Algorithms and Machine Learning Overview

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Questions and Answers

How is 'affect' best understood in relation to algorithms?

As a static emotional response, directly caused by the algorithm's actions.

As a predetermined set of rules, dictating how algorithms process emotions.

As a form of logical calculation, inherent in the algorithm's design.

As fluid moods and intensities, resulting from interactions with algorithms. (correct)

What does the text suggest about the location of an algorithm's 'doing'?

It is exclusively contained within the coded instructions of the algorithm.

It is found within the domain of public articulation, experience, and contestation. (correct)

It is primarily determined by the user's existing emotional state.

It is solely dependent on the technical specifications and hardware performance.

What key inquiry about algorithmic intensification is highlighted in the text?

The economic advantages of widespread algorithmic adoption in society.

The technical challenges of improving the efficiency and speed of algorithms.

The possibilities for coexisting with algorithms considering the forces of encounter they generate. (correct)

The potential for algorithms to eliminate human biases and improve decision-making.

Which of the following best represents the 'Cathedral of Computation' analogy?

Algorithms are seen as an infallible, almost divine, power. Signup and view all the answers

What does the text imply about algorithms' influence on an individual's sense of self?

Algorithms actively shape the concept of the self through ongoing encounters and interactions. Signup and view all the answers

What is the primary function of supervised machine learning?

To predict outcomes based on pre-annotated training data. Signup and view all the answers

Why might the process of creating an annotated dataset for machine learning be considered 'extraordinarily expensive'?

It involves extensive manual labor to verify and categorize data. Signup and view all the answers

According to Bishop, what is the primary nature of our supposedly algorithmic culture?

A devotional practice where computers have replaced deities in people's minds. Signup and view all the answers

According to the information provided, what is a significant risk associated with the data used to train AI systems?

The data may encode and perpetuate existing societal biases and discrimination. Signup and view all the answers

What role does Amazon Mechanical Turk play in the development of machine learning?

It facilitates the crowdsourcing of the annotation process. Signup and view all the answers

What does Bishop mean by 'algorithmic lore'?

A combination of data-informed assumptions woven into a subjective narrative. Signup and view all the answers

Which of the following is a key distinction between supervised and unsupervised machine learning?

Supervised learning makes predictions based on labeled data. Signup and view all the answers

What is a focus of Bishop's analysis of algorithmic lore?

The focus is on specialists shaping content, rather than the 'ordinary' users. Signup and view all the answers

What is meant by the phrase 'registry of power' in the context of AI, as Crawford argues?

AI systems reinforce existing structures of power through their algorithms and data. Signup and view all the answers

What is the main aim of algorithmic experts on platforms like YouTube?

To align content with YouTube's guidelines and maximise audience reach. Signup and view all the answers

What does the text suggest about the trustworthiness of YouTube creators trained by algorithmic experts?

Their independence is often just an appearance, and they align to YouTube’s practices. Signup and view all the answers

How does the provided information describe the relationship between machine learning and artificial intelligence?

Artificial Intelligence uses machine learning to achieve particular tasks. Signup and view all the answers

Considering that AI systems are trained on existing data, what would be the outcome of an AI model that is trained mostly on images of light skinned people?

The model would be biased in favor of light-skinned people over others. Signup and view all the answers

What is the primary use of urban algorithms according to the text?

To analyse, manage and optimize various aspects of urban environments. Signup and view all the answers

What is the potential negative consequence of urban algorithms, according to the text?

They can negatively affect people's lives based on who controls these systems. Signup and view all the answers

What was a key internal debate within NTechLab regarding the use of their facial recognition technology?

The debate focussed on the ethics of the technology, particularly concerning surveillance of activists. Signup and view all the answers

What is a key characteristic of platform-independent media?

Ability to exist across multiple channels or in open formats. Signup and view all the answers

How have traditional news producers transitioned towards platform dependency?

By distributing their content through third-party platforms and adapting it to trending topics. Signup and view all the answers

What distinguishes super apps like WeChat or KakaoTalk from typical single-purpose apps?

