' algorithms. The page calls for recognition and action against these biases to promote fairness and equity in technology.
- 2.4: The Attention Economy
- This page discusses how algorithms on social media and news platforms prioritize sensational content to boost engagement, leading to emotional reactions and societal shifts. This focus on "engagement," often at the expense of substance, spurs "outrage cascades" and alters how news is consumed and interactions occur, with visibility increasingly based on engagement rather than relevance.
- 2.5: Algorithms and Polarization
- This page explores the internet's dual nature, revealing its role in amplifying diverse voices as well as fostering divisiveness due to profit-driven algorithmic polarization. Scholars note that algorithms enhance engagement by promoting outrage and user segmentation, benefiting corporations through targeted advertising.
- 2.6: Filter Bubbles
- This page examines the effects of algorithmic personalization on information consumption, focusing on "filter bubbles" that distort perspectives and increase polarization. It discusses how these algorithms can create echo chambers by reinforcing existing beliefs, while recent studies suggest that exposure to opposing views may also heighten polarization, particularly among older users less engaged with social media.
- 2.7: Conclusion
- This page explores the impact of algorithms on our lives, addressing issues like algorithmic bias, the attention economy, and digital polarization. It emphasizes how these factors influence our online information and behavior. Although it points out the negative aspects of digital platforms, the chapter advocates for greater awareness of our information landscapes to effectively engage with these tools while recognizing their importance in communication and community.