They've evolved to be platforms for everyday cultural and economic activities. Signup and view all the answers

What is a key change regarding the platforms that games are dependent upon, according to the text?

Games transitioned from dedicated consoles to digital platforms like app stores. Signup and view all the answers

What is one way that creators on platforms like YouTube are affected by the platform?

Their content strategy and monetization are controlled by the platform's algorithms and policies. Signup and view all the answers

How do platforms like LINE create new cultural commodities using user content?

By developing emoji and sticker sets which are then sold to other users. Signup and view all the answers

What is the main point made about the study of platforms?

To analyze platforms considering historical and regional specificities. Signup and view all the answers

What can be said about the cultural production of journalists and news platforms?

It is increasingly shaped by platform trends, except for organizations that have maintained independence. Signup and view all the answers

What was a key strategy employed by gig platforms to rapidly expand and gain market share?

Utilizing large amounts of investment capital to adapt operational strategies to local norms and regulations. Signup and view all the answers

How did gig platforms primarily justify their exemption from traditional industry and sector-specific regulations?

By emphasizing their status as technology companies rather than labor-driven services. Signup and view all the answers

What was the primary initial reaction among policymakers to the rise of gig platforms?

Hesitation due to focus on economic growth and competition, combined with a narrative of economic empowerment. Signup and view all the answers

Why did food delivery and domestic cleaning services not face similar levels of institutional resistance as transportation and hospitality services when gig platforms emerged?

These sectors were primarily informal with less established institutional actors to oppose. Signup and view all the answers

What did a specific gig platform do, to build community and keep their contractors engaged?

They held monthly meetings with food and drinks, to discuss company plans and share performance data. Signup and view all the answers

According to Vallas and Schor, what is a key characteristic of platform firms?

They retain authority over important functions like pricing and data collection while ceding control over work methods and schedules to the workers. Signup and view all the answers

What does the term 'permissive potentates' as applied to platform firms by Vallas and Schor imply?

Platform firms wield significant power by controlling key functions, despite their appearance of decentralization. Signup and view all the answers

Which of the following best describes the allocation of power in the gig economy, as described in the text?

Power is centralized in the hands of platform firms, which control critical aspects of the work. Signup and view all the answers

What is a key method through which platform firms profit according to the content?

By leveraging digital intermediation, avoiding traditional employer responsibilities, and utilizing a fragmented workforce. Signup and view all the answers

What does the text suggest about the nature of worker autonomy within the gig economy?

Worker autonomy is often constrained by algorithmic oversight, rating systems, and fluctuating demand. Signup and view all the answers

What is one of the consequences of platform models on workers?

It disperses workers geographically, undermines worker solidarity and fosters competition. Signup and view all the answers

Based on the text, how do platform firms handle costs and risks commonly borne by employers?

They delegate costs and risks such as maintenance and job security to workers. Signup and view all the answers

What does the author of this text mean by stating that platforms create 'unstable and precarious labor arrangements'?

That the lines between labor and marketplace participation are ambiguous, leading to conditions where workers have little employment security and income fluctuations. Signup and view all the answers

Study Notes

Algorithms and Fictions

Algorithms are sets of rules for calculations and problem-solving, often used by computers.
Public perception of algorithms is strong, but they also have real socio-technical aspects that can be studied.
Public opinion about algorithms matters as much as their function.
Generative AI and foundation models are complicated and exacerbate previous understanding.
Algorithms are defined as step-by-step processes, such as those employed by YouTube.
Algorithmic systems sort, manipulate, and predict.
Public perception of algorithms has an affective dimension.
Opaqueness leads to a need to visualize algorithms.
People create narratives around algorithms.
Twitter and Facebook were researched to understand public perception of algorithms.
Reactions to algorithms were scrutinized for any patterns in people's understanding.

Algorithmic Affect

Algorithms affect mood and intensity.
Personal narratives about algorithms demonstrate that understanding them goes beyond mere code.
Algorithms are not only "in" the code but are performed and contested through public discourse.
Algorithms' role in everyday life warrants consideration of their affective impact.
Considering how algorithms evoke feelings is essential to understanding their effects.
Public perception, and how these feelings influence the logic of the system, is critical.

Algorithmic Lore

Algorithmic experts and lore are a mix of data-informed opinions and subjective narratives.
YouTube motivational speakers/influencers are experts in algorithmic lore.
Algorithmic experts attempt broad generalizations, often ignoring specific audience data.
Emphasis on gendered performance during generalization might obscure important data.
Expert training usually aligns with YouTube's platform trends, disregarding systemic issues.

Urban Algorithms

Urban algorithms refer to computational rules that analyze, manage, or optimize urban environments.
These algorithms are employed in various urban aspects, such as planning, transportation, and infrastructure.
Algorithms analyze data to improve urban dynamics (traffic, population patterns, etc)
Optimizing efficiency, sustainability, and quality of life are key goals of algorithms.

Generative AI (Neural Networks)

Neural networks resemble the human brain in structure and processing.
Layers of interconnected nodes (neurons) in a neural network handle data processing.
Neural networks are often used in machine learning for tasks like image and speech recognition.
Adjusting connections ("weights") is how neural networks improve with time.
Tokenization is the division of text into smaller units.
Identifying characters, words, or phrases are methods of tokenization.
Language structure, meaning, and context analysis is easier with tokenization.

Post-Training Alignment (Weights)

Pre-trained AI models are fine-tuned using techniques like reinforcement learning from human feedback.
This fine-tuning aligns the model with human values and desired behavior.
This ensures appropriate responses in real-world applications.
Backpropagation is a type of adjustment used for alignment.
Scale of resources used (compute power, dataset size, etc.) exponentially increases with larger models.

Foundation Models

Large-scale AI models trained on extensive data are "foundation models".
Foundation models are adaptable to many applications, with little additional fine-tuning required.
They benefit from training on diverse data.
Foundation models are versatile across various applications.

AI and Discrimination

Classification in machine learning is a historical practice connected to discrimination.
Contemporary classification systems reproduce bias.
Different processes (including AI, machine learning, and algorithms) are often confused.
Understanding these processes is crucial.
Examples of how classification and bias can emerge include the Home Owners Loan Corporation and its policies.
Redlining is a discriminatory practice that denies services to certain communities, often racial minorities.
The Home Owners Loan Corporation (HOLC) used subjective judgments to create segregation maps.

Content Moderation and Digital Labor

Content Moderation: The process of monitoring, reviewing, and potentially controlling social media content.
Soft Moderation: The reviewing of social media content that is typically done by humans.
Hard Moderation: Algorithmic methods used to filter and classify content.
Moderation on social media platforms is often performed by a globally distributed workforce at very low wages.
Factors influencing business models for content moderation include policy pressure, legal requirements, business interests, and societal expectations.
Transparency within content moderation affects who’s accountable.
Companies use metrics and feedback from users to measure the effectiveness of their moderation systems.

Platform Labor

Platform labor encompasses jobs facilitated by digital platforms.
Workers on these platforms are typically contract workers, not employees.
Various worker types fall under this category, including creators, online gig workers, and app-based gig workers.
There are ethical concerns related to the working conditions for those who work on platforms.
Platform workers are motivated through incentives like bonus pay, referral bonuses, and hourly/piece-rate wages.

Ecology

Ecology: The interrelations of living things with their environment.
Technology's impact on the environment is a primary concern.
Methods for mining resources are examples of large-scale environmental effects.
Production and processes behind modern technology (media, etc.) have environmental consequences.
Data centres consume significant resources and energy.
The impact of data centers on the environment and physical reality.

Advertising Platforms

Advertising platforms employ resource-intensive machine learning for personalization.
Marketing campaigns are designed to create a cycle of obsolescence in advertising.

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Description

This quiz explores fundamental concepts in algorithms and machine learning, focusing on their impact on individual identity and culture. Key topics include supervised machine learning, the cost of data annotation, and the implications of algorithmic influences. Challenge your understanding of these modern technologies and their societal roles